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

Authors :
Chiloiro, Giuditta
Boldrini, Luca
Preziosi, Francesco
Cusumano, Davide
Yadav, Poonam
Romano, Angela
Placidi, Lorenzo
Lenkowicz, Jacopo
Dinapoli, Nicola
Bassetti, Michael F
Gambacorta, Maria Antonietta
Valentini, Vincenzo
Gambacorta, Maria Antonietta (ORCID:0000-0001-5455-8737)
Valentini, Vincenzo (ORCID:0000-0003-4637-6487)
Chiloiro, Giuditta
Boldrini, Luca
Preziosi, Francesco
Cusumano, Davide
Yadav, Poonam
Romano, Angela
Placidi, Lorenzo
Lenkowicz, Jacopo
Dinapoli, Nicola
Bassetti, Michael F
Gambacorta, Maria Antonietta
Valentini, Vincenzo
Gambacorta, Maria Antonietta (ORCID:0000-0001-5455-8737)
Valentini, Vincenzo (ORCID:0000-0003-4637-6487)
Publication Year :
2022

Abstract

PurposeDistant 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). MethodsPatients 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). Results48 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). ConclusionsThe 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.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1382660087
Document Type :
Electronic Resource