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Han W, Xin C, Wang Z, Wang F, Cheng Y, Yang X, Zhou Y, Liu J, Yu W, Wang S. DKI and 1H-MRS in angiogenesis evaluation of soft tissue sarcomas: a prospective clinical study based on MRI-pathology control method. BMC Med Imaging 2024; 24:340. [PMID: 39695437 DOI: 10.1186/s12880-024-01526-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2024] [Accepted: 12/09/2024] [Indexed: 12/20/2024] Open
Abstract
BACKGROUND The vascular endothelial growth factor (VEGF) and microvessel density (MVD) have been widely employed as angiogenesis indicators in the diagnosis and treatment of soft tissue sarcomas. While diffusion kurtosis imaging (DKI) and proton magnetic resonance spectroscopy (1H-MRS) imaging hold potential in assessing angiogenesis in other tumors, their reliability in correlating with angiogenesis in soft tissue sarcomas remains uncertain, contingent upon accurately acquiring the region of interest (ROI). METHODS 23 patients with soft tissue sarcomas (STSs) confirmed by pathology were selected, underwent DKI and 1H-MRS at 3.0T MRI. The DKI parameters mean diffusivity (MD), mean kurtosis (MK), kurtosis anisotropy (KA), and 1H-MRS parameters choline (Cho), lipid/lactate (LL) were measured by two radiologists. Two pathologists obtained pathological slices using a new sampling method called MRI-pathology control and evaluated VEGF and MVD in the selected regions. Correlations between MRI parameters and angiogenesis markers were assessed by Person or Spearman tests. RESULTS The DKI parameters MD and KA, and the 1H-MRS parameters Cho and LL, have varying degrees of correlation with the expression levels of VEGF and MVD. Among them, Cho exhibits the strongest correlation (r = 0.875, P < 0.001; r = 0.807, P < 0.001). CONCLUSION Based on this preliminary clinical studies, DKI and 1H-MRS parameters are correlated with angiogenesis markers obtained through the "MRI-pathology control" method.
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Affiliation(s)
- Wubing Han
- Department of Radiology, Qingdao Municipal Hospital, University of Health and Rehabilitation Sciences, 5 Donghai Middle Rd, Qingdao, 266071, China
| | - Cheng Xin
- Department of Radiology, Qingdao Municipal Hospital, University of Health and Rehabilitation Sciences, 5 Donghai Middle Rd, Qingdao, 266071, China
| | - Zeguo Wang
- Department of Radiology, Qingdao Municipal Hospital, University of Health and Rehabilitation Sciences, 5 Donghai Middle Rd, Qingdao, 266071, China
| | - Fei Wang
- Department of Radiology, Qingdao Municipal Hospital, University of Health and Rehabilitation Sciences, 5 Donghai Middle Rd, Qingdao, 266071, China
| | - Yu Cheng
- Department of Radiology, The Second Hospital, Dalian Medical University, 467 Zhongshan Rd, Dalian, 116023, China
| | - Xingrong Yang
- Department of Pathology, The Second Hospital, Dalian Medical University, 467 Zhongshan Rd, Dalian, 116023, China
| | - Yangyun Zhou
- Department of Radiology, The Second Hospital, Dalian Medical University, 467 Zhongshan Rd, Dalian, 116023, China
| | - Juntong Liu
- Department of Radiology, The Second Hospital, Dalian Medical University, 467 Zhongshan Rd, Dalian, 116023, China
| | - Wanjiang Yu
- Department of Radiology, Qingdao Municipal Hospital, University of Health and Rehabilitation Sciences, 5 Donghai Middle Rd, Qingdao, 266071, China.
| | - Shaowu Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, 467 Zhongshan Rd, Dalian, 116023, China.
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Martín-Noguerol T, Santos-Armentia E, Fernandez-Palomino J, López-Úbeda P, Paulano-Godino F, Luna A. Role of advanced MRI sequences for thyroid lesions assessment. A narrative review. Eur J Radiol 2024; 176:111499. [PMID: 38735157 DOI: 10.1016/j.ejrad.2024.111499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 04/12/2024] [Accepted: 05/05/2024] [Indexed: 05/14/2024]
Abstract
Despite not being the first imaging modality for thyroid gland assessment, Magnetic Resonance Imaging (MRI), thanks to its optimal tissue contrast and spatial resolution, has provided some advancements in detecting and characterizing thyroid abnormalities. Recent research has been focused on improving MRI sequences and employing advanced techniques for a more comprehensive understanding of thyroid pathology. Although not yet standard practice, advanced MRI sequences have shown high accuracy in preliminary studies, correlating well with histopathological results. They particularly show promise in determining malignancy risk in thyroid lesions, which may reduce the need for invasive procedures like biopsies. In this line, functional MRI sequences like Diffusion Weighted Imaging (DWI), Dynamic Contrast-Enhanced MRI (DCE-MRI), and Arterial Spin Labeling (ASL) have demonstrated their potential usefulness in evaluating both diffuse thyroid conditions and focal lesions. Multicompartmental DWI models, such as Intravoxel Incoherent Motion (IVIM) and Diffusion Kurtosis Imaging (DKI), and novel methods like Amide Proton Transfer (APT) imaging or artificial intelligence (AI)-based analyses are being explored for their potential valuable insights into thyroid diseases. This manuscript reviews the critical physical principles and technical requirements for optimal functional MRI sequences of the thyroid and assesses the clinical utility of each technique. It also considers future prospects in the context of advanced MR thyroid imaging and analyzes the current role of advanced MRI sequences in routine practice.
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Affiliation(s)
| | | | | | | | | | - Antonio Luna
- MRI unit, Radiology department. HT medica, Carmelo Torres 2, 23007 Jaén, Spain.
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Zheng T, Wang L, Wang H, Tang L, Xie X, Fu Q, Wu PY, Song B. Prediction model based on MRI morphological features for distinguishing benign and malignant thyroid nodules. BMC Cancer 2024; 24:256. [PMID: 38395783 PMCID: PMC10885392 DOI: 10.1186/s12885-024-11995-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 02/12/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND The low specificity of Thyroid Imaging Reporting and Data System (TI-RADS) for preoperative benign-malignant diagnosis leads to a large number of unnecessary biopsies. This study developed and validated a predictive model based on MRI morphological features to improve the specificity. METHODS A retrospective analysis was conducted on 825 thyroid nodules pathologically confirmed postoperatively. Univariate and multivariate logistic regression were used to obtain β coefficients, construct predictive models and nomogram incorporating MRI morphological features in the training cohort, and validated in the validation cohort. The discrimination, calibration, and decision curve analysis of the nomogram were performed. The diagnosis efficacy, area under the curve (AUC) and net reclassification index (NRI) were calculated and compared with TI-RADS. RESULTS 572 thyroid nodules were included (training cohort: n = 397, validation cohort: n = 175). Age, low signal intensity on T2WI, restricted diffusion, reversed halo sign in delay phase, cystic degeneration and wash-out pattern were independent predictors of malignancy. The nomogram demonstrated good discrimination and calibration both in the training cohort (AUC = 0.972) and the validation cohort (AUC = 0.968). The accuracy, sensitivity, specificity, PPV, NPV and AUC of MRI-based prediction were 94.4%, 96.0%, 93.4%, 89.9%, 96.5% and 0.947, respectively. The MRI-based prediction model exhibited enhanced accuracy (NRI>0) in comparison to TI-RADSs. CONCLUSIONS The prediction model for diagnosis of benign and malignant thyroid nodules demonstrated a more notable diagnostic efficacy than TI-RADS. Compared with the TI-RADSs, predictive model had better specificity along with a high sensitivity and can reduce overdiagnosis and unnecessary biopsies.
