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Liu SZ, Yang SH, Ye M, Fu BJ, Lv FJ, Chu ZG. Bubble-like lucency in pulmonary ground glass nodules on computed tomography: a specific pattern of air-containing space for diagnosing neoplastic lesions. Cancer Imaging 2024; 24:47. [PMID: 38566150 PMCID: PMC10985942 DOI: 10.1186/s40644-024-00694-8] [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: 11/29/2023] [Accepted: 03/29/2024] [Indexed: 04/04/2024] Open
Abstract
PURPOSE To investigate the computed tomography (CT) characteristics of air-containing space and its specific patterns in neoplastic and non-neoplastic ground glass nodules (GGNs) for clarifying their significance in differential diagnosis. MATERIALS AND METHODS From January 2015 to October 2022, 1328 patients with 1,350 neoplastic GGNs and 462 patients with 465 non-neoplastic GGNs were retrospectively enrolled. Their clinical and CT data were analyzed and compared with emphasis on revealing the differences of air-containing space and its specific patterns (air bronchogram and bubble-like lucency [BLL]) between neoplastic and non-neoplastic GGNs and their significance in differentiating them. RESULTS Compared with patients with non-neoplastic GGNs, female was more common (P < 0.001) and lesions were larger (P < 0.001) in those with neoplastic ones. Air bronchogram (30.1% vs. 17.2%), and BLL (13.0% vs. 2.6%) were all more frequent in neoplastic GGNs than in non-neoplastic ones (each P < 0.001), and the BLL had the highest specificity (93.6%) in differentiation. Among neoplastic GGNs, the BLL was more frequently detected in the larger (14.9 ± 6.0 mm vs. 11.4 ± 4.9 mm, P < 0.001) and part-solid (15.3% vs. 10.7%, P = 0.011) ones, and its incidence significantly increased along with the invasiveness (9.5-18.0%, P = 0.001), whereas no significant correlation was observed between the occurrence of BLL and lesion size, attenuation, or invasiveness. CONCLUSION The air containing space and its specific patterns are of great value in differentiating GGNs, while BLL is a more specific and independent sign of neoplasms.
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Affiliation(s)
- Si-Zhu Liu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1# Youyi Road, Yuanjiagang, Yuzhong district, 400016, Chongqing, China
| | - Shi-Hai Yang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1# Youyi Road, Yuanjiagang, Yuzhong district, 400016, Chongqing, China
- Department of Radiology, People's Hospital of Nanchuan district, 16# South street, Nanchuan district, 408400, Chongqing, China
| | - Min Ye
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1# Youyi Road, Yuanjiagang, Yuzhong district, 400016, Chongqing, China
- Department of Radiology, The First People's Hospital of Neijiang, No.31 Tuozhong Road, Shizhong District, 641099, Neijiang, Sichuang Province, China
| | - Bin-Jie Fu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1# Youyi Road, Yuanjiagang, Yuzhong district, 400016, Chongqing, China
| | - Fa-Jin Lv
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1# Youyi Road, Yuanjiagang, Yuzhong district, 400016, Chongqing, China
| | - Zhi-Gang Chu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, 1# Youyi Road, Yuanjiagang, Yuzhong district, 400016, Chongqing, China.
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Roy R, Mazumdar S, Chowdhury AS. ADGAN: Attribute-Driven Generative Adversarial Network for Synthesis and Multiclass Classification of Pulmonary Nodules. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024; 35:2484-2495. [PMID: 35853058 DOI: 10.1109/tnnls.2022.3190331] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Lung cancer is the leading cause of cancer-related deaths worldwide. According to the American Cancer Society, early diagnosis of pulmonary nodules in computed tomography (CT) scans can improve the five-year survival rate up to 70% with proper treatment planning. In this article, we propose an attribute-driven Generative Adversarial Network (ADGAN) for synthesis and multiclass classification of Pulmonary Nodules. A self-attention U-Net (SaUN) architecture is proposed to improve the generation mechanism of the network. The generator is designed with two modules, namely, self-attention attribute module (SaAM) and a self-attention spatial module (SaSM). SaAM generates a nodule image based on given attributes whereas SaSM specifies the nodule region of the input image to be altered. A reconstruction loss along with an attention localization loss (AL) is used to produce an attention map prioritizing the nodule regions. To avoid resemblance between a generated image and a real image, we further introduce an adversarial loss containing a regularization term based on KL divergence. The discriminator part of the proposed model is designed to achieve the multiclass nodule classification task. Our proposed approach is validated over two challenging publicly available datasets, namely LIDC-IDRI and LUNGX. Exhaustive experimentation on these two datasets clearly indicate that we have achieved promising classification accuracy as compared to other state-of-the-art methods.
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Borgheresi A, Agostini A, Pierpaoli L, Bruno A, Valeri T, Danti G, Bicci E, Gabelloni M, De Muzio F, Brunese MC, Bruno F, Palumbo P, Fusco R, Granata V, Gandolfo N, Miele V, Barile A, Giovagnoni A. Tips and Tricks in Thoracic Radiology for Beginners: A Findings-Based Approach. Tomography 2023; 9:1153-1186. [PMID: 37368547 PMCID: PMC10301342 DOI: 10.3390/tomography9030095] [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: 05/05/2023] [Revised: 06/03/2023] [Accepted: 06/12/2023] [Indexed: 06/29/2023] Open
Abstract
This review has the purpose of illustrating schematically and comprehensively the key concepts for the beginner who approaches chest radiology for the first time. The approach to thoracic imaging may be challenging for the beginner due to the wide spectrum of diseases, their overlap, and the complexity of radiological findings. The first step consists of the proper assessment of the basic imaging findings. This review is divided into three main districts (mediastinum, pleura, focal and diffuse diseases of the lung parenchyma): the main findings will be discussed in a clinical scenario. Radiological tips and tricks, and relative clinical background, will be provided to orient the beginner toward the differential diagnoses of the main thoracic diseases.
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Affiliation(s)
- Alessandra Borgheresi
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliero Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
| | - Andrea Agostini
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliero Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Luca Pierpaoli
- School of Radiology, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
| | - Alessandra Bruno
- School of Radiology, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
| | - Tommaso Valeri
- School of Radiology, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
| | - Ginevra Danti
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Eleonora Bicci
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Michela Gabelloni
- Nuclear Medicine Unit, Department of Translational Research, University of Pisa, 56126 Pisa, Italy
| | - Federica De Muzio
- Department of Medicine and Health Sciences V. Tiberio, University of Molise, 86100 Campobasso, Italy
| | - Maria Chiara Brunese
- Department of Medicine and Health Sciences V. Tiberio, University of Molise, 86100 Campobasso, Italy
| | - Federico Bruno
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health, Unit 1, 67100 L’Aquila, Italy
| | - Pierpaolo Palumbo
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health, Unit 1, 67100 L’Aquila, Italy
| | - Roberta Fusco
- Medical Oncology Division, Igea SpA, 80013 Naples, Italy
| | - Vincenza Granata
- Division of Radiology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, 80131 Naples, Italy
| | - Nicoletta Gandolfo
- Diagnostic Imaging Department, Villa Scassi Hospital-ASL 3, 16149 Genoa, Italy
| | - Vittorio Miele
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
- Department of Radiology, Azienda Ospedaliero-Universitaria Careggi, 50134 Florence, Italy
| | - Antonio Barile
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, Italy
| | - Andrea Giovagnoni
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Via Tronto 10/a, 60126 Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliero Universitaria delle Marche”, Via Conca 71, 60126 Ancona, Italy
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Leveraging Deep Learning Decision-Support System in Specialized Oncology Center: A Multi-Reader Retrospective Study on Detection of Pulmonary Lesions in Chest X-ray Images. Diagnostics (Basel) 2023; 13:diagnostics13061043. [PMID: 36980351 PMCID: PMC10047277 DOI: 10.3390/diagnostics13061043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 02/27/2023] [Accepted: 03/07/2023] [Indexed: 03/12/2023] Open
Abstract
Chest X-ray (CXR) is considered to be the most widely used modality for detecting and monitoring various thoracic findings, including lung carcinoma and other pulmonary lesions. However, X-ray imaging shows particular limitations when detecting primary and secondary tumors and is prone to reading errors due to limited resolution and disagreement between radiologists. To address these issues, we developed a deep-learning-based automatic detection algorithm (DLAD) to automatically detect and localize suspicious lesions on CXRs. Five radiologists were invited to retrospectively evaluate 300 CXR images from a specialized oncology center, and the performance of individual radiologists was subsequently compared with that of DLAD. The proposed DLAD achieved significantly higher sensitivity (0.910 (0.854–0.966)) than that of all assessed radiologists (RAD 10.290 (0.201–0.379), p < 0.001, RAD 20.450 (0.352–0.548), p < 0.001, RAD 30.670 (0.578–0.762), p < 0.001, RAD 40.810 (0.733–0.887), p = 0.025, RAD 50.700 (0.610–0.790), p < 0.001). The DLAD specificity (0.775 (0.717–0.833)) was significantly lower than for all assessed radiologists (RAD 11.000 (0.984–1.000), p < 0.001, RAD 20.970 (0.946–1.000), p < 0.001, RAD 30.980 (0.961–1.000), p < 0.001, RAD 40.975 (0.953–0.997), p < 0.001, RAD 50.995 (0.985–1.000), p < 0.001). The study results demonstrate that the proposed DLAD could be utilized as a decision-support system to reduce radiologists’ false negative rate.
