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Zhang Y, Li Z, Zhang C, Shao C, Duan Y, Zheng G, Cai Y, Ge M, Xu J. Recent advances of photodiagnosis and treatment for head and neck squamous cell carcinoma. Neoplasia 2025; 60:101118. [PMID: 39721461 PMCID: PMC11732236 DOI: 10.1016/j.neo.2024.101118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 12/19/2024] [Indexed: 12/28/2024]
Abstract
Head and neck squamous cell carcinoma (HNSCC) are the most common type of head and neck tumor that severely threatens human health due to its highly aggressive nature and susceptibility to distant metastasis. The diagnosis of HNSCC currently relies on biopsy and histopathological examination of suspicious lesions. However, the early mucosal changes are subtle and difficult to detect by conventional oral examination. As for treatment, surgery is still the primary treatment modality. Due to the complex anatomy and the lack of intraoperative modalities to accurately determine the incision margins, surgeons are in a dilemma between extensive tumor removal and improving the quality of patient survival. As more knowledge is gained about HNSCC, the increasing recognition of the value of optical imaging has been emphasized. Optical technology offers distinctive possibilities for early preoperative diagnosis, intraoperative real-time visualization of tumor margins, sentinel lymph node biopsies, phototherapy. Fluorescence imaging, narrow-band imaging, Raman spectroscopy, optical coherence tomography, hyperspectral imaging, and photoacoustic imaging have been reported for imaging HNSCC. This article provides a comprehensive overview of the fundamental principles and clinical applications of optical imaging in the diagnosis and treatment of HNSCC, focusing on identifying its strengths and limitations to facilitate advancements in this field.
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Affiliation(s)
- Yining Zhang
- Otolaryngology & Head and Neck Center, Cancer Center, Department of Head and Neck Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou 310014, Zhejiang, China; Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Zhenfang Li
- Otolaryngology & Head and Neck Center, Cancer Center, Department of Head and Neck Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou 310014, Zhejiang, China
| | - Chengchi Zhang
- Otolaryngology & Head and Neck Center, Cancer Center, Department of Head and Neck Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou 310014, Zhejiang, China; Zhejiang University of Technology, Hangzhou 310023, China
| | - Chengying Shao
- Otolaryngology & Head and Neck Center, Cancer Center, Department of Head and Neck Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou 310014, Zhejiang, China; Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Yanting Duan
- Zhejiang Provincial Clinical Research Center for Head & Neck Cancer, Hangzhou 310014, China; Zhejiang Key Laboratory of Precision Medicine Research on Head & Neck Cancer, Hangzhou 310014, China
| | - Guowan Zheng
- Zhejiang Provincial Clinical Research Center for Head & Neck Cancer, Hangzhou 310014, China; Zhejiang Key Laboratory of Precision Medicine Research on Head & Neck Cancer, Hangzhou 310014, China
| | - Yu Cai
- Department of Rehabilitation Medicine, Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Cancer Center, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang 310014, China.
| | - Minghua Ge
- Otolaryngology & Head and Neck Center, Cancer Center, Department of Head and Neck Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou 310014, Zhejiang, China; Zhejiang Provincial Clinical Research Center for Head & Neck Cancer, Hangzhou 310014, China; Zhejiang Key Laboratory of Precision Medicine Research on Head & Neck Cancer, Hangzhou 310014, China.
| | - Jiajie Xu
- Otolaryngology & Head and Neck Center, Cancer Center, Department of Head and Neck Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou 310014, Zhejiang, China; Zhejiang Provincial Clinical Research Center for Head & Neck Cancer, Hangzhou 310014, China; Zhejiang Key Laboratory of Precision Medicine Research on Head & Neck Cancer, Hangzhou 310014, China.
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Hanna K, Asiedu AL, Theurer T, Muirhead D, Speirs V, Oweis Y, Abu-Eid R. Advances in Raman spectroscopy for characterising oral cancer and oral potentially malignant disorders. Expert Rev Mol Med 2024; 26:e25. [PMID: 39375841 PMCID: PMC11488342 DOI: 10.1017/erm.2024.26] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 06/18/2024] [Accepted: 08/16/2024] [Indexed: 10/09/2024]
Abstract
Oral cancer survival rates have seen little improvement over the past few decades. This is mainly due to late detection and a lack of reliable markers to predict disease progression in oral potentially malignant disorders (OPMDs). There is a need for highly specific and sensitive screening tools to enable early detection of malignant transformation. Biochemical alterations to tissues occur as an early response to pathological processes; manifesting as modifications to molecular structure, concentration or conformation. Raman spectroscopy is a powerful analytical technique that can probe these biochemical changes and can be exploited for the generation of novel disease-specific biomarkers. Therefore, Raman spectroscopy has the potential as an adjunct tool that can assist in the early diagnosis of oral cancer and the detection of disease progression in OPMDs. This review describes the use of Raman spectroscopy for the diagnosis of oral cancer and OPMDs based on ex vivo and liquid biopsies as well as in vivo applications that show the potential of this powerful tool to progress from benchtop to chairside.
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Affiliation(s)
- Katie Hanna
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Scotland, UK
- Aberdeen Cancer Centre, University of Aberdeen, Scotland, UK
| | - Anna-Lena Asiedu
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Scotland, UK
| | - Thomas Theurer
- School of Geoscience, University of Aberdeen, Aberdeen, Scotland, UK
| | - David Muirhead
- School of Geoscience, University of Aberdeen, Aberdeen, Scotland, UK
| | - Valerie Speirs
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Scotland, UK
- Aberdeen Cancer Centre, University of Aberdeen, Scotland, UK
| | - Yara Oweis
- School of Dentistry, University of Jordan, Amman, Jordan
| | - Rasha Abu-Eid
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Scotland, UK
- Aberdeen Cancer Centre, University of Aberdeen, Scotland, UK
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Pierfelice TV, D’Amico E, Cinquini C, Iezzi G, D’Arcangelo C, D’Ercole S, Petrini M. The Diagnostic Potential of Non-Invasive Tools for Oral Cancer and Precancer: A Systematic Review. Diagnostics (Basel) 2024; 14:2033. [PMID: 39335712 PMCID: PMC11431589 DOI: 10.3390/diagnostics14182033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2024] [Revised: 08/24/2024] [Accepted: 09/12/2024] [Indexed: 09/30/2024] Open
Abstract
OBJECTIVES This systematic review aimed to analyse the published evidence for the use of non-invasive methods for the early detection of oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMDs). METHODS The literature was systematically searched through several databases: PubMed, Cochrane Library, and Web of Science. Additional exploration was performed through cross-checks on the bibliographies of selected reviews. The inclusion criteria involved studies assessing the application of non-invasive tests on humans in the screening, diagnosis, or surveillance of OSCC or OPMDs and reporting sensitivity (SE) and specificity (SP). The Newcastle-Ottawa scale (NOS) was applied to assess the quality of the studies included. RESULTS The search strategy resulted in 8012 preliminary records. After a duplicate check, 116 titles remained. After abstract analysis, 70 papers remained. After full text analysis, only 54 of the 70 papers fit the inclusion criteria (28 were original articles and 26 were reviews). Those 26 reviews were used to manually search for further original articles. From this last search, 33 original articles were found. Thus, a total of 61 original studies were included and investigated. Findings from this systematic review indicate useful information, such as a description of the mechanisms, ease of use, limitations, and SE and SP values, to drive the choice of the optimal minimally invasive method to be utilized as an adjunctive tool to examine the suspicious lesions. CONCLUSIONS Each of the analysed tools can be improved or implemented, considering their high SE and low SP. Despite advancements, incisional biopsy continues to be the gold standard for the definitive diagnosis of oral cancer and precancerous lesions. Further research and development are essential to improving the sensitivity, specificity, and reliability of non-invasive tools for widespread clinical application.
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Affiliation(s)
- Tania Vanessa Pierfelice
- Department of Medical, Oral and Biotechnological Sciences, University “G. d’Annunzio” of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy; (T.V.P.); (E.D.); (G.I.); (C.D.); (S.D.)
| | - Emira D’Amico
- Department of Medical, Oral and Biotechnological Sciences, University “G. d’Annunzio” of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy; (T.V.P.); (E.D.); (G.I.); (C.D.); (S.D.)
| | - Chiara Cinquini
- Department of Surgical, Medical, Molecular Pathologies and of the Critical Needs, School of Dentistry, University of Pisa, 56100 Pisa, Italy;
| | - Giovanna Iezzi
- Department of Medical, Oral and Biotechnological Sciences, University “G. d’Annunzio” of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy; (T.V.P.); (E.D.); (G.I.); (C.D.); (S.D.)
| | - Camillo D’Arcangelo
- Department of Medical, Oral and Biotechnological Sciences, University “G. d’Annunzio” of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy; (T.V.P.); (E.D.); (G.I.); (C.D.); (S.D.)
| | - Simonetta D’Ercole
- Department of Medical, Oral and Biotechnological Sciences, University “G. d’Annunzio” of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy; (T.V.P.); (E.D.); (G.I.); (C.D.); (S.D.)
| | - Morena Petrini
- Department of Medical, Oral and Biotechnological Sciences, University “G. d’Annunzio” of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy; (T.V.P.); (E.D.); (G.I.); (C.D.); (S.D.)
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Matthies L, Amir-Kabirian H, Gebrekidan MT, Braeuer AS, Speth US, Smeets R, Hagel C, Gosau M, Knipfer C, Friedrich RE. Raman difference spectroscopy and U-Net convolutional neural network for molecular analysis of cutaneous neurofibroma. PLoS One 2024; 19:e0302017. [PMID: 38603731 PMCID: PMC11008861 DOI: 10.1371/journal.pone.0302017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 03/26/2024] [Indexed: 04/13/2024] Open
Abstract
In Neurofibromatosis type 1 (NF1), peripheral nerve sheaths tumors are common, with cutaneous neurofibromas resulting in significant aesthetic, painful and functional problems requiring surgical removal. To date, determination of adequate surgical resection margins-complete tumor removal while attempting to preserve viable tissue-remains largely subjective. Thus, residual tumor extension beyond surgical margins or recurrence of the disease may frequently be observed. Here, we introduce Shifted-Excitation Raman Spectroscopy in combination with deep neural networks for the future perspective of objective, real-time diagnosis, and guided surgical ablation. The obtained results are validated through established histological methods. In this study, we evaluated the discrimination between cutaneous neurofibroma (n = 9) and adjacent physiological tissues (n = 25) in 34 surgical pathological specimens ex vivo at a total of 82 distinct measurement loci. Based on a convolutional neural network (U-Net), the mean raw Raman spectra (n = 8,200) were processed and refined, and afterwards the spectral peaks were assigned to their respective molecular origin. Principal component and linear discriminant analysis was used to discriminate cutaneous neurofibromas from physiological tissues with a sensitivity of 100%, specificity of 97.3%, and overall classification accuracy of 97.6%. The results enable the presented optical, non-invasive technique in combination with artificial intelligence as a promising candidate to ameliorate both, diagnosis and treatment of patients affected by cutaneous neurofibroma and NF1.