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Affiliation(s)
- Tingting Zheng
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Lanyun Wang
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Hao Wang
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Lang Tang
- Department of Ultrasound, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Xiaoli Xie
- Department of Pathology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Qingyin Fu
- Department of Ultrasound, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China
| | - Pu-Yeh Wu
- GE Healthcare, MR Research China, Beijing, China
| | - Bin Song
- Department of Radiology, Minhang Hospital, Fudan University, No 170, Xinsong Road, Minhang District, 201199, Shanghai, China.
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Zhu X, Wang J, Wang YC, Zhu ZF, Tang J, Wen XW, Fang Y, Han J. Quantitative differentiation of malignant and benign thyroid nodules with multi-parameter diffusion-weighted imaging. World J Clin Cases 2022; 10:8587-8598. [PMID: 36157818 PMCID: PMC9453341 DOI: 10.12998/wjcc.v10.i24.8587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 01/25/2022] [Accepted: 07/22/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND The value of conventional magnetic resonance imaging in the differential diagnosis of thyroid nodules is limited; however, the value of multi-parameter diffusion-weighted imaging (DWI) in the quantitative evaluation of thyroid nodules has not been well determined.
AIM To determine the utility of multi-parametric DWI including mono-exponential, bi-exponential, stretched exponential, and kurtosis models for the differentiation of thyroid lesions.
METHODS Seventy-nine patients (62 with benign and 17 with malignant nodules) underwent multi-b value diffusion-weighted imaging of the thyroid. Multiple DWI parameters were obtained for statistical analysis.
RESULTS Good agreement was found for diffusion parameters of thyroid nodules. Malignant lesions displayed lower diffusion parameters including apparent diffusion coefficient (ADC), the true diffusion coefficient (D), the perfusion fraction (f), the distributed diffusion coefficient (DDC), the intravoxel water diffusion heterogeneity (α) and kurtosis model-derived ADC (Dapp), and higher apparent diffusional kurtosis (Kapp) than benign entities (all P < 0.01), except for the pseudodiffusion coefficient (D*) (P > 0.05). The area under the ROC curve (AUC) of the ADC(0 and 1000) was not significantly different from that of the ADC(0 and 2000), ADC(0 to 2000), ADC(0 to 1000), D, DDC, Dapp and Kapp (all P > 0.05), but was significantly higher than the AUC of D*, f and α (all P < 0.05) for differentiating benign from malignant lesions.
CONCLUSION Multiple DWI parameters including ADC, D, f, DDC, α, Dapp and Kapp could discriminate benign and malignant thyroid nodules. The metrics including D, DDC, Dapp and Kapp provide additional information with similar diagnostic performance of ADC, combination of these metrics may contribute to differentiate benign and malignant thyroid nodules. The ADC calculated with higher b values may not lead to improved diagnostic performance.
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Affiliation(s)
- Xiang Zhu
- Department of Radiology, The First Hospital of Jiaxing & The Affiliated Hospital of Jiaxing University, Jiaxing 314000, Zhejiang Province, China
| | - Jia Wang
- Department of Radiology, The First Hospital of Jiaxing & The Affiliated Hospital of Jiaxing University, Jiaxing 314000, Zhejiang Province, China
| | - Yan-Chun Wang
- Department of Radiology, The First Hospital of Jiaxing & The Affiliated Hospital of Jiaxing University, Jiaxing 314000, Zhejiang Province, China
| | - Ze-Feng Zhu
- Department of Radiology, The First Hospital of Jiaxing & The Affiliated Hospital of Jiaxing University, Jiaxing 314000, Zhejiang Province, China
| | - Jian Tang
- Department of Head and Neck Surgery, the First Hospital of Jiaxing & The Affiliated Hospital of Jiaxing University, Jiaxing 314000, Zhejiang Province, China
| | - Xiao-Wei Wen
- Department of Pathology, The First Hospital of Jiaxing & The Affiliated Hospital of Jiaxing University, Jiaxing 314000, Zhejiang Province, China
| | - Ying Fang
- Department of Pathology, The First Hospital of Jiaxing & The Affiliated Hospital of Jiaxing University, Jiaxing 314000, Zhejiang Province, China
| | - Jun Han
- Department of Radiology, The First Hospital of Jiaxing & The Affiliated Hospital of Jiaxing University, Jiaxing 314000, Zhejiang Province, China
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Jiang L, Chen J, Huang H, Wu J, Zhang J, Lan X, Liu D, Zhang J. Comparison of the Differential Diagnostic Performance of Intravoxel Incoherent Motion Imaging and Diffusion Kurtosis Imaging in Malignant and Benign Thyroid Nodules. Front Oncol 2022; 12:895972. [PMID: 35936691 PMCID: PMC9354485 DOI: 10.3389/fonc.2022.895972] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 06/22/2022] [Indexed: 11/29/2022] Open
Abstract
Objective This study aimed to compare the diagnostic capacity between IVIM and DKI in differentiating malignant from benign thyroid nodules. Material and Methods This study is based on magnetic resonance imaging data of the thyroid with histopathology as the reference standard. Spearman analysis was used to assess the relationship of IVIM-derived parameters D, f, D* and the DKI-derived parameters Dapp and Kapp. The parameters of IVIM and DKI were compared between the malignant and benign groups. Binary logistic regression analysis was performed to establish the diagnostic model, and receiver operating characteristic (ROC) curve analysis was subsequently performed. The DeLong test was used to compare the diagnostic effectiveness of different prediction models. Spearman analysis was used to assess the relationship of Ki-67 expression and parameters of IVIM and DKI. Results Among the 93 nodules, 46 nodules were malignant, and 47 nodules were benign. The Dapp of DKI-derived parameter was related to the D (P < 0.001, r = 0.863) of IVIM-derived parameter. The Kapp of DKI-derived parameter was related to the D (P < 0.001, r = -0.831) of IVIM-derived parameters. The malignant group had a significantly lower D value (P < 0.001) and f value (P = 0.013) than the benign group. The malignant group had significantly higher Kapp and lower Dapp values (all P < 0.001). The D+f had an area under the curve (AUC) of 0.951. The Dapp+Kapp had an AUC of 0.943. The D+f+Dapp+Kapp had an AUC of 0.954. The DeLong test showed no statistical significance among there prediction models. The D (P = 0.007) of IVIM-derived parameters and Dapp (P = 0.045) of DKI-derived parameter were correlated to the Ki-67 expression. Conclusions IVIM and DKI were alternative for each other in in differentiating malignant from benign thyroid nodules.
