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Ma YH, Zhang J, Yan WQ, Lan JT, Feng XL, Wang SM, Yang G, Hu YC, Cui GB. Risk factor analysis for major mediastinal vessel invasion in thymic epithelial tumors based on multi-slice CT Imaging. Front Oncol 2023; 13:1239419. [PMID: 37752995 PMCID: PMC10518454 DOI: 10.3389/fonc.2023.1239419] [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: 06/13/2023] [Accepted: 08/25/2023] [Indexed: 09/28/2023] Open
Abstract
Objective To explore the characteristics and risk factors for major mediastinal vessel invasion in different risk grades of thymic epithelial tumors (TETs) based on computed tomography (CT) imaging, and to develop prediction models of major mediastinal artery and vein invasion. Methods One hundred and twenty-two TET patients confirmed by histopathological analysis who underwent thorax CT were enrolled in this study. Clinical and CT data were retrospectively reviewed for these patients. According to the abutment degree between the tumor and major mediastinal vessels, the arterial invasion was divided into grade I, II, and III (< 25%, 25 - 49%, and ≥ 50%, respectively); the venous invasion was divided into grade I and II (< 50% and ≥ 50%). The degree of vessel invasion was compared among different defined subtypes or stages of TETs using the chi-square tests. The risk factors associated with TET vascular invasion were identified using multivariate logistic regression analysis. Results Based on logistic regression analysis, male patients (β = 1.549; odds ratio, 4.824) and the pericardium or pleural invasion (β = 2.209; odds ratio, 9.110) were independent predictors of 25% artery invasion, and the midline location (β = 2.504; odds ratio, 12.234) and mediastinal lymphadenopathy (β = 2.490; odds ratio, 12.06) were independent predictors of 50% artery invasion. As for 50% venous invasion, the risk factors include midline location (β = 2.303; odds ratio, 10.0), maximum tumor diameter larger than 5.9 cm (β = 4.038; odds ratio, 56.736), and pericardial or pleural effusion (β = 1.460; odds ratio, 4.306). The multivariate logistic model obtained relatively high predicting efficacy, and the area under the curve (AUC), sensitivity, and specificity were 0.944, 84.6%, and 91.7% for predicting 50% artery invasion, and 0.913, 81.8%, and 86.0% for 50% venous invasion in TET patients, respectively. Conclusion Several CT features can be used as independent predictors of ≥50% artery or venous invasion. A multivariate logistic regression model based on CT features is helpful in predicting the vascular invasion grades in patients with TET.
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Affiliation(s)
- Yu-Hui Ma
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi’an, Shaanxi, China
- Functional and Molecular Imaging Key Lab of Shaanxi Province, Xi’an, Shaanxi, China
| | - Jie Zhang
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi’an, Shaanxi, China
| | - Wei-Qiang Yan
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi’an, Shaanxi, China
| | - Jiang-Tao Lan
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi’an, Shaanxi, China
| | - Xiu-Long Feng
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi’an, Shaanxi, China
| | - Shu-Mei Wang
- Department of Pathology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi’an, Shaanxi, China
| | - Guang Yang
- Department of Thoracic Surgery, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi’an, Shaanxi, China
| | - Yu-Chuan Hu
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi’an, Shaanxi, China
- Functional and Molecular Imaging Key Lab of Shaanxi Province, Xi’an, Shaanxi, China
| | - Guang-Bin Cui
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi’an, Shaanxi, China
- Functional and Molecular Imaging Key Lab of Shaanxi Province, Xi’an, Shaanxi, China
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Hu YC, Yan WQ, Yan LF, Xiao G, Han Y, Liu CX, Wang SZ, Li GF, Wang SM, Yang G, Duan SJ, Li B, Wang W, Cui GB. Differentiating thymoma, thymic carcinoma and lymphoma based on collagen fibre patterns with T2- and diffusion-weighted magnetic resonance imaging. Eur Radiol 2021; 32:194-204. [PMID: 34215941 DOI: 10.1007/s00330-021-08143-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 01/14/2021] [Accepted: 02/11/2021] [Indexed: 10/21/2022]
Abstract
