Article
Radiology, Nuclear Medicine & Medical Imaging
Eui Jin Hwang, Jin Mo Goo, Hyae Young Kim, Jaeyoun Yi, Yeol Kim
Summary: Elevating the diameter threshold for solid nodules from 6 to 9 mm may lead to a substantial reduction in unnecessary follow-up LDCTs with a small proportion of diagnostic delay of lung cancers.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Sung Hyun Yoon, Yong Ju Kim, Kibbeum Doh, Junghoon Kim, Kyung Hee Lee, Kyung Won Lee, Jihang Kim
Summary: This study assessed interobserver agreement in Lung-RADS categorisation of subsolid nodules in low-dose screening CTs, showing higher concordance among experienced thoracic radiologists. Overall, the interobserver agreement was moderate.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Elisabeth O'Dwyer, Darragh F. Halpenny, Michelle S. Ginsberg
Summary: This study aimed to determine the rate of SPLC in individuals with a history of cancer undergoing LDCT lung cancer screening, finding a higher occurrence rate than previously reported. The results suggest the need for further research to evaluate the potential mortality benefit of screening in this population.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Sohee Park, Hyunho Park, Sang Min Lee, Yura Ahn, Wooil Kim, Kyuhwan Jung, Joon Beom Seo
Summary: The study found that the use of CAD can slightly improve inter-reader agreement in Lung-RADS categorization while reducing measurement variability and substantial management change in cancer-positive cases.
EUROPEAN RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Robert W. Foley, Vanessa Nassour, Helen C. Oliver, Toby Hall, Vidan Masani, Graham Robinson, Jonathan C. L. Rodrigues, Benjamin J. Hudson
Summary: The use of chest radiography as the first-line investigation in primary care patients with suspected lung cancer may have negative consequences, as a normal chest X-ray result may be misleading and resources may be prioritized for advanced disease.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yong Li, Jieke Liu, Xi Yang, Ai Wang, Chi Zang, Lu Wang, Changjiu He, Libo Lin, Haomiao Qing, Jing Ren, Peng Zhou
Summary: This study aims to construct a radiomic model of low-dose CT (LDCT) to predict the differentiation grade of invasive non-mucinous pulmonary adenocarcinoma (IPA) and compare its diagnostic performance with quantitative-semantic model and radiologists. The results showed that the radiomic model demonstrated excellent diagnostic performance in the validation cohort, with comparable accuracy to radiological experts.
EUROPEAN RADIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Zixing Wang, Cuihong Yang, Wei Han, Xin Sui, Fuling Zheng, Fang Xue, Xiaoli Xu, Peng Wu, Yali Chen, Wentao Gu, Wei Song, Jingmei Jiang
Summary: This study validates the clinical value of promising radiomic features in decoding lung cancer heterogeneity. The features were robust and associated with patient long-term prognosis, cancer profiles, and could predict survival and death risk better than routine characteristics.
INSIGHTS INTO IMAGING
(2022)
Article
Multidisciplinary Sciences
Jorge Diaz-Alvarez, Patricia Roiz, Luis Gorospe, Ana Ayala, Sergio Perez-Pinto, Javier Martinez-Sanz, Matilde Sanchez-Conde, Jose L. Casado, Maria J. Perez-Elias, Ana Moreno, Raquel Ron, Maria J. Vivancos, Pilar Vizcarra, Santiago Moreno, Sergio Serrano-Villar
Summary: In this pilot program, the prevalence of lung cancer among people with HIV screened using LDCT was 3.6%, and the number needed to screen to detect one case of lung cancer was 28. While data from additional cohorts with longitudinal measurements are needed, people with HIV are a target population for lung cancer screening with LDCT.
Review
Medicine, General & Internal
Scott J. Adams, Emily Stone, David R. Baldwin, Rozemarijn Vliegenthart, Pyng Lee, Florian J. Fintelmann
Summary: Randomised controlled trials have shown that low-dose CT lung cancer screening reduces mortality compared with chest radiography or no screening. However, uncertainties remain about optimizing clinical and cost effectiveness. This Review provides an international perspective on lung cancer screening, covering clinical trials, identification of individuals who benefit, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, artificial intelligence and biomarkers, and challenges and opportunities in implementation.