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Affiliation(s)
- Liling Jiang
- Department of Radiology, Cancer Hospital, Chongqing University, Chongqing, China
| | - Jiao Chen
- Department of Radiology, Cancer Hospital, Chongqing University, Chongqing, China
| | - Haiping Huang
- Department of Pathology, Cancer Hospital, Chongqing University, Chongqing, China
| | - Jian Wu
- Head and Neck Cancer Center, Cancer Hospital, Chongqing University, Chongqing, China
| | - Junbin Zhang
- Head and Neck Cancer Center, Cancer Hospital, Chongqing University, Chongqing, China
| | - Xiaosong Lan
- Department of Radiology, Cancer Hospital, Chongqing University, Chongqing, China
| | - Daihong Liu
- Department of Radiology, Cancer Hospital, Chongqing University, Chongqing, China
| | - Jiuquan Zhang
- Department of Radiology, Cancer Hospital, Chongqing University, Chongqing, China
- *Correspondence: Jiuquan Zhang,
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Jiang L, Liu D, Long L, Chen J, Lan X, Zhang J. Dual-source dual-energy computed tomography-derived quantitative parameters combined with machine learning for the differential diagnosis of benign and malignant thyroid nodules. Quant Imaging Med Surg 2022; 12:967-978. [PMID: 35111598 DOI: 10.21037/qims-21-501] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 08/12/2021] [Indexed: 01/05/2023]
Abstract
Background This study aimed to investigate the ability of quantitative parameter-derived dual-source dual-energy computed tomography (DS-DECT) combined with machine learning to distinguish between benign and malignant thyroid nodules. Methods Patients with thyroid nodules and pathological surgical results who underwent preoperative DS-DECT were selected. Quantitative parameter-derived DS-DECT was applied to classify benign and malignant nodules. Then, machine learning and binary logistic regression analysis models were constructed using the DS-DECT quantitative parameters to distinguish between benign and malignant nodules. The receiver operating characteristic curve was used to assess the diagnostic performance. The DeLong test was used to compare the diagnostic efficacy. Results One hundred and thirty patients with 139 confirmed thyroid nodules were involved in the study. The malignant group had a significantly higher iodine concentrationnodule (arterial phase) (P=0.001), normalized iodine concentration (arterial phase) (P=0.002), iodine concentration difference (P<0.001), spectral curve slope (nonenhancement) (P=0.007), spectral curve slope (arterial phase) (P=0.001), effective atomic number (nonenhancement) (P<0.001), and effective atomic number (arterial phase) (P=0.039) than the benign group. The binary logistic regression analysis model had an AUC (area under the curve) of 0.76, a sensitivity of 0.821, and a specificity of 0.667. The machine learning model had an AUC of 0.86, a sensitivity of 0.822, specificity of 0.791 in the training cohort, an AUC of 0.84, a sensitivity of 0.727, and specificity of 0.750 in the testing cohort. Conclusions Multiple quantitative parameters of DS-DECT combined with machine learning could differentiate between benign and malignant thyroid nodules.
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Affiliation(s)
- Liling Jiang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Daihong Liu
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Ling Long
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Jiao Chen
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Xiaosong Lan
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.,Chongqing Cancer Multi-omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
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Meyer HJ, Wienke A, Surov A. Discrimination between malignant and benign thyroid tumors by diffusion-weighted imaging - A systematic review and meta analysis. Magn Reson Imaging 2021; 84:41-57. [PMID: 34560233 DOI: 10.1016/j.mri.2021.09.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 08/19/2021] [Accepted: 09/05/2021] [Indexed: 01/01/2023]
Abstract
PURPOSE Magnetic resonance imaging is used to stage thyroid tumors. Diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. Our aim was to compare ADC values of malignant and benign thyroid lesions based on a large sample. METHODS MEDLINE library, EMBASE and SCOPUS databases were screened for the associations between ADC values and thyroid lesions up to August 2021. The primary endpoint of the systematic review were ADC values of benign and malignant thyroid lesions. In total, 29 studies were suitable for the analysis and were included into the present study. RESULTS The included studies comprised a total of 2137 lesions, 1118 (52.3%) benign and 1019 (47.7%) malignant lesions. The pooled mean ADC value of the benign thyroid lesions was 1.88 × 10-3 mm2/s [95% CI 1.77-2.0] and the pooled mean ADC value of malignant thyroid lesions was 1.15 × 10-3 mm2/s [95% CI 1.04-1.25]. CONCLUSIONS ADC can well discriminate benign and malignant thyroid tumors. Therefore, DWI should be implemented into the presurgical diagnostic work-up in clinical routine.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany.
| | - Andreas Wienke
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Alexey Surov
- Department of Radiology and Nuclear Medicine, University of Magdeburg, Magdeburg, Germany
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Wu X, Li J, Mou Y, Yao Y, Cui J, Mao N, Song X. Radiomics Nomogram for Identifying Sub-1 cm Benign and Malignant Thyroid Lesions. Front Oncol 2021; 11:580886. [PMID: 34164333 PMCID: PMC8215667 DOI: 10.3389/fonc.2021.580886] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 05/19/2021] [Indexed: 12/28/2022] Open
Abstract
PURPOSE To develop and validate a radiomics nomogram for identifying sub-1 cm benign and malignant thyroid lesions. METHOD A total of 171 eligible patients with sub-1 cm thyroid lesions (56 benign and 115 malignant) who were treated in Yantai Yuhuangding Hospital between January and September 2019 were retrospectively collected and randomly divided into training (n = 136) and validation sets (n = 35). The radiomics features were extracted from unenhanced and arterial contrast-enhanced computed tomography images of each patient. In the training set, one-way analysis of variance and least absolute shrinkage and selection operator (LASSO) logistic regression were used to select the features related to benign and malignant lesions, and the LASSO algorithm was used to construct the radiomics signature. Combined with clinical independent predictive factors, a radiomics nomogram was constructed with a multivariate logistic regression model. The performance of the radiomics nomogram was evaluated by using the receiver operating characteristic (ROC) and calibration curves in the training and validation sets. The clinical usefulness was evaluated by using decision curve analysis (DCA). RESULTS The radiomics signature consisting of 13 selected features achieved favorable prediction efficiency. The radiomics nomogram, which incorporated radiomics signature and clinical independent predictive factors including age and Thyroid Imaging Reporting and Data System category, showed good calibration and discrimination in the training (area under the ROC [AUC]: 0.853; 95% confidence interval [CI]: 0.797, 0.899) and validation sets (AUC: 0.851; 95% CI: 0.735, 0.931). DCA demonstrated that the nomogram was clinically useful. CONCLUSION As a noninvasive preoperative prediction tool, the radiomics nomogram incorporating radiomics signature and clinical predictive factors shows favorable predictive efficiency for identifying sub-1 cm benign and malignant thyroid lesions.
