Prognostic value of the texture analysis parameters of the initial computed tomographic scan for response to neoadjuvant chemoradiation therapy in patients with locally advanced rectal cancer. (June 2019)

• Record Type: Journal Article
• Authors: Vandendorpe, Benjamin; Durot, Carole; Lebellec, Loïc; Le Deley, Marie-Cécile; Sylla, Dienabou; Bimbai, André-Michel; Amroun, Kocéila; Ramiandrisoa, Fabrice; Cordoba, Abel; Mirabel, Xavier; Hoeffel, Christine; Pasquier, David; Servagi-Vernat, Stéphanie
• Is Part Of: Radiotherapy and oncology. Volume 135(2019)
• Page Start: 153
• Page End: 160
• Publication Date: 2019-06
• Subjects: TA texture analysis -- SSF spatial scale filtration -- Mpp mean positive