Abstract
ObjectivesTo develop and validate a MRI-based radiomic method to predict malignancies in lipomatous soft tissue tumors.MethodsThis retrospective study searched in the database of our pathology department, data from patients with lipomatous soft tissue tumors, with histology and gadolinium-contrast enhanced T1w MR images, obtained from 56 centers with non-uniform protocols. For each tumor, 87 radiomic features were extracted by two independent observers to evaluate the inter-observer reproducibility. A reduction of learning base dimension was performed from reproducibility and relevancy criteria. A model was subsequently prototyped using a linear support vector machine to predict malignant lesions.ResultsEighty-one subjects with lipomatous soft tissue tumors including 40 lipomas and 41 atypical lipomatous tumors or well-differentiated liposarcomas with fat-suppressed T1w contrast enhanced MR images available were retrospectively enrolled. Based on a Pearson’s correlation coefficient threshold at 0.8, 55 out of 87 (63.2%) radiomic features were considered reproducible. Further introduction of relevancy finally selected 35 radiomic features to be integrated in the model. To predict malignant tumors, model diagnostic performances were as follow: AUROC = 0.96; sensitivity = 100%; specificity = 90%; positive predictive value = 90.9%; negative predictive value = 100% and overall accuracy = 95.0%.ConclusionThis work demonstrates that radiomics allows to predict malignancy in soft tissue lipomatous tumors with routinely used MR acquisition in clinical oncology. These encouraging results need to be further confirmed in an external validation population.
Highlights
Lipomatous soft tissue tumors are rare tumors arising from benign or malignant mesenchymal tissue proliferation
Benign lipomas are treated with marginal resection or simple medical follow-up, borderline lesions such as well-differentiated liposarcomas and atypical lipomatous tumors (ALT) require a complete resection to prevent local recurrence and potential dedifferentiation [1, 4]
We aim to develop and validate a Magnetic Resonance Imaging (MRI)-based radiomic method to distinguish benign lipomas from malignant ALT or Well-Differentiated Lipomas (WDL)
Summary
Lipomatous soft tissue tumors are rare tumors arising from benign (such as lipomas) or malignant (liposarcomas) mesenchymal tissue proliferation. Benign lipomas are treated with marginal resection or simple medical follow-up, borderline lesions such as well-differentiated liposarcomas and atypical lipomatous tumors (ALT) require a complete resection to prevent local recurrence and potential dedifferentiation [1, 4]. Noninvasive diagnosis to differentiate benign lipomas from malignant lipomatous soft tissue tumors is crucial to guide the therapeutic strategy. Specific imaging methods should be considered prior to conducting invasive procedures potentially risky, and preventing unnecessary patient exposure to expensive procedures. These ethical and clinical challenges related to biopsy-based assays can be addressed using medical imaging, routinely used for cancer diagnosis and staging in clinical oncology. Many biopsies for benign lesions could be avoided and more specific methods are needed to enhance diagnosis
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