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Affiliation(s)
- Xinxin Wu
- Department of Otorhinolaryngology-Head and Neck Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China
| | - Jingjing Li
- Department of Otorhinolaryngology-Head and Neck Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China
- School of Clinical Medicine, Binzhou Medical University, Yantai, China
| | - Yakui Mou
- Department of Otorhinolaryngology-Head and Neck Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China
| | - Yao Yao
- Department of Otorhinolaryngology-Head and Neck Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China
| | - Jingjing Cui
- Collaboration Department, Huiying Medical Technology Co., Ltd, Beijing, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China
| | - Xicheng Song
- Department of Otorhinolaryngology-Head and Neck Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China
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Zheng Y, Huang W, Zhang X, Lu C, Fu C, Li S, Lin G. A Noninvasive Assessment of Tumor Proliferation in Lung cancer Patients using Intravoxel Incoherent Motion Magnetic Resonance Imaging. J Cancer 2021; 12:190-197. [PMID: 33391415 PMCID: PMC7738818 DOI: 10.7150/jca.48589] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Accepted: 10/26/2020] [Indexed: 12/15/2022] Open
Abstract
Ki-67 is a nuclear antigen widely used in routine pathologic analyses as a tumor cell proliferation marker for lung cancer. However, Ki-67 expression analyses using immunohistochemistry (IHC) are invasive and frequently influenced by tissue sampling quality. In this study, we assessed the feasibility of noninvasive magnetic resonance imaging (MRI) in predicting the Ki-67 labeling indices (LIs). A total of 51 lung cancer patients, including 42 non-small cell lung cancer (NSCLC) cases and nine small cell lung cancer (SCLC) cases, were enrolled in this study. Quantitative MRI parameters from conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) were obtained, and their correlations with tumor tissue Ki-67 expression were analyzed. We found that the true diffusion coefficient (D value) from IVIM was negatively correlated with Ki-67 expression (Spearman r = -0.76, P < 0.001). The D values in the high Ki-67 group were significantly lower than those in the low Ki-67 group (0.90 ± 0.21 × 10-3 mm2/s vs. 1.22 ± 0.30 × 10-3 mm2/s). Among three MRI techniques used, D values from IVIM showed the best performance for distinguishing the high Ki-67 group from low Ki-67 group in receiver operating characteristic (ROC) analysis with an area under the ROC curve (AUROC) of 0.85 (95% CI: 0.73-0.97, P < 0.05). Moreover, D values performed well for differentiating SCLC from NSCLC with an AUROC of 0.82 (95% CI: 0.68-0.90), Youden index of 0.72, and F1 score of 0.81. In conclusion, D values were negatively correlated with Ki-67 expression in lung cancer tissues and can be used to distinguish high from low proliferation statuses, as well as SCLC from NSCLC.
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Affiliation(s)
- Yu Zheng
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China
| | - Wenjun Huang
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China
| | - Xuelin Zhang
- Department of Thoracic Surgery, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China
| | - Chen Lu
- Department of Pathology, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China
| | - Caixia Fu
- Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, Guangdong Province, 518057, China
| | - Shihong Li
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China
| | - Guangwu Lin
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China
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Zheng T, Yuan Y, Yang H, Du J, Wu S, Jin Y, Wang Z, Liu D, Shi Q, Wang X, Liu L. Evaluating the Therapeutic Effect of Low-Intensity Transcranial Ultrasound on Traumatic Brain Injury With Diffusion Kurtosis Imaging. J Magn Reson Imaging 2020; 52:520-531. [PMID: 31999388 DOI: 10.1002/jmri.27063] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 01/08/2020] [Accepted: 01/09/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Low-intensity transcranial ultrasound (LITUS) has a therapeutic effect on traumatic brain injury (TBI). Diffusion kurtosis imaging (DKI) might be able to evaluate the effect changes of injured brain microstructure. PURPOSE To evaluate the therapeutic effect of LITUS in a moderate TBI rat model with DKI parameters. STUDY TYPE Prospective case-control animal study. ANIMAL MODEL Forty-five rats were randomly divided into sham control, TBI, and LITUS treatment groups (n = 15). FIELD STRENGTH/SEQUENCE Single-shot spin echo echo-planar imaging and fast T2 WI sequences at 3.0T. ASSESSMENT DKI parameters were obtained on days 1, 7, 14, 21, 28, 35, and 42 after TBI. STATISTICAL TESTS For the mean kurtosis (MK), axial kurtosis (Ka), and radial kurtosis (Kr) values, groups were compared using a two-way analysis of variance (ANOVA). RESULTS LITUS inhibited TBI and caused MK values to increase significantly during the early stage (LITUS vs. TBI, day 7, adjusted P < 0.0001) and decrease during the late stage (LITUS vs. TBI, day 42, adjusted P = 0.0156) in the damaged cortex. In the thalamus, the MK value of the TBI group began to rise on day 7, with no change observed in the LITUS group. TBI increases Ka value during the early stage in the cortex and decreases during the late stage in the cortex and thalamus. LITUS inhibited these Ka changes (LITUS vs. TBI, day 7, adjusted P = 0.0014; LITUS vs. TBI, day 42, adjusted P = 0.0026 and 0.0478, respectively, for cortex and thalamus). The Kr value increased slightly during the early stage in the cortex (TBI vs. Sham, day 1, adjusted P = 0.0016). DATA CONCLUSION The DKI parameter, particularly the MK value, evaluates primary cortical injury as well as the secondary brain injury that could not be detected by conventional T2 WI. LEVEL OF EVIDENCE 1 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2020;52:520-531.