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Gandomkar Z, Khong PL, Punch A, Lewis S. Using Occlusion-Based Saliency Maps to Explain an Artificial Intelligence Tool in Lung Cancer Screening: Agreement Between Radiologists, Labels, and Visual Prompts. J Digit Imaging 2022; 35:1164-1175. [PMID: 35484439 PMCID: PMC9582174 DOI: 10.1007/s10278-022-00631-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 03/03/2022] [Accepted: 04/04/2022] [Indexed: 11/29/2022] Open
Abstract
Occlusion-based saliency maps (OBSMs) are one of the approaches for interpreting decision-making process of an artificial intelligence (AI) system. This study explores the agreement among text responses from a cohort of radiologists to describe diagnostically relevant areas on low-dose CT (LDCT) images. It also explores if radiologists' descriptions of cases misclassified by the AI provide a rationale for ruling out the AI's output. The OBSM indicating the importance of different pixels on the final decision made by an AI were generated for 10 benign cases (3 misclassified by the AI tool as malignant) and 10 malignant cases (2 misclassified by the AI tool as benign). Thirty-six radiologists were asked to use radiological vocabulary, typical to reporting LDCT scans, to describe the mapped regions of interest (ROI). The radiologists' annotations were then grouped by using a clustering-based technique. Topics were extracted from the annotations and for each ROI, a percentage of annotations containing each topic were found. Radiologists annotated 17 and 24 unique ROIs on benign and malignant cases, respectively. Agreement on the main label (e.g., "vessel," "nodule") by radiologists was only seen in only in 12% of all areas (5/41 ROI). Topic analyses identified six descriptors which are commonly associated with a lower malignancy likelihood. Eight common topics related to a higher malignancy likelihood were also determined. Occlusion-based saliency maps were used to explain an AI decision-making process to radiologists, who in turn have provided insight into the level of agreement between the AI's decision and radiological lexicon.
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Affiliation(s)
- Ziba Gandomkar
- Discipline of Medical Imaging Science, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Pek Lan Khong
- Clinical Imaging Research Center (CIRC), Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Amanda Punch
- Discipline of Medical Imaging Science, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Sarah Lewis
- Discipline of Medical Imaging Science, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
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Lu YL, Chen ST, Ho TY, Chan WH, Wong RJ, Hsueh C, Lin SF. Primary lung cancer with radioiodine avidity: A thyroid cancer cohort study. World J Clin Cases 2021; 9:71-80. [PMID: 33511173 PMCID: PMC7809679 DOI: 10.12998/wjcc.v9.i1.71] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 10/30/2020] [Accepted: 11/12/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND A proportion of lung cancers show sodium/iodide symporter (NIS) expression. Lung cancers with NIS expression may uptake radioiodine (RAI) and show RAI-avid lesions on RAI scan for differentiated thyroid cancer (DTC) surveillance.
AIM To investigate the possibility of RAI uptake by lung cancer in a cohort with thyroid cancer.
METHODS RAI-avid lung cancers were analyzed using a prospectively maintained database of patients with thyroid cancer who were registered at a medical center between December 1, 1976 and May 28, 2018. NIS expression in lung cancer was assessed using immunohistochemical staining.
RESULTS Of the 5000 patients with thyroid cancer from the studied dataset, 4602 had DTC. During follow-up, 33 patients developed primary lung cancer. Of these patients, nine received an iodine-131 (131I) scan within 1 year before the diagnosis of lung cancer. One of these nine lung cancers was RAI-avid. NIS expression was evaluated, and three of the eight available lung cancers revealed NIS expression. The proportions of lung cancer cells with NIS expression were 60%, 15%, and 10%. The RAI-avid lung cancer had the highest level of expression (60%). The RAI-avid lung cancer had a spiculated border upon single-photon emission computed tomography/computed tomography, which led to an accurate diagnosis.
CONCLUSION A proportion of lung cancer demonstrates NIS expression and is RAI-avid. Clinicians should be aware of this possibility in the interpretation of RAI scintigraphy.
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Affiliation(s)
- Yu-Ling Lu
- Department of Internal Medicine, New Taipei Municipal TuCheng Hospital, New Taipei City 236, Taiwan
- Department of Internal Medicine, Chang Gung Memorial Hospital, Taoyuan 333, Taiwan
| | - Szu-Tah Chen
- Department of Internal Medicine, Chang Gung Memorial Hospital, Taoyuan 333, Taiwan
- College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
| | - Tsung-Ying Ho
- Department of Nuclear Medicine, Chang Gung Memorial Hospital, Taoyuan 333, Taiwan
| | - Wen-Hui Chan
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Taoyuan 333, Taiwan
- Institute for Radiological Research, College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
| | - Richard J Wong
- Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, United States
| | - Chuen Hsueh
- Department of Pathology, Chang-Gung Memorial Hospital, Taoyuan 333, Taiwan
| | - Shu-Fu Lin
- Department of Internal Medicine, New Taipei Municipal TuCheng Hospital, New Taipei City 236, Taiwan
- Department of Internal Medicine, Chang Gung Memorial Hospital, Taoyuan 333, Taiwan
- College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
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Liu L, Dou Q, Chen H, Qin J, Heng PA. Multi-Task Deep Model With Margin Ranking Loss for Lung Nodule Analysis. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:718-728. [PMID: 31403410 DOI: 10.1109/tmi.2019.2934577] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Lung cancer is the leading cause of cancer deaths worldwide and early diagnosis of lung nodule is of great importance for therapeutic treatment and saving lives. Automated lung nodule analysis requires both accurate lung nodule benign-malignant classification and attribute score regression. However, this is quite challenging due to the considerable difficulty of lung nodule heterogeneity modeling and the limited discrimination capability on ambiguous cases. To solve these challenges, we propose a Multi-Task deep model with Margin Ranking loss (referred as MTMR-Net) for automated lung nodule analysis. Compared to existing methods which consider these two tasks separately, the relatedness between lung nodule classification and attribute score regression is explicitly explored in a cause-and-effect manner within our multi-task deep model, which can contribute to the performance gains of both tasks. The results of different tasks can be yielded simultaneously for assisting the radiologists in diagnosis interpretation. Furthermore, a Siamese network with a margin ranking loss is elaborately designed to enhance the discrimination capability on ambiguous nodule cases. To further explore the internal relationship between two tasks and validate the effectiveness of the proposed model, we use the recursive feature elimination method to iteratively rank the most malignancy-related features. We validate the efficacy of our method MTMR-Net on the public benchmark LIDC-IDRI dataset. Extensive experiments show that the diagnosis results with internal relationship explicitly explored in our model has met some similar patterns in clinical usage and also demonstrate that our approach can achieve competitive classification performance and more accurate scoring on attributes over the state-of-the-arts. Codes are publicly available at: https://github.com/CaptainWilliam/MTMR-NET.
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Miyata T, Yanagawa M, Hata A, Honda O, Yoshida Y, Kikuchi N, Tsubamoto M, Tsukagoshi S, Uranishi A, Tomiyama N. Influence of field of view size on image quality: ultra-high-resolution CT vs. conventional high-resolution CT. Eur Radiol 2020; 30:3324-3333. [PMID: 32072253 PMCID: PMC7248011 DOI: 10.1007/s00330-020-06704-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Accepted: 02/03/2020] [Indexed: 12/03/2022]
Abstract
Objectives This study was conducted in order to compare the effect of field of view (FOV) size on image quality between ultra-high-resolution CT (U-HRCT) and conventional high-resolution CT (HRCT). Methods Eleven cadaveric lungs were scanned with U-HRCT and conventional HRCT and reconstructed with five FOVs (40, 80, 160, 240, and 320 mm). Three radiologists evaluated and scored the images. Three image evaluations were performed, comparing the image quality with the five FOVs with respect to the 160-mm FOV. The first evaluation was performed on conventional HRCT images, and the second evaluation on U-HRCT images. Images were scored on normal structure, abnormal findings, and overall image quality. The third evaluation was a comparison of the images obtained with conventional HRCT and U-HRCT, with scoring performed on overall image quality. Quantitative evaluation of noise was performed by setting ROIs. Results In conventional HRCT, image quality was improved when the FOV was reduced to 160 mm. In U-HRCT, image quality, except for noise, improved when the FOV was reduced to 80 mm. In the third evaluation, overall image quality was improved in U-HRCT over conventional HRCT at all FOVs. Noise of U-HRCT increased with respect to conventional HRCT when the FOV was reduced from 160 to 40 mm. However, at 240- and 320-mm FOVs, the noise of U-HRCT and conventional HRCT showed no differences. Conclusions In conventional HRCT, image quality did not improve when the FOV was reduced below 160 mm. However, in U-HRCT, image quality improved even when the FOV was reduced to 80 mm. Key Points • Reducing the size of the field of view to 160 mm improves diagnostic imaging quality in high-resolution CT. • In ultra-high-resolution CT, improvements in image quality can be obtained by reducing the size of the field of view to 80 mm. • Ultra-high-resolution CT produces images of higher quality compared with conventional HRCT irrespective of the size of the field of view. Electronic supplementary material The online version of this article (10.1007/s00330-020-06704-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tomo Miyata
- Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita City, Osaka, 565-0871, Japan.