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Affiliation(s)
- Levi Matthies
- Department of Oral and Maxillofacial Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Mildred Scheel Cancer Career Center HaTriCS4, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hendrik Amir-Kabirian
- Department of Oral and Maxillofacial Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Medhanie T. Gebrekidan
- Institute of Thermal-, Environmental- and Resources‘ Process Engineering, Technische Universität Bergakademie Freiberg, Freiberg, Germany
| | - Andreas S. Braeuer
- Institute of Thermal-, Environmental- and Resources‘ Process Engineering, Technische Universität Bergakademie Freiberg, Freiberg, Germany
| | - Ulrike S. Speth
- Department of Oral and Maxillofacial Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Ralf Smeets
- Department of Oral and Maxillofacial Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Division of “Regenerative Orofacial Medicine”, Department of Oral and Maxillofacial Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian Hagel
- Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Martin Gosau
- Department of Oral and Maxillofacial Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian Knipfer
- Department of Oral and Maxillofacial Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Reinhard E. Friedrich
- Department of Oral and Maxillofacial Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Xi Z, Zhang R, Kiessling F, Lammers T, Pallares RM. Role of Surface Curvature in Gold Nanostar Properties and Applications. ACS Biomater Sci Eng 2024; 10:38-50. [PMID: 37249042 DOI: 10.1021/acsbiomaterials.3c00249] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Gold nanostars (AuNSs) are nanoparticles with intricate three-dimensional structures and shape-dependent optoelectronic properties. For example, AuNSs uniquely display three distinct surface curvatures, i.e. neutral, positive, and negative, which provide different environments to adsorbed ligands. Hence, these curvatures are used to introduce different surface chemistries in nanoparticles. This review summarizes and discusses the role of surface curvature in AuNS properties and its impact on biomedical and chemical applications, including surface-enhanced Raman spectroscopy, contrast agent performance, and catalysis. We examine the main synthetic approaches to generate AuNSs, control their morphology, and discuss their benefits and drawbacks. We also describe the optical characteristics of AuNSs and discuss how these depend on nanoparticle morphology. Finally, we analyze how AuNS surface curvature endows them with properties distinctly different from those of other nanoparticles, such as strong electromagnetic fields at the tips and increased hydrophilic environments at the indentations, together making AuNSs uniquely useful for biosensing, imaging, and local chemical manipulation.
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Affiliation(s)
- Zhongqian Xi
- Biohybrid Nanomedical Materials Group, Institute for Experimental Molecular Imaging, RWTH Aachen University Hospital, Aachen 52074, Germany
- Institute for Experimental Molecular Imaging, RWTH Aachen University Hospital, Aachen 52074, Germany
| | - Rui Zhang
- Biohybrid Nanomedical Materials Group, Institute for Experimental Molecular Imaging, RWTH Aachen University Hospital, Aachen 52074, Germany
- Institute for Experimental Molecular Imaging, RWTH Aachen University Hospital, Aachen 52074, Germany
| | - Fabian Kiessling
- Institute for Experimental Molecular Imaging, RWTH Aachen University Hospital, Aachen 52074, Germany
| | - Twan Lammers
- Institute for Experimental Molecular Imaging, RWTH Aachen University Hospital, Aachen 52074, Germany
| | - Roger M Pallares
- Biohybrid Nanomedical Materials Group, Institute for Experimental Molecular Imaging, RWTH Aachen University Hospital, Aachen 52074, Germany
- Institute for Experimental Molecular Imaging, RWTH Aachen University Hospital, Aachen 52074, Germany
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Vlocskó M, Piffkó J, Janovszky Á. Intraoperative Assessment of Resection Margin in Oral Cancer: The Potential Role of Spectroscopy. Cancers (Basel) 2023; 16:121. [PMID: 38201548 PMCID: PMC10777979 DOI: 10.3390/cancers16010121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 01/12/2024] Open
Abstract
In parallel with the increasing number of oncological cases, the need for faster and more efficient diagnostic tools has also appeared. Different diagnostic approaches are available, such as radiological imaging or histological staining methods, but these do not provide adequate information regarding the resection margin, intraoperatively, or are time consuming. The purpose of this review is to summarize the current knowledge on spectrometric diagnostic modalities suitable for intraoperative use, with an emphasis on their relevance in the management of oral cancer. The literature agrees on the sensitivity, specificity, and accuracy of spectrometric diagnostic modalities, but further long-term prospective, multicentric clinical studies are needed, which may standardize the intraoperative assessment of the resection margin and the use of real-time spectroscopic approaches.
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Affiliation(s)
| | | | - Ágnes Janovszky
- Department of Oral and Maxillofacial Surgery, Albert Szent-Györgyi Medical School, University of Szeged, Kálvária 57, H-6725 Szeged, Hungary; (M.V.); (J.P.)
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Sharma M, Li YC, Manjunatha SN, Tsai CL, Lin RM, Huang SF, Chang LB. Identification of Healthy Tissue from Malignant Tissue in Surgical Margin Using Raman Spectroscopy in Oral Cancer Surgeries. Biomedicines 2023; 11:1984. [PMID: 37509623 PMCID: PMC10377260 DOI: 10.3390/biomedicines11071984] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 07/04/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Accurate identification of tissue types in surgical margins is essential for ensuring the complete removal of cancerous cells and minimizing the risk of recurrence. The objective of this study was to explore the clinical utility of Raman spectroscopy for the detection of oral squamous cell carcinoma (OSCC) in both tumor and healthy tissues obtained from surgical resection specimens during surgery. This study enrolled a total of 64 patients diagnosed with OSCC. Among the participants, approximately 50% of the cases were classified as the most advanced stage, referred to as T4. Raman experiments were conducted on cryopreserved tissue samples collected from patients diagnosed with OSCC. Prominent spectral regions containing key oral biomarkers were analyzed using the partial least squares-support vector machine (PLS-SVM) method, which is a powerful multivariate analysis technique for discriminant analysis. This approach effectively differentiated OSCC tissue from non-OSCC tissue, achieving a sensitivity of 95.7% and a specificity of 93.3% with 94.7% accuracy. In the current study, Raman analysis of fresh tissue samples showed that OSCC tissues contained significantly higher levels of nucleic acids, proteins, and several amino acids compared to the adjacent healthy tissues. In addition to differentiating between OSCC and non-OSCC tissues, we have also explored the potential of Raman spectroscopy in classifying different stages of OSCC. Specifically, we have investigated the classification of T1, T2, T3, and T4 stages based on their Raman spectra. These findings emphasize the importance of considering both stage and subsite factors in the application of Raman spectroscopy for OSCC analysis. Future work will focus on expanding our tissue sample collection to better comprehend how different subsites influence the Raman spectra of OSCC at various stages, aiming to improve diagnostic accuracy and aid in identifying tumor-free margins during surgical interventions.
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Affiliation(s)
- Mukta Sharma
- Department of Electronic Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Ying-Chang Li
- Department of Ph.D. Program, Prospective Technology of Electrical Engineering and Computer Science, National Chin-Yi University of Technology, Taichung 411030, Taiwan
| | - S N Manjunatha
- Department of Electronic Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Chia-Lung Tsai
- Department of Electronic Engineering, Chang Gung University, Taoyuan 33302, Taiwan
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 333, Taiwan
| | - Ray-Ming Lin
- Department of Electronic Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Shiang-Fu Huang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 333, Taiwan
- Department of Public Health, Chang Gung University, Taoyuan 33302, Taiwan
| | - Liann-Be Chang
- Department of Electronic Engineering, Chang Gung University, Taoyuan 33302, Taiwan
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Lin J, Lin D, Qiu S, Huang Z, Liu F, Huang W, Xu Y, Zhang X, Feng S. Shifted-excitation Raman difference spectroscopy for improving in vivo detection of nasopharyngeal carcinoma. Talanta 2023; 257:124330. [PMID: 36773510 DOI: 10.1016/j.talanta.2023.124330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/03/2023] [Accepted: 02/05/2023] [Indexed: 02/10/2023]
Abstract
A strong fluorescence background is one of the common interference factors of Raman spectroscopic analysis in biological tissue. This study developed an endoscopic shifted-excitation Raman difference spectroscopy (SERDS) system for real-time in vivo detection of nasopharyngeal carcinoma (NPC) for the first time. Owing to the use of the SERDS method, the high-quality Raman signals of nasopharyngeal tissue could be well extracted and characterized from the complex raw spectra by removing the fluorescence interference signals. Significant spectral differences relating to proteins, phospholipids, glucose, and DNA were found between 42 NPC and 42 normal tissue sites. Using linear discriminant analysis, the diagnostic accuracy of SERDS for NPC detection was 100%, which was much higher than that of raw Raman spectroscopy (75.0%), showing the great potential of SERDS for improving the accurate in vivo detection of NPC.
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Affiliation(s)
- Jinyong Lin
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China; Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou, 350007, China
| | - Duo Lin
- Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou, 350007, China
| | - Sufang Qiu
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Zufang Huang
- Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou, 350007, China.
| | - Feng Liu
- Simple & Smart Instrument (Beijing) Co.,Ltd, China
| | - Wei Huang
- Department of Forensic Science, Fujian Police College, Fuzhou, 350007, PR China
| | - Yuanji Xu
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Xianzeng Zhang
- Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou, 350007, China.
| | - Shangyuan Feng
- Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou, 350007, China.
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Han R, Lin N, Huang J, Ma X. Diagnostic accuracy of Raman spectroscopy in oral squamous cell carcinoma. Front Oncol 2022; 12:925032. [PMID: 35992884 PMCID: PMC9389172 DOI: 10.3389/fonc.2022.925032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 07/06/2022] [Indexed: 11/13/2022] Open
Abstract
Background Raman spectroscopy (RS) has shown great potential in the diagnosis of oral squamous cell carcinoma (OSCC). Although many single-central original studies have been carried out, it is difficult to use RS in real clinical settings based on the current limited evidence. Herein, we conducted this meta-analysis of diagnostic studies to evaluate the overall performance of RS in OSCC diagnosis. Methods We systematically searched databases including Medline, Embase, and Web of Science for studies from January 2000 to March 2022. Data of true positives, true negatives, false positives, and false negatives were extracted from the included studies to calculate the pooled sensitivity, specificity, accuracy, positive and negative likelihood ratios (LRs), and diagnostic odds ratio (DOR) with 95% confidence intervals, then we plotted the summary receiver operating characteristic (SROC) curve and the area under the curve (AUC) to evaluate the overall performance of RS. Quality assessments and publication bias were evaluated by Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) checklist in Review Manager 5.3. The statistical parameters were calculated with StataSE version 12 and MetaDiSc 1.4. Results In total, 13 studies were included in our meta-analysis. The pooled diagnostic sensitivity and specificity of RS in OSCC were 0.89 (95% CI, 0.85–0.92) and 0.84 (95% CI, 0.78–0.89). The AUC of SROC curve was 0.93 (95% CI, 0.91–0.95). Conclusions RS is a non-invasive diagnostic technology with high specificity and sensitivity for detecting OSCC and has the potential to be applied clinically.
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Affiliation(s)
- Ruiying Han
- Department of Biotherapy, West China Hospital and State Key Laboratory of Biotherapy, Sichuan University, Chengdu, China
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Sichuan University, Chengdu, China
| | - Nan Lin
- Department of Biotherapy, West China Hospital and State Key Laboratory of Biotherapy, Sichuan University, Chengdu, China
| | - Juan Huang
- Department of Hematology, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
- *Correspondence: Xuelei Ma, ; Juan Huang,
| | - Xuelei Ma
- Department of Biotherapy, West China Hospital and State Key Laboratory of Biotherapy, Sichuan University, Chengdu, China
- *Correspondence: Xuelei Ma, ; Juan Huang,
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Faur C, Falamas A, Chirila M, Roman R, Rotaru H, Moldovan M, Albu S, Baciut M, Robu I, Hedesiu M. Raman spectroscopy in oral cavity and oropharyngeal cancer: a systematic review. Int J Oral Maxillofac Surg 2022; 51:1373-1381. [DOI: 10.1016/j.ijom.2022.02.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 02/22/2022] [Accepted: 02/25/2022] [Indexed: 12/24/2022]
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Sharma M, Jeng MJ, Young CK, Huang SF, Chang LB. Developing an Algorithm for Discriminating Oral Cancerous and Normal Tissues Using Raman Spectroscopy. J Pers Med 2021; 11:1165. [PMID: 34834517 PMCID: PMC8623962 DOI: 10.3390/jpm11111165] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 11/01/2021] [Accepted: 11/08/2021] [Indexed: 11/17/2022] Open
Abstract
The aim of this study was to investigate the clinical potential of Raman spectroscopy (RS) in detecting oral squamous cell carcinoma (OSCC) in tumor and healthy tissues in surgical resection specimens during surgery. Raman experiments were performed on cryopreserved specimens from patients with OSCC. Univariate and multivariate analysis was performed based on the fingerprint region (700-1800 cm-1) of the Raman spectra. One hundred thirty-one ex-vivo Raman experiments were performed on 131 surgical resection specimens obtained from 67 patients. The principal component analysis (PCA) and partial least square (PLS) methods with linear discriminant analysis (LDA) were applied on an independent validation dataset. Both models were able to differentiate between the tissue types, but PLS-LDA showed 100% accuracy, sensitivity, and specificity. In this study, Raman measurements of fresh resection tissue specimens demonstrated that OSCC had significantly higher nucleic acid, protein, and several amino acid contents than adjacent healthy tissues. The specific spectral information obtained in this study can be used to develop an in vivo Raman spectroscopic method for the tumor-free resection boundary during surgery.
