Building a pre-surgical multiparametric-MRI-based morphologic, qualitative, semiquantitative, first and high-order radiomic predictive treatment response model for undifferentiated pleomorphic sarcoma to replace RECIST

构建基于术前多参数磁共振成像的形态学、定性、半定量、一级和高级放射组学预测未分化多形性肉瘤治疗反应的模型,以替代RECIST标准。

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Abstract

BACKGROUND: Undifferentiated pleomorphic sarcoma (UPS) is the largest subgroup of soft-tissue sarcomas. It demonstrates post-therapeutic hemosiderin deposition, granulation tissue formation, fibrosis, and calcification. Our research aims to establish the multiparametric MRI (mp-MRI) value for predicting UPS treatment response. METHODS: An IRB-approved retrospective study included 33 extremity UPS patients with pre-operative mp-MRI, including diffusion-weighted imaging (DWI), contrast-enhanced susceptibility-weighted imaging (CE-SWI), and perfusion-weighted imaging with dynamic contrast-enhancement (PWI/DCE), and surgical resection between February 2021 and May 2023. Lesions were visually classified on CE-SWI into one of 6 morphology patterns. On PWI/DCE, lesions were classified into one of 6 patterns, and time-intensity curves (TICs) were classified as types I-V. Patients were categorized into three groups based on the percentage of pathology-assessed treatment effect (PATE) in the surgical specimen: Responders (> = 90% PATE, n = 16), partial-responders (31-89% PATE, n = 10), and non-responders (< = 30% PATE, n = 7). RESULTS: At post-radiation therapy (PRT), a CE-SWI Complete-Ring pattern was observed in 71% of responders (p = 7.71 × 10(-6)). On PWI/DCE images, 79% of responders displayed a Capsular pattern (p = 1.49 × 10(-7)), and 100% demonstrated a TIC-type II (p = 8.32 × 10(-7)). ROC analysis comparing responders (n = 14) vs. partial/non-responders (n = 16) at PRT showed that the model combining PWI/DCE TIC-type II, PWI/DCE Capsular pattern, and CE-SWI Complete-Ring pattern yielded the highest classification performance (AUC = 0.99), outperforming PWI/DCE Capsular + TIC-type II (AUC = 0.97), PWI/DCE Capsular (AUC = 0.89), PWI/DCE TIC-type II (AUC = 0.88), and CE-SWI Complete Ring (AUC = 0.79). Contrary to prior reports, DWI/ADC played a secondary role in predicting response: ADC mean & skewness (AUC = 0.63). RECIST demonstrated 100% stability at PRT and 100% pseudo-progression at PC in responders and partial/non-responders (AUC = 0.47). CONCLUSION: Mp-MRI-derived features are valuable in assessing UPS treatment response. A pre-operative model that combines PWI/DCE TIC-type II, PWI/DCE Capsular pattern, and CE-SWI Complete Ring pattern can reliably predict successfully treated UPS with > = 90% PATE, outperforming RECIST, which was proven unreliable in separating responders from partial/non-responders. Institutions that have not yet implemented CE-SWI can rely on a single-sequence approach based on PWI/DCE, combining the presence of TIC II and Capsular enhancement as criteria for response prediction.

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