| | - Masahiro Yanagawa
- Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita City, Osaka, 565-0871, Japan
| | - Akinori Hata
- Department of Future Diagnostic Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita City, Osaka, 565-0871, Japan
| | - Osamu Honda
- Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita City, Osaka, 565-0871, Japan
| | - Yuriko Yoshida
- Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita City, Osaka, 565-0871, Japan
| | - Noriko Kikuchi
- Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita City, Osaka, 565-0871, Japan
| | - Mitsuko Tsubamoto
- Department of Future Diagnostic Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita City, Osaka, 565-0871, Japan
| | - Shinsuke Tsukagoshi
- Department of CT Systems, Canon Medical Systems Corp., Otawara, Tochigi, Japan
| | - Ayumi Uranishi
- Department of CT Systems, Canon Medical Systems Corp., Otawara, Tochigi, Japan
| | - Noriyuki Tomiyama
- Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita City, Osaka, 565-0871, Japan
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Shi W, Zhou L, Peng X, Ren H, Wang Q, Shan F, Zhang Z, Liu L, Shi Y. HIV-infected patients with opportunistic pulmonary infections misdiagnosed as lung cancers: the clinicoradiologic features and initial application of CT radiomics. J Thorac Dis 2019; 11:2274-2286. [PMID: 31372264 DOI: 10.21037/jtd.2019.06.22] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Background To characterize clinicoradiologic and radiomic features for identifying opportunistic pulmonary infections (OPIs) misdiagnosed as lung cancers in patients with human immunodeficiency virus (HIV). Methods Twenty-four HIV-infected patients who were misdiagnosed with lung cancers on CT images and had OPIs confirmed by pathological examination or integration of clinical and laboratory findings and 49 HIV-infected patients with lung cancers confirmed pathologically were included. Semiautomated segmentation of the lesion was implemented with an in-house software. The lesion boundary was adjusted manually by radiologists. A total of 99 nonenhanced-CT-based radiomic features were then extracted with PyRadiomics. The clinicoradiologic and radiomic features were compared between the OPI and cancer groups. Results In the OPI group, 19 patients (79.2%) had tuberculosis (TB) infections, 2 (8.3%) had nontuberculosis mycobacterium (NTM) infections, 2 (8.3%) had cryptococcus infections and 1 (4.2%) had a mixed infection of TB and NTM. There were significant differences in age, proportion of smokers, smoking index, highly active antiretroviral therapy (HAART) duration, CD4+ counts and CD4+/CD8+ ratio between the two groups (P=0.000, 0.012, 0.007, 0.002, 0.000, and 0.000, respectively). In peripheral-type lesions, the presence of pleural indentation was less common, and the presence of satellite lesions was more common in the OPI group (P=0.016 and 0.020, respectively). Four radiomic parameters of central-type lesions were significantly different, including large dependence high gray level emphasis (LDHGLE), skewness, inverse difference normalized (IDN) and kurtosis (P=0.008, 0.017, 0.017, and 0.017, respectively). However, neither CT features of central-type lesions nor radiomic parameters of peripheral-type lesions were significantly different between the two groups. Conclusions Clinicoradiologic features together with radiomics may help identify OPIs mimicking lung cancers in HIV-infected patients.
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Affiliation(s)
- Weiya Shi
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China
| | - Lingxiao Zhou
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Xueqing Peng
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - He Ren
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Qinglei Wang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Fei Shan
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China
| | - Zhiyong Zhang
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China.,Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.,Headmaster's Office, Fudan University, Shanghai 200433, China
| | - Lei Liu
- Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China
| | - Yuxin Shi
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China
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Zhu Y, Hou D, Lan M, Sun X, Ma X. A comparison of ultra-high-resolution CT target scan versus conventional CT target reconstruction in the evaluation of ground-glass-nodule-like lung adenocarcinoma. Quant Imaging Med Surg 2019; 9:1087-1094. [PMID: 31367562 DOI: 10.21037/qims.2019.06.09] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background The aim of this study was to determine whether the clinical value of scanned computed tomography (CT) images is higher when using ultra-high-resolution CT (U-HRCT) target scanning than conventional CT target reconstruction scanning in the evaluation of ground-glass-nodule (GGN)-like lung adenocarcinoma. Methods A total of 91 consecutive patients with isolated GGN-like lung adenocarcinoma were included in this study from April 2017 to June 2018. U-HRCT and conventional CT scans were conducted in all enrolled patients. Two experienced thoracic radiologists independently assessed image quality and made diagnoses. Based on the pathological results, the accuracies of U-HRCT target scanning and conventional CT target reconstruction for detecting morphological features on CT, including spiculation of GGNs, bronchial vascular bundles, solid components in the nodules, burr, vacuole, air bronchial signs, and fissure distortion, were calculated. All statistical analyses were performed using SPSS 17.0 software. Enumeration data were tested using the Chi-square test. A P value of <0.05 was considered statistically significant. Results When both techniques were compared with the pathological findings, the detection rate for CT images obtained using U-HRCT target scanning and conventional CT target reconstruction with regard to the spiculation of GGNs, bronchial vascular bundles, and solid components in the nodules were 78% vs. 61.5%, 72.5% vs. 54.9%, 65.9% vs. 49.5%, respectively. The presence of the spiculation of GGNs, bronchial vascular bundles, and solid components in the nodules in U-HRCT target scanning was significantly higher than that in conventional CT target reconstruction (all P<0.05). However, no significant difference was observed between the two techniques with regard to the burr, vacuole, air bronchial signs, and fissure distortion (all P>0.05). Conclusions When viewing GGNs, the detection rate was higher for U-HRCT target scanning than for conventional CT target reconstruction, and this improvement significantly enhanced the diagnostic accuracy of early lung adenocarcinoma.
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Affiliation(s)
- Yanyan Zhu
- Division of Computed Tomography, Department of Radiology, Shandong University School of Medicine, Shandong Provincial Third Hospital, Jinan 250031, China
| | - Dailun Hou
- Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Meihong Lan
- Department of Radiology, Shandong Chest Hospital, Jinan 250101, China
| | - Xiaoli Sun
- Department of Computed Tomography, Beijing Shijitan Hospital, Ninth Clinical Medical College of Peking University, Capital Medical University, Beijing 100038, China
| | - Xiangxing Ma
- Department of Radiology, Qilu Hospital, Shandong University, Jinan 250012, China
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11
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Dang S, Gao X, Ma G, Yu N, Han D, Yang Q, Tian X, Duan H. Combination of free-breathing radial 3D fat-suppressed T1-weighted gradient-echo sequence with diffusion weighted images: Potential for differentiating malignant from benign peripheral solid pulmonary masses. Magn Reson Imaging 2018; 57:271-276. [PMID: 30557591 DOI: 10.1016/j.mri.2018.12.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Accepted: 12/08/2018] [Indexed: 12/31/2022]
Abstract
OBJECTIVES High resolution CT is the most commonly used radiological method for differentiating benign from malignant peripheral solid pulmonary masses, however, some of them are not easily diagnosed by morphology alone. Furthermore, due to the radiation dose, it is unsuitable for patients with disorders requiring repeated examinations over prolonged periods. The aims of this study were to evaluate whether a combination of diffusion-weighted images (DWI) and free-breathing radial 3D fat-suppressed T1-weighted gradient echo (radial volumetric interpolated breath-hold examination, radial VIBE) sequence can enable discrimination between benign from malignant peripheral solid pulmonary masses. MATERIALS AND METHODS Both chest CT scan and MR imaging with radial VIBE and DWI were obtained from 47 patients; 30 males and 17 females (mean age 64 years old; age range 48-83 years old). Benign and malignant peripheral solid pulmonary masses were conclusively identified by pathology results. Two radiologists independently reviewed all the images and record radiological features including morphological signs on radial VIBE, CT images, and ADC value. Receiver operating characteristic (ROC) was used to analyze the capability of radial VIBE as well as DWI to distinguish malignant from benign peripheral solid pulmonary masses. RESULTS In 77% of patients, malignant peripheral solid pulmonary masses were found. Morphological signs of mediastinal lymph node enlargement and lobulation were more easily found in malignant masses in both radial VIBE (mediastinal lymph node enlargement: p = 0.033, lobulation: p = 0.039) and CT (mediastinal lymph node enlargement: p = 0.004, lobulation: p = 0.012). The ADC value were also significant difference between benign and malignant groups (p = 0.001). Combined ADC value with radial VIBE was a most specific test than routine-dose CT (86.1% vs 75%, p < 0.001), but less sensitive than routine-dose CT (81.8% vs 90.9%; p < 0.001) for malignant peripheral solid pulmonary masses detection. Diagnostic accuracy was 89% for combining ADC value with radial VIBE, and 85% for routine-dose CT. CONCLUSIONS Combination of morphological signs and ADC value seems to improve differentiating malignant from benign peripheral solid pulmonary masses. Especially in patients unable to endure radiation exposure, suspend respiration, radial VIBE provides similar morphological signs displaying to those on routine-dose CT.
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Affiliation(s)
- Shan Dang
- Department of Radiology, The affiliated hospital of Shaanxi university of Chinese medicine, Xian Yang, China
| | - Xiang Gao
- Department of Clinical Lab, Nuclear Industry 215 Hospital of Shaanxi Province, Xian Yang, China
| | - Guangming Ma
- Department of Radiology, The affiliated hospital of Shaanxi university of Chinese medicine, Xian Yang, China
| | - Nan Yu
- Department of Radiology, The affiliated hospital of Shaanxi university of Chinese medicine, Xian Yang, China
| | - Dong Han
- Department of Radiology, The affiliated hospital of Shaanxi university of Chinese medicine, Xian Yang, China
| | - Qi Yang
- Department of Radiology, The affiliated hospital of Shaanxi university of Chinese medicine, Xian Yang, China
| | - Xin Tian
- Department of Radiology, The affiliated hospital of Shaanxi university of Chinese medicine, Xian Yang, China
| | - Haifeng Duan
- Department of Radiology, The affiliated hospital of Shaanxi university of Chinese medicine, Xian Yang, China.
