Benjamin Vandendorpe1, Carole Durot2, Loïc Lebellec3, Marie-Cécile Le Deley4, Dienabou Sylla3, André-Michel Bimbai3, Kocéila Amroun5, Fabrice Ramiandrisoa1, Abel Cordoba6, Xavier Mirabel6, Christine Hoeffel2, David Pasquier6, Stéphanie Servagi-Vernat7. 1. Department of Radiation Oncology, Institut Jean Godinot, Reims, France. 2. Radiology, Centre Hospitalier Universitaire de Reims, France. 3. Biostatistics Unit, Centre Oscar Lambret, Lille, France. 4. Biostatistics Unit, Centre Oscar Lambret, Lille, France; CESP, INSERM, Paris-Sud Paris-Orsay University, Villejuif, France. 5. Department of Surgery, Institut Jean Godinot, Reims, France. 6. Department of Radiation Oncology, Centre Oscar Lambret, Lille, France. 7. Department of Radiation Oncology, Institut Jean Godinot, Reims, France; CRESTIC, University of Reims, France. Electronic address: stephanie.servagivernat@reims.unicancer.fr.
Abstract
BACKGROUND AND PURPOSE: Baseline contrast-enhanced computed tomography (CT)-derived texture analysis in locally advanced rectal cancer could help offer the best personalized treatment. The purpose of this study was to determine the value of baseline-CT texture analysis in the prediction of downstaging in patients with locally advanced rectal cancer. PATIENTS AND METHODS: We retrospectively included all consecutive patients treated with neoadjuvant chemoradiation therapy (CRT) followed by surgery for locally advanced rectal cancer. Tumor texture analysis was performed on the baseline pre-CRT contrast-enhanced CT examination. Based on the selected model of downstaging with a penalized logistic regression in a training set, a radiomics score (Radscore) was calculated as a linear combination of selected features. A multivariable prognostic model that included Radscore and clinical factors was created. RESULTS: Of the 121 patients included in the study, 109 patients (90%) had T3-T4 cancer and 99 (82%) had N+ cancer. A downstaging response was observed in 96 patients (79%). In the training set (79 patients), the best model (ELASTIC-NET method) reduced the 36 texture features to a combination of 6 features. The multivariate analysis retained the Radscore (odds ratio [OR] = 13.25; 95% confidence interval [95% CI], 4.06-71.64; p < 0.001) and age (OR = 1.10/1 year; 1.03-1.20; p = 0.008) as independent factors. In the test set, the area under the curve was estimated to be 0.70 (95% CI, 0.48-0.92). CONCLUSION: This study presents a prognostic score for downstaging, from initial computed tomography-derived texture analysis in locally advanced rectal cancer, which may lead to a more personalized treatment for each patient.
BACKGROUND AND PURPOSE: Baseline contrast-enhanced computed tomography (CT)-derived texture analysis in locally advanced rectal cancer could help offer the best personalized treatment. The purpose of this study was to determine the value of baseline-CT texture analysis in the prediction of downstaging in patients with locally advanced rectal cancer. PATIENTS AND METHODS: We retrospectively included all consecutive patients treated with neoadjuvant chemoradiation therapy (CRT) followed by surgery for locally advanced rectal cancer. Tumor texture analysis was performed on the baseline pre-CRT contrast-enhanced CT examination. Based on the selected model of downstaging with a penalized logistic regression in a training set, a radiomics score (Radscore) was calculated as a linear combination of selected features. A multivariable prognostic model that included Radscore and clinical factors was created. RESULTS: Of the 121 patients included in the study, 109 patients (90%) had T3-T4 cancer and 99 (82%) had N+ cancer. A downstaging response was observed in 96 patients (79%). In the training set (79 patients), the best model (ELASTIC-NET method) reduced the 36 texture features to a combination of 6 features. The multivariate analysis retained the Radscore (odds ratio [OR] = 13.25; 95% confidence interval [95% CI], 4.06-71.64; p < 0.001) and age (OR = 1.10/1 year; 1.03-1.20; p = 0.008) as independent factors. In the test set, the area under the curve was estimated to be 0.70 (95% CI, 0.48-0.92). CONCLUSION: This study presents a prognostic score for downstaging, from initial computed tomography-derived texture analysis in locally advanced rectal cancer, which may lead to a more personalized treatment for each patient.
Authors: Toru Tochigi; Sophia C Kamran; Anushri Parakh; Yoshifumi Noda; Balaji Ganeshan; Lawrence S Blaszkowsky; David P Ryan; Jill N Allen; David L Berger; Jennifer Y Wo; Theodore S Hong; Avinash Kambadakone Journal: Eur Radiol Date: 2021-10-13 Impact factor: 7.034