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Affiliation(s)
- Mukta Sharma
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan; (M.S.); (L.-B.C.)
| | - Ming-Jer Jeng
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan; (M.S.); (L.-B.C.)
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan;
| | - Chi-Kuang Young
- Department of Otolaryngology, Head and Neck Surgery, Chang Gung Memorial Hospital, Keelung Branch, Keelung 204, Taiwan;
| | - Shiang-Fu Huang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan;
- Department of Public Health, Chang Gung University, Taoyuan 333, Taiwan
| | - Liann-Be Chang
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan; (M.S.); (L.-B.C.)
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan;
- Green Technology Research Center, Chang Gung University, Taoyuan 333, Taiwan
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12
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Korinth F, Shaik TA, Popp J, Krafft C. Assessment of shifted excitation Raman difference spectroscopy in highly fluorescent biological samples. Analyst 2021; 146:6760-6767. [PMID: 34704561 DOI: 10.1039/d1an01376a] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Shifted excitation Raman difference spectroscopy (SERDS) can be used as an instrumental baseline correction technique to retrieve Raman bands in highly fluorescent samples. Genipin (GE) cross-linked equine pericardium (EP) was used as a model system since a blue pigment is formed upon cross-linking, which results in a strong fluorescent background in the Raman spectra. EP was cross-linked with 0.25% GE solution for 0.5 h, 2 h, 4 h, 6 h, 12 h, and 24 h, and compared with corresponding untreated EP. Raman spectra were collected with three different excitation wavelengths. For the assessment of the SERDS technique, the preprocessed SERDS spectra of two excitation wavelengths (784 nm-786 nm) were compared with the mathematical baseline-corrected Raman spectra at 785 nm excitation using extended multiplicative signal correction, rubberband, the sensitive nonlinear iterative peak and polynomial fitting algorithms. Whereas each baseline correction gave poor quality spectra beyond 6 h GE crosslinking with wave-like artefacts, the SERDS technique resulted in difference spectra, that gave superior reconstructed spectra with clear collagen and resonance enhanced GE pigment bands with lower standard deviation. Key for this progress was an advanced difference optimization approach that is described here. Furthermore, the results of the SERDS technique were independent of the intensity calibration because the system transfer response was compensated by calculating the difference spectrum. We conclude that this SERDS strategy can be transferred to Raman studies on biological and non-biological samples with a strong fluorescence background at 785 nm and also shorter excitation wavelengths which benefit from more intense scattering intensities and higher quantum efficiencies of CCD detectors.
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Affiliation(s)
- Florian Korinth
- Leibniz Institute of Photonic Technology and Member of Leibniz Research Alliance "Health Technologies", 07745 Jena, Germany. .,Leibniz Institute for Astrophysics Potsdam and Member of Leibniz Research Alliance "Health Technologies", 14482 Potsdam, Germany
| | - Tanveer Ahmed Shaik
- Leibniz Institute of Photonic Technology and Member of Leibniz Research Alliance "Health Technologies", 07745 Jena, Germany.
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology and Member of Leibniz Research Alliance "Health Technologies", 07745 Jena, Germany. .,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, 07743 Jena, Germany
| | - Christoph Krafft
- Leibniz Institute of Photonic Technology and Member of Leibniz Research Alliance "Health Technologies", 07745 Jena, Germany.
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Yerolatsitis S, Kufcsák A, Ehrlich K, Wood HAC, Fernandes S, Quinn T, Young V, Young I, Hamilton K, Akram AR, Thomson RR, Finlayson K, Dhaliwal K, Stone JM. Sub millimetre flexible fibre probe for background and fluorescence free Raman spectroscopy. JOURNAL OF BIOPHOTONICS 2021; 14:e202000488. [PMID: 33855811 DOI: 10.1002/jbio.202000488] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 03/26/2021] [Accepted: 04/11/2021] [Indexed: 06/12/2023]
Abstract
Using the shifted-excitation Raman difference spectroscopy technique and an optical fibre featuring a negative curvature excitation core and a coaxial ring of high numerical aperture collection cores, we have developed a portable, background and fluorescence free, endoscopic Raman probe. The probe consists of a single fibre with a diameter of less than 0.25 mm packaged in a sub-millimetre tubing, making it compatible with standard bronchoscopes. The Raman excitation light in the fibre is guided in air and therefore interacts little with silica, enabling an almost background free transmission of the excitation light. In addition, we used the shifted-excitation Raman difference spectroscopy technique and a tunable 785 nm laser to separate the fluorescence and the Raman spectrum from highly fluorescent samples, demonstrating the suitability of the probe for biomedical applications. Using this probe we also acquired fluorescence free human lung tissue data.
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Affiliation(s)
| | - András Kufcsák
- Translational Healthcare Technologies Team, Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Katjana Ehrlich
- Translational Healthcare Technologies Team, Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
- Scottish Universities Physics Alliance (SUPA), Institute of Photonics and Quantum Sciences, Heriot-Watt University, Edinburgh, UK
| | | | - Susan Fernandes
- Translational Healthcare Technologies Team, Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Tom Quinn
- Translational Healthcare Technologies Team, Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Vikki Young
- Translational Healthcare Technologies Team, Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Irene Young
- Translational Healthcare Technologies Team, Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Katie Hamilton
- Translational Healthcare Technologies Team, Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Ahsan R Akram
- Translational Healthcare Technologies Team, Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Robert R Thomson
- Scottish Universities Physics Alliance (SUPA), Institute of Photonics and Quantum Sciences, Heriot-Watt University, Edinburgh, UK
| | - Keith Finlayson
- Translational Healthcare Technologies Team, Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Kevin Dhaliwal
- Translational Healthcare Technologies Team, Centre for Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
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14
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Song D, Chen Y, Li J, Wang H, Ning T, Wang S. A graphical user interface (NWUSA) for Raman spectral processing, analysis and feature recognition. JOURNAL OF BIOPHOTONICS 2021; 14:e202000456. [PMID: 33547854 DOI: 10.1002/jbio.202000456] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 01/20/2021] [Accepted: 02/04/2021] [Indexed: 05/08/2023]
Abstract
It is a practical necessity for non-professional users to interpret biologically derived Raman spectral information for obtaining accurate and reliable analytical results. An integrated Raman spectral analysis software (NWUSA) was developed for spectral processing, analysis, and feature recognition. It provides a user-friendly graphical interface to perform the following preprocessing tasks: spectral range selection, cosmic ray removal, polynomial fitting based background subtraction, Savitzky-Golay smoothing, area-under-curve normalization, mean-centered procedure, as well as multivariate analysis algorithms including principal component analysis (PCA), linear discriminant analysis, partial least squares-discriminant analysis, support vector machine (SVM), and PCA-SVM. A spectral dataset obtained from two different samples was utilized to evaluate the performance of the developed software, which demonstrated that the analysis software can quickly and accurately achieve functional requirements in spectral data processing and feature recognition. Besides, the open-source software can not only be customized with more novel functional modules to suit the specific needs, but also benefit many Raman based investigations, especially for clinical usages.
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Affiliation(s)
- Dongliang Song
- State Key Laboratory of Photon-Technology in Western China Energy, Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, China
| | - Yishen Chen
- State Key Laboratory of Photon-Technology in Western China Energy, Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, China
| | - Jie Li
- State Key Laboratory of Photon-Technology in Western China Energy, Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, China
| | - Haifeng Wang
- State Key Laboratory of Photon-Technology in Western China Energy, Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, China
| | - Tian Ning
- State Key Laboratory of Photon-Technology in Western China Energy, Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, China
| | - Shuang Wang
- State Key Laboratory of Photon-Technology in Western China Energy, Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, China
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15
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Matthies L, Gebrekidan MT, Tegtmeyer JF, Oetter N, Rohde M, Vollkommer T, Smeets R, Wilczak W, Stelzle F, Gosau M, Braeuer AS, Knipfer C. Optical diagnosis of oral cavity lesions by label-free Raman spectroscopy. BIOMEDICAL OPTICS EXPRESS 2021; 12:836-851. [PMID: 33680545 PMCID: PMC7901324 DOI: 10.1364/boe.409456] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 11/21/2020] [Accepted: 12/08/2020] [Indexed: 06/12/2023]
Abstract
Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers and frequently preceded by non-malignant lesions. Using Shifted-Excitation Raman Difference Spectroscopy (SERDS), principal component and linear discriminant analysis in native tissue specimens, 9500 raw Raman spectra of OSCC, 4300 of non-malignant lesions and 4200 of physiological mucosa were evaluated. Non-malignant lesions were distinguished from physiological mucosa with a classification accuracy of 95.3% (95.4% sensitivity, 95.2% specificity, area under the curve (AUC) 0.99). Discriminating OSCC from non-malignant lesions showed an accuracy of 88.4% (93.7% sensitivity, 76.7% specificity, AUC 0.93). OSCC was identified against physiological mucosa with an accuracy of 89.8% (93.7% sensitivity, 81.0% specificity, AUC 0.90). These findings underline the potential of SERDS for the diagnosis of oral cavity lesions.
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Affiliation(s)
- Levi Matthies
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
- These authors contributed equally
| | - Medhanie T. Gebrekidan
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen Graduate School in Advanced Optical Technologies (SAOT), Paul-Gordan-Straße 6, D-91054 Erlangen, Germany
- Technische Universität Bergakademie Freiberg (TUBAF), Institute of Thermal-, Environmental- and Resources‘ Process Engineering (ITUN), Leipziger Straße 28, D-09599 Freiberg, Germany
- These authors contributed equally
| | - Jasper F. Tegtmeyer
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
| | - Nicolai Oetter
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen Graduate School in Advanced Optical Technologies (SAOT), Paul-Gordan-Straße 6, D-91054 Erlangen, Germany
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Oral and Maxillofacial Surgery, Glückstraße 11, D-91054 Erlangen, Germany
| | - Maximilian Rohde
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Oral and Maxillofacial Surgery, Glückstraße 11, D-91054 Erlangen, Germany
| | - Tobias Vollkommer
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
| | - Ralf Smeets
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
| | - Waldemar Wilczak
- University Medical Center Hamburg-Eppendorf (UKE), Institute of Pathology, Martinistraße 52, D-20246 Hamburg, Germany
| | - Florian Stelzle
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen Graduate School in Advanced Optical Technologies (SAOT), Paul-Gordan-Straße 6, D-91054 Erlangen, Germany
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Oral and Maxillofacial Surgery, Glückstraße 11, D-91054 Erlangen, Germany
| | - Martin Gosau
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
| | - Andreas S. Braeuer
- Technische Universität Bergakademie Freiberg (TUBAF), Institute of Thermal-, Environmental- and Resources‘ Process Engineering (ITUN), Leipziger Straße 28, D-09599 Freiberg, Germany
| | - Christian Knipfer
- University Medical Center Hamburg-Eppendorf (UKE), Department of Oral and Maxillofacial Surgery, Martinistraße 52, D-20246 Hamburg, Germany
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16
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Korinth F, Schmälzlin E, Stiebing C, Urrutia T, Micheva G, Sandin C, Müller A, Maiwald M, Sumpf B, Krafft C, Tränkle G, Roth MM, Popp J. Wide Field Spectral Imaging with Shifted Excitation Raman Difference Spectroscopy Using the Nod and Shuffle Technique. SENSORS (BASEL, SWITZERLAND) 2020; 20:E6723. [PMID: 33255459 PMCID: PMC7727830 DOI: 10.3390/s20236723] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 11/17/2020] [Accepted: 11/19/2020] [Indexed: 12/13/2022]
Abstract
Wide field Raman imaging using the integral field spectroscopy approach was used as a fast, one shot imaging method for the simultaneous collection of all spectra composing a Raman image. For the suppression of autofluorescence and background signals such as room light, shifted excitation Raman difference spectroscopy (SERDS) was applied to remove background artifacts in Raman spectra. To reduce acquisition times in wide field SERDS imaging, we adapted the nod and shuffle technique from astrophysics and implemented it into a wide field SERDS imaging setup. In our adapted version, the nod corresponds to the change in excitation wavelength, whereas the shuffle corresponds to the shifting of charges up and down on a Charge-Coupled Device (CCD) chip synchronous to the change in excitation wavelength. We coupled this improved wide field SERDS imaging setup to diode lasers with 784.4/785.5 and 457.7/458.9 nm excitation and applied it to samples such as paracetamol and aspirin tablets, polystyrene and polymethyl methacrylate beads, as well as pork meat using multiple accumulations with acquisition times in the range of 50 to 200 ms. The results tackle two main challenges of SERDS imaging: gradual photobleaching changes the autofluorescence background, and multiple readouts of CCD detector prolong the acquisition time.
