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Jiang J, Xiao Y, Liu J, Cui L, Shao W, Hao S, Xu G, Fu Y, Hu C. T1 mapping-based radiomics in the identification of histological types of lung cancer: a reproducibility and feasibility study. BMC Med Imaging 2024; 24:308. [PMID: 39543517 PMCID: PMC11566602 DOI: 10.1186/s12880-024-01487-y] [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: 07/30/2024] [Accepted: 11/03/2024] [Indexed: 11/17/2024] Open
Abstract
BACKGROUND T1 mapping can quantify the longitudinal relaxation time of tissues. This study aimed to investigate the repeatability and reproducibility of T1 mapping radiomics features of lung cancer and the feasibility of T1 mapping-based radiomics model to predict its pathological types. METHODS The chest T1 mapping images and clinical characteristics of 112 lung cancer patients (54 with adenocarcinoma and 58 with other types of lung cancer) were collected retrospectively. 54 patients underwent twice short-term T1 mapping scans. Regions of interest were manually delineated on T1 mapping pseudo-color images to measure the mean native T1 values of lung cancer, and radiomics features were extracted using the semi-automatic segmentation method by two independent observers. The patients were randomly divided into training group (77 cases) and validation group (35 cases) with the ratio of 7:3. Interclass correlation coefficients (ICCs), Student's t-test or Mann-Whitney U tests and least absolute shrinkage and selection operator (LASSO) were used for feature selection. The optimum features were selected to establish a logistic regression (LR) radiomics model. Independent sample t-test, Mann Whitney U-test or chi square test were used to compare the differences of clinical characteristics and T1 values. Performance was compared by the area under the receiver operating characteristic (ROC) curve (AUC). RESULTS In the training group, smoking history, lesion type and native T1 values were different between adenocarcinoma and non-adenocarcinoma patients (P = 0.004-0.038). There were 1035 (54.30%) radiomics features meet the intra-and inter-observer, and test-retest reproducibility with ICC > 0.80. After feature dimensionality reduction and model construction, the AUC of T1 mapping-based radiomics model for predicting the pathological types of lung cancer was 0.833 and 0.843, respectively, in the training and validation cohorts. The AUCs of T1 value and clinical model (including smoking history and lesion type) were 0.657 and 0.692 in the training group, and 0.722 and 0.686 in the validation group. Combined with T1 mapping radiomics, clinical model and T1 value to establish a combined model, the prediction efficiency was further improved to 0.895 and 0.915 in the training and validation groups. CONCLUSIONS About 50% of the T1 mapping-based radiomics features displayed relatively poor repeatability and reproducibility. While T1 mapping-based radiomics model is valuable in identification of histological types of lung cancer despite the measurement variability. Combination of T1 mapping radiomics model, clinical characteristics and native T1 value can improve the predictive value of pathological types of lung cancer.
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Affiliation(s)
- Jianqin Jiang
- Department of Radiology, The Yancheng Clinical College of Xuzhou Medical University and The First people's Hospital of Yancheng, Yulong West Road No. 166, Yancheng, 224001, China
- Department of Radiology, The First Affiliated Hospital of Soochow University, Shizi Street No. 188, Suzhou, 215002, China
| | - Yong Xiao
- Department of Radiology, The Yancheng Clinical College of Xuzhou Medical University and The First people's Hospital of Yancheng, Yulong West Road No. 166, Yancheng, 224001, China
| | - Jia Liu
- Department of Radiology, The Second Affiliated Hospital of Nantong University, Haierxiang North Road No. 6, Nantong, 226001, China
| | - Lei Cui
- Department of Radiology, The Second Affiliated Hospital of Nantong University, Haierxiang North Road No. 6, Nantong, 226001, China
| | - Weiwei Shao
- Department of Pathology, The Yancheng Clinical College of Xuzhou Medical University and The First people's Hospital of Yancheng, Yulong West Road No. 166, Yancheng, 224001, China
| | - Shaowei Hao
- Siemens Healthineers Digital Technology (Shanghai) Co., Ltd, Haiyang West Road No. 399, Shanghai, 200000, China
| | - Gaofeng Xu
- Department of Radiology, The Yancheng Clinical College of Xuzhou Medical University and The First people's Hospital of Yancheng, Yulong West Road No. 166, Yancheng, 224001, China
| | - Yigang Fu
- Department of Radiology, The Yancheng Clinical College of Xuzhou Medical University and The First people's Hospital of Yancheng, Yulong West Road No. 166, Yancheng, 224001, China.
| | - Chunhong Hu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Shizi Street No. 188, Suzhou, 215002, China.
- Institute of Medical Imaging, Soochow University, Shizi Street No. 1, Suzhou, 215002, China.