OBJECTIVES The amount and distribution of intratumoural collagen fibre vary among different thymic tumours, which can be clearly detected with T2- and diffusion-weighted MR images. To explore the incidences of collagen fibre patterns (CFPs) among thymomas, thymic carcinomas and lymphomas on imaging, and to evaluate the efficacy and reproducibility of CFPs in differential diagnosis of thymic tumours. MATERIALS AND METHODS Three hundred and ninety-eight patients with pathologically diagnosed thymoma, thymic carcinoma and lymphoma who underwent T2- and diffusion-weighted MR imaging were retrospectively enrolled. CFPs were classified into four categories: septum sign, patchy pattern, mixed pattern and no septum sign. The incidences of CFPs were compared among different thymic tumours, and the efficacy and reproducibility in differentiating the defined tumour types were analysed. RESULTS There were significant differences in CFPs among thymomas, thymic squamous cell carcinomas (TSCCs), other thymic carcinomas and neuroendocrine tumours (OTC&NTs) and thymic lymphomas. Septum signs were found in 209 (86%) thymomas, which differed between thymomas and any other thymic neoplasms (all p < 0.005). The patchy, mixed patterns and no septum sign were mainly seen in TSCCs (80.3%), OTC&NTs (78.9%) and thymic lymphomas (56.9%), respectively. The consistency of different CFP evaluation between two readers was either good or excellent. CFPs achieved high efficacy in identifying the thymic tumours. CONCLUSION The CFPs based on T2- and diffusion-weighted MR imaging were of great value in the differential diagnosis of thymic tumours. KEY POINTS • Significant differences are found in intratumoural collagen fibre patterns among thymomas, thymic squamous cell carcinomas, other thymic carcinomas and neuroendocrine tumours and thymic lymphomas. • The septum sign, patchy pattern, mixed pattern and no septum sign are mainly seen in thymomas (86%), thymic squamous cell carcinomas (80.3%), other thymic carcinomas and neuroendocrine tumours (79%) and thymic lymphomas (57%), respectively. • The collagen fibre patterns have high efficacy and reproducibility in differentiating thymomas, thymic squamous cell carcinomas and thymic lymphomas.
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Affiliation(s)
- Yu-Chuan Hu
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China.,Functional and Molecular Imaging Key Lab of Shaanxi Province, Xi'an, 710038, Shaanxi, People's Republic of China
| | - Wei-Qiang Yan
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China
| | - Lin-Feng Yan
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China.,Functional and Molecular Imaging Key Lab of Shaanxi Province, Xi'an, 710038, Shaanxi, People's Republic of China
| | - Gang Xiao
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China.,Functional and Molecular Imaging Key Lab of Shaanxi Province, Xi'an, 710038, Shaanxi, People's Republic of China
| | - Yu Han
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China.,Functional and Molecular Imaging Key Lab of Shaanxi Province, Xi'an, 710038, Shaanxi, People's Republic of China
| | - Chen-Xi Liu
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China.,Functional and Molecular Imaging Key Lab of Shaanxi Province, Xi'an, 710038, Shaanxi, People's Republic of China
| | - Sheng-Zhong Wang
- Faculty of Medical Technology, Shaanxi University of Traditional Chinese Medicine, Xianyang, 712046, Shaanxi, People's Republic of China
| | - Gang-Feng Li
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China.,Functional and Molecular Imaging Key Lab of Shaanxi Province, Xi'an, 710038, Shaanxi, People's Republic of China
| | - Shu-Mei Wang
- Department of Pathology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China
| | - Guang Yang
- Department of Thoracic Surgery, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China
| | - Shi-Jun Duan
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China
| | - Bo Li
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China
| | - Wen Wang
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China. .,Functional and Molecular Imaging Key Lab of Shaanxi Province, Xi'an, 710038, Shaanxi, People's Republic of China.
| | - Guang-Bin Cui
- Department of Radiology, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, Shaanxi, People's Republic of China. .,Functional and Molecular Imaging Key Lab of Shaanxi Province, Xi'an, 710038, Shaanxi, People's Republic of China.
