Roden AC, Fang W, Shen Y, et al. Distribution of mediastinal lesions across multi-institutional, international, radiology databases. J Thorac Oncol. 2020;15:568–79.

Article  PubMed  Google Scholar 

Suster S, Moran CA. Histologic classification of thymoma: the World Health Organization and beyond. Hematol Oncol Clin North Am. 2008;22:381–92.

Article  PubMed  Google Scholar 

Marx A, Strobel P, Badve SS, et al. ITMIG consensus statement on the use of the WHO histological classification of thymoma and thymic carcinoma: refined definitions, histological criteria, and reporting. J Thorac Oncol. 2014;9:596–611.

Article  PubMed  CAS  Google Scholar 

Marchevsky AM, Gupta R, McKenna RJ, et al. Evidence-based pathology and the pathologic evaluation of thymomas: the World Health Organization classification can be simplified into only 3 categories other than thymic carcinoma. Cancer. 2008;112:2780–8.

Article  PubMed  Google Scholar 

Weis CA, Yao X, Deng Y, et al. The impact of thymoma histotype on prognosis in a worldwide database. J Thorac Oncol. 2015;10:367–72.

Article  PubMed  PubMed Central  Google Scholar 

Takahashi K, Al-Janabi NJ. Computed tomography and magnetic resonance imaging of mediastinal tumors. J Magn Reson Imaging. 2010;32:1325–39.

Article  PubMed  Google Scholar 

Koyasu S. Imaging of thymic epithelial tumors-a clinical practice review. Mediastinum. 2024;8:41.

Article  PubMed  PubMed Central  Google Scholar 

Ruffini E, Filosso PL, Mossetti C, et al. Thymoma: inter-relationships among World Health Organization histology, Masaoka staging and myasthenia gravis and their independent prognostic significance: a single-centre experience. Eur J Cardiothorac Surg. 2011;40:146–53.

Article  PubMed  Google Scholar 

Lambin P, Rios-Velazquez E, Leijenaar R, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012;48:441–6.

Article  PubMed  PubMed Central  Google Scholar 

Lambin P, Leijenaar R, Deist TM, et al. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol. 2017;14:749–62.

Article  PubMed  Google Scholar 

Gao C, Yang L, Xu Y, et al. Differentiating low-risk thymomas from high-risk thymomas: preoperative radiomics nomogram based on contrast enhanced CT to minimize unnecessary invasive thoracotomy. BMC Med Imaging. 2024;24:197.

Article  PubMed  PubMed Central  Google Scholar 

Liang Z, Li J, Tang Y, et al. Predicting the risk category of thymoma with machine learning-based computed tomography radiomics signatures and their between-imaging phase differences. Sci Rep. 2024;14:19215.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Bi Q, Miao K, Xu N, et al. Habitat radiomics based on MRI for predicting platinum resistance in patients with high-grade serous ovarian carcinoma: a multicenter study. Acad Radiol. 2024;31:2367–80.

Article  PubMed  Google Scholar 

Kong W, Xu J, Huang Y, et al. CT-based habitat radiomics for predicting treatment response to neoadjuvant chemoimmunotherapy in esophageal cancer patients. Front Oncol. 2024;14:1418252.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Wu J, Meng H, Zhou L, et al. Habitat radiomics and deep learning fusion nomogram to predict EGFR mutation status in stage I non-small cell lung cancer: a multicenter study. Sci Rep. 2024;14:15877.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Jiang J, Wang S, Xiao F, et al. Dual-energy CT-based assessment of thrombotic heterogeneity for predicting stroke source and response to machine thrombectomy: a step toward visualization thrombus treatment. Adv Sci (Weinh) 2025:e17295.

Shafiq-Ul-Hassan M, Latifi K, Zhang G, Ullah G, Gillies R, Moros E. Voxel size and gray level normalization of CT radiomic features in lung cancer. Sci Rep. 2018;8:10545.

Article  PubMed  PubMed Central  Google Scholar 

Shintani Y, Funaki S, Ose N, et al. Surgical management of thymic epithelial tumors. Surg Today. 2021;51:331–9.