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Han H, Guo W, Ren H, Hao H, Lin X, Tian M, Xin J, Zhao P. Predictors of lung cancer subtypes and lymph node status in non-small-cell lung cancer: intravoxel incoherent motion parameters and extracellular volume fraction. Insights Imaging 2024; 15:168. [PMID: 38971908 PMCID: PMC11227484 DOI: 10.1186/s13244-024-01758-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Accepted: 06/22/2024] [Indexed: 07/08/2024] Open
Abstract
OBJECTIVE To determine the performance of intravoxel incoherent motion (IVIM) parameters and the extracellular volume fraction (ECV) in distinguishing between different subtypes of lung cancer and predicting lymph node metastasis (LNM) status in patients with non-small-cell lung cancer (NSCLC). METHODS One hundred sixteen patients with lung cancer were prospectively recruited. IVIM, native, and postcontrast T1 mapping examinations were performed, and the T1 values were measured to calculate the ECV. The differences in IVIM parameters and ECV were compared between NSCLC and small-cell lung cancer (SCLC), adenocarcinoma (Adeno-Ca) and squamous cell carcinoma (SCC), and NSCLC without and with LNM. The assessment of each parameter's diagnostic performance was based on the area under the receiver operating characteristic curve (AUC). RESULTS The apparent diffusion coefficient (ADC), true diffusion coefficient (D), and ECV values in SCLC were considerably lower compared with NSCLC (all p < 0.001, AUC > 0.887). The D value in SCC was substantially lower compared with Adeno-Ca (p < 0.001, AUC = 0.735). The perfusion fraction (f) and ECV values in LNM patients were markedly higher compared with those without LNM patients (p < 0.01, < 0.001, AUC > 0.708). CONCLUSION IVIM parameters and ECV can serve as non-invasive biomarkers for assisting in the pathological classification and LNM status assessment of lung cancer patients. CRITICAL RELEVANCE STATEMENT IVIM parameters and ECV demonstrated remarkable potential in distinguishing pulmonary carcinoma subtypes and predicting LNM status in NSCLC. KEY POINTS Lung cancer is prevalent and differentiating subtype and invasiveness determine the treatment course. True diffusion coefficient and ECV showed promise for subtyping and determining lymph node status. These parameters could serve as non-invasive biomarkers to help determine personalized treatment strategies.
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Affiliation(s)
- Huizhi Han
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Wenxiu Guo
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Hong Ren
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Huiting Hao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Xiangtao Lin
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Mimi Tian
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Jiaxiang Xin
- MR Research Collaboration, Siemens Healthineers Ltd, Shanghai, China
| | - Peng Zhao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
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Qu J, Pan B, Su T, Chen Y, Zhang T, Chen X, Zhu X, Xu Z, Wang T, Zhu J, Zhang Z, Feng F, Jin Z. T1 and T2 mapping for identifying malignant lymph nodes in head and neck squamous cell carcinoma. Cancer Imaging 2023; 23:125. [PMID: 38105217 PMCID: PMC10726506 DOI: 10.1186/s40644-023-00648-6] [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: 09/05/2023] [Accepted: 12/04/2023] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND This study seeks to assess the utility of T1 and T2 mapping in distinguishing metastatic lymph nodes from reactive lymphadenopathy in patients with head and neck squamous cell carcinoma (HNSCC), using diffusion-weighted imaging (DWI) as a comparison. METHODS Between July 2017 and November 2019, 46 HNSCC patients underwent neck MRI inclusive of T1 and T2 mapping and DWI. Quantitative measurements derived from preoperative T1 and T2 mapping and DWI of metastatic and non-metastatic lymph nodes were compared using independent samples t-test or Mann-Whitney U test. Receiver operating characteristic curves and the DeLong test were employed to determine the most effective diagnostic methodology. RESULTS We examined a total of 122 lymph nodes, 45 (36.9%) of which were metastatic proven by pathology. Mean T2 values for metastatic lymph nodes were significantly lower than those for benign lymph nodes (p < 0.001). Conversely, metastatic lymph nodes exhibited significantly higher apparent diffusion coefficient (ADC) and standard deviation of T1 values (T1SD) (p < 0.001). T2 generated a significantly higher area under the curve (AUC) of 0.890 (0.826-0.954) compared to T1SD (0.711 [0.613-0.809]) and ADC (0.660 [0.562-0.758]) (p = 0.007 and p < 0.001). Combining T2, T1SD, ADC, and lymph node size achieved an AUC of 0.929 (0.875-0.983), which did not significantly enhance diagnostic performance over using T2 alone (p = 0.089). CONCLUSIONS The application of T1 and T2 mapping is feasible in differentiating metastatic from non-metastatic lymph nodes in HNSCC and can improve diagnostic efficacy compared to DWI.