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Affiliation(s)
- Tao Zheng
- Department of Magnetic Resonance Imaging, Qinhuangdao Municipal No. 1 Hospital, Qinhuangdao, China
| | - Yi Yuan
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China
| | - Haoxiang Yang
- Department of Cardiovascular Medicine, Qinhuangdao Municipal No. 1 Hospital, Qinhuangdao, China
| | - Juan Du
- Department of Magnetic Resonance Imaging, Qinhuangdao Municipal No. 1 Hospital, Qinhuangdao, China
| | - Shuo Wu
- Department of Magnetic Resonance Imaging, Qinhuangdao Municipal No. 1 Hospital, Qinhuangdao, China
| | - Yinglan Jin
- Peking University Health Science Center, Beijing, China
| | - Zhanqiu Wang
- Department of Magnetic Resonance Imaging, Qinhuangdao Municipal No. 1 Hospital, Qinhuangdao, China
| | - Defeng Liu
- Department of Magnetic Resonance Imaging, Qinhuangdao Municipal No. 1 Hospital, Qinhuangdao, China
| | - Qinglei Shi
- Scientific Clinical Specialist, Siemens Ltd., Beijing, China
| | - Xiaohan Wang
- Department of Magnetic Resonance Imaging, Qinhuangdao Municipal No. 1 Hospital, Qinhuangdao, China
| | - Lanxiang Liu
- Department of Magnetic Resonance Imaging, Qinhuangdao Municipal No. 1 Hospital, Qinhuangdao, China
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Song M, Yue Y, Jin Y, Guo J, Zuo L, Peng H, Chan Q. Intravoxel incoherent motion and ADC measurements for differentiating benign from malignant thyroid nodules: utilizing the most repeatable region of interest delineation at 3.0 T. Cancer Imaging 2020; 20:9. [PMID: 31969196 PMCID: PMC6977258 DOI: 10.1186/s40644-020-0289-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 01/13/2020] [Indexed: 01/17/2023] Open
Abstract
Background There is a growing need for a reproducible and effective imaging method for the quantitative differentiation of benign from malignant thyroid nodules. This study aimed to investigate the performances of intravoxel incoherent motion (IVIM) parameters and the apparent diffusion coefficient (ADC) in differentiating malignant from benign thyroid nodules derived from the most repeatable region of interest (ROI) delineation. Methods Forty-three patients with 46 pathologically confirmed thyroid nodules underwent diffusion-weighted imaging (DWI) with 8 b values. Two observers measured the intravoxel incoherent motion (IVIM) parameters (D, f and D*) and the apparent diffusion coefficient (ADC), ADC600 and ADC990 values using whole-lesion (W-L) ROI and IVIM parameters using single-section (S-S) ROI delineation. The intraclass correlation coefficients (ICCs) and Bland-Altman plots were used to evaluate the intra- and interobserver variability. The diagnostic performance of these parameters was evaluated by generating receiver operating characteristic (ROC) curves. Results The ICC values of all IVIM with W-L ROI delineation were higher than those with S-S ROI delineation, and excellent intra- and interobserver reproducibility was obtained. According to the Bland-Altman plots, the 95% limits of agreement of the IVIM parameters determined by the W-L ROIs revealed smaller absolute intra- and interobserver variability than those determined by S-S ROIs. The D and ADC600 values obtained from the W-L ROIs were the most powerful parameters in differentiating benign from the malignant nodules [area under the ROC curve = 0.962 and 0.970, P = 0.771]. Conclusions The W-L ROI of the thyroid was considered an effective method for obtaining IVIM measurements with excellent reproducibility for differentiating benign from malignant nodules.
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Affiliation(s)
- Minghui Song
- Department of MR, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Tieyilu #10, Haidian District, Beijing, 100038, China
| | - Yunlong Yue
- Department of MR, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Tieyilu #10, Haidian District, Beijing, 100038, China.
| | - Yanfang Jin
- Department of MR, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Tieyilu #10, Haidian District, Beijing, 100038, China
| | - Jinsong Guo
- Department of MR, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Tieyilu #10, Haidian District, Beijing, 100038, China
| | - Lili Zuo
- Department of MR, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Tieyilu #10, Haidian District, Beijing, 100038, China
| | - Hong Peng
- Department of Otolaryngology, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Beijing, China
| | - Queenie Chan
- Philips Healthcare, Shatin, New Territories, Hong Kong, China
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12
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Fiordelisi MF, Cavaliere C, Auletta L, Basso L, Salvatore M. Magnetic Resonance Imaging for Translational Research in Oncology. J Clin Med 2019; 8:jcm8111883. [PMID: 31698697 PMCID: PMC6912299 DOI: 10.3390/jcm8111883] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 10/28/2019] [Accepted: 10/29/2019] [Indexed: 12/19/2022] Open
Abstract
The translation of results from the preclinical to the clinical setting is often anything other than straightforward. Indeed, ideas and even very intriguing results obtained at all levels of preclinical research, i.e., in vitro, on animal models, or even in clinical trials, often require much effort to validate, and sometimes, even useful data are lost or are demonstrated to be inapplicable in the clinic. In vivo, small-animal, preclinical imaging uses almost the same technologies in terms of hardware and software settings as for human patients, and hence, might result in a more rapid translation. In this perspective, magnetic resonance imaging might be the most translatable technique, since only in rare cases does it require the use of contrast agents, and when not, sequences developed in the lab can be readily applied to patients, thanks to their non-invasiveness. The wide range of sequences can give much useful information on the anatomy and pathophysiology of oncologic lesions in different body districts. This review aims to underline the versatility of this imaging technique and its various approaches, reporting the latest preclinical studies on thyroid, breast, and prostate cancers, both on small laboratory animals and on human patients, according to our previous and ongoing research lines.
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13
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Li C, Ye J, Peng Y, Dou W, Shang S, Wu J, Jafari R, Gillen KM, Wang Y, Prince M, Luo X. Evaluation of diffusion kurtosis imaging in stratification of nonalcoholic fatty liver disease and early diagnosis of nonalcoholic steatohepatitis in a rabbit model. Magn Reson Imaging 2019; 63:267-273. [PMID: 31445117 DOI: 10.1016/j.mri.2019.08.032] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Revised: 08/19/2019] [Accepted: 08/21/2019] [Indexed: 02/07/2023]
Abstract
PURPOSE To examine the feasibility of MR diffusion kurtosis imaging (DKI) for characterizing nonalcoholic fatty liver disease (NAFLD) and diagnosing nonalcoholic steatohepatitis (NASH). METHODS Thirty-two rabbits on high fat diet with different severities of NAFLD were imaged at 3 T MR including diffusion weighted imaging (DWI) and DKI using b values of 0, 400, 800 s/mm2 with 15 diffusion directions at each b value. Apparent diffusion coefficient (ADC) was derived from the linear exponential DWI model. Mean diffusion (MD) and mean kurtosis (MK) were derived from the quadratic exponential model of DKI. Correlations between MR parameters and hepatic pathology determined by the NAFLD activity scoring system were analyzed by Spearman rank correlation analysis. Receiver operating characteristic analyses were applied to determine the cutoff values of MD, MK as well as ADC in distinguishing NASH from non-NASH. The diagnostic efficacies of MD and MK in detecting NASH were compared with that of ADC. RESULTS Values for ADC and MD significantly decreased as the severity of NAFLD increased (ρ = -0.529, -0.904, respectively; P < 0.05). MK values significantly increased as the severity of NAFLD increased (ρ = 0.761; P < 0.05). In addition, both MD and MK values were significantly different between borderline NASH and NASH groups (MD: 1.729 ± 0.144 vs. 1.458 ± 0.240[×10-3 mm2/s]; MK: 1.096 ± 0.079 vs. 1.237 ± 0.180; P < 0.05). Moreover, there was a significantly higher area under the curve (AUC) for both MD (0.955) and MK (0.905), as compared to ADC (0.736). CONCLUSION Diffusion kurtosis imaging was feasible for stratifying NAFLD, and more accurately discriminated NASH from non-NASH when compared with DWI.