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Affiliation(s)
- Florian Korinth
- Leibniz Institute of Photonic Technology (Leibniz IPHT), Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07743 Jena, Germany; (F.K.); (C.S.); (J.P.)
| | - Elmar Schmälzlin
- Leibniz Institute for Astrophysics Potsdam (AIP), Research Alliance “Health Technologies”, An der Sternwarte 16, 14482 Potsdam, Germany; (E.S.); (T.U.); (G.M.); (M.M.R.)
| | - Clara Stiebing
- Leibniz Institute of Photonic Technology (Leibniz IPHT), Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07743 Jena, Germany; (F.K.); (C.S.); (J.P.)
| | - Tanya Urrutia
- Leibniz Institute for Astrophysics Potsdam (AIP), Research Alliance “Health Technologies”, An der Sternwarte 16, 14482 Potsdam, Germany; (E.S.); (T.U.); (G.M.); (M.M.R.)
| | - Genoveva Micheva
- Leibniz Institute for Astrophysics Potsdam (AIP), Research Alliance “Health Technologies”, An der Sternwarte 16, 14482 Potsdam, Germany; (E.S.); (T.U.); (G.M.); (M.M.R.)
| | - Christer Sandin
- Sandin Advanced Visualization, Tylögränd 14, 12156 Johanneshov, Sweden;
| | - André Müller
- Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik, Research Alliance “Health Technologies”, Gustav-Kirchhoff-Str. 4, 12489 Berlin, Germany; (A.M.); (M.M.); (B.S.); (G.T.)
| | - Martin Maiwald
- Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik, Research Alliance “Health Technologies”, Gustav-Kirchhoff-Str. 4, 12489 Berlin, Germany; (A.M.); (M.M.); (B.S.); (G.T.)
| | - Bernd Sumpf
- Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik, Research Alliance “Health Technologies”, Gustav-Kirchhoff-Str. 4, 12489 Berlin, Germany; (A.M.); (M.M.); (B.S.); (G.T.)
| | - Christoph Krafft
- Leibniz Institute of Photonic Technology (Leibniz IPHT), Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07743 Jena, Germany; (F.K.); (C.S.); (J.P.)
| | - Günther Tränkle
- Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik, Research Alliance “Health Technologies”, Gustav-Kirchhoff-Str. 4, 12489 Berlin, Germany; (A.M.); (M.M.); (B.S.); (G.T.)
| | - Martin M. Roth
- Leibniz Institute for Astrophysics Potsdam (AIP), Research Alliance “Health Technologies”, An der Sternwarte 16, 14482 Potsdam, Germany; (E.S.); (T.U.); (G.M.); (M.M.R.)
| | - Jürgen Popp
- Leibniz Institute of Photonic Technology (Leibniz IPHT), Research Alliance “Health Technologies”, Albert-Einstein-Straße 9, 07743 Jena, Germany; (F.K.); (C.S.); (J.P.)
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
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17
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Jeng MJ, Sharma M, Sharma L, Huang SF, Chang LB, Wu SL, Chow L. Novel Quantitative Analysis Using Optical Imaging (VELscope) and Spectroscopy (Raman) Techniques for Oral Cancer Detection. Cancers (Basel) 2020; 12:E3364. [PMID: 33202869 PMCID: PMC7696965 DOI: 10.3390/cancers12113364] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 10/27/2020] [Accepted: 11/10/2020] [Indexed: 12/15/2022] Open
Abstract
In this study, we developed a novel quantitative analysis method to enhance the detection capability for oral cancer screening. We combined two different optical techniques, a light-based detection technique (visually enhanced lesion scope) and a vibrational spectroscopic technique (Raman spectroscopy). Materials and methods: Thirty-five oral cancer patients who went through surgery were enrolled. Thirty-five cancer lesions and thirty-five control samples with normal oral mucosa (adjacent to the cancer lesion) were analyzed. Thirty-five autofluorescence images and 70 Raman spectra were taken from 35 cancer and 35 control group cryopreserved samples. The normalized intensity and heterogeneity of the 70 regions of interest (ROIs) were calculated along with 70 averaged Raman spectra. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used with principal component analysis (PCA) to differentiate the cancer and control groups (normal). The classifications rates were validated using two different validation methods, leave-one-out cross-validation (LOOCV) and k-fold cross-validation. Results: The cryopreserved normal and tumor tissues were differentiated using the PCA-LDA and PCA-QDA models. The PCA-LDA of Raman spectroscopy (RS) had 82.9% accuracy, 80% sensitivity, and 85.7% specificity, while ROIs on the autofluorescence images were differentiated with 90% accuracy, 100% sensitivity, and 80% specificity. The combination of two optical techniques differentiated cancer and normal group with 97.14% accuracy, 100% sensitivity, and 94.3% specificity. Conclusion: In this study, we combined the data of two different optical techniques. Furthermore, PCA-LDA and PCA-QDA quantitative analysis models were used to differentiate tumor and normal groups, creating a complementary pathway for efficient tumor diagnosis. The error rates of RS and VELcope analysis were 17.10% and 10%, respectively, which was reduced to 3% when the two optical techniques were combined.
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Affiliation(s)
- Ming-Jer Jeng
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan; (M.-J.J.); (M.S.)
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan
| | - Mukta Sharma
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan; (M.-J.J.); (M.S.)
| | - Lokesh Sharma
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 333, Taiwan; (L.S.); (S.-L.W.)
| | - Shiang-Fu Huang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan
- Department of Public Health, Chang Gung University, Taoyuan 333, Taiwan
- Graduate Institute of Clinical Medical Sciences, Chang Gung University, Taoyuan 333, Taiwan
| | - Liann-Be Chang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan
- Green Technology Research Center, Chang Gung University, Guishan, Taoyuan 333, Taiwan
| | - Shih-Lin Wu
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 333, Taiwan; (L.S.); (S.-L.W.)
- Department of Cardiology, Chang Gung Memorial Hospital, Taoyuan 333, Taiwan
| | - Lee Chow
- Department of Physics, University of Central Florida, Orlando, FL 32816, USA;
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18
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Towards shifted position-diffuse reflectance imaging of anatomically correctly scaled human microvasculature. Sci Rep 2020; 10:17391. [PMID: 33060791 PMCID: PMC7567838 DOI: 10.1038/s41598-020-74447-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 09/30/2020] [Indexed: 11/10/2022] Open
Abstract
Due to significant advantages, the trend in the field of medical technology is moving towards minimally or even non-invasive examination methods. In this respect, optical methods offer inherent benefits, as does diffuse reflectance imaging (DRI). The present study attempts to prove the suitability of DRI—when implemented alongside a suitable setup and data evaluation algorithm—to derive information from anatomically correctly scaled human capillaries (diameter: \documentclass[12pt]{minimal}
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\begin{document}$$10\,\upmu \hbox {m}$$\end{document}10μm, length: \documentclass[12pt]{minimal}
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\begin{document}$$45\,\upmu \hbox {m}$$\end{document}45μm) by conducting extensive Monte–Carlo simulations and by verifying the findings through laboratory experiments. As a result, the method of shifted position-diffuse reflectance imaging (SP-DRI) is established by which average signal modulations of up to 5% could be generated with an illumination wavelength of \documentclass[12pt]{minimal}
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\begin{document}$$\lambda =424\,\hbox {nm}$$\end{document}λ=424nm and a core diameter of the illumination fiber of \documentclass[12pt]{minimal}
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\begin{document}$$50\,\upmu \hbox {m}$$\end{document}50μm. No reference image is needed for this technique. The present study reveals that the diffuse reflectance data in combination with the SP-DRI normalization are suitable to localize human capillaries within turbid media.
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19
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Zhan Q, Li Y, Yuan Y, Liu J, Li Y. The accuracy of Raman spectroscopy in the detection and diagnosis of oral cancer: A systematic review and meta‐analysis. JOURNAL OF RAMAN SPECTROSCOPY 2020. [DOI: 10.1002/jrs.5940] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- Qi Zhan
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology Sichuan University Chengdu China
| | - Yuan Li
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology Sichuan University Chengdu China
| | - Yihang Yuan
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology Sichuan University Chengdu China
| | - Jinchi Liu
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology Sichuan University Chengdu China
| | - Yi Li
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology Sichuan University Chengdu China
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20
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Diagnostic Adjuncts for Oral Cavity Squamous Cell Carcinoma and Oral Potentially Malignant Disorders. ACTA ACUST UNITED AC 2020. [DOI: 10.1007/978-3-030-32316-5_9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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21
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Can ethanol affect the cell structure? A dynamic molecular and Raman spectroscopy study. Photodiagnosis Photodyn Ther 2020; 30:101675. [PMID: 31991233 DOI: 10.1016/j.pdpdt.2020.101675] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 12/27/2019] [Accepted: 01/24/2020] [Indexed: 11/24/2022]
Abstract
The role that tobacco consumption plays in the etiology of oral cancer carcinogenesis, and of alcohol consumption acting as a co-factor, have been well established. However, in recent years, the contribution of alcohol consumption alone to oral cancer has been proposed. In fact, a high percentage of patients who develop oral cancer have both habits (tobacco and alcohol consumption), and other small patient groups only consume alcohol or do not have any other identifiable bad habits. In the present study we demonstrate, using a combination of dynamic molecular modelling and Raman spectroscopy, that ethanol has a significant effect on oral cells in vitro, mainly interacting with the lipids of the cell membrane, changing their conformation. Thus, it is possible to conclude that ethanol can affect the cell permeability, and by consequence serve as a possible trigger in oral carcinogenesis.