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Yu C, Li T, Zhang R, Yang X, Yang Z, Xin L, Zhao Z. Dual-energy CT perfusion imaging for differentiating WHO subtypes of thymic epithelial tumors. Sci Rep 2020; 10:5511. [PMID: 32218504 PMCID: PMC7098982 DOI: 10.1038/s41598-020-62466-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Accepted: 03/13/2020] [Indexed: 11/09/2022] Open
Abstract
To evaluate the role of conventional contrast-enhanced CT (CECT) imaging and dual-energy spectral CT (DECT) perfusion imaging in differentiating the WHO histological subtypes of thymic epithelial tumours (TETs). Eighty-eight patients with TETs who underwent DECT perfusion scans (n = 51) and conventional CT enhancement scans (n = 37) using a GE Discovery CT750 HD scanner were enrolled in this study. The mean maximal contrast-enhanced range (mean CEmax) and the perfusion and spectral parameters of the lesions were analysed. Among the six WHO subtypes (Type A, AB, B1, B2, and B3 thymoma and thymic carcinoma), the mean CEmax values and most of the perfusion and spectral parameter values of Type A and Type AB were significantly higher than those of the other subtypes (all P < 0.05), and there was no difference among Type B1, B2 and B3 (all P > 0.05). The mean CEmax value was not different between Type B (including Type B1, B2, and B3) and thymic carcinoma (P = 1.000). The PS, IC, NIC and λHU values in the optimal venous phase of thymic carcinoma were higher than those of Type B (all P < 0.05). The parameters of conventional CECT imaging and DECT perfusion imaging can help identify the subtype of TETs, especially those of DECT perfusion imaging in type B thymomas and thymic carcinomas.
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Affiliation(s)
- Chunhai Yu
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China
| | - Ting Li
- Department of Nephrology, Taiyuan People's Hospital, Taiyuan, Shanxi, 030001, P.R. China
| | - Ruiping Zhang
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China.
| | - Xiaotang Yang
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China
| | - Zhao Yang
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China
| | - Lei Xin
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China
| | - Zhikai Zhao
- Imaging Department, Shanxi Tumor Hospital, The Affiliated Tumor Hospital of Shanxi Medical University, Taiyuan, Shanxi, 030013, P.R. China
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Yan WQ, Xin YK, Jing Y, Li GF, Wang SM, Rong WC, Xiao G, Lei XB, Li B, Hu YC, Cui GB. Iodine Quantification Using Dual-Energy Computed Tomography for Differentiating Thymic Tumors. J Comput Assist Tomogr 2018; 42:873-880. [PMID: 30339550 PMCID: PMC6250292 DOI: 10.1097/rct.0000000000000800] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 08/17/2018] [Indexed: 12/27/2022]
Abstract
The aim of the study was to explore the efficacy of iodine quantification with dual-energy computed tomography (DECT) in differentiating thymoma, thymic carcinoma, and thymic lymphoma. MATERIALS AND METHODS Fifty-seven patients with pathologically confirmed low-risk thymoma (n = 16), high-risk thymoma (n = 15), thymic carcinoma (n = 14), and thymic lymphoma (n = 12) underwent chest contrast-enhanced DECT scan were enrolled in this study. Tumor DECT parameters including iodine-related Hounsfield unit (IHU), iodine concentration (IC), mixed HU (MHU), and iodine ratio in dual phase, slope of energy spectral HU curve (λ), and virtual noncontrast (VNC) were compared for differences among 4 groups by one-way analysis of variance. Receiver operating characteristic curve was used to determine the efficacy for differentiating the low-risk thymoma from other thymic tumor by defined parameters. RESULTS According to quantitative analysis, dual-phase IHU, IC, and MHU values in patients with low-risk thymoma were significantly increased compared with patients with high-risk thymoma, thymic carcinoma, and thymic lymphoma (P < 0.05/4).The venous phase IHU value yielded the highest performance with area under the curve of 0.893, 75.0% sensitivity, and 89.7% specificity for differentiating the low-risk thymomas from high-risk thymomas or thymic carcinoma at the cutoff value of 34.3 HU. When differentiating low-risk thymomas from thymic lymphoma, the venous phase IC value obtained the highest diagnostic efficacy with the area under the curve of 0.969, and sensitivity, specificity, and cutoff value were 87.5%, 100.0%, and 1.25 mg/mL, respectively. CONCLUSIONS Iodine quantification with DECT may be useful for differentiating the low-risk thymomas from other thymic tumors.
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Affiliation(s)
- Wei-Qiang Yan
- From the Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, and
| | - Yong-Kang Xin
- From the Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, and
| | - Yong Jing
- From the Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, and
| | - Gang-Feng Li
- From the Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, and
| | - Shu-Mei Wang
- Department of Pathology, Tangdu Hospital, the Military Medical University of PLA Airforce (Fourth Military Medical University), Shaanxi, PR China
| | - Wei-Cheng Rong
- From the Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, and
| | - Gang Xiao
- From the Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, and
| | - Xue-Bin Lei
- From the Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, and
| | - Bo Li
- From the Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, and
| | - Yu-Chuan Hu
- From the Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, and
| | - Guang-Bin Cui
- From the Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, and
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