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Evaluation of the solitary pulmonary nodule: size matters, but do not ignore the power of morphology. Insights Imaging 2017; 9:73-86. [PMID: 29143191 PMCID: PMC5825309 DOI: 10.1007/s13244-017-0581-2] [Citation(s) in RCA: 115] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2017] [Revised: 10/02/2017] [Accepted: 10/05/2017] [Indexed: 12/17/2022] Open
Abstract
Abstract Subsequent to the widespread use of multidetector computed tomography and growing interest in lung cancer screening, small pulmonary nodules are more frequently detected. The differential diagnosis for a solitary pulmonary nodule is extremely broad and includes both benign and malignant causes. Recognition of early lung cancers is vital, since stage at diagnosis is crucial for prognosis. Estimation of the probability of malignancy is a challenging task, but crucial for follow-up and further work-up. In addition to the clinical setting and metabolic assessment, morphological assessment on thin-section computed tomography is essential. Size and growth are key factors in assessment of the malignant potential of a nodule. The likelihood of malignancy positively correlates with nodule diameter: as the diameter increases, so does the likelihood of malignancy. Although there is a considerable overlap in the features of benign and malignant nodules, the importance of morphology however should not be underestimated. Features that are associated with benignity include a perifissural location and triangular morphology, internal fat and benign calcifications. Malignancy is suspected in nodules presenting with spiculation, lobulation, pleural indentation, vascular convergence sign, associated cystic airspace, bubble-like lucencies, irregular air bronchogram, and subsolid morphology. Nodules often show different features and combination of findings is certainly more powerful. Teaching points • Size of a pulmonary nodule is important, but morphological assessment should not be underestimated. • Lung nodules should be evaluated on thin section CT, in both lung and mediastinal window setting. • Features associated with benignity include a triangular morphology, internal fat and calcifications. • Spiculation, pleural retraction and notch sign are highly suggestive of a malignant nature. • Complex features (e.g. bubble-like lucencies) are highly indicative of a malignant nature.
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Yang W, Sun Y, Fang W, Qian F, Ye J, Chen Q, Jiang Y, Yu K, Han B. High-resolution Computed Tomography Features Distinguishing Benign and Malignant Lesions Manifesting as Persistent Solitary Subsolid Nodules. Clin Lung Cancer 2017; 19:e75-e83. [PMID: 28822623 DOI: 10.1016/j.cllc.2017.05.023] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2017] [Revised: 05/28/2017] [Accepted: 05/30/2017] [Indexed: 01/24/2023]
Abstract
INTRODUCTION We retrospectively investigated the high-resolution computed tomography features that distinguish benign lesions (BLs) from malignant lesions (MLs) appearing as persistent solitary subsolid nodules (SSNs). MATERIALS AND METHODS In 2015, the data from patients treated in our department with persistent solitary SSNs 5 to 30 mm in size were analyzed retrospectively. The demographic data and HRCT findings were analyzed and compared between those with BLs and MLs. RESULTS Of the 1934 SSNs, 94 were BLs and 1840 were MLs. One half of the MLs (920 SSNs) were randomly selected and analyzed. The BLs were classified into 2 subgroups: 28 pure ground-glass nodules (pGGNs) and 66 part-solid nodules (PSNs). After matching in each group, 56 pGGNs and 132 PSNs in the ML group were selected. In the pGGN subgroup, multivariate analysis found that a well-defined border (odds ratio [OR], 4.320; 95% confidence interval [CI], 1.534-12.168; P = .006; area under the curve, 0.705; 95% CI, 0.583-0.828; P = .002) and a higher average CT value (OR, 1.007; 95% CI, 1.001-1.013; P = .026; area under the curve, 0.715; 95% CI, 0.599-0.831; P = .001) favored the diagnosis of malignancy. In the PSN subgroup, multivariate analysis revealed that a larger size (OR, 1.084; 95% CI, 1.015-1.158; P = .016), a well-defined border (OR, 3.447; 95% CI, 1.675-7.094; P = .001), and a spiculated margin (OR, 2.735; 95% CI, 1.359-5.504; P = .005) favored the diagnosis of malignancy. CONCLUSION In pGGNs, a well-defined lesion border and a larger average CT value can be valuable discriminators to distinguish between MLs and BLs. In PSNs, a larger size, well-defined border, and spiculated margin had greater predictive value for malignancy.
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Affiliation(s)
- Wenjia Yang
- Department of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yifeng Sun
- Department of Thoracic Surgery Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Wentao Fang
- Department of Thoracic Surgery Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Fangfei Qian
- Department of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Jianding Ye
- Department of Radiology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Qunhui Chen
- Department of Radiology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yifeng Jiang
- Department of Radiology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Keke Yu
- Department of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Baohui Han
- Department of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
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Sawada S, Suehisa H, Ueno T, Sugimoto R, Yamashita M. Monitoring and management of lung cancer patients following curative-intent treatment: clinical utility of 2-deoxy-2-[fluorine-18]fluoro-d-glucose positron emission tomography/computed tomography. LUNG CANCER-TARGETS AND THERAPY 2016; 7:45-51. [PMID: 28210160 PMCID: PMC5310700 DOI: 10.2147/lctt.s83644] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
A large number of studies have demonstrated that 2-deoxy-2-[fluorine-18]fluoro-d-glucose positron emission tomography/computed tomography (FDG-PET/CT) is superior to conventional modalities for the diagnosis of lung cancer and the evaluation of the extent of the disease. However, the efficacy of PET/CT in a follow-up surveillance setting following curative-intent treatments for lung cancer has not yet been established. We reviewed previous papers and evaluated the potential efficacy of PET-CT in the setting of follow-up surveillance. The following are our findings: 1) PET/CT is considered to be superior or equivalent to conventional modalities for the detection of local recurrence. However, inflammatory changes and fibrosis after treatments in local areas often result in false-positive findings; 2) the detection of asymptomatic distant metastasis is considered to be an advantage of PET/CT in a follow-up setting. However, it should be noted that detection of brain metastasis with PET/CT has some limitation, similar to its use in pretreatment staging; 3) additional radiation exposure and higher medical cost arising from the use of PET/CT should be taken into consideration, particularly in patients who might not have cancer after curative-intent treatment and are expected to have a long lifespan. The absence of any data regarding survival benefits and/or improvements in quality of life is another critical issue. In summary, PET/CT is considered to be more accurate and sensitive than conventional modalities for the detection of asymptomatic recurrence after curative-intent treatments. These advantages could modify subsequent management in patients with suspected recurrence and might contribute to the selection of appropriate treatments for recurrence. Therefore, PET/CT may be an alternative to conventional follow-up modalities. However, several important issues remain to be solved. PET/CT in a follow-up surveillance setting is generally not recommended in clinical practice at the moment.
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Affiliation(s)
- Shigeki Sawada
- Department of Thoracic Surgery, National Hospital Organization Shikoku Cancer Center, Matsuyama, Japan
| | - Hiroshi Suehisa
- Department of Thoracic Surgery, National Hospital Organization Shikoku Cancer Center, Matsuyama, Japan
| | - Tsuyoshi Ueno
- Department of Thoracic Surgery, National Hospital Organization Shikoku Cancer Center, Matsuyama, Japan
| | - Ryujiro Sugimoto
- Department of Thoracic Surgery, National Hospital Organization Shikoku Cancer Center, Matsuyama, Japan
| | - Motohiro Yamashita
- Department of Thoracic Surgery, National Hospital Organization Shikoku Cancer Center, Matsuyama, Japan
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Yasaka K, Katsura M, Hanaoka S, Sato J, Ohtomo K. High-resolution CT with new model-based iterative reconstruction with resolution preference algorithm in evaluations of lung nodules: Comparison with conventional model-based iterative reconstruction and adaptive statistical iterative reconstruction. Eur J Radiol 2016; 85:599-606. [PMID: 26860673 DOI: 10.1016/j.ejrad.2016.01.001] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Revised: 01/04/2016] [Accepted: 01/06/2016] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To compare the image quality of high-resolution computed tomography (HRCT) for evaluating lung nodules reconstructed with the new version of model-based iterative reconstruction and spatial resolution preference algorithm (MBIRn) vs. conventional model-based iterative reconstruction (MBIRc) and adaptive statistical iterative reconstruction (ASIR). MATERIALS AND METHODS This retrospective clinical study was approved by our institutional review board and included 70 lung nodules in 58 patients (mean age, 71.2±10.9years; 34 men and 24 women). HRCT of lung nodules were reconstructed using MBIRn, MBIRc and ASIR. Objective image noise was measured by placing the regions of interest on lung parenchyma. Two blinded radiologists performed subjective image analyses. RESULTS Significant improvements in the following points were observed in MBIRn compared with ASIR (p<0.005): objective image noise (24.4±8.0 vs. 37.7±10.4), subjective image noise, streak artifacts, and adequateness for evaluating internal characteristics and borders of nodules. The sharpness of small vessels and bronchi and diagnostic acceptability with MBIRn were significantly better than with MBIRc and ASIR (p<0.008). CONCLUSION HRCT reconstructed with MBIRn provides diagnostically more acceptable images for the detailed analyses of lung nodules compared with MBIRc and ASIR.
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Affiliation(s)
- Koichiro Yasaka
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan.
| | - Masaki Katsura
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
| | - Shouhei Hanaoka
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
| | - Jiro Sato
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
| | - Kuni Ohtomo
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
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Sawicki LM, Grueneisen J, Buchbender C, Schaarschmidt BM, Gomez B, Ruhlmann V, Wetter A, Umutlu L, Antoch G, Heusch P. Comparative Performance of ¹⁸F-FDG PET/MRI and ¹⁸F-FDG PET/CT in Detection and Characterization of Pulmonary Lesions in 121 Oncologic Patients. J Nucl Med 2016; 57:582-6. [PMID: 26742715 DOI: 10.2967/jnumed.115.167486] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Accepted: 11/16/2015] [Indexed: 11/16/2022] Open
Abstract
UNLABELLED Our objective was to compare (18)F-FDG PET/MRI (performed using a contrast-enhanced T1-weighted fat-suppressed volume-interpolated breath-hold examination [VIBE]) with (18)F-FDG PET/CT for detecting and characterizing lung lesions in oncologic patients. METHODS In 121 oncologic patients with 241 lung lesions, PET/MRI was performed after PET/CT in a single-injection protocol (260 ± 58 MBq of (18)F-FDG). The detection rates were computed for MRI, the PET component of PET/CT, and the PET component of PET/MRI in relation to the CT component of PET/CT. Wilcoxon testing was used to assess differences in lesion contrast (4-point scale) and size between morphologic datasets and differences in image quality (4-point scale), SUVmean, SUVmax, and characterization (benign/malignant) between PET/MRI and PET/CT. Correlation was determined using the Pearson coefficient (r) for SUV and size and the Spearman rank coefficient (ρ) for contrast. RESULTS The detection rates for MRI, the PET component of PET/CT, and the PET component of PET/MRI were 66.8%, 42.7%, and 42.3%, respectively. There was a strong correlation in size (r= 0.98) and SUV (r= 0.91) and a moderate correlation in contrast (ρ = 0.48). Image quality was better for PET/CT than for PET/MRI (P< 0.001). Lesion measurements were smaller for MRI than for CT (P< 0.001). SUVmax and SUVmean were significantly higher for PET/MRI than for PET/CT (P< 0.001 each). There was no significant difference in lesion contrast (P= 0.11) or characterization (P= 0.076). CONCLUSION In the detection and characterization of lung lesions 10 mm or larger, (18)F-FDG PET/MRI and (18)F-FDG PET/CT perform comparably. Lesion size, SUV and characterization correlate strongly between the two modalities. However, the overall detection rate of PET/MRI remains inferior to that of PET/CT because of the limited ability of MRI to detect lesions smaller than 10 mm. Thus, thoracic staging with PET/MRI bears a risk of missing small lung metastases.