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22
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Sowoidnich K, Towrie M, Maiwald M, Sumpf B, Matousek P. Shifted Excitation Raman Difference Spectroscopy with Charge-Shifting Charge-Coupled Device (CCD) Lock-In Detection. APPLIED SPECTROSCOPY 2019; 73:1265-1276. [PMID: 31219325 DOI: 10.1177/0003702819859352] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Shifted excitation Raman difference spectroscopy (SERDS) can provide effective, chemically specific information on fluorescent samples. However, the restricted ability for fast alternating detection (usually < 10 Hz) of spectra excited at two shifted laser wavelengths can limit its effectiveness when rapidly varying emission backgrounds are present. This paper presents a novel charge-shifting lock-in approach permitting fast SERDS operation (exemplarily demonstrated at 1000 Hz) using a specialized dual-wavelength diode laser (emitting at 829.40 nm and 828.85 nm) and a custom-built charge-coupled device (CCD) enabling charge retention and shifting back and forth on the CCD chip. For six selected mineral samples (moved irregularly during spectral acquisition), results demonstrate superior reproducibility of the fast charge-shifting read-out over the conventional read-out (operated at 5.4 Hz). Partial least squares discriminant analysis revealed improved classification performance of charge-shifting (four latent variables, sensitivity: 99%, specificity: 94%) versus conventional read-out (six latent variables, sensitivity: 90%, specificity: 92%). The charge-shifting concept was also successfully translated to sub-surface analysis using spatially offset Raman spectroscopy (SORS). Charge-shifting SERDS-SORS spectra recorded from a polytetrafluoroethylene layer, concealed behind a 0.25 mm thick, opaque, heterogeneous layer, matched reference spectra much more closely and exhibited a signal-to-background-noise (S/NB) ratio two times higher than that achieved with conventional CCD read-out SERDS-SORS. The novel approach overcomes fundamental limitations of conventional CCDs. In conjunction with the inherent capability of the charge-shifting lock-in technique to suppress rapidly varying ambient light interference demonstrated by us earlier it is expected to be particularly beneficial with heterogeneous fluorescent samples in field applications.
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Affiliation(s)
- Kay Sowoidnich
- Central Laser Facility, Research Complex at Harwell, STFC Rutherford Appleton Laboratory, UKRI, Oxford, UK
- Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik, Berlin, Germany
| | - Michael Towrie
- Central Laser Facility, Research Complex at Harwell, STFC Rutherford Appleton Laboratory, UKRI, Oxford, UK
| | - Martin Maiwald
- Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik, Berlin, Germany
| | - Bernd Sumpf
- Ferdinand-Braun-Institut, Leibniz-Institut für Höchstfrequenztechnik, Berlin, Germany
| | - Pavel Matousek
- Central Laser Facility, Research Complex at Harwell, STFC Rutherford Appleton Laboratory, UKRI, Oxford, UK
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Jeng MJ, Sharma M, Sharma L, Chao TY, Huang SF, Chang LB, Wu SL, Chow L. Raman Spectroscopy Analysis for Optical Diagnosis of Oral Cancer Detection. J Clin Med 2019; 8:E1313. [PMID: 31461884 PMCID: PMC6780219 DOI: 10.3390/jcm8091313] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 08/17/2019] [Accepted: 08/22/2019] [Indexed: 12/11/2022] Open
Abstract
Raman spectroscopy (RS) is widely used as a non-invasive technique in screening for the diagnosis of oral cancer. The potential of this optical technique for several biomedical applications has been proved. This work studies the efficacy of RS in detecting oral cancer using sub-site-wise differentiation. A total of 80 samples (44 tumor and 36 normal) were cryopreserved from three different sub-sites: The tongue, the buccal mucosa, and the gingiva of the oral mucosa during surgery. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used with principal component analysis (PCA) to classify the samples and the classifications were validated by leave-one-out-cross-validation (LOOCV) and k-fold cross-validation methods. The normal and tumor tissues were differentiated under the PCA-LDA model with an accuracy of 81.25% (sensitivity: 77.27%, specificity: 86.11%). The PCA-QDA classifier model differentiated these tissues with an accuracy of 87.5% (sensitivity: 90.90%, specificity: 83.33%). The PCA-QDA classifier model outperformed the PCA-LDA-based classifier. The model studies revealed that protein, amino acid, and beta-carotene variations are the main biomolecular difference markers for detecting oral cancer.
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Affiliation(s)
- Ming-Jer Jeng
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan
| | - Mukta Sharma
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan
| | - Lokesh Sharma
- AI Innovation Research Center, Chang Gung University, Taoyuan 333, Taiwan
| | - Ting-Yu Chao
- Department of Electronic Engineering, Chang Gung University, Taoyuan 333, Taiwan
| | - Shiang-Fu Huang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan.
- Department of Public Health, Chang Gung University, Taoyuan 333, Taiwan.
| | - Liann-Be Chang
- Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Linkou 244, Taiwan.
- Green Technology Research Center, Chang Gung University, Taoyuan 333, Taiwan.
| | - Shih-Lin Wu
- AI Innovation Research Center, Chang Gung University, Taoyuan 333, Taiwan
- Department of Cardiology, Chang Gung Memorial Hospital, Taoyuan 333, Taiwan
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 333, Taiwan
| | - Lee Chow
- Department of Physics, University of Central Florida, Orlando, FL 32816, USA
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Ralbovsky NM, Lednev IK. Raman spectroscopy and chemometrics: A potential universal method for diagnosing cancer. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2019; 219:463-487. [PMID: 31075613 DOI: 10.1016/j.saa.2019.04.067] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 04/20/2019] [Accepted: 04/24/2019] [Indexed: 05/14/2023]
Abstract
Cancer is the second-leading cause of death worldwide. It affects an unfathomable number of people, with almost 16 million Americans currently living with it. While many cancers can be detected, current diagnostic efforts exhibit definite room for improvement. It is imperative that a person be diagnosed with cancer as early on in its progression as possible. An earlier diagnosis allows for the best treatment and intervention options available to be presented. Unfortunately, existing methods for diagnosing cancer can be expensive, invasive, inconclusive or inaccurate, and are not always made during initial stages of the disease. As such, there is a crucial unmet need to develop a singular universal method that is reliable, cost-effective, and non-invasive and can diagnose all forms of cancer early-on. Raman spectroscopy in combination with advanced statistical analysis is offered here as a potential solution for this need. This review covers recently published research in which Raman spectroscopy was used for the purpose of diagnosing cancer. The benefits and the risks of the methodology are presented; however, there is overwhelming evidence that suggests Raman spectroscopy is highly suitable for becoming the first universal method to be used for diagnosing cancer.
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Affiliation(s)
- Nicole M Ralbovsky
- Department of Chemistry, University at Albany, SUNY, 1400 Washington Avenue, Albany, NY 12222, USA
| | - Igor K Lednev
- Department of Chemistry, University at Albany, SUNY, 1400 Washington Avenue, Albany, NY 12222, USA.
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25
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Yu M, Yan H, Xia J, Zhu L, Zhang T, Zhu Z, Lou X, Sun G, Dong M. Deep convolutional neural networks for tongue squamous cell carcinoma classification using Raman spectroscopy. Photodiagnosis Photodyn Ther 2019; 26:430-435. [PMID: 31082525 DOI: 10.1016/j.pdpdt.2019.05.008] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 04/30/2019] [Accepted: 05/09/2019] [Indexed: 10/26/2022]
Abstract
With deep convolutional neural networks and fiber optic Raman spectroscopy, this study presents a novel classification method that discriminates tongue squamous cell carcinoma (TSCC) from non-tumorous tissue. To achieve this purpose, 24 tissues spectral data were first collected from 12 patients who had undergone a surgical resection due to the tongue squamous cell carcinomas. Then 6 blocks with each block including 1 convolutional layer and 1 max-pooling layer are used to extract the nonlinear feature representations from Raman spectra. The derived features form a representative vector, which is fed into a fully-connected network for performing classification task. Experimental results demonstrated that the proposed method achieved high sensitivity (99.31%) and specificity (94.44%). To show the superiority for the ConvNets classifier, comparison results with the state-of-the-art methods show it had a competitive classification accuracy. Moreover, these promising results may pave the way to apply the deep ConvNets model in the fiber optic Raman instrument for intra-operative evaluation of TSCC resection margins and improve patient survival.
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Affiliation(s)
- Mingxin Yu
- Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, No. 6 Hongxia Road, Chaoyang District, Beijing 100015, China.
| | - Hao Yan
- Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, No. 6 Hongxia Road, Chaoyang District, Beijing 100015, China.
| | - Jiabin Xia
- Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, No. 6 Hongxia Road, Chaoyang District, Beijing 100015, China.
| | - Lianqing Zhu
- Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, No. 6 Hongxia Road, Chaoyang District, Beijing 100015, China.
| | - Tao Zhang
- Department of stomatology, Peking Union Medical College Hospital, No. 1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing 100730, China.
| | - Zhihui Zhu
- Department of stomatology, Peking Union Medical College Hospital, No. 1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing 100730, China.
| | - Xiaoping Lou
- Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, No. 6 Hongxia Road, Chaoyang District, Beijing 100015, China.
| | - Guangkai Sun
- Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, No. 6 Hongxia Road, Chaoyang District, Beijing 100015, China.
| | - Mingli Dong
- Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, No. 6 Hongxia Road, Chaoyang District, Beijing 100015, China.
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26
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Transferability of Deep Learning Algorithms for Malignancy Detection in Confocal Laser Endomicroscopy Images from Different Anatomical Locations of the Upper Gastrointestinal Tract. BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES 2019. [DOI: 10.1007/978-3-030-29196-9_4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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27
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Cui X, Zhao Z, Zhang G, Chen S, Zhao Y, Lu J. Analysis and classification of kidney stones based on Raman spectroscopy. BIOMEDICAL OPTICS EXPRESS 2018; 9:4175-4183. [PMID: 30615745 PMCID: PMC6157795 DOI: 10.1364/boe.9.004175] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 06/27/2018] [Accepted: 07/25/2018] [Indexed: 05/08/2023]
Abstract
The number of patients with kidney stones worldwide is increasing, and it is particularly important to facilitate accurate diagnosis methods. Accurate analysis of the type of kidney stones plays a crucial role in the patient's follow-up treatment. This study used microscopic Raman spectroscopy to analyze and classify the different mineral components present in kidney stones. There were several Raman changes observed for the different types of kidney stones and the four types were oxalates, phosphates, purines and L-cystine kidney stones. We then combined machine learning techniques with Raman spectroscopy. KNN and SVM combinations with PCA (PCA-KNN, PCA-SVM) methods were implemented to classify the same spectral data set. The results show the diagnostic accuracies are 96.3% for the PCA-KNN and PCA-SVM methods with high sensitivity (0.963, 0.963) and specificity (0.995,0.985). The experimental Raman spectra results of kidney stones show the proposed method has high classification accuracy. This approach can provide support for physicians making treatment recommendations to patients with kidney stones.
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Affiliation(s)
- Xiaoyu Cui
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang 110167, China
- Authors contributed equally to this work
| | - Zeyin Zhao
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang 110167, China
- Authors contributed equally to this work
| | - Gejun Zhang
- Department of Urology, the First Hospital of China Medical University, Shenyang 110001, China
| | - Shuo Chen
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang 110167, China
| | - Yue Zhao
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang 110167, China
| | - Jiao Lu
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang 110167, China
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28
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Cordero E, Latka I, Matthäus C, Schie I, Popp J. In-vivo Raman spectroscopy: from basics to applications. JOURNAL OF BIOMEDICAL OPTICS 2018; 23:1-23. [PMID: 29956506 DOI: 10.1117/1.jbo.23.7.071210] [Citation(s) in RCA: 118] [Impact Index Per Article: 16.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Accepted: 05/23/2018] [Indexed: 05/20/2023]
Abstract
For more than two decades, Raman spectroscopy has found widespread use in biological and medical applications. The instrumentation and the statistical evaluation procedures have matured, enabling the lengthy transition from ex-vivo demonstration to in-vivo examinations. This transition goes hand-in-hand with many technological developments and tightly bound requirements for a successful implementation in a clinical environment, which are often difficult to assess for novice scientists in the field. This review outlines the required instrumentation and instrumentation parameters, designs, and developments of fiber optic probes for the in-vivo applications in a clinical setting. It aims at providing an overview of contemporary technology and clinical trials and attempts to identify future developments necessary to bring the emerging technology to the clinical end users. A comprehensive overview of in-vivo applications of fiber optic Raman probes to characterize different tissue and disease types is also given.