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Affiliation(s)
- Chang Li
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou 225001, China; Xiangya School of Medicine, Central South University, No. 172 Tongzipo Road, Changsha 410013, China
| | - Jing Ye
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou 225001, China
| | - Yun Peng
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou 225001, China; Xiangya School of Medicine, Central South University, No. 172 Tongzipo Road, Changsha 410013, China
| | - Weiqiang Dou
- GE Healthcare, MR Research China, Beijing, China
| | - Songan Shang
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou 225001, China; Xiangya School of Medicine, Central South University, No. 172 Tongzipo Road, Changsha 410013, China
| | - Jingtao Wu
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou 225001, China
| | - Ramin Jafari
- Department of Radiology, Weill Medical College of Cornell University, 407 E 61st Street, New York, NY 10065, USA
| | - Kelly McCabe Gillen
- Department of Radiology, Weill Medical College of Cornell University, 407 E 61st Street, New York, NY 10065, USA
| | - Yi Wang
- Department of Radiology, Weill Medical College of Cornell University, 407 E 61st Street, New York, NY 10065, USA; Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Martin Prince
- Department of Radiology, Weill Medical College of Cornell University, 407 E 61st Street, New York, NY 10065, USA
| | - Xianfu Luo
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou 225001, China.
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Association Between VEGF Expression and Diffusion Weighted Imaging in Several Tumors-A Systematic Review and Meta-Analysis. Diagnostics (Basel) 2019; 9:diagnostics9040126. [PMID: 31547581 PMCID: PMC6963772 DOI: 10.3390/diagnostics9040126] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 09/18/2019] [Accepted: 09/20/2019] [Indexed: 02/07/2023] Open
Abstract
To date, only a few studies have investigated relationships between Diffusion-weighted imaging (DWI) and Vascular endothelial growth factor (VEGF) expression in tumors. The reported results are contradictory. The aim of the present analysis was to review the published results and to perform a meta-analysis regarding associations between apparent diffusion coefficients (ADC) derived from DWI and VEGF expression. MEDLINE library was screened for relationships between ADC and VEGF expression up to January 2019. Overall, 14 studies with 578 patients were identified. In 10 studies (71.4%) 3 T scanners were used and in four studies (28.6%) 1.5 T scanners. Furthermore, seven studies (50%) had a prospective design and seven studies (50%) had a retrospective design. Most frequently, prostate cancer, followed by rectal cancer, cervical cancer and esophageal cancer were identified. The pooled correlation coefficient of all tumors was r = -0.02 [95% CI -0.26-0.21]. ADC values derived from routinely acquired DWI do not correlate with VEGF expression in various tumors. Therefore, DWI is not sensitive enough to reflect angiogenesis-related microstructure of tumors.
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Meyer HJ, Hamerla G, Leifels L, Höhn AK, Surov A. Whole-lesion ADC histogram analysis is not able to reflect microvessel density in HNSCC. Medicine (Baltimore) 2019; 98:e15520. [PMID: 31124932 PMCID: PMC6571415 DOI: 10.1097/md.0000000000015520] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Diffusion-weighted imaging (DWI) is a functional imaging technique sensitive to microstructure in tissues. It is widely acknowledged to reflect cellularity in tumors. A small part of DWI is also sensitive to perfusion-related information and might therefore be also be able to reflect microvessel density in tumor tissues. Aim of the present study was to elucidate possible correlations between microvessel density and apparent diffusion coefficient (ADC) values in head and neck squamous cell carcinoma (HNSCC).Thirty-four patients with histologically proven primary HNSCC were included in the study. DWI was performed with a 3 T magnetic resonance imaging (MRI) (b-values 0 and 800 s/mm) and histogram analysis was calculated with a whole lesion measurement. In every case, microvessel density was estimated with CD105-stained specimens.There were no statistically significant correlations between ADC histogram parameters and microvessel density. The calculated correlation coefficients ranged from r = -0.27, P = .13 for entropy and vessel area to r = 0.16, P = .40 for ADCmin and vessel count.Whole-lesion histogram analysis of ADC values cannot reflect microvessel density in HNSCC.
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Affiliation(s)
| | | | | | | | - Alexey Surov
- Department of Diagnostic and Interventional Radiology
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Li L, Zhou Z, Li J, Fang J, Qing Y, Tian T, Zhang S, Wu G, Scotti A, Cai K, Zhu W. Diffusion kurtosis imaging provides quantitative assessment of the microstructure changes of disc degeneration: an in vivo experimental study. EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2019; 28:1005-1013. [PMID: 30778770 DOI: 10.1007/s00586-019-05924-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Revised: 02/08/2019] [Accepted: 02/12/2019] [Indexed: 10/27/2022]
Abstract
OBJECTIVE Our aim was to assess the microstructural changes of intervertebral disc degeneration induced by annulus needle puncture in rats by diffusion kurtosis imaging (DKI). METHODS Eighteen rats (36 discs) were punctured percutaneously at the intervertebral disc between C6/7, C7/8 (C-coccygeal vertebrae) with a 21-gauge needle. The rats were divided into six groups according to the time after the puncture: 3 h, 48 h, 3 days, 7 days, 10 days and 14 days. There were six discs in three rats in the control group. The rats' tail was imaged at 3T MRI with T2-weighted and diffusion-weighted and diffusion kurtosis imaging (DWI)/DKI sequences. The discs were categorized using a five-grade degeneration system based on the T2 images. The height of the discs and the parameters in DWI/DKI were measured and compared between the different time points. The histological images were also obtained from the discs. RESULTS The histological study revealed that the discs in the rat of the punctured groups were degenerated. The T2 grades of different groups presented an increasing trend from 7 to 10 days after puncture (R2 = 0.9424, P < 0.001), while the DWI/DKI parameters changes were consistent with the histological changes at the different time points and showed significant differences between the different groups (P < 0.05). CONCLUSIONS DKI provides quantitative assessment of the microstructure changes of disc degeneration, and it is a non-invasive method. The DKI multi-parameter analysis is sensitive to discs changes caused by puncture. These slides can be retrieved under Electronic Supplementary Material.