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Affiliation(s)
- Lino M Sawicki
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Dusseldorf, Germany Department of Diagnostic and Interventional Radiology and Neuroradiology, University Duisburg-Essen, Essen, Germany; and
| | - Johannes Grueneisen
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Duisburg-Essen, Essen, Germany; and
| | - Christian Buchbender
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Dusseldorf, Germany
| | - Benedikt M Schaarschmidt
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Dusseldorf, Germany
| | - Benedikt Gomez
- Department of Nuclear Medicine, University Duisburg-Essen, Essen, Germany
| | - Verena Ruhlmann
- Department of Nuclear Medicine, University Duisburg-Essen, Essen, Germany
| | - Axel Wetter
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Duisburg-Essen, Essen, Germany; and
| | - Lale Umutlu
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Duisburg-Essen, Essen, Germany; and
| | - Gerald Antoch
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Dusseldorf, Germany
| | - Philipp Heusch
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Dusseldorf, Germany
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Kakinuma R, Moriyama N, Muramatsu Y, Gomi S, Suzuki M, Nagasawa H, Kusumoto M, Aso T, Muramatsu Y, Tsuchida T, Tsuta K, Maeshima AM, Tochigi N, Watanabe SI, Sugihara N, Tsukagoshi S, Saito Y, Kazama M, Ashizawa K, Awai K, Honda O, Ishikawa H, Koizumi N, Komoto D, Moriya H, Oda S, Oshiro Y, Yanagawa M, Tomiyama N, Asamura H. Ultra-High-Resolution Computed Tomography of the Lung: Image Quality of a Prototype Scanner. PLoS One 2015; 10:e0137165. [PMID: 26352144 PMCID: PMC4564227 DOI: 10.1371/journal.pone.0137165] [Citation(s) in RCA: 87] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2014] [Accepted: 08/14/2015] [Indexed: 12/21/2022] Open
Abstract
Purpose The image noise and image quality of a prototype ultra-high-resolution computed tomography (U-HRCT) scanner was evaluated and compared with those of conventional high-resolution CT (C-HRCT) scanners. Materials and Methods This study was approved by the institutional review board. A U-HRCT scanner prototype with 0.25 mm x 4 rows and operating at 120 mAs was used. The C-HRCT images were obtained using a 0.5 mm x 16 or 0.5 mm x 64 detector-row CT scanner operating at 150 mAs. Images from both scanners were reconstructed at 0.1-mm intervals; the slice thickness was 0.25 mm for the U-HRCT scanner and 0.5 mm for the C-HRCT scanners. For both scanners, the display field of view was 80 mm. The image noise of each scanner was evaluated using a phantom. U-HRCT and C-HRCT images of 53 images selected from 37 lung nodules were then observed and graded using a 5-point score by 10 board-certified thoracic radiologists. The images were presented to the observers randomly and in a blinded manner. Results The image noise for U-HRCT (100.87 ± 0.51 Hounsfield units [HU]) was greater than that for C-HRCT (40.41 ± 0.52 HU; P < .0001). The image quality of U-HRCT was graded as superior to that of C-HRCT (P < .0001) for all of the following parameters that were examined: margins of subsolid and solid nodules, edges of solid components and pulmonary vessels in subsolid nodules, air bronchograms, pleural indentations, margins of pulmonary vessels, edges of bronchi, and interlobar fissures. Conclusion Despite a larger image noise, the prototype U-HRCT scanner had a significantly better image quality than the C-HRCT scanners.
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Affiliation(s)
- Ryutaro Kakinuma
- Division of Cancer Screening, National Cancer Center, Research Center for Cancer Prevention and Screening, Chuo-ku, Tokyo, Japan
- Department of Radiology, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan
- * E-mail:
| | - Noriyuki Moriyama
- Division of Cancer Screening, National Cancer Center, Research Center for Cancer Prevention and Screening, Chuo-ku, Tokyo, Japan
| | - Yukio Muramatsu
- Division of Cancer Screening, National Cancer Center, Research Center for Cancer Prevention and Screening, Chuo-ku, Tokyo, Japan
| | - Shiho Gomi
- Department of Radiology, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan
| | - Masahiro Suzuki
- Department of Radiology, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan
| | - Hirobumi Nagasawa
- Department of Radiology, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan
| | - Masahiko Kusumoto
- Department of Radiology, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan
- Department of Radiology, National Cancer Center Hospital East, Kashiwa, Chiba, Japan
| | - Tomohiko Aso
- Department of Radiology, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan
| | - Yoshihisa Muramatsu
- Department of Radiology, National Cancer Center Hospital East, Kashiwa, Chiba, Japan
| | - Takaaki Tsuchida
- Department of Endoscopy, Respiratory Endoscopy Division, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan
| | - Koji Tsuta
- Division of Pathology, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan
| | | | - Naobumi Tochigi
- Division of Pathology, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan
| | - Shun-ichi Watanabe
- Department of Thoracic Surgery, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan
| | - Naoki Sugihara
- Department of CT Systems Division, Toshiba Medical Systems Corporation, Otawara, Tochigi, Japan
| | - Shinsuke Tsukagoshi
- Department of CT Systems Division, Toshiba Medical Systems Corporation, Otawara, Tochigi, Japan
| | - Yasuo Saito
- Department of CT Systems Division, Toshiba Medical Systems Corporation, Otawara, Tochigi, Japan
| | - Masahiro Kazama
- Department of CT Systems Division, Toshiba Medical Systems Corporation, Otawara, Tochigi, Japan
| | - Kazuto Ashizawa
- Department of Clinical Oncology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Nagasaki, Japan
| | - Kazuo Awai
- Department of Diagnostic Radiology, Hiroshima University, Institute and Graduate School of Biomedical Sciences, Hiroshima, Hiroshima, Japan
| | - Osamu Honda
- Department of Radiology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Hiroyuki Ishikawa
- Department of Radiology, Niigata University Medical and Dental Hospital, Niigata, Niigata, Japan
| | - Naoya Koizumi
- Department of Radiology, Niigata Cancer Center Hospital, Niigata, Niigata, Japan
| | - Daisuke Komoto
- Department of Diagnostic Radiology, Hiroshima University, Institute and Graduate School of Biomedical Sciences, Hiroshima, Hiroshima, Japan
| | - Hiroshi Moriya
- Department of Radiology, Ohara General Hospital, Fukushima, Fukushima, Japan
| | - Seitaro Oda
- Department of Diagnostic Radiology, Kumamoto University, Faculty of Life Sciences, Kumamoto, Kumamoto, Japan
| | - Yasuji Oshiro
- Department of Radiology, National Hospital Organization Okinawa National Hospital, Ginowan, Okinawa, Japan
| | - Masahiro Yanagawa
- Department of Radiology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Noriyuki Tomiyama
- Department of Radiology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Hisao Asamura
- Department of Thoracic Surgery, National Cancer Center Hospital, Chuo-ku, Tokyo, Japan
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Harders SW, Madsen HH, Hjorthaug K, Rehling M, Rasmussen TR, Pedersen U, Pilegaard HK, Meldgaard P, Baandrup UT, Rasmussen F. Limited value of ⁹⁹mTc depreotide single photon emission CT compared with CT for the evaluation of pulmonary lesions. Br J Radiol 2012; 85:e307-13. [PMID: 22745210 DOI: 10.1259/bjr/10438644] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVES A contrast-enhanced multidetector CT (MDCT) scan is the first choice examination when evaluating patients with suspected lung cancer. However, while the clinical focus is on CT, research focus is on molecular biological methods whereby radiolabelled pharmaceuticals are injected into participants and target malignant lung tumours. We examined whether a contrast-enhanced MDCT scan supplied with an additional non-contrast enhanced high-resolution CT scan, or a newer but more expensive (99m)Tc depreotide single photon emission CT (SPECT) scan, was the better first-choice examination for the work-up of pulmonary lesions. Furthermore, we examined whether a (99m)Tc depreotide SPECT scan was an appropriate second-choice examination for patients with indeterminate lesions. METHODS 140 participants were included in the analysis. CT images were given a malignancy potential rating of 1, 2 or 3 with higher rating being indicative of disease. (99m)Tc depreotide SPECT images were graded either positive or negative. Histopathology and CT follow-up were used as reference standard. Sensitivity, specificity and diagnostic accuracy were calculated. RESULTS Overall sensitivity, specificity and diagnostic accuracy of CT were 97%, 30% and 84%, respectively. Overall sensitivity, specificity and diagnostic accuracy of (99m)Tc depreotide SPECT were 94%, 58% and 76%, respectively. For indeterminate lesions sensitivity, specificity and diagnostic accuracy of (99m)Tc depreotide SPECT were 71%, 68% and 69%, respectively. CONCLUSION Both CT and (99m)Tc depreotide SPECT made valuable contributions to the evaluation of pulmonary lesions. (99m)Tc depreotide SPECT results were not superior to CT results and did not contribute further to the diagnostic work-up. Regarding indeterminate lesions,( 99m)Tc depreotide SPECT sensitivity was too low.