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Affiliation(s)
- Eliana Cordero
- Leibniz-Institut für Photonische Technologien e.V., Germany
| | - Ines Latka
- Leibniz-Institut für Photonische Technologien e.V., Germany
| | - Christian Matthäus
- Leibniz-Institut für Photonische Technologien e.V., Germany
- Institut für Physikalische Chemie, Friedrich-Schiller-Univ. Jena, Germany
- Abbe Ctr. of Photonics, Germany
| | - Iwan Schie
- Leibniz-Institut für Photonische Technologien e.V., Germany
| | - Jürgen Popp
- Leibniz-Institut für Photonische Technologien e.V., Germany
- Institute für Physikalische Chemie, Friedrich-Schiller-Univ. Jena, Germany
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29
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Holler S, Haig B, Donovan MJ, Sobrero M, Miles BA. A monolithic microsphere-fiber probe for spatially resolved Raman spectroscopy: Application to head and neck squamous cell carcinomas. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2018; 89:034301. [PMID: 29604745 DOI: 10.1063/1.5011771] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
The ability to identify precise cancer margins in vivo during a surgical excision is critical to the well-being of the patient. Decreased operative time has been linked to shorter patient recovery time, and there are risks associated with removing either too much or too little tissue from the surgical site. The more rapidly and accurately a surgeon can identify and excise diseased tissue, the better the prognosis for the patient. To this end, we investigate both malignant and healthy oral cavity tissue using the Raman spectroscopy, with a monolithic microsphere-fiber probe. Our results indicate that this probe has decreased the size of the analyzed area by more than an order of magnitude, as compared to a conventional fiber reflection probe. Scanning the probe across the tissues reveals variations in the Raman spectra that enable us to differentiate between malignant and healthy tissues. Consequently, we anticipate that the high spatial resolution afforded by the probe will permit us to identify tumor margins in detail, thereby optimizing tissue removal and improving patient outcomes.
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Affiliation(s)
- S Holler
- Department of Physics and Engineering Physics, Fordham University, 441 E. Fordham Road, Bronx, New York 10458, USA
| | - B Haig
- Department of Physics and Engineering Physics, Fordham University, 441 E. Fordham Road, Bronx, New York 10458, USA
| | - M J Donovan
- Department of Pathology, Icahn School of Medicine at Mount Sinai Hospital, 1 Gustave L. Levy Place, New York, New York 10029, USA
| | - M Sobrero
- Department of Otolaryngology Head and Neck Surgery, Icahn School of Medicine at Mount Sinai Hospital, 1 Gustave L. Levy Place, New York, New York 10029, USA
| | - B A Miles
- Department of Otolaryngology Head and Neck Surgery, Icahn School of Medicine at Mount Sinai Hospital, 1 Gustave L. Levy Place, New York, New York 10029, USA
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30
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Schuster JJ, Bahr LA, Fehr L, Tippelt M, Schulmeyr J, Wuzik A, Braeuer AS. Online monitoring of the supercritical CO2 extraction of hop. J Supercrit Fluids 2018. [DOI: 10.1016/j.supflu.2017.10.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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31
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Wang J, Zheng W, Lin K, Huang Z. Characterizing biochemical and morphological variations of clinically relevant anatomical locations of oral tissue in vivo with hybrid Raman spectroscopy and optical coherence tomography technique. JOURNAL OF BIOPHOTONICS 2018; 11. [PMID: 28985038 DOI: 10.1002/jbio.201700113] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Accepted: 10/04/2017] [Indexed: 05/08/2023]
Abstract
This study aims to characterize biochemical and morphological variations of the clinically relevant anatomical locations of in vivo oral tissue (ie, alveolar process, lateral tongue and floor of the mouth) by using hybrid Raman spectroscopy (RS) and optical coherence tomography (OCT) technique. A total of 1049 in vivo fingerprint (FP: 800-1800 cm-1 ) and high wavenumber (HW: 2800-3600 cm-1 ) Raman spectra were acquired from different oral tissue (alveolar process = 331, lateral tongue = 339 and floor of mouth = 379) of 26 normal subjects in the oral cavity under the OCT imaging guidance. The total Raman dataset were split into 2 parts: 80% for training and 20% for testing. Tissue optical attenuation coefficients of alveolar process, lateral tongue and the floor of the mouth were derived from OCT images, revealing the inter-anatomical morphological differences; while RS uncovers subtle FP/HW Raman spectral differences among different oral tissues that can be attributed to the differences in inter- and intra-cellular proteins, lipids, DNA and water structures and conformations, enlightening biochemical variability of different oral tissues at the molecular level. Partial least squares-discriminant analysis implemented on the training dataset show that the integrated tissue optical attenuation coefficients and FP/HW Raman spectra provide diagnostic sensitivities of 99.6%, 82.3%, 50.2%, and specificities of 97.0%, 75.1%, 92.1%, respectively, which are superior to using either RS (sensitivities of 90.2%, 77.5%, 48.8%, and specificities of 95.8%, 72.1%, 88.8%) or optical attenuation coefficients derived from OCT (sensitivities of 75.0%, 78.2%, 47.2%, and specificities of 96.2%, 67.7%, 85.0%) for the differentiation among alveolar process, lateral tongue and the floor of the mouth. Furthermore, the diagnostic algorithms applied to the independent testing dataset based on hybrid RS-OCT technique gives predictive diagnostic sensitivities of 100%, 76.5%, 51.3%, and specificities of 95.1%, 77.6%, 89.6%, respectively, for the classifications among alveolar process, lateral tongue and the floor of the mouth, which performs much better than either RS or optical attenuation coefficient derived from OCT imaging. This work suggests that inter-anatomical morphological and biochemical variability are significant which should be considered as an important parameter in the interpretation and rendering of hybrid RS-OCT technique for oral tissue diagnosis and characterization.
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Affiliation(s)
- Jianfeng Wang
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore
| | - Wei Zheng
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
| | - Kan Lin
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
| | - Zhiwei Huang
- Optical Bioimaging Laboratory, Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore
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Gebrekidan MT, Erber R, Hartmann A, Fasching PA, Emons J, Beckmann MW, Braeuer A. Breast Tumor Analysis Using Shifted-Excitation Raman Difference Spectroscopy (SERDS). Technol Cancer Res Treat 2018; 17:1533033818782532. [PMID: 29991340 PMCID: PMC6048663 DOI: 10.1177/1533033818782532] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Revised: 12/13/2017] [Accepted: 05/17/2018] [Indexed: 11/17/2022] Open
Abstract
We used a shifted-excitation Raman difference spectroscopy method for the ex vivo classification of resected and formalin-fixed breast tissue samples as normal (healthy) tissue, fibroadenoma, or invasive carcinoma. We analyzed 8 tissue samples containing invasive carcinoma that were surrounded by normal tissue and 3 tissue samples with fibroadenoma only. We made various measurement sites on various tissue samples, in total 240 measurements for each type of tissue. Although the acquired raw spectra contain enough information to clearly differentiate between normal and tumor (fibroadenoma and invasive carcinoma) tissue, the differentiation between fibroadenoma and invasive carcinoma was possible only after the shifted-excitation Raman difference spectroscopy isolation of pure Raman spectra from the heavily fluorescence interfered raw spectra. We used 784 and 785 nm as excitation wavelengths for the shifted-excitation Raman difference spectroscopy method. The differences in the obtained pure Raman spectra are assigned to the different chemical compositions of normal breast tissue, fibroadenoma, and invasive breast carcinoma. Principal component analysis and linear discriminant analysis showed excellent classification results in the Raman shift range between 1000 and 1800 cm-1. Invasive breast carcinoma was identified with 99.15% sensitivity, and the absence of invasive carcinoma was identified with 90.40% specificity. Tumor tissue in tumor-containing tissue was identified with 100% sensitivity, and the absence of tumor in no-tumor containing tissue was identified with 100% specificity. As gold standard for the determination of the sensitivity and the specificity, we considered the conventional histopathological classification. In summary, shifted-excitation Raman difference spectroscopy could be potentially very useful to support histopathological diagnosis in breast pathology.
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Affiliation(s)
- Medhanie Tesfay Gebrekidan
- Lehrstuhl für Technische Thermodynamik, Friedrich-Alexander-Universität
(FAU), Erlangen-Nürnberg, Germany
- Erlangen Graduate School in Advanced Optical Technologies (SAOT),
Friedrich-Alexander-Universität (FAU), Erlangen-Nürnberg, Germany
- Institut für Thermische Verfahrenstechnik, Umwelt- und
Naturstoffverfahrenstechnik, Technische Universität Bergakademie Freiberg (TUBAF), Freiberg,
Germany
| | - Ramona Erber
- Pathologisches Institut, Friedrich-Alexander-Universität (FAU),
Erlangen-Nürnberg, Germany
| | - Arndt Hartmann
- Pathologisches Institut, Friedrich-Alexander-Universität (FAU),
Erlangen-Nürnberg, Germany
| | - Peter A. Fasching
- Pathologisches Institut, Friedrich-Alexander-Universität (FAU),
Erlangen-Nürnberg, Germany
| | - Julius Emons
- Frauenklinik, Friedrich-Alexander-Universität (FAU), Erlangen-Nürnberg,
Germany
| | - Mathias W. Beckmann
- Frauenklinik, Friedrich-Alexander-Universität (FAU), Erlangen-Nürnberg,
Germany
| | - Andreas Braeuer
- Lehrstuhl für Technische Thermodynamik, Friedrich-Alexander-Universität
(FAU), Erlangen-Nürnberg, Germany
- Erlangen Graduate School in Advanced Optical Technologies (SAOT),
Friedrich-Alexander-Universität (FAU), Erlangen-Nürnberg, Germany
- Institut für Thermische Verfahrenstechnik, Umwelt- und
Naturstoffverfahrenstechnik, Technische Universität Bergakademie Freiberg (TUBAF), Freiberg,
Germany
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33
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de Carvalho LFDCES, Saito Nogueira M. New insights of Raman spectroscopy for oral clinical applications. Analyst 2018; 143:6037-6048. [DOI: 10.1039/c8an01363b] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Oral injuries are currently diagnosed by histopathological analysis of biopsy, which is an invasive procedure and does not give immediate results.
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34
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Aubreville M, Knipfer C, Oetter N, Jaremenko C, Rodner E, Denzler J, Bohr C, Neumann H, Stelzle F, Maier A. Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning. Sci Rep 2017; 7:11979. [PMID: 28931888 PMCID: PMC5607286 DOI: 10.1038/s41598-017-12320-8] [Citation(s) in RCA: 123] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Accepted: 09/07/2017] [Indexed: 12/15/2022] Open
Abstract
Oral Squamous Cell Carcinoma (OSCC) is a common type of cancer of the oral epithelium. Despite their high impact on mortality, sufficient screening methods for early diagnosis of OSCC often lack accuracy and thus OSCCs are mostly diagnosed at a late stage. Early detection and accurate outline estimation of OSCCs would lead to a better curative outcome and a reduction in recurrence rates after surgical treatment. Confocal Laser Endomicroscopy (CLE) records sub-surface micro-anatomical images for in vivo cell structure analysis. Recent CLE studies showed great prospects for a reliable, real-time ultrastructural imaging of OSCC in situ. We present and evaluate a novel automatic approach for OSCC diagnosis using deep learning technologies on CLE images. The method is compared against textural feature-based machine learning approaches that represent the current state of the art. For this work, CLE image sequences (7894 images) from patients diagnosed with OSCC were obtained from 4 specific locations in the oral cavity, including the OSCC lesion. The present approach is found to outperform the state of the art in CLE image recognition with an area under the curve (AUC) of 0.96 and a mean accuracy of 88.3% (sensitivity 86.6%, specificity 90%).
