Porter GA, Baxter NN, Pisters PW. Retroperitoneal sarcoma: a population-based analysis of epidemiology, surgery, and radiotherapy. Cancer. 2006;106(7):1610–6. https://doi.org/10.1002/cncr.21761.

Article  PubMed  Google Scholar 

Morosi C, Stacchiotti S, Marchianò A, et al. Correlation between radiological assessment and histopathological diagnosis in retroperitoneal tumors: analysis of 291 consecutive patients at a tertiary reference sarcoma center. Eur J Surg Oncol. 2014;40:1662–70. https://doi.org/10.1016/j.ejso.2014.10.005.

Article  CAS  PubMed  Google Scholar 

Swallow CJ, Strauss DC, Bonvalot S, et al. Management of primary retroperitoneal sarcoma (RPS) in the adult: an updated consensus approach from the Transatlantic Australasian RPS working group. Ann Surg Oncol. 2021;28(12):7873–88. https://doi.org/10.1245/s10434-021-09654-z.

Article  PubMed  PubMed Central  Google Scholar 

Bonvalot S, Gronchi A, Le Péchoux C, et al. Preoperative radiotherapy plus surgery versus surgery alone for patients with primary retroperitoneal sarcoma (EORTC-62092: STRASS): a multicenter, open-label, randomised, phase 3 trial. Lancet Oncol. 2020;21(10):1366–77. https://doi.org/10.1016/S1470-2045(20)30446-0.

Article  PubMed  Google Scholar 

Callegaro D, Raut CP, Ajayi T, et al. Preoperative radiotherapy in patients with primary retroperitoneal sarcoma: EORTC-62092 Trial (STRASS) versus off-trial (STREXIT) results. Ann Surg. 2022 in press. https://doi.org/10.1097/SLA.0000000000005492.

Lambdin J, Ryan C, Gregory S, et al. A randomized phase III study of neoadjuvant chemotherapy followed by surgery versus surgery alone for patients with high-risk retroperitoneal sarcoma (STRASS2). Ann Surg Oncol. 2023;30(8):4573–5. https://doi.org/10.1245/s10434-023-13500-9.

Article  PubMed  PubMed Central  Google Scholar 

Almond LM, Tirotta F, Tattersall H, et al. Diagnostic accuracy of percutaneous biopsy in retroperitoneal sarcoma. Br J Surg. 2019;106(4):395–403. https://doi.org/10.1002/bjs.11064.

Article  CAS  PubMed  Google Scholar 

Tirotta F, Morosi C, Hodson J, et al. Improved biopsy accuracy in retroperitoneal dedifferentiated liposarcoma. Ann Surg Oncol. 2020;27(11):4574–81. https://doi.org/10.1245/s10434-020-08519-1.

Article  PubMed  Google Scholar 

Shur JD, Doran SJ, Kumar S, et al. Radiomics in oncology: a practical guide. Radiographics. 2021;41:1717–32. https://doi.org/10.1148/rg.2021210037.

Article  PubMed  Google Scholar 

Lambin P, Leijenaar RTH, Deist TM, et al. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol. 2017;14:749–62. https://doi.org/10.1038/nrclinonc.2017.141.

Article  PubMed  Google Scholar 

Crombé A, Fadli D, Italiano A, et al. Systematic review of sarcomas radiomics studies: bridging the gap between concepts and clinical applications? Eur J Radiol. 2020;132:109283. https://doi.org/10.1016/j.ejrad.2020.109283.

Article  PubMed  Google Scholar 

Arthur A, Orton MR, Emsley R, et al. A CT-based radiomics classification model for the prediction of histological type and tumour grade in retroperitoneal sarcoma (RADSARC-R): a retrospective multicohort analysis. Lancet Oncol. 2023;24(11):1277–86. https://doi.org/10.1016/S1470-2045(23)00462-X.

Article  PubMed  PubMed Central  Google Scholar 

Pasquali S, Iadecola S, Vanzulli A, et al. Radiomic features of primary retroperitoneal sarcomas: a prognostic study. Eur J Cancer. 2024;213:115120. https://doi.org/10.1016/j.ejca.2024.115120.

Article  CAS  PubMed  Google Scholar 

Coindre JM, Trojani M, Contesso G, et al. Reproducibility of a histopathologic grading system for adult soft tissue sarcoma. Cancer. 1986;58(2):306–9. https://doi.org/10.1002/1097-0142(19860715)58.

