Delta Radiomics Analysis for Local Control Prediction in Pancreatic Cancer Patients Treated Using Magnetic Resonance Guided Radiotherapy

Cusumano, Davide and Boldrini, Luca and Yadav, Poonam and Casà, Calogero and Lee, Sangjune Laurence and Romano, Angela and Piras, Antonio and Chiloiro, Giuditta and Placidi, Lorenzo and Catucci, Francesco and Votta, Claudio and Mattiucci, Gian Carlo and Indovina, Luca and Gambacorta, Maria Antonietta and Bassetti, Michael and Valentini, Vincenzo (2021) Delta Radiomics Analysis for Local Control Prediction in Pancreatic Cancer Patients Treated Using Magnetic Resonance Guided Radiotherapy. Diagnostics, 11 (1). p. 72. ISSN 2075-4418

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Abstract

The aim of this study is to investigate the role of Delta Radiomics analysis in the prediction of one-year local control (1yLC) in patients affected by locally advanced pancreatic cancer (LAPC) and treated using Magnetic Resonance guided Radiotherapy (MRgRT). A total of 35 patients from two institutions were enrolled: A 0.35 Tesla T2*/T1 MR image was acquired for each case during simulation and on each treatment fraction. Physical dose was converted in biologically effective dose (BED) to compensate for different radiotherapy schemes. Delta Radiomics analysis was performed considering the gross tumour volume (GTV) delineated on MR images acquired at BED of 20, 40, and 60 Gy. The performance of the delta features in predicting 1yLC was investigated in terms of Wilcoxon Mann–Whitney test and area under receiver operating characteristic (ROC) curve (AUC). The most significant feature in predicting 1yLC was the variation of cluster shade calculated at BED = 40 Gy, with a p-value of 0.005 and an AUC of 0.78 (0.61–0.94). Delta Radiomics analysis on low-field MR images might play a promising role in 1yLC prediction for LAPC patients: further studies including an external validation dataset and a larger cohort of patients are recommended to confirm the validity of this preliminary experience.

Item Type: Article
Subjects: Institute Archives > Medical Science
Depositing User: Managing Editor
Date Deposited: 29 Nov 2022 04:43
Last Modified: 06 May 2024 05:50
URI: http://eprint.subtopublish.com/id/eprint/518

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