Clinical-MRI-IVIM combined model for differentiating thymic epithelial tumors from anterior mediastinal lymphoma in large masses
- 1Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021 China
Abstract
Objectives: To evaluate the diagnostic value of clinical and intravoxel incoherent motion (IVIM) parameters for differentiating large anterior mediastinal invasive masses (≥ 3 cm), particularly thymic epithelial tumors (TETs) and lymphomas.
Methods: This prospective study included 92 patients (mean age, 44.8 ± 15.5 years) with pathologically confirmed TETs (n = 52) or lymphomas (n = 40) who underwent routine MRI, diffusion-weighted imaging, and IVIM sequences. Quantitative parameters, including the apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f), were measured. Univariate and multivariate logistic regression analyses were used to construct predictive models. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis, with area under the curve (AUC) compared by the DeLong test. Internal validation was performed using bootstrap resampling, and multicollinearity was assessed using variance inflation factors.
Results: Compared with TET, lymphoma was associated with younger age, higher female proportion, higher LDH, larger volume, more frequent pleural and/or lung invasion, and higher D * values (all p < 0.05). Age, sex, LDH level, lung and/or pleural infiltration, and f in the IVIM model were risk predictive factors for distinguishing lymphoma from TET. Among all models, the clinical MRI-IVM model achieved the highest diagnostic performance numerically (AUC = 0.946, 95% CI: 0.901–0.991); However, compared with the clinical MRI model (AUC = 0.929, 95% CI: 0.873–0.985), the increment brought by adding IVIM parameters was not significant (DeLong test, P = 0.316). Calibration analysis showed good consistency between predicted probabilities. The apparent AUC of Bootstrap’s internal validation was 0.946, the estimation deviation was 0.017, and the standard error was 0.022, indicating limited optimism in the model’s performance.
Conclusions: The clinical-MRI-IVIM model had shown relatively good diagnostic performance in preoperative differentiation of large anterior mediastinal TETs and lymphoma. However, there is no statistical difference in the increment benefit generated by IVIM parameters in the composite model. Therefore, in order to elucidate the clinical efficacy of IVIM, further large-scale, prospective, and multi-center studies are necessary.
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BibTeX
@article{chen2026clinicalmriivim,
title = {{Clinical-MRI-IVIM combined model for differentiating thymic epithelial tumors from anterior mediastinal lymphoma in large masses}},
author = {Jiaqi Chen and Wei Tang and Linlin Qi and Fenglan Li and Shulei Cui and Yao Huang and Jianwei Wang},
journal = {Cancer Imaging},
year = {2026},
month = aug,
doi = {10.1186/s40644-026-01104-x},
url = {https://doi.org/10.1186/s40644-026-01104-x},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Clinical-MRI-IVIM combined model for differentiating thymic epithelial tumors from anterior mediastinal lymphoma in large masses
AU - Jiaqi Chen
AU - Wei Tang
AU - Linlin Qi
AU - Fenglan Li
AU - Shulei Cui
AU - Yao Huang
AU - Jianwei Wang
PY - 2026
DA - 2026/08/08
JO - Cancer Imaging
DO - 10.1186/s40644-026-01104-x
UR - https://doi.org/10.1186/s40644-026-01104-x
AB - Objectives: To evaluate the diagnostic value of clinical and intravoxel incoherent motion (IVIM) parameters for differentiating large anterior mediastinal invasive masses (≥ 3 cm), particularly thymic epithelial tumors (TETs) and lymphomas. Methods: This prospective study included 92 patients (mean age, 44.8 ± 15.5 years) with pathologically confirmed TETs (n = 52) or lymphomas (n = 40) who underwent routine MRI, diffusion-weighted imaging, and IVIM sequences. Quantitative parameters, including the apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f), were measured. Univariate and multivariate logistic regression analyses were used to construct predictive models. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis, with area under the curve (AUC) compared by the DeLong test. Internal validation was performed using bootstrap resampling, and multicollinearity was assessed using variance inflation factors. Results: Compared with TET, lymphoma was associated with younger age, higher female proportion, higher LDH, larger volume, more frequent pleural and/or lung invasion, and higher D * values (all p < 0.05). Age, sex, LDH level, lung and/or pleural infiltration, and f in the IVIM model were risk predictive factors for distinguishing lymphoma from TET. Among all models, the clinical MRI-IVM model achieved the highest diagnostic performance numerically (AUC = 0.946, 95% CI: 0.901–0.991); However, compared with the clinical MRI model (AUC = 0.929, 95% CI: 0.873–0.985), the increment brought by adding IVIM parameters was not significant (DeLong test, P = 0.316). Calibration analysis showed good consistency between predicted probabilities. The apparent AUC of Bootstrap’s internal validation was 0.946, the estimation deviation was 0.017, and the standard error was 0.022, indicating limited optimism in the model’s performance. Conclusions: The clinical-MRI-IVIM model had shown relatively good diagnostic performance in preoperative differentiation of large anterior mediastinal TETs and lymphoma. However, there is no statistical difference in the increment benefit generated by IVIM parameters in the composite model. Therefore, in order to elucidate the clinical efficacy of IVIM, further large-scale, prospective, and multi-center studies are necessary.
SN - 1740-5025
SN - 1470-7330
ER -