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Affiliation(s)
- Marc Aubreville
- Pattern Recognition Lab, Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
| | - Christian Knipfer
- Department of Oral and Maxillofacial Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Nicolai Oetter
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.,Department of Oral and Maxillofacial Surgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Christian Jaremenko
- Pattern Recognition Lab, Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Erik Rodner
- Computer Vision Group, Friedrich-Schiller-Universität Jena, Jena, Germany
| | - Joachim Denzler
- Computer Vision Group, Friedrich-Schiller-Universität Jena, Jena, Germany
| | - Christopher Bohr
- Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Helmut Neumann
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.,First Department of Internal Medicine, University Hospital Mainz, Johannes Gutenberg-Universität Mainz, Mainz, Germany
| | - Florian Stelzle
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.,Department of Oral and Maxillofacial Surgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Andreas Maier
- Pattern Recognition Lab, Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.,Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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35
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Lin K, Zheng W, Lim CM, Huang Z. Real-time In vivo Diagnosis of Nasopharyngeal Carcinoma Using Rapid Fiber-Optic Raman Spectroscopy. Am J Cancer Res 2017; 7:3517-3526. [PMID: 28912892 PMCID: PMC5596440 DOI: 10.7150/thno.16359] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2016] [Accepted: 07/23/2017] [Indexed: 12/17/2022] Open
Abstract
We report the utility of a simultaneous fingerprint (FP) (i.e., 800-1800 cm-1) and high-wavenumber (HW) (i.e., 2800-3600 cm-1) fiber-optic Raman spectroscopy developed for real-time in vivo diagnosis of nasopharyngeal carcinoma (NPC) at endoscopy. A total of 3731 high-quality in vivo FP/HW Raman spectra (normal=1765; cancer=1966) were acquired in real-time from 204 tissue sites (normal=95; cancer=109) of 95 subjects (normal=57; cancer=38) undergoing endoscopic examination. FP/HW Raman spectra differ significantly between normal and cancerous nasopharyngeal tissues that could be attributed to changes of proteins, lipids, nucleic acids, and the bound water content in NPC. Principal components analysis (PCA) and linear discriminant analysis (LDA) together with leave-one subject-out, cross-validation (LOO-CV) were implemented to develop robust Raman diagnostic models. The simultaneous FP/HW Raman spectroscopy technique together with PCA-LDA and LOO-CV modeling provides a diagnostic accuracy of 93.1% (sensitivity of 93.6%; specificity of 92.6%) for nasopharyngeal cancer identification, which is superior to using either FP (accuracy of 89.2%; sensitivity of 89.9%; specificity of 88.4%) or HW (accuracy of 89.7%; sensitivity of 89.0%; specificity of 90.5%) Raman technique alone. Further receiver operating characteristic (ROC) analysis reconfirms the best performance of the simultaneous FP/HW Raman technique for in vivo diagnosis of NPC. This work demonstrates for the first time that simultaneous FP/HW fiber-optic Raman spectroscopy technique has great promise for enhancing real-time in vivo cancer diagnosis in the nasopharynx during endoscopic examination.
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36
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Yang T, Zheng J. Biological tissues identification from their spectral signals acquired by a Raman needle. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2017; 2017:2279-2282. [PMID: 29060352 DOI: 10.1109/embc.2017.8037310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
In this paper, biological tissues are discriminated based on their intrinsic Raman spectral features. First, a Raman needle, which comprises of a Raman probe and a puncture needle, is devised to insert into biological tissues and acquire their Raman spectral data. The Savitzky-Golay filter is used to remove the data noise, and an adaptive iterative penalized least squares method to rectify the baseline. To extract the spectral features from the data, the principal component analysis (PCA) is used. Then, a genetic algorithm (GA) based support vector machine (SVM) method is proposed to classify the biological tissues based on the spectral features. Experimental study was conducted with different animal specimens and approved that the proposed methods can identify efficiently the different biological tissues.
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37
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Adeola HA, Soyele OO, Adefuye AO, Jimoh SA, Butali A. Omics-based molecular techniques in oral pathology centred cancer: prospect and challenges in Africa. Cancer Cell Int 2017; 17:61. [PMID: 28592923 PMCID: PMC5460491 DOI: 10.1186/s12935-017-0432-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Accepted: 05/29/2017] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The completion of the human genome project and the accomplished milestones in the human proteome project; as well as the progress made so far in computational bioinformatics and "big data" processing have contributed immensely to individualized/personalized medicine in the developed world. MAIN BODY At the dawn of precision medicine, various omics-based therapies and bioengineering can now be applied accurately for the diagnosis, prognosis, treatment, and risk stratification of cancer in a manner that was hitherto not thought possible. The widespread introduction of genomics and other omics-based approaches into the postgraduate training curriculum of diverse medical and dental specialties, including pathology has improved the proficiency of practitioners in the use of novel molecular signatures in patient management. In addition, intricate details about disease disparity among different human populations are beginning to emerge. This would facilitate the use of tailor-made novel theranostic methods based on emerging molecular evidences. CONCLUSION In this review, we examined the challenges and prospects of using currently available omics-based technologies vis-à-vis oral pathology as well as prompt cancer diagnosis and treatment in a resource limited setting.
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Affiliation(s)
- Henry A. Adeola
- Department of Oral and Maxillofacial Pathology, Faculty of Dentistry, University of the Western Cape and Tygerberg Hospital, Cape Town, South Africa
- International Centre for Genetic Engineering and Biotechnology, Cape Town, South Africa
- Division of Dermatology, Department of Medicine, Faculty of Health Sciences and Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa
| | - Olujide O. Soyele
- Department of Oral Maxillo-facial Surgery and Oral Pathology, Obafemi Awolowo University, Ile-Ife, Nigeria
| | - Anthonio O. Adefuye
- Division of Health Sciences Education, Faculty of Health Sciences, University of the Free State, Bloemfontein, South Africa
| | - Sikiru A. Jimoh
- Department of Anatomical Sciences, Faculty of Health Sciences, Walter Sisulu University, Mthatha, Eastern Cape South Africa
| | - Azeez Butali
- Department of Oral Pathology, Radiology and Medicine, University of Iowa, Iowa City, IA USA
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38
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Holler S, Mansley E, Mazzeo C, Donovan MJ, Sobrero M, Miles BA. Raman Spectroscopy of Head and Neck Cancer: Separation of Malignant and Healthy Tissue Using Signatures Outside the "Fingerprint" Region. BIOSENSORS 2017; 7:E20. [PMID: 28505107 PMCID: PMC5487965 DOI: 10.3390/bios7020020] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2016] [Revised: 05/01/2017] [Accepted: 05/11/2017] [Indexed: 12/18/2022]
Abstract
The ability to rapidly and accurately discriminate between healthy and malignant tissue offers surgeons a tool for in vivo analysis that would potentially reduce operating time, facilitate quicker recovery, and improve patient outcomes. To this end, we investigate discrimination between diseased tissue and adjacent healthy controls from patients with head and neck cancer using near-infrared Raman spectroscopy. Our results indicate previously unreported peaks in the Raman spectra that lie outside the conventional "fingerprint" region (400 cm-1-1800 cm -1) played an important role in our analysis and in discriminating between the tissue classes. Preliminary multivariate statistical analyses of the Raman spectra indicate that discrimination between diseased and healthy tissue is possible based on these peaks.
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Affiliation(s)
- Stephen Holler
- Department of Physics & Engineering Physics, Fordham University, 441 East Fordham Road, Bronx, NY 10458, USA.
| | - Elaina Mansley
- Department of Physics & Engineering Physics, Fordham University, 441 East Fordham Road, Bronx, NY 10458, USA.
| | - Christopher Mazzeo
- Department of Physics & Engineering Physics, Fordham University, 441 East Fordham Road, Bronx, NY 10458, USA.
| | - Michael J Donovan
- Icahn School of Medicine at Mount Sinai Hospital, 1 Gustave L. Levy Place, New York, NY 10029, USA.
| | - Maximiliano Sobrero
- Icahn School of Medicine at Mount Sinai Hospital, 1 Gustave L. Levy Place, New York, NY 10029, USA.
| | - Brett A Miles
- Icahn School of Medicine at Mount Sinai Hospital, 1 Gustave L. Levy Place, New York, NY 10029, USA.
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39
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Farhane Z, Bonnier F, Maher MA, Bryant J, Casey A, Byrne HJ. Differentiating responses of lung cancer cell lines to Doxorubicin exposure: in vitro Raman micro spectroscopy, oxidative stress and bcl-2 protein expression. JOURNAL OF BIOPHOTONICS 2017; 10:151-165. [PMID: 27088439 DOI: 10.1002/jbio.201600019] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Revised: 02/23/2016] [Accepted: 03/14/2016] [Indexed: 06/05/2023]
Abstract
The potential of Raman micro spectroscopy as an in vitro, non-invasive tool for clinical applications has been demonstrated in recent years, specifically for cancer research. To further illustrate its potential as a high content and label free technique, it is important to show its capability to elucidate drug mechanisms of action and cellular resistances. In this study, cytotoxicity assays were employed to establish the toxicity profiles for 24 hr exposure of lung cancer cell lines, A549 and Calu-1, to the commercially available drug, doxorubicin (DOX). Raman spectroscopy, coupled with Confocal Laser Scanning Microscopy and Flow Cytometry, was used to track the DOX mechanism of action, at a subcellular level, and to study the mechanisms of cellular resistance to DOX. Biomarkers related to the drug mechanism of action and cellular resistance to apoptosis, namely reactive oxygen species (ROS) and bcl-2 protein expression, respectively, were also measured and correlated to Raman spectral profiles. Calu-1 cells are shown to exhibit spectroscopic signatures of both direct DNA damage due to intercalation in the nucleus and indirect damage due to oxidative stress in the cytoplasm, whereas the A549 cell line only exhibits signatures of the former mechanism of action. PCA of nucleolar, nuclear and cytoplasmic regions of A549 and Calu-1 with corresponding loadings of PC1 and PC2.
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Affiliation(s)
- Zeineb Farhane
- FOCAS Research Institute, Dublin Institute of Technology, Kevin Street, Dublin, 8, Ireland
- School of Physics, Dublin Institute of Technology, Kevin Street, Dublin, 8, Ireland
| | - Franck Bonnier
- Université François-Rabelais de Tours, Faculty of Pharmacy, EA 6295 Nanomédicaments et Nanosondes, 31 avenue Monge, 37200, Tours, France
| | - Marcus Alexander Maher
- FOCAS Research Institute, Dublin Institute of Technology, Kevin Street, Dublin, 8, Ireland
- School of Physics, Dublin Institute of Technology, Kevin Street, Dublin, 8, Ireland
| | - Jane Bryant
- FOCAS Research Institute, Dublin Institute of Technology, Kevin Street, Dublin, 8, Ireland
| | - Alan Casey
- FOCAS Research Institute, Dublin Institute of Technology, Kevin Street, Dublin, 8, Ireland
| | - Hugh James Byrne
- FOCAS Research Institute, Dublin Institute of Technology, Kevin Street, Dublin, 8, Ireland
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40
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Marshall S, Cooper JB. Quantitative Raman Spectroscopy when the Signal-to-Noise is Below the Limit of Quantitation due to Fluorescence Interference: Advantages of a Moving Window Sequentially Shifted Excitation Approach. APPLIED SPECTROSCOPY 2016; 70:1489-1501. [PMID: 27613308 DOI: 10.1177/0003702816662621] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2015] [Accepted: 02/03/2016] [Indexed: 06/06/2023]
Abstract
Raman spectroscopy is a useful analytical tool. However, its application is often limited because shot noise from fluorescence obscures the Raman signal. In such cases, quantitative analysis is not possible when the signal-to-noise ratio (SNR) drops below two. A method is described for performing quantitative Raman spectroscopy that not only removes fluorescence backgrounds, but also results in a significant improvement in the SNR. The Raman data is extracted using a moving window sequentially shifted excitation algorithm. To demonstrate the capabilities of the method, a binary mixture of two analytes at varying concentrations is quantified in the presence of a highly fluorescent dye. Linear calibration plots were constructed and validated for the binary model using individual Raman peaks with SNR ranging from 0.073-12.6; r(2) values are greater than 0.96 in all cases, with all but the weakest peaks yielding values greater than 0.997. The presented method demonstrates a universal and autonomous approach for the quantitative analysis of highly fluorescent samples via Raman spectroscopy. The lower limit on the SNR ratio for quantitative Raman analysis with the described method is 0.1. In order to assess the effectiveness of the presented method, the entire set of experiments was also processed using the more common shifted excitation Raman difference spectroscopy (SERDS) approach. The advantages of the proposed method over SERDS are demonstrated for both the detection limit and the SNR of the processed spectra.