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Affiliation(s)
- Li Li
- Radiological Department, Tongji Hospital, Tongji Medical College, HUST, Wuhan, 430030, Hubei, People's Republic of China
| | - Zhiguo Zhou
- Department of Orthopedics, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, HUST, Wuhan, 430030, Hubei, People's Republic of China
| | - Jing Li
- Department of Orthopaedic Surgery, Tongji Hospital, Tongji Medical College, HUST, Wuhan, 430030, Hubei, People's Republic of China
| | - Jicheng Fang
- Radiological Department, Tongji Hospital, Tongji Medical College, HUST, Wuhan, 430030, Hubei, People's Republic of China
| | - Yuanyuan Qing
- Radiological Department, Tongji Hospital, Tongji Medical College, HUST, Wuhan, 430030, Hubei, People's Republic of China
| | - Tian Tian
- Radiological Department, Tongji Hospital, Tongji Medical College, HUST, Wuhan, 430030, Hubei, People's Republic of China
| | - Shun Zhang
- Radiological Department, Tongji Hospital, Tongji Medical College, HUST, Wuhan, 430030, Hubei, People's Republic of China
| | - Gang Wu
- Radiological Department, Tongji Hospital, Tongji Medical College, HUST, Wuhan, 430030, Hubei, People's Republic of China
| | - Alessandro Scotti
- Departments of Radiology, Department of Bioengineering, and the Center for MR Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Kejia Cai
- Departments of Radiology, Department of Bioengineering, and the Center for MR Research, University of Illinois at Chicago, Chicago, IL, USA
| | - WenZhen Zhu
- Radiological Department, Tongji Hospital, Tongji Medical College, HUST, Wuhan, 430030, Hubei, People's Republic of China.
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Song B, Wang H, Chen Y, Liu W, Wei R, Ding Y. Efficacy of apparent diffusion coefficient in predicting aggressive histological features of papillary thyroid carcinoma. Diagn Interv Radiol 2018; 24:348-356. [PMID: 30373722 PMCID: PMC6223822 DOI: 10.5152/dir.2018.18130] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Revised: 07/29/2018] [Accepted: 08/28/2018] [Indexed: 12/16/2022]
Abstract
PURPOSE We aimed to evaluate preoperative diffusion-weighted magnetic resonance imaging (DWI) for predicting aggressive histological features in papillary thyroid cancer (PTC). METHODS This prospective study included 141 PTC patients, who underwent DWI prior to thyroidectomy; 88 patients with 88 PTC lesions were finally analyzed. Multiple comparisons of mean and minimum apparent diffusion coefficient (ADC) values (ADCmean and ADCmin) and ADC of the solid component (ADCsolid) between the lowly aggressive PTC, highly aggressive PTC without hobnail, and hobnail variant PTC groups were performed by one-way ANOVA or the Welch test. The nonparametric Kruskal-Wallis H-test was used to assess lesion size differences. Receiver-operating characteristic (ROC) curve analysis was also performed. RESULTS ADC values in the lowly aggressive PTC group were found to be significantly higher than those in the highly aggressive PTC without hobnail group (ADCmean: 1.35±0.20×10-3 mm2/s vs. 1.16±0.17×10-3 mm2/s, P = 0.003; ADCmin: 1.10±0.17×10-3 mm2/s vs. 0.88±0.16×10-3 mm2/s, P < 0.001; ADCsolid: 1.26±0.23×10-3 mm2/s vs. 1.04±0.17×10-3 mm2/s, P < 0.001). No significant differences for the ADCmean, ADCmin, and ADCsolid were observed between the lowly aggressive and hobnail variant PTC groups (all P > 0.05). Lesion sizes in the hobnail variant PTC group was significantly elevated compared with the lowly aggressive PTC group (2.19±1.21 cm vs. 0.93±0.37 cm, P < 0.001). Areas under the curves (AUCs) for ADCmean, ADCmin, and ADCsolid between the lowly aggressive PTC and highly aggressive PTC group without hobnail were 0.758, 0.851, and 0.787, respectively. The AUC for size between the lowly aggressive and hobnail variant PTC group was 0.896. CONCLUSION ADCmin from DWI could potentially provide quantitative information to differentiate lowly aggressive PTC from highly aggressive PTC lesions without hobnail variants.
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Affiliation(s)
- Bin Song
- From the Departments of Radiology (B.S. , H.W., R.W., Y.D.), Pathology (Y.C.) and General Surgery (W.L.), Minhang Branch, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hao Wang
- From the Departments of Radiology (B.S. , H.W., R.W., Y.D.), Pathology (Y.C.) and General Surgery (W.L.), Minhang Branch, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yongqi Chen
- From the Departments of Radiology (B.S. , H.W., R.W., Y.D.), Pathology (Y.C.) and General Surgery (W.L.), Minhang Branch, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Weiyan Liu
- From the Departments of Radiology (B.S. , H.W., R.W., Y.D.), Pathology (Y.C.) and General Surgery (W.L.), Minhang Branch, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ran Wei
- From the Departments of Radiology (B.S. , H.W., R.W., Y.D.), Pathology (Y.C.) and General Surgery (W.L.), Minhang Branch, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yi Ding
- From the Departments of Radiology (B.S. , H.W., R.W., Y.D.), Pathology (Y.C.) and General Surgery (W.L.), Minhang Branch, Zhongshan Hospital, Fudan University, Shanghai, China
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Guo BL, Ouyang FS, Ouyang LZ, Liu ZW, Lin SJ, Meng W, Huang XY, Chen HX, Yang SM, Hu QG. Development and validation of an ultrasound-based nomogram to improve the diagnostic accuracy for malignant thyroid nodules. Eur Radiol 2018; 29:1518-1526. [DOI: 10.1007/s00330-018-5715-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Revised: 07/17/2018] [Accepted: 08/14/2018] [Indexed: 12/16/2022]
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Meyer HJ, Leifels L, Hamerla G, Höhn AK, Surov A. ADC-histogram analysis in head and neck squamous cell carcinoma. Associations with different histopathological features including expression of EGFR, VEGF, HIF-1α, Her 2 and p53. A preliminary study. Magn Reson Imaging 2018; 54:214-217. [PMID: 30189236 DOI: 10.1016/j.mri.2018.07.013] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Revised: 07/23/2018] [Accepted: 07/23/2018] [Indexed: 12/27/2022]
Abstract
OBJECTIVE Apparent diffusion coefficient (ADC) values derived from Diffusion-weighted images are able to reflect tumor microstructure, such as cellularity, extracellular matrix or proliferation potential. This present study sought to correlate prognostic relevant histopathologic parameters with ADC values derived from a whole lesion measurement in head and neck squamous cell carcinoma (HNSCC). MATERIALS AND METHODS Thirty-four patients with histological proven primary HNSCC were prospectively acquired. Histogram analysis was derived from ADC maps. In all cases, expression of Hif1-alpha, VEGF, EGFR, p53, p16, Her 2 were analyzed. RESULTS In the overall patient sample, ADCmax correlated with p53 expression (p = -0.446, p = 0.009) and ADCmode correlated with Her2-expression (p = -0.354, p = 0.047). In the p16 positive group there were several correlations. P25, P90 and entropy correlated with Hif1-alpha (p = -0.423, p = 0.05, p = -0.494, p = 0.019, p = 0.479, p = 0.024, respectively). Kurtosis correlated with P53 expression (p = -0.466, p = 0.029). For p16 negative carcinomas the following associations could be identified. Mode correlated with VEGF-expression (p = -0.657, p = 0.039). ADCmax, P75, P90, and Std correlated with p53-expression (p = -0.827, p = 0.002, p = -0.736, p = 0.01, p = -0.836, p = 0.001 and p = -0.70, p = 0.016, respectively). There were no statistically significant differences of ADC histogram parameters between p16 positive and p16 negative carcinomas. CONCLUSION ADC histogram values can reflect different histopathological features in HNSCC. Associations between ADC histogram analysis parameters and histopathology depend on p16 status.