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Affiliation(s)
- S W Harders
- Department of Radiology, Aarhus University Hospital, Aarhus, Denmark.
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Harders SW, Madsen HH, Rasmussen TR, Hager H, Rasmussen F. High resolution spiral CT for determining the malignant potential of solitary pulmonary nodules: refining and testing the test. Acta Radiol 2011; 52:401-9. [PMID: 21498302 DOI: 10.1258/ar.2011.100377] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
BACKGROUND A solitary pulmonary nodule (SPN) may represent early stage lung cancer. Lung cancer is a devastating disease with an overall 5-year mortality rate of approximately 84% but with early detection and surgery as low as 47%. Currently a contrast-enhanced multiple-row detector CT (MDCT) scan is the first examination when evaluating patients with suspected lung cancer. PURPOSE To apply an additional high resolution CT (HRCT) to SPNs to test whether certain morphological characteristics are associated with malignancy, to assess the diagnostic accuracy of HRCT in the characterization of SPNs, and to address the reproducibility of all measures. MATERIAL AND METHOD Two hundred and thirteen participants with SPNs were included in a follow-up study. Blinded HRCT images were assessed with regard to margin risk categories (MRCs), calcification patterns and certain other characteristics and overall malignancy potential ratings (MPRs) were given. Morphological characteristics were tested against reference standard and ROC methodology was applied to assess diagnostic accuracy. Reproducibility was measured with Kappa statistics and 95% confidence intervals were computed for all results. Histopathology (90%) and CT follow-up (10%) were used as reference standard. RESULTS MRCs (P < 0.001), calcification patterns (P = 0.003), and pleural retraction (P < 0.001) were all statistically significantly associated to malignancy. Reproducibility was moderate to substantial. Sensitivity, specificity, and overall diagnostic accuracy of HRCT were 98%, 23% and 87%, respectively. Reproducibility was substantial. CONCLUSION Statistically significant associations between SPN MRCs, calcification patterns, pleural retraction and malignancy were found. HRCT yielded a very high sensitivity and a somewhat lower specificity for malignancy. Reproducibility was high.
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Affiliation(s)
| | | | | | - Henrik Hager
- Department of Pathology, Aarhus University Hospital, Noerrebrogade 44, DK-8000 Aarhus, Denmark
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Sato S, Koike T, Yamato Y, Yoshiya K, Motono N, Takeshige M, Koizumi N, Homma K, Tsukada H, Yokoyama A. Diagnostic yield of preoperative computed tomography imaging and the importance of a clinical decision for lung cancer surgery. Gen Thorac Cardiovasc Surg 2010; 58:461-6. [PMID: 20859725 DOI: 10.1007/s11748-010-0601-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2009] [Accepted: 02/11/2010] [Indexed: 12/19/2022]
Abstract
PURPOSE This study aimed to evaluate the diagnostic yield of preoperative computed tomography (CT) imaging and the validity of surgical intervention based on the clinical decision to perform surgery for lung cancer or suspected lung cancer. METHODS We retrospectively evaluated 1755 patients who had undergone pulmonary resection for lung cancer or suspected lung cancer. CT scans were performed on all patients. Surgical intervention to diagnose and treat was based on a medical staff conference evaluation for the suspected lung cancer patients who were pathologically undiagnosed. We evaluated the relation between resected specimens and preoperative CT imaging in detail. RESULTS A total of 1289 patients were diagnosed with lung cancer by preoperative pathology examination; another 466 were not pathologically diagnosed preoperatively. Among the 1289 patients preoperatively diagnosed with lung cancer, the diagnoses were confirmed postoperatively in 1282. Among the 466 patients preoperatively undiagnosed, 435 were definitively diagnosed with lung cancer, and there were 383 p-stage I disease patients. There were 38 noncancerous patients who underwent surgery with a diagnosis of confirmed or suspected lung cancer. Among the 1755 patients who underwent surgery, 1717 were pathologically confirmed with lung cancer, and the diagnostic yield of preoperative CT imaging was 97.8%. Among the 466 patients who were preoperatively undiagnosed, 435 were compatible with the predicted findings of lung cancer. CONCLUSION Diagnostic yields of preoperative CT imaging based on clinical evaluation are sufficiently reliable. Diagnostic surgical intervention was acceptable when the clinical probability of malignancy was high and the malignancy was pathologically undiagnosed.
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Affiliation(s)
- Shuichi Sato
- Division of Chest Surgery, Niigata Cancer Center Hospital, 2-15-3 Kawagishi-cho, Niigata, 951-8566, Japan
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Meniga IN, Tiljak MK, Ivankovic D, Aleric I, Zekan M, Hrabac P, Mazuranic I, Puljic I. Prognostic Value of Computed Tomography Morphologic Characteristics in Stage I Non–Small-Cell Lung Cancer. Clin Lung Cancer 2010; 11:98-104. [DOI: 10.3816/clc.2010.n.013] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Influence of pixel size on quantification of airway wall thickness in computed tomography. J Comput Assist Tomogr 2009; 33:725-30. [PMID: 19820501 DOI: 10.1097/rct.0b013e318190699a] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
OBJECTIVES The purpose of this study was to determine the point where a further decrease in voxel size does not result in better automatic quantification of the bronchial wall thickness by using 2 different assessment techniques. MATERIALS AND METHODS The results from the commonly used full-width-at-half-maximum (FWHM) principle and a new technique (integral-based method [IBM]) were compared for thin-section multidetector computed tomography (MDCT) data sets from an airway phantom containing 10 different tubular airway phantoms and in a human subsegmental bronchus in vivo. Correlation with the actual wall thickness and comparison of the wall thicknesses assessed for different voxel sizes were performed, and the image resolutions were also compared subjectively. RESULTS The relative error ranged from 0% (biggest phantom) to 330% (smallest phantom, biggest field of view, smaller matrix, and FWHM). Using IBM, the maximum relative error was 10% in the same setting. For FWHM, the improvement was marginal for most settings with a pixel spacing less than 0.195 x 0.195 x 0.8 mm; however, it still decreases the relative error from 290% to 273.6% for a wall thickness of 0.3 mm and a pixel spacing of 0.076 x 0.076 x 0.8 mm. CONCLUSIONS (1) Using a special technique such as IBM to account for computed tomography's blurring effect in assessing airway wall thickness had the greatest impact on correct quantification. (2) The visual impression and the automatic quantification using the FWHM technique improved marginally by decreasing the voxel size to less than 0.195 x 0.195 x 0.8 mm. (3) The FWHM technique as a model for visual quantification is not reliable for airway wall thicknesses less than 1.5 mm.
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Honda O, Johkoh T, Sekiguchi J, Tomiyama N, Mihara N, Sumikawa H, Inoue A, Yanagawa M, Daimon T, Okumura M, Nakamura H. Doubling time of lung cancer determined using three-dimensional volumetric software: comparison of squamous cell carcinoma and adenocarcinoma. Lung Cancer 2009; 66:211-7. [PMID: 19250697 DOI: 10.1016/j.lungcan.2009.01.018] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2008] [Revised: 12/29/2008] [Accepted: 01/23/2009] [Indexed: 12/21/2022]
Abstract
The aim of the present study was to investigate the difference in doubling time between squamous cell carcinoma (SCC) and adenocarcinoma of solid pulmonary cancer using three-dimensional volumetric software. We included 40 patients with adenocarcinoma and 11 patients with SCC, who underwent CT examinations more than once before surgical treatment. Tumor volumes and doubling times were obtained using three-dimensional volumetric computer software. Statistical analysis was performed using Mann-Whitney's U-test except for negative doubling times (doubling times less than 0 day). Negative doubling time was found in 5 of the 40 adenocarcinomas (13%), but not in any of the patients with SCC. Doubling time was beyond 400 days in 11 of the 40 adenocarcinomas (28%), but was always less than 400 days in SCC. The mean doubling time of SCC was 126+/-58 days (range, 39-221 days; median, 131 days), while that of adenocarcinomas, except for the negative doubling times, was 976+/-3134 days (range, 69-18,678 days; median, 258 days). Doubling time differed significantly between adenocarcinomas and SCC (p<0.01). In conclusion, the median doubling time of SCC lung cancers is less than that of adenocarcinomas, as measured with automated volumetric measurement software.
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Affiliation(s)
- Osamu Honda
- Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan.
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TSUSHIMA K, SONE S, HANAOKA T, KUBO K. Radiological diagnosis of small pulmonary nodules detected on low-dose screening computed tomography. Respirology 2008; 13:817-24. [DOI: 10.1111/j.1440-1843.2008.01379.x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Iwano S, Nakamura T, Kamioka Y, Ikeda M, Ishigaki T. Computer-aided differentiation of malignant from benign solitary pulmonary nodules imaged by high-resolution CT. Comput Med Imaging Graph 2008; 32:416-22. [PMID: 18501556 DOI: 10.1016/j.compmedimag.2008.04.001] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2007] [Revised: 03/21/2008] [Accepted: 04/11/2008] [Indexed: 10/22/2022]
Abstract
We investigated the possibility of using computer analysis of high-resolution CT images to radiologically classify the shape of pulmonary nodules. From a total of 107 HRCT images of solid, solitary pulmonary nodules with prior differentiation as benign (n=55) or malignant (n=52), we extracted the desired pulmonary nodules and calculated two quantitative parameters for characterizing nodules: circularity and second central moment. Using discriminant analysis for two thresholds in differentiating malignant from benign states resulted in a sensitivity of 76.9%, a specificity of 80%, a positive predictive value of 78.4%, and a negative predictive value of 78.6%.
