A Predictive Model of 2yDFS During MR-Guided RT Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients.

Abstract

Purpose:

Distant metastasis is the main cause of treatment failure in locally advanced rectal cancer (LARC) patients, despite the recent improvement in treatment strategies. This study aims to evaluate the "delta radiomics" approach in patients undergoing neoadjuvant chemoradiotherapy (nCRT) treated with 0.35-T magnetic resonance-guided radiotherapy (MRgRT), developing a logistic regression model able to predict 2-year disease-free-survival (2yDFS).

Methods:

Patients affected by LARC were enrolled in this multi-institutional study. A predictive model of 2yDFS was developed taking into account both clinical and radiomics variables. Gross tumour volume (GTV) was delineated on the magnetic resonance (MR) images acquired during MRgRT, and 1,067 radiomic features (RF) were extracted using the MODDICOM platform. The performance of RF in predicting 2yDFS was investigated in terms of the Wilcoxon-Mann-Whitney test and area under receiver operating characteristic (ROC) curve (AUC).

Results:

48 patients have been retrospectively enrolled, with 8 patients (16.7%) developing distant metastases at the 2-year follow-up. A total of 1,099 variables (1,067 RF and 32 clinical variables) were evaluated in two different models: radiomics and radiomics/clinical. The best-performing 2yDFS predictive model was a delta radiomics one, based on the variation in terms of area/surface ratio between biologically effective doses (BED) at 54 Gy and simulation (AUC of 0.92).

Conclusions:

The results of this study suggest a promising role of delta radiomics analysis on 0.35-T MR images in predicting 2yDFS for LARC patients. Further analyses including larger cohorts of patients and an external validation are needed to confirm these preliminary results.

• Authors: Giuditta Chiloiro, Luca Boldrini, Francesco Preziosi, Davide Cusumano, Poonam Yadav, Angela Romano, Lorenzo Placidi, Jacopo Lenkowicz, Nicola Dinapoli, Michael F Bassetti, Maria Antonietta Gambacorta, Vincenzo Valentini
• Journal: Frontiers in oncology (Front Oncol) Vol. 12 Pg. 831712 ( 2022) ISSN: 2234-943X [Print] Switzerland
• PMID: 35280799 (Publication Type: Journal Article)
• Copyright: Copyright © 2022 Chiloiro, Boldrini, Preziosi, Cusumano, Yadav, Romano, Placidi, Lenkowicz, Dinapoli, Bassetti, Gambacorta and Valentini.