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Affiliation(s)
- Hans Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany.
| | - Leonard Leifels
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany.
| | - Gordian Hamerla
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany.
| | | | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Germany.
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Greco A, Auletta L, Orlandella FM, Iervolino PLC, Klain M, Salvatore G, Mancini M. Preclinical Imaging for the Study of Mouse Models of Thyroid Cancer. Int J Mol Sci 2017; 18:E2731. [PMID: 29258188 PMCID: PMC5751332 DOI: 10.3390/ijms18122731] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Revised: 12/05/2017] [Accepted: 12/08/2017] [Indexed: 12/23/2022] Open
Abstract
Thyroid cancer, which represents the most common tumors among endocrine malignancies, comprises a wide range of neoplasms with different clinical aggressiveness. One of the most important challenges in research is to identify mouse models that most closely resemble human pathology; other goals include finding a way to detect markers of disease that common to humans and mice and to identify the most appropriate and least invasive therapeutic strategies for specific tumor types. Preclinical thyroid imaging includes a wide range of techniques that allow for morphological and functional characterization of thyroid disease as well as targeting and in most cases, this imaging allows quantitative analysis of the molecular pattern of the thyroid cancer. The aim of this review paper is to provide an overview of all of the imaging techniques used to date both for diagnosis and theranostic purposes in mouse models of thyroid cancer.
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Affiliation(s)
- Adelaide Greco
- Dipartimento di Scienze Biomediche Avanzate, Università degli Studi di Napoli Federico II, 80131 Napoli, Italy.
- Istituto di Biostrutture e Bioimmagini, Consiglio Nazionale delle Ricerche-IBB, CNR, 80145 Napoli, Italy.
- CEINGE Biotecnologie Avanzate s.c.ar.l., 80131 Napoli, Italy.
| | | | | | | | - Michele Klain
- Dipartimento di Scienze Biomediche Avanzate, Università degli Studi di Napoli Federico II, 80131 Napoli, Italy.
| | - Giuliana Salvatore
- IRCCS S.D.N., 80134 Napoli, Italy.
- Dipartimento di Scienze Motorie e del Benessere, Università di Napoli Parthenope, 80133 Napoli, Italy.
| | - Marcello Mancini
- Istituto di Biostrutture e Bioimmagini, Consiglio Nazionale delle Ricerche-IBB, CNR, 80145 Napoli, Italy.
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Meyer HJ, Schob S, Höhn AK, Surov A. MRI Texture Analysis Reflects Histopathology Parameters in Thyroid Cancer - A First Preliminary Study. Transl Oncol 2017; 10:911-916. [PMID: 28987630 PMCID: PMC5645305 DOI: 10.1016/j.tranon.2017.09.003] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2017] [Accepted: 09/14/2017] [Indexed: 11/23/2022] Open
Abstract
OBJECT Thyroid cancer represents the most frequent malignancy of the endocrine system with an increasing incidence worldwide. Novel imaging techniques are able to further characterize tumors and even predict histopathology features. Texture analysis is an emergent imaging technique to extract extensive data from an radiology images. The present study was therefore conducted to identify possible associations between texture analysis and histopathology parameters in thyroid cancer. METHODS The radiological database was retrospectively reviewed for thyroid carcinoma. Overall, 13 patients (3 females, 23.1%) with a mean age of 61.6 years were identified. The MaZda program was used for texture analysis. The T1-precontrast and T2-weighted images were analyzed and overall 279 texture feature for each sequence was investigated. For every patient cell count, Ki67-index and p53 count were investigated. RESULTS Several significant correlations between texture features and histopathology were identified. Regarding T1-weighted images, S(0;1)Sum Averg correlated the most with cell count (r=0.82). An inverse correlations with S(5;0)AngScMom, S(5;0)DifVarnc S(5;0), DiffEntrp and GrNonZeros (r=-0.69, -0.66, -0.69 and -0.63, respectively) was also identified. For T2-weighted images, Variance with r=0.63 was the highest coefficient, WavEnLL_S3 correlated inversely with cell count (r=-0.57). WavEnLL_S2 derived from T1-weighted images was the highest coefficient r=-0.80, S(0;5)SumVarnc was positively with r=0.74. Regarding T2-weighted images WavEnHL_s-1 was inverse correlated with Ki67 index (r=-0.77). S(1;0)Correlat was with r=0.75 the best correlation with Ki67 index. For T1-weighed images S(5;0)SumofSqs was the best with r=0.65 with p53 count. For T2-weighted images S(1;-1)SumEntrp was the inverse correlation with r=-0.72, whereas S(0;4)AngScMom correlated positively with r=0.63. CONCLUSIONS MRI texture analysis derived from conventional sequences reflects histopathology features in thyroid cancer. This technique might be a novel noninvasive modality to further characterize thyroid cancer in clinical oncology.
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Affiliation(s)
- Hans-Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany.
| | - Stefan Schob
- Department of Neuroradiology, University of Leipzig, Leipzig, Germany
| | | | - Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
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