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Affiliation(s)
- Sarah Marshall
- Department of Chemistry and Biochemistry, Old Dominion University, USA
| | - John B Cooper
- Department of Chemistry and Biochemistry, Old Dominion University, USA
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41
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Bocklitz TW, Salah FS, Vogler N, Heuke S, Chernavskaia O, Schmidt C, Waldner MJ, Greten FR, Bräuer R, Schmitt M, Stallmach A, Petersen I, Popp J. Pseudo-HE images derived from CARS/TPEF/SHG multimodal imaging in combination with Raman-spectroscopy as a pathological screening tool. BMC Cancer 2016; 16:534. [PMID: 27460472 PMCID: PMC4962450 DOI: 10.1186/s12885-016-2520-x] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Accepted: 07/05/2016] [Indexed: 01/14/2023] Open
Abstract
Background Due to the steadily increasing number of cancer patients worldwide the early diagnosis and treatment of cancer is a major field of research. The diagnosis of cancer is mostly performed by an experienced pathologist via the visual inspection of histo-pathological stained tissue sections. To save valuable time, low quality cryosections are frequently analyzed with diagnostic accuracies that are below those of high quality embedded tissue sections. Thus, alternative means have to be found that enable for fast and accurate diagnosis as the basis of following clinical decision making. Methods In this contribution we will show that the combination of the three label-free non-linear imaging modalities CARS (coherent anti-Stokes Raman-scattering), TPEF (two-photon excited autofluorescence) and SHG (second harmonic generation) yields information that can be translated into computational hematoxylin and eosin (HE) images by multivariate statistics. Thereby, a computational HE stain is generated resulting in pseudo-HE overview images that allow for identification of suspicious regions. The latter are analyzed further by Raman-spectroscopy retrieving the tissue’s molecular fingerprint. Results The results suggest that the combination of non-linear multimodal imaging and Raman-spectroscopy possesses the potential as a precise and fast tool in routine histopathology. Conclusions As the key advantage, both optical methods are non-invasive enabling for further pathological investigations of the same tissue section, e.g. a direct comparison with the current pathological gold-standard.
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Affiliation(s)
- Thomas W Bocklitz
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, Jena, Germany. .,Leibniz-Institute of Photonic Technology, Albert-Einstein-Str. 9, Jena, 07745, Germany.
| | - Firas Subhi Salah
- Iraqi Centre for Cancer and Medical Genetics Research, Al-Mustansiriya University, Baghdad, Iraq.,Institute of Pathology, University Hospital - Friedrich Schiller University Jena, Ziegelmühlenweg 1, Jena, D-07743, Germany
| | - Nadine Vogler
- Leibniz-Institute of Photonic Technology, Albert-Einstein-Str. 9, Jena, 07745, Germany
| | - Sandro Heuke
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, Jena, Germany.,Leibniz-Institute of Photonic Technology, Albert-Einstein-Str. 9, Jena, 07745, Germany
| | - Olga Chernavskaia
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, Jena, Germany.,Leibniz-Institute of Photonic Technology, Albert-Einstein-Str. 9, Jena, 07745, Germany
| | - Carsten Schmidt
- Clinic for Internal Medicine IV, Jena University Hospital, Jena, 07747, Germany
| | - Maximilian J Waldner
- Department of Medicine 1, Friedrich-Alexander-University, Erlangen, 91054, Germany.,Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Florian R Greten
- Institute for Tumor Biology and Experimental Therapy, Georg-Speyer-Haus, Paul-Ehrlich-Straße 42-44, Frankfurt, 60596, Germany
| | - Rolf Bräuer
- Institute of Pathology, University Hospital - Friedrich Schiller University Jena, Ziegelmühlenweg 1, Jena, D-07743, Germany
| | - Michael Schmitt
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, Jena, Germany
| | - Andreas Stallmach
- Clinic for Internal Medicine IV, Jena University Hospital, Jena, 07747, Germany
| | - Iver Petersen
- Institute of Pathology, University Hospital - Friedrich Schiller University Jena, Ziegelmühlenweg 1, Jena, D-07743, Germany
| | - Jürgen Popp
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller University Jena, Helmholtzweg 4, Jena, Germany. .,Leibniz-Institute of Photonic Technology, Albert-Einstein-Str. 9, Jena, 07745, Germany.
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42
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Sharma G. Diagnostic aids in detection of oral cancer: An update. World J Stomatol 2015; 4:115-120. [DOI: 10.5321/wjs.v4.i3.115] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2015] [Revised: 05/07/2015] [Accepted: 08/17/2015] [Indexed: 02/06/2023] Open
Abstract
Oral cancer is the sixth most common malignancy with almost 500000 new cases reported worldwide annually. The diagnosis of oral cancer at an early stage has a good prognosis as the survival rate is high (around 80%). However, the majority of oral cancer cases are diagnosed at a later stage with a considerably poor 5-year survival rate of 50% according to World Health Organization statistics. Thus, an effective management strategy for oral cancer will depend on its early identification and intervention which would pave the way for superior prognosis. Despite the obvious advantage of earlier diagnosis of oral cancer, no approach has yet proven to be a reliably successful in diagnosis of oral cancer at an early stage. Currently; the primary line of screening of oral cancer is performed by visual inspection, which is a subjective examination. Among the screening tests or diagnostic aids now available for oral cancer, few (toluidine blue, brush biopsy, salivary and serum bio-markers) have been utilised and studied for many years while others have recently become commercially available. The authors in the present article review all the modalities of screening aids used in oral cancer detection and provide an update on the latest screening tools used in oral cancer detection.
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43
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Knipfer C, Motz J, Adler W, Brunner K, Gebrekidan MT, Hankel R, Agaimy A, Will S, Braeuer A, Neukam FW, Stelzle F. Erratum: Raman difference spectroscopy: a non-invasive method for identification of oral squamous cell carcinoma: publisher's note. BIOMEDICAL OPTICS EXPRESS 2015; 6:2675. [PMID: 26203390 PMCID: PMC4505718 DOI: 10.1364/boe.6.002675] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2015] [Indexed: 03/07/2024]
Abstract
The author list appeared incorrectly in [Biomed. Opt. Express 5(9), 3252-3265 (2014)]. The author names were corrected online as of January 17, 2015: https://www.osapublishing.org/boe/abstract.cfm?uri=boe-5-9-3252.[This corrects the article on p. 3252 in vol. 5, PMID: 25401036.].
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Affiliation(s)
- Christian Knipfer
- Department of Oral and Maxillofacial Surgery, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Johanna Motz
- Department of Oral and Maxillofacial Surgery, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Werner Adler
- Department of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Kathrin Brunner
- Department of Pathology, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Medhaine Tesfay Gebrekidan
- Lehrstuhl für Technische Thermodynamik, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Robert Hankel
- Lehrstuhl für Technische Thermodynamik, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Abbas Agaimy
- Department of Pathology, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Stefan Will
- Lehrstuhl für Technische Thermodynamik, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Andreas Braeuer
- Lehrstuhl für Technische Thermodynamik, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Friedrich Wilhelm Neukam
- Department of Oral and Maxillofacial Surgery, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Florian Stelzle
- Department of Oral and Maxillofacial Surgery, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
- Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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44
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Carvalho LFC, Bonnier F, O'Callaghan K, O'Sullivan J, Flint S, Byrne HJ, Lyng FM. Raman micro-spectroscopy for rapid screening of oral squamous cell carcinoma. Exp Mol Pathol 2015; 98:502-9. [DOI: 10.1016/j.yexmp.2015.03.027] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2014] [Revised: 03/12/2015] [Accepted: 03/18/2015] [Indexed: 02/07/2023]
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45
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Zhu S, Su K, Liu Y, Yin H, Li Z, Huang F, Chen Z, Chen W, Zhang G, Chen Y. Identification of cancerous gastric cells based on common features extracted from hyperspectral microscopic images. BIOMEDICAL OPTICS EXPRESS 2015; 6:1135-45. [PMID: 25909000 PMCID: PMC4399655 DOI: 10.1364/boe.6.001135] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Revised: 02/26/2015] [Accepted: 02/26/2015] [Indexed: 05/27/2023]
Abstract
We construct a microscopic hyperspectral imaging system to distinguish between normal and cancerous gastric cells. We study common transmission-spectra features that only emerge when the samples are dyed with hematoxylin and eosin (H&E) stain. Subsequently, we classify the obtained visible-range transmission spectra of the samples into three zones. Distinct features are observed in the spectral responses between the normal and cancerous cell nuclei in each zone, which depend on the pH level of the cell nucleus. Cancerous gastric cells are precisely identified according to these features. The average cancer-cell identification accuracy obtained with a backpropagation algorithm program trained with these features is 95%.
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Affiliation(s)
- Siqi Zhu
- Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, Jinan University, Guangzhou, Guangdong 510632,
China
- Department of Optoelectronic Engineering, Jinan University, Guangzhou, Guangdong 510632,
China
| | - Kang Su
- Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, Jinan University, Guangzhou, Guangdong 510632,
China
- Department of Optoelectronic Engineering, Jinan University, Guangzhou, Guangdong 510632,
China
| | - Yumeng Liu
- Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, Jinan University, Guangzhou, Guangdong 510632,
China
- Department of Optoelectronic Engineering, Jinan University, Guangzhou, Guangdong 510632,
China
| | - Hao Yin
- Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, Jinan University, Guangzhou, Guangdong 510632,
China
- Department of Optoelectronic Engineering, Jinan University, Guangzhou, Guangdong 510632,
China
| | - Zhen Li
- Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, Jinan University, Guangzhou, Guangdong 510632,
China
- Department of Optoelectronic Engineering, Jinan University, Guangzhou, Guangdong 510632,
China
| | - Furong Huang
- Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, Jinan University, Guangzhou, Guangdong 510632,
China
- Department of Optoelectronic Engineering, Jinan University, Guangzhou, Guangdong 510632,
China
| | - Zhenqiang Chen
- Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, Jinan University, Guangzhou, Guangdong 510632,
China
- Department of Optoelectronic Engineering, Jinan University, Guangzhou, Guangdong 510632,
China
| | - Weidong Chen
- Key Laboratory of Optoelectronic Materials Chemistry and Physics, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian 350002,
China
| | - Ge Zhang
- Key Laboratory of Optoelectronic Materials Chemistry and Physics, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian 350002,
China
| | - Yihong Chen
- Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, Jinan University, Guangzhou, Guangdong 510632,
China
- Department of Optoelectronic Engineering, Jinan University, Guangzhou, Guangdong 510632,
China
- Guangzhou Ante Laser Technology Co. Ltd, Guangzhou, Guangdong 510663,
China
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46
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Farhane Z, Bonnier F, Casey A, Maguire A, O'Neill L, Byrne HJ. Cellular discrimination using in vitro Raman micro spectroscopy: the role of the nucleolus. Analyst 2015. [DOI: 10.1039/c5an01157d] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Raman micro spectroscopy is employed to discriminate between cell lines. Results show the importance of the nuclear sub-cellular organelle, the nucleoli, to differentiate between cancer cell lines with high specificity and sensitivity.
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Affiliation(s)
- Z. Farhane
- FOCAS Research Institute
- Dublin Institute of Technology
- Dublin 8
- Ireland
| | - F. Bonnier
- Université François-Rabelais de Tours
- Faculty of Pharmacy
- 37200 Tours
- France
| | - A. Casey
- FOCAS Research Institute
- Dublin Institute of Technology
- Dublin 8
- Ireland
| | - A. Maguire
- FOCAS Research Institute
- Dublin Institute of Technology
- Dublin 8
- Ireland
| | - L. O'Neill
- FOCAS Research Institute
- Dublin Institute of Technology
- Dublin 8
- Ireland
| | - H. J. Byrne
- FOCAS Research Institute
- Dublin Institute of Technology
- Dublin 8
- Ireland
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