Article  CAS  PubMed  Google Scholar 

Vos M, Starmans MPA, Timbergen MJM, et al. Radiomics approach to distinguish between well differentiated liposarcomas and lipomas on MRI. Br J Surg. 2019;106(13):1800–9. https://doi.org/10.1002/bjs.11410.

Article  CAS  PubMed  Google Scholar 

Starmans MPA, Miclea RL, van der Voort SR, et al. Classification of malignant and benign liver tumors using a radiomics approach, Proc. SPIE 10574, Medical Imaging. 2018: Image Processing, 105741D. 2018; https://doi.org/10.1117/12.2293609.

Starmans MPA, van der Voort SR, Phil T, et al. Reproducible radiomics through automated machine learning validated on twelve clinical applications. arXiv. 2021, https://doi.org/10.48550/arXiv.2108.08618:2108.08618.

Starmans MPA, Van der Voort SR, Phil T, et al. Workflow for optimal radiomics classification (WORC). Zenodo, URL: https://github.com/MStarmans91/WORC, https://doi.org/10.5281/zenodo.3840534.

van der Voort SR, Starmans MPA. Predict: a radiomics extensive digital interchangeable classification toolkit (PREDICT). Zenodo. 2018, URL: https://github.com/Svdvoort/PREDICTFastr, https://doi.org/10.5281/zenodo.3854839.

van Griethuysen JJ, Fedorov A, Parmar, et al. Computational radiomics system to decode the radiographic phenotype. Cancer Res. 2017;77(21):e104–7. https://doi.org/10.1158/0008-5472.can-17-0339.

Article  PubMed  PubMed Central  Google Scholar 

Nadeau C, Bengio Y. Inference for the generalization error. Mach Learn. 2018;52:239–81. https://doi.org/10.1023/A:1024068626366.

Article  Google Scholar 

McHugh ML. Interrater reliability: the kappa statistic. Biochem Med (Zagreb). 2012;22(3):276–82.

PubMed  Google Scholar 

Bonvalot S, Roland C, Raut C, Le Péchoux C, Tzanis D, Frezza AM, Gronchi A. Histology-tailored multidisciplinary management of primary retroperitoneal sarcomas. Eur J Surg Oncol. 2022;49:1061. https://doi.org/10.1016/j.ejso.2022.05.010.

Article  PubMed  Google Scholar 

Navarro F, Dapper H, Asadpour R, et al. Development and external validation of deep-learning-based tumor grading models in soft-tissue sarcoma patients using MR imaging. Cancers (Basel). 2021;13:2866. https://doi.org/10.3390/cancers13122866.

Article  PubMed  Google Scholar 

Gitto S, Cuocolo R, Albano D, et al. CT and MRI radiomics of bone and soft-tissue sarcomas: a systematic review of reproducibility and validation strategies. Insights Imaging. 2021;12(1):68. https://doi.org/10.1186/s13244-021-01008-3.

Article  PubMed  PubMed Central  Google Scholar 

Crombé A, Spinnato P, Italiano A, et al. Radiomics and artificial intelligence for soft-tissue sarcomas: current status and perspectives. Diagn Interv Imaging. 2023;104(12):567–83. https://doi.org/10.1016/j.diii.2023.09.005.

Article  PubMed  Google Scholar 

Berger-Richardson D, Burtenshaw SM, Ibrahim AM, et al. Early and late complications of percutaneous core needle biopsy of retroperitoneal tumors at two tertiary sarcoma centers. Ann Surg Oncol. 2019;26(13):4692–8. https://doi.org/10.1245/s10434-019-07656-6.

Article  PubMed  Google Scholar 

Tirotta F, Napolitano A, Noh S, et al. Current management of benign retroperitoneal tumors. Eur J Surg Oncol. 2023;49(6):1081–90. https://doi.org/10.1016/j.ejso.2022.07.006.

Article  PubMed  Google Scholar 

LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436–44. https://doi.org/10.1038/nature14539.

Article  CAS  PubMed  Google Scholar 

Bozzo A, Hollingsworth A, Chatterjee S, et al. A multimodal neural network with gradient blending improves predictions of survival and metastasis in sarcoma. NPJ Precis Oncol. 2024;8:188. https://doi.org/10.1038/s41698-024-00695-7.

Article  PubMed  PubMed Central  Google Scholar