Article  PubMed  Google Scholar 

Tartarone A, Lerose R, Lettini AR, Tartarone M. Current treatment approaches for thymic epithelial tumors. Life (Basel). 2023. https://doi.org/10.3390/life13051170.

Article  PubMed  Google Scholar 

Yamada Y, Hamaji M, Okada H, et al. Re-evaluation and operative indications after induction therapy for thymic epithelial tumors. Mediastinum. 2024;8:43.

Article  PubMed  PubMed Central  Google Scholar 

Falkson CB, Vella ET, Ellis PM, Maziak DE, Ung YC, Yu E. Surgical, radiation, and systemic treatments of patients with thymic epithelial tumors: a systematic review. J Thorac Oncol. 2023;18:299–312.

Article  PubMed  Google Scholar 

Ozawa Y, Hara M, Shimohira M, Sakurai K, Nakagawa M, Shibamoto Y. Associations between computed tomography features of thymomas and their pathological classification. Acta Radiol. 2016;57:1318–25.

Article  PubMed  Google Scholar 

Liu GB, Qu YJ, Liao MY, Hu HJ, Yang GF, Zhou SJ. Relationship between computed tomography manifestations of thymic epithelial tumors and the WHO pathological classification. Asian Pac J Cancer Prev. 2012;13:5581–5.

Article  PubMed  Google Scholar 

Sadohara J, Fujimoto K, Muller NL, et al. Thymic epithelial tumors: comparison of CT and MR imaging findings of low-risk thymomas, high-risk thymomas, and thymic carcinomas. Eur J Radiol. 2006;60:70–9.

Article  PubMed  Google Scholar 

Moon JW, Lee KS, Shin MH, et al. Thymic epithelial tumors: prognostic determinants among clinical, histopathologic, and computed tomography findings. Ann Thorac Surg. 2015;99:462–70.

Article  PubMed  Google Scholar 

Yang Y, Cheng J, Peng Z, et al. Development and validation of contrast-enhanced CT-based deep transfer learning and combined clinical-radiomics model to discriminate thymomas and thymic cysts: a multicenter study. Acad Radiol. 2024;31:1615–28.

Article  PubMed  Google Scholar 

Huang X, Wang X, Liu Y, Wang Z, Li S, Kuang P. Contrast-enhanced CT-based radiomics differentiate anterior mediastinum lymphoma from thymoma without myasthenia gravis and calcification. Clin Radiol. 2024;79:e500–10.

Article  PubMed  CAS  Google Scholar 

Dong W, Xiong S, Wang X, et al. Development and validation of a contrast-enhanced CT-based radiomics nomogram for differentiating mass-like thymic hyperplasia and low-risk thymoma. J Cancer Res Clin Oncol. 2023;149:14901–10.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Yu C, Li T, Yang X, et al. Contrast-enhanced CT-based radiomics model for differentiating risk subgroups of thymic epithelial tumors. BMC Med Imaging. 2022;22:37.

Article  PubMed  PubMed Central  Google Scholar 

Tabassum M, Suman AA, Suero ME, Pan E, Di Ieva A, Liu S. radiomics and machine learning in brain tumors and their habitat: a systematic review. Cancers (Basel) 2023; 15.

Bernatowicz K, Grussu F, Ligero M, Garcia A, Delgado E, Perez-Lopez R. Robust imaging habitat computation using voxel-wise radiomics features. Sci Rep. 2021;11:20133.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Shang Y, Zeng Y, Luo S, et al. Habitat imaging with tumoral and peritumoral radiomics for prediction of lung adenocarcinoma invasiveness on preoperative chest CT: a multicenter study. AJR Am J Roentgenol. 2024;223: e2431675.

Article  PubMed  Google Scholar 

Slavkova KP, Patel SH, Cacini Z, et al. Mathematical modelling of the dynamics of image-informed tumor habitats in a murine model of glioma. Sci Rep. 2023;13:2916.

Article  PubMed  PubMed Central  CAS  Google Scholar