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Affiliation(s)
- Shingo Iwano
- Department of Radiology, Nagoya University, School of Medicine, 65 Tsurumai-cho, Shouwa-ku, Nagoya 466-8550, Japan.
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Xu DM, van Klaveren RJ, de Bock GH, Leusveld ALM, Dorrius MD, Zhao Y, Wang Y, de Koning HJ, Scholten ET, Verschakelen J, Prokop M, Oudkerk M. Role of baseline nodule density and changes in density and nodule features in the discrimination between benign and malignant solid indeterminate pulmonary nodules. Eur J Radiol 2008; 70:492-8. [PMID: 18417311 DOI: 10.1016/j.ejrad.2008.02.022] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2007] [Revised: 01/20/2008] [Accepted: 02/22/2008] [Indexed: 12/21/2022]
Abstract
PURPOSE To retrospectively evaluate whether baseline nodule density or changes in density or nodule features could be used to discriminate between benign and malignant solid indeterminate nodules. MATERIALS AND METHODS Solid indeterminate nodules between 50 and 500 mm(3) (4.6-9.8mm) were assessed at 3 and 12 months after baseline lung cancer screening (NELSON study). Nodules were classified based on morphology (spherical or non-spherical), shape (round, polygonal or irregular) and margin (smooth, lobulated, spiculated or irregular). The mean CT density of the nodule was automatically generated in Hounsfield units (HU) by the Lungcare software. RESULTS From April 2004 to July 2006, 7310 participants underwent baseline screening. In 312 participants 372 solid purely intra-parenchymal nodules were found. Of them, 16 (4%) were malignant. Benign nodules were 82.8mm(3) (5.4mm) and malignant nodules 274.5mm(3) (8.1mm) (p=0.000). Baseline CT density for benign nodules was 42.7 HU and for malignant nodules -2.2 HU (p=ns). The median change in density for benign nodules was -0.1 HU and for malignant nodules 12.8 HU (p<0.05). Compared to benign nodules, malignant nodules were more often non-spherical, irregular, lobulated or spiculated at baseline, 3-month and 1-year follow-up (p<0.0001). In the majority of the benign and malignant nodules there was no change in morphology, shape and margin during 1 year of follow-up (p=ns). CONCLUSION Baseline nodule density and changes in nodule features cannot be used to discriminate between benign and malignant solid indeterminate pulmonary nodules, but an increase in density is suggestive for malignancy and requires a shorter follow-up or a biopsy.
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Affiliation(s)
- Dong Ming Xu
- Department of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University, 600 Yi Shan Road, PO Box 200233, Shanghai, China.
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Pulmonary cavitary nodules on computed tomography: differentiation of malignancy and benignancy. J Comput Assist Tomogr 2008; 31:943-9. [PMID: 18043361 DOI: 10.1097/rct.0b013e3180415e20] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
OBJECTIVE To establish computed tomographic findings that enable accurate differentiation between malignant and benign cavitary lung nodules. METHODS Computed tomographic scans from 39 patients with malignant cavitary nodules and from 39 patients with benign cavitary nodules were independently assessed by 2 observers. They recorded the computed tomographic findings of both types of cavitary nodules and surrounding pulmonary parenchyma. The computed tomographic findings were then compared using chi test. RESULTS The notch was found in 29% of benign cavitary nodule cases and in 54% of malignant cavitary nodule cases (P < 0.01). An irregular internal wall was found in 26% of benign nodules and in 49% of malignant nodule cases (P < 0.01). A linear margin (P < 0.01), satellite nodule presence (P < 0.01), bronchial wall thickening (P < 0.05), consolidation (P < 0.05), and ground-glass attenuation (P < 0.01) were significantly more frequent in benign cavitary nodules than in malignant ones. CONCLUSIONS Although the computed tomographic findings of benign and malignant cavitary nodules overlap, some computed tomographic findings are useful for differentiating cavitary nodules.
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Honda O, Johkoh T, Sumikawa H, Inoue A, Tomiyama N, Mihara N, Fujita Y, Tsubamoto M, Yanagawa M, Daimon T, Natsag J, Nakamura H. Pulmonary Nodules: 3D Volumetric Measurement with Multidetector CT—Effect of Intravenous Contrast Medium. Radiology 2007; 245:881-7. [DOI: 10.1148/radiol.2453062116] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Xu DM, van Klaveren RJ, de Bock GH, Leusveld A, Zhao Y, Wang Y, Vliegenthart R, de Koning HJ, Scholten ET, Verschakelen J, Prokop M, Oudkerk M. Limited value of shape, margin and CT density in the discrimination between benign and malignant screen detected solid pulmonary nodules of the NELSON trial. Eur J Radiol 2007; 68:347-52. [PMID: 17920800 DOI: 10.1016/j.ejrad.2007.08.027] [Citation(s) in RCA: 73] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2007] [Revised: 08/23/2007] [Accepted: 08/23/2007] [Indexed: 12/21/2022]
Abstract
PURPOSE To evaluate prospectively the value of size, shape, margin and density in discriminating between benign and malignant CT screen detected solid non-calcified pulmonary nodules. MATERIAL AND METHODS This study was institutional review board approved. For this study 405 participants of the NELSON lung cancer screening trial with 469 indeterminate or potentially malignant solid pulmonary nodules (>50mm3) were selected. The nodules were classified based on size, shape (round, polygonal, irregular) and margin (smooth, lobulated, spiculated). Mean nodule density and nodule volume were automatically generated by software. Analyses were performed by univariate and multivariate logistic regression. Results were presented as likelihood ratios (LR) with 95% confidence intervals (CI). Receiver operating characteristic analysis was performed for mean density as predictor for lung cancer. RESULTS Of the 469 nodules, 387 (83%) were between 50 and 500mm3, 82 (17%) >500mm3, 59 (13%) malignant, 410 (87%) benign. The median size of the nodules was 103mm3 (range 50-5486mm3). In multivariate analysis lobulated nodules had LR of 11 compared to smooth; spiculated nodules a LR of 7 compared to smooth; irregular nodules a LR of 6 compared to round and polygonal; volume a LR of 3. The mean nodule CT density did not predict the presence of lung cancer (AUC 0.37, 95% CI 0.32-0.43). CONCLUSION In solid non-calcified nodules larger than 50mm3, size and to a lesser extent a lobulated or spiculated margin and irregular shape increased the likelihood that a nodule was malignant. Nodule density had no discriminative power.
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Affiliation(s)
- Dong Ming Xu
- Department of Radiology, University Medical Center Groningen, University of Groningen, The Netherlands.
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Iwano S, Nakamura T, Kamioka Y, Ishigaki T. Computer-aided diagnosis: a shape classification of pulmonary nodules imaged by high-resolution CT. Comput Med Imaging Graph 2005; 29:565-70. [PMID: 16140500 DOI: 10.1016/j.compmedimag.2005.04.009] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2005] [Accepted: 04/25/2005] [Indexed: 11/23/2022]
Abstract
We investigated the possibility of using computer analysis of high-resolution CT images to radiologically classify the shape of pulmonary nodules. Using a combination of circularity and second moment as quantitative measures we were able to classify pulmonary nodules in each shape group as effectively as could a radiologist. We found that pulmonary nodules with circularity < or =0.75 and second moment < or =0.18 were very likely to reveal lung cancer.
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Affiliation(s)
- Shingo Iwano
- Department of Radiology, School of Medicine, Nagoya University, Nagoya, 65 Tsurumai-cho, Shouwa-ku, Nagoya 466-8550, Japan
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Matsuoka S, Kurihara Y, Yagihashi K, Niimi H, Nakajima Y. Peripheral solitary pulmonary nodule: CT findings in patients with pulmonary emphysema. Radiology 2005; 235:266-73. [PMID: 15716392 DOI: 10.1148/radiol.2351040674] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE To analyze retrospectively the computed tomographic (CT) features of peripheral noncalcified solitary pulmonary nodules in patients with and those without emphysema. MATERIALS AND METHODS The authors' institutional review board required neither its approval nor patient informed consent for this retrospective study. The authors retrospectively reviewed 2-mm-thick CT images of 41 nodules (21 malignant, 20 benign) in 41 patients with emphysema (age range, 58-88 years; mean, 71.9 years) and 40 nodules (20 malignant, 20 benign) in 40 patients without emphysema (age range, 50-85 years; mean, 69.2 years). Two radiologists who were unaware of the diagnosis independently evaluated the shape and margin of the nodule, recorded the presence of ground-glass opacities and air bronchograms, and classified nodules into two diagnostic categories: malignant and benign. Final decisions were reached by consensus. For quantitative assessment of the nodules, the fractal dimensions of the nodule interfaces and circularity of the nodule shape were calculated with an image-processing program, and the percentage of the nodule surrounded by emphysema was obtained. Statistical comparisons were made with a chi(2) or Fisher exact test and the Mann-Whitney U test. RESULTS In patients with emphysema, there were no significant differences in fractal dimension, circularity, or frequency of lobulation or spiculation between malignant and benign nodules. Of the 41 nodules in patients with emphysema, 26 (63%) were correctly diagnosed. Thirteen benign nodules (65%) were diagnosed as malignant in patients with emphysema. Of the 40 nodules in nonemphysematous lungs, 37 (93%) were correctly diagnosed. The mean percentage of emphysema around the nodule was greater for misdiagnosed nodules than for correctly diagnosed nodules (P = .003). CONCLUSION Malignant and benign nodules associated with emphysema exhibited considerably more overlap in CT features than did nodules in nonemphysematous lungs.
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Affiliation(s)
- Shin Matsuoka
- Department of Radiology, St Marianna University School of Medicine, 2-16-1 Sugao, Miyamae-Ku, Kawasaki City, Kanagawa 216-8511, Japan.