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Affiliation(s)
- Jiangming Qu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Boju Pan
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Tong Su
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Yu Chen
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
| | - Tao Zhang
- Department of Stomatology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Xingming Chen
- Department of Otolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Xiaoli Zhu
- Department of Otolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Zhentan Xu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Tianjiao Wang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Jinxia Zhu
- MR Research Collaboration, Siemens Healthineers Ltd, Beijing, China
| | - Zhuhua Zhang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
| | - Feng Feng
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical Union Medical College, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
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Bortolotto C, Messana G, Lo Tito A, Stella GM, Pinto A, Podrecca C, Bellazzi R, Gerbasi A, Agustoni F, Han F, Nickel MD, Zacà D, Filippi AR, Bottinelli OM, Preda L. The Role of Native T1 and T2 Mapping Times in Identifying PD-L1 Expression and the Histological Subtype of NSCLCs. Cancers (Basel) 2023; 15:3252. [PMID: 37370861 DOI: 10.3390/cancers15123252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 06/08/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023] Open
Abstract
We investigated the association of T1/T2 mapping values with programmed death-ligand 1 protein (PD-L1) expression in lung cancer and their potential in distinguishing between different histological subtypes of non-small cell lung cancers (NSCLCs). Thirty-five patients diagnosed with stage III NSCLC from April 2021 to December 2022 were included. Conventional MRI sequences were acquired with a 1.5 T system. Mean T1 and T2 mapping values were computed for six manually traced ROIs on different areas of the tumor. Data were analyzed through RStudio. Correlation between T1/T2 mapping values and PD-L1 expression was studied with a Wilcoxon-Mann-Whitney test. A Kruskal-Wallis test with a post-hoc Dunn test was used to study the correlation between T1/T2 mapping values and the histological subtypes: squamocellular carcinoma (SCC), adenocarcinoma (ADK), and poorly differentiated NSCLC (PD). There was no statistically significant correlation between T1/T2 mapping values and PD-L1 expression in NSCLC. We found statistically significant differences in T1 mapping values between ADK and SCC for the periphery ROI (p-value 0.004), the core ROI (p-value 0.01), and the whole tumor ROI (p-value 0.02). No differences were found concerning the PD NSCLCs.
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Affiliation(s)
- Chandra Bortolotto
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
- Radiology Institute, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Gaia Messana
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Antonio Lo Tito
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Giulia Maria Stella
- Unit of Respiratory Diseases, Department of Medical Sciences and Infective Diseases, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
- Department of Internal Medicine and Medical Therapeutics, University of Pavia, 27100 Pavia, Italy
| | - Alessandra Pinto
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Chiara Podrecca
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Alessia Gerbasi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Francesco Agustoni
- Department of Medical Oncology, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Fei Han
- MR Application Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | - Marcel Dominik Nickel
- MR Application Predevelopment, Siemens Healthcare GmbH, Allee am Roethelheimpark 2, 91052 Erlangen, Germany
| | | | - Andrea Riccardo Filippi
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
- Department of Radiation Oncology, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Olivia Maria Bottinelli
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Lorenzo Preda
- Diagnostic Imaging and Radiotherapy Unit, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
- Radiology Institute, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
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Tissue Characteristics of Endometrial Carcinoma Analyzed by Quantitative Synthetic MRI and Diffusion-Weighted Imaging. Diagnostics (Basel) 2022; 12:diagnostics12122956. [PMID: 36552962 PMCID: PMC9776551 DOI: 10.3390/diagnostics12122956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 11/08/2022] [Accepted: 11/24/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND This study investigates the association of T1, T2, proton density (PD) and the apparent diffusion coefficient (ADC) with histopathologic features of endometrial carcinoma (EC). METHODS One hundred and nine EC patients were prospectively enrolled from August 2019 to December 2020. Synthetic magnetic resonance imaging (MRI) was acquired through one acquisition, in addition to diffusion-weighted imaging (DWI) and other conventional sequences using 1.5T MRI. T1, T2, PD derived from synthetic MRI and ADC derived from DWI were compared among different histopathologic features, namely the depth of myometrial invasion (MI), tumor grade, cervical stromal invasion (CSI) and lymphovascular invasion (LVSI) of EC by the Mann-Whitney U test. Classification models based on the significant MRI metrics were constructed with their respective receiver operating characteristic (ROC) curves, and their micro-averaged ROC was used to evaluate the overall performance of these significant MRI metrics in determining aggressive histopathologic features of EC. RESULTS EC with MI had significantly lower T2, PD and ADC than those without MI (p = 0.007, 0.006 and 0.043, respectively). Grade 2-3 EC and EC with LVSI had significantly lower ADC than grade 1 EC and EC without LVSI, respectively (p = 0.005, p = 0.020). There were no differences in the MRI metrics in EC with or without CSI. Micro-averaged ROC of the three models had an area under the curve of 0.83. CONCLUSIONS Synthetic MRI provided quantitative metrics to characterize EC with one single acquisition. Low T2, PD and ADC were associated with aggressive histopathologic features of EC, offering excellent performance in determining aggressive histopathologic features of EC.
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