Article
Radiology, Nuclear Medicine & Medical Imaging
Madhurima R. Chetan, Fergus V. Gleeson
Summary: The review summarized the current status of radiomics research in predicting treatment response in non-small-cell lung cancer, indicating low quality, lack of reproducibility, and limited clinical evaluation. Efforts towards standardization and collaboration are necessary to identify reproducible radiomic predictors of response. Promising radiomic models need external validation and evaluation within the clinical pathway before being implemented for personalized treatment in NSCLC patients.
EUROPEAN RADIOLOGY
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Taeho Ha, Wooil Kim, Jaehyung Cha, Young Hen Lee, Hyung Suk Seo, So Young Park, Nan Hee Kim, Sung Ho Hwang, Hwan Seok Yong, Yu-Whan Oh, Eun-Young Kang, Cherry Kim
Summary: DECT parameters play an important role in distinguishing between metastatic and benign lung nodules in thyroid cancer. The study found that specific cutoff values for IC, NIC, lambda HU, NICPA, and Z(eff) can aid in diagnosing metastases.
EUROPEAN RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Eui Jin Hwang, Jin Mo Goo, Hyae Young Kim, Soon Ho Yoon, Gong Yong Jin, Jaeyoun Yi, Yeol Kim
Summary: This study evaluated the variability in computer-assisted interpretation of LDCTs among radiologists in a nationwide lung cancer screening program. The results showed significant differences in positive rates and variability between institutional readings and central reviews, indicating that the different usage of computer-assisted systems is a major factor in inter-institution variability.
EUROPEAN RADIOLOGY
(2021)
Article
Medicine, General & Internal
Michael G. Milligan, Inga T. Lennes, Saif Hawari, Melin J. Khandekar, Yolonda Colson, Jo-Anne O. Shepard, Angela Frank, Lecia Sequist, Henning Willers, Florence K. Keane
Summary: This study conducted in a lung nodule and lung cancer screening clinic aimed to evaluate the role of stereotactic body radiation therapy among patients enrolled in a lung cancer screening program. The findings revealed that one in four patients with screen-detected pulmonary nodules requiring intervention were treated with stereotactic body radiation therapy, highlighting the importance of radiation oncologists in the multidisciplinary management of pulmonary nodules.
Article
Radiology, Nuclear Medicine & Medical Imaging
Anastasia K. A. L. Kwee, Bart Luijk, Pim A. de Jong, Harry J. M. Groen, Joachim G. J. V. Aerts, Jean-Paul Charbonnier, Rozemarijn Vliegenthart, Firdaus A. A. Mohamed Hoesein
Summary: Bronchiectasis has a prevalence of 5.4% in lung cancer screening participants and is associated with more respiratory symptoms and, in those with COPD, lower lung function and more emphysema. However, incidental findings of mild bronchiectasis are not very relevant in a lung cancer screening population unless COPD is also present.
EUROPEAN RADIOLOGY
(2023)
Review
Oncology
Jan P. Van Meerbeeck, Emma O'Dowd, Brian Ward, Paul Van Schil, Annemiek Snoeckx
Summary: This paper reviews the current status and challenges of lung cancer screening in Europe, emphasizing the importance of multidisciplinary cooperation. The implementation of Europe's Beating Cancer Plan is expected to promote the general implementation of lung cancer screening. Low-dose CT screening has shown significant reduction in lung cancer-specific mortality in high-risk populations. The implementation of population-based lung cancer screening in Europe is variable and fragmented, mainly due to the cost and capacity of CT scanners and radiologists.
Review
Radiology, Nuclear Medicine & Medical Imaging
Xiuxiu Zhou, Yu Pu, Di Zhang, Yi Xia, Yu Guan, Shiyuan Liu, Li Fan
Summary: This review explores the chest CT findings and dynamic changes of COVID-19, aiming to guide clinical imaging diagnosis. Most lesions in COVID-19 patients were bilateral, multifocal, and distributed subpleurally. Ground-glass opacity or ground-glass opacity with consolidation were common presentations. The dynamic changes of lesions included absorption and improvement, progressive deterioration, fluctuation, or stability.
Article
Computer Science, Hardware & Architecture
Shichao Quan, Hui Chen, Liaoyi Lin, Zeren Shi, Haochao Ying, Changzheng Yuan, Ping Wang, Shiyuan Liu, Li Fan
Summary: In this study, an automatic radiomics method based on whole-lung segmentation was proposed for discriminating pneumonia and assisting in clinical diagnosis. The results showed that the model was effective in distinguishing influenza pneumonia, COVID-19, and health, and could assist in the diagnosis of influenza pneumonia and COVID-19.
Article
Radiology, Nuclear Medicine & Medical Imaging
Xueqing Peng, Shuyi Yang, Lingxiao Zhou, Yu Mei, Lili Shi, Rengyin Zhang, Fei Shan, Lei Liu
Summary: This study explores the impact of repeatability and reproducibility of radiomic features on their generalizability in clinical applications, and identifies a subset of stable and informative features for further research. Through systematic experiments and analysis, factors with the greatest and least influence on the features were identified, and 19 nonredundant stable features were selected for clinical validation.
INVESTIGATIVE RADIOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Fangyun Li, Lingxiao Zhou, Yunpeng Wang, Chuan Chen, Shuyi Yang, Fei Shan, Lei Liu
Summary: In this paper, a CXR detection method that integrates CNN with a ViT for modeling patch-wise and inter-patch dependencies is proposed. Experimental results show that the method achieves the best performance in disease classification and lesion localization, and demonstrates good generalization ability on an external validation dataset.
QUANTITATIVE IMAGING IN MEDICINE AND SURGERY
(2022)
Article
Multidisciplinary Sciences
Xiaoyang Han, Ziqi Yu, Yaoyao Zhuo, Botao Zhao, Yan Ren, Lorenz Lamm, Xiangyang Xue, Jianfeng Feng, Carsten Marr, Fei Shan, Tingying Peng, Xiao-Yong Zhang
Summary: This study developed an AI system to predict the progression of COVID-19 by combining CT scans and clinical data. CT examinations have significant value in predicting disease progression in the early stage of COVID-19.
Article
Oncology
Xiang Wang, Man Gao, Jicai Xie, Yanfang Deng, Wenting Tu, Hua Yang, Shuang Liang, Panlong Xu, Mingzi Zhang, Yang Lu, ChiCheng Fu, Qiong Li, Li Fan, Shiyuan Liu
Summary: The study found that image-based deep learning models and fusion models can effectively assist radiologists in distinguishing between benign and malignant nodules for precise management of patients with GGNs. Clinical feature-based machine learning models performed well in some cases but showed poor diagnostic performance in other situations.
FRONTIERS IN ONCOLOGY
(2022)
Review
Radiology, Nuclear Medicine & Medical Imaging
Li Fan, Wenjie Yang, Wenting Tu, Xiuxiu Zhou, Qin Zou, Hanxiao Zhang, Yan Feng, Shiyuan Liu
Summary: This article reviews the development of thoracic imaging in China from the past to the present and explores future trends, aiming to establish new strategies for further advancement.
JOURNAL OF THORACIC IMAGING
(2022)
Article
Respiratory System
Yu Pu, Xiuxiu Zhou, Di Zhang, Yu Guan, Yi Xia, Wenting Tu, Yang Lu, Weidong Zhang, Chi-Cheng Fu, Qu Fang, Geertruida H. de Bock, Shiyuan Liu, Li Fan
Summary: This study used machine learning classification model PRM to explore the optimal threshold of FEV1% predicted value for high-risk COPD. The results showed that PRM parameters were more consistent with PFT and could better distinguish high-risk COPD from normal patients.
INTERNATIONAL JOURNAL OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE
(2022)
Article
Computer Science, Interdisciplinary Applications
Yanbei Liu, Henan Li, Tao Luo, Changqing Zhang, Zhitao Xiao, Ying Wei, Yaozong Gao, Feng Shi, Fei Shan, Dinggang Shen
Summary: In this study, a novel framework called Structural Attention Graph Neural Network (SAGNN) is proposed for COVID-19 diagnosis, which combines multi-source information to diagnose the severity and predict the conversion time from mild to severe. Experiment results show that SAGNN outperforms other comparison methods in terms of classification and regression tasks.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yun Wang, Deng Lyu, Taohu Zhou, Wenting Tu, Li Fan, Shiyuan Liu
Summary: The study aimed to develop and validate a multivariate logistic regression model that incorporates the maximum standardized uptake value (SUVmax) and valuable computed tomography (CT) signs for the non-invasive prediction of visceral pleural invasion (VPI) status in subpleural clinical stage IA lung adenocarcinoma patients before surgery. The results showed that the model had good predictive performance in both the training set and validation set.
DIAGNOSTIC AND INTERVENTIONAL RADIOLOGY
(2023)
Article
Respiratory System
Wenting Tu, Taohu Zhou, Xiuxiu Zhou, Yanqing Ma, Shaofeng Duan, Yun Wang, Xiang Wang, Tian Liu, HanXiao Zhang, Yan Feng, Wenjun Huang, Xinang Jiang, Yi Xiao, Shiyuan Liu, Li Fan
Summary: This study aimed to identify and validate diagnostic nomograms for predicting whether lung cancer is comorbid with COPD based on CT morphological features and clinical characteristics. Using data from 498 patients with lung cancer, including 280 with COPD, logistic regression models were developed and compared to evaluate the performance of different nomograms. The combined nomogram generated with clinical and imaging features showed the best performance.
INTERNATIONAL JOURNAL OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE
(2023)
Review
Oncology
Yun Wang, Deng Lyu, Li Fan, Shiyuan Liu
Summary: In 2015, the World Health Organization officially defined spread through air spaces (STAS) as the fourth type of lung adenocarcinoma invasion. Predicting STAS for lung cancer patients is clinically significant. CT, 18F-FDG PET/CT, radiomics, and DL have been found to be valuable in predicting STAS.
TRANSLATIONAL CANCER RESEARCH
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yaoyao Zhuo, Yi Zhan, Ye Tian, Mingfeng Yu, Shuyi Yang, Peiyan Ye, Li Fan, Zhiyong Zhang, Fei Shan
Summary: The study aimed to evaluate the efficacy of ComBat harmonization in reducing variability of voxel size-related CT radiomics. Results showed that ComBat correction was more effective than image resampling correction, leading to significant improvements in the stability of CT radiomics features. Additionally, the study found that first-order and shape features were more robust than texture features.
QUANTITATIVE IMAGING IN MEDICINE AND SURGERY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Qiong Ma, Yinqiao Yi, Tiejun Liu, Xinnian Wen, Fei Shan, Feng Feng, Qinqin Yan, Jie Shen, Guang Yang, Yuxin Shi
Summary: This study developed and evaluated a radiomics signature based on MRI to identify invisible changes of basal cisterns in tuberculous meningitis patients. The signature combined T2-weighted images and deep learning segmentation, providing a fully automatic and non-invasive tool for the diagnosis of TBM.
EUROPEAN RADIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Shuai Yang, Yun Ling, Fang Zhao, Wei Li, Zhigang Song, Lu Wang, Qiuting Li, Mengxing Liu, Ying Tong, Lu Chen, Daoping Ru, Tongsheng Zhang, Kaicheng Zhou, Baolong Zhang, Peng Xu, Zhicong Yang, Wenxuan Li, Yuanlin Song, Jianqing Xu, Tongyu Zhu, Fei Shan, Wenqiang Yu, Hongzhou Lu
Summary: The study reveals the correlation between hyaluronic acid (HA) and COVID-19, and suggests that hymecromone, an inhibitor of HA synthesis, shows promise as a therapeutic drug for COVID-19. Hymecromone reduces HA levels, decreases pulmonary lesions, and promotes lymphocyte recovery.
SIGNAL TRANSDUCTION AND TARGETED THERAPY
(2022)