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Iwano S, Makino N, Ikeda M, Itoh S, Tadokoro M, Satake H, Ishigaki T. Solitary pulmonary nodules. Clin Imaging 2004; 28:322-8. [PMID: 15471662 DOI: 10.1016/s0899-7071(03)00282-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2003] [Revised: 06/10/2003] [Indexed: 10/26/2022]
Abstract
The purpose of this study was to determine an optimal slice thickness that was efficient in differentiating malignant from benign solitary pulmonary nodules (SPNs) on high-resolution computed tomography (HRCT) images. For a total of 92 SPNs, four radiologist indicated their confidence level for the malignant or benign SPN on the CT images presented in 1-, 3-, and 5-mm slice thickness. HRCT could be used to differentiate more accurately the malignant nodules from the benign ones using 1-mm-thick sections than 3- or 5-mm-thick sections.
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Affiliation(s)
- Shingo Iwano
- Department of Radiology, Nagoya University School of Medicine, 65 Tsurumai, Shouwa-ku, Nagoya 466-85500, Japan.
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Shah RM, Edmonds P, Wechsler RJ, Salazar AM. Adjacent Parenchymal Abnormalities in Peripheral Bronchogenic Carcinoma. J Thorac Imaging 2004; 19:87-92. [PMID: 15071325 DOI: 10.1097/00005382-200404000-00005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Our purpose is to correlate thin section CT of peripheral bronchogenic carcinomas with histologically detected lymphatic or vascular invasion. Retrospective 3-year database search revealed 186 surgical resections for primary bronchogenic carcinoma, of which 58 had available preoperative imaging performed at our institution. Cases with prior surgery, nonconfirmatory pathology, remote imaging, or central location were excluded, resulting in a study population of 42 patients, 25 men, 17 women, with a mean age of 69 years. Imaging with 1-3 mm collimation was performed within a mean of 32 days prior to surgery. Histologic diagnoses included adenocarcinoma (n = 24, 57%), squamous cell carcinoma (n = 13, 31%), large cell carcinoma (n = 4, 10%), and small cell carcinoma (n = 1, 2%), with a mean tumor size of 27 mm. Three radiologists blindly and independently recorded bronchovascular thickening, septal and nonseptal opacities, and the extent of each beyond tumor margins: 1) <5 mm, 2) 5-10 mm, and 3) >10 mm. Lymphangio-invasion was correlated with imaging findings, tumor size, and histology. Adjacent parenchymal abnormalities were recorded in 40 (95%) of 42 masses, with isolated nonseptal opacities representing the most frequent abnormality in 21 (50%), followed by bronchovascular thickening in 16 (38%), and septal opacities in 12 (29%). Lymphangio-invasion was present in 16 (38%) of cases. The frequency of lymphangio-invasion was highest (53%) in cases with 2 or more positive findings, and extension beyond 10mm from the tumor margin. This trend did not achieve statistical significance by ROC analysis. Lymphangio-invasion was positively correlated with tumor size, P =.03, but not histology.In conclusion, parenchymal abnormalities beyond tumor margins shown by CT may be due to lymphangio-invasion but imaging findings did not reliably distinguish cases with and without lymphangio-invasion.
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Affiliation(s)
- Rosita M Shah
- Thomas Jefferson University Hospital, Philadelphia, PA 19107, USA
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Marten K, Grabbe E. The challenge of the solitary pulmonary nodule: diagnostic assessment with multislice spiral CT. Clin Imaging 2003; 27:156-61. [PMID: 12727051 DOI: 10.1016/s0899-7071(02)00541-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The advent of fast multiscale computed tomography (MSCT) technology has sparked new interest in the noninvasive assessment of the solitary pulmonary nodule (SPN). Fast scanning within a single breath-hold period, simultaneous acquisition of multiple thin slices with subsequent morphologic characterization of the nodule, determination of perfusion patterns as well as growth rates has led to unprecedented improvements in this emerging field. This article reviews the capabilities of MSCT in the diagnostic assessment of the SPN.
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Affiliation(s)
- Katharina Marten
- Department of Radiology, Georg August University, Robert-Koch-Str. 40, D-37075 Göttingen, Germany
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Munden RF, Erasmus JJ. Thoracic Imaging Techniques for Non-Small Cell and Small Cell Lung Cancer. Lung Cancer 2003. [DOI: 10.1007/0-387-22652-4_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Kim H, Kang SJ, Suh GY, Chung MP, Kwon OJ, Rhee CH, Jung KJ, Kim TS, Lee KS. Predictors for benign solitary pulmonary nodule in tuberculosis-endemic area. Korean J Intern Med 2001; 16:236-41. [PMID: 11855152 PMCID: PMC4578052 DOI: 10.3904/kjim.2001.16.4.236] [Citation(s) in RCA: 22] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Solitary pulmonary nodule (SPN) may show different presentation in tuberculosis (TB)-endemic countries. The aim of this study was to identify clinical and radiological predictors favoring benign or malignant SPN in TB-endemic region. METHODS Two hundred one SPNs in 201 consecutive Korean patients were included (< 3 cm in diameter, all confirmed by pathology or bacteriology, 93 benign and 108 malignant diseases). For clinical parameters, age, sex, smoking status and amount, and past history of pulmonary tuberculosis and diabetes mellitus were investigated retrospectively. For radiological parameters, size, location, margin characteristics, presence of calcification, pleural tag, surrounding satellite nodule, cavitation, internal low attenuation, open bronchus sign, surrounding ground-glass opacity, enhancement pattern of the SPNs and mediastinal lymph node (LN) enlargement were analyzed on chest CT scans. RESULTS Patients with a older age (60.7 +/- 9.6 vs 56.2 +/- 13.1, p = 0.008) and more than 40-pack years smoking (27.8% vs 14.0%, p = 0.017) were more frequently related with malignant than benign SPN. On chest CT scans, spiculated margin, contrast enhancement more than 20 Hounsfield unit and presence of pleural tag and mediastinal LN enlargement were more frequently observed in malignant than benign SPNs. In contrast to previous studies, satellite lesions (21.5% vs 1.9%, p < 0.001) and cavitation (20.4% vs 5.6%, p = 0.001) were more frequently seen in benign than malignant SPN. Positive predictive values of benignity were 90.9% and 76.0%, respectively, when satellite lesions and cavitation were found in cases of SPN. CONCLUSION Satellite lesions and cavitation on chest CT scan could be useful predictors for benign SPN in TB-endemic areas.
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Affiliation(s)
- H Kim
- Division of Pulmonary and Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
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Can HRCT Contribute in Decision-Making on Indication for Flexible Bronchoscopy for Solitary Pulmonary Nodules and Masses? ACTA ACUST UNITED AC 2001. [DOI: 10.1097/00128594-200107000-00002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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Seemann MD, Seemann O, Luboldt W, Bonél H, Sittek H, Dienemann H, Staebler A. Differentiation of malignant from benign solitary pulmonary lesions using chest radiography, spiral CT and HRCT. Lung Cancer 2000; 29:105-24. [PMID: 10963841 DOI: 10.1016/s0169-5002(00)00104-5] [Citation(s) in RCA: 66] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The aim of this prospective study was to summarize all of the qualitative and quantitative imaging criteria for the differentiation of solitary pulmonary lesions (SPLs) as malignant (MSPLs) or benign (BSPLs) described in the literature and to critically analyze the different characteristics in order to evaluate their clinical importance and usefulness as criteria for a discrimination during the primary diagnostic assessment of SPLs using chest radiography, spiral computed tomography (SCT) and high-resolution computed tomography (HRCT). MATERIALS AND METHODS SPLs were examined, evaluated and then completely removed by surgery in 104 consecutive patients (MSPLs n=81, BSPLs n=23). No SPL was excluded by size. Chest radiography was performed with frontal and lateral views, SCT was carried out with a slice thickness of 8 mm and HRCT with a slice thickness of 1 mm and a 12-cm field of view. RESULTS All the characteristics which enabled a reliable differentiation of MSPLs from BSPLs were characteristics which were observed significantly more frequently in MSPLs than BSPLs. Useful characteristics for the differentiation of MSPLs from BSPLs (1) using chest radiography were the indistinct edge (P<0.0001) and a ground-glass opacity of the lung parenchyma adjacent to the SPL (P<0. 05); (2) using SCT the presence of spicules (P<0.0005), the vessel sign (P<0.0005), necrotic areas (P<0.001), spicules extending to the visceral pleura (P<0.005), circumscribed pleural thickening (P<0. 005), inhomogeneity (P<0.01), a ground-glass opacity of the lung parenchyma adjacent to the SPL (P<0.01), the lesion density (P<0.05), pleural retraction (P<0.05) and the bronchus sign (P<0.05); and (3) using HRCT the presence of spicules (P<0.00005), spicules extending to the visceral pleura (P<0.0005), the vessel sign (P<0.0005), pleural retraction (P<0.001), circumscribed pleural thickening (P<0. 001), the bronchus sign (P<0.005), a ground-glass opacity of the lung parenchyma adjacent to the SPL (P<0.01), the lesion density (P<0.05) and the length of spicules (P<0.05). Using any one of the characteristics with a significance level of P<0.01, the identification of MSPLs (1) using chest radiography showed a sensitivity of 64.2% and a specificity of 82.6% (accuracy of 68.3%); (2) using SCT a sensitivity of 88.9% and a specificity of 60.9% (accuracy of 82.7%); and (3) using HRCT a sensitivity of 91.4% and a specificity of 56.5% (accuracy of 83.7%). CONCLUSIONS Using chest radiography, SCT and HRCT, a precise morphological assessment of the periphery of the pulmonary lesion and the adjacent visceral pleura is necessary to distinguish MSPLs from BSPLs. In this respect SCT and HRCT are useful in differentiation of MSPLs from BSPLs. However, metastases strongly resembled benign lesions in terms of size and edge type and chronic inflammatory pseudotumors as a group mimic MSPLs.
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Affiliation(s)
- M D Seemann
- Department of Diagnostic Radiology, Klinikum Grosshadern, Ludwig-Maximilians-University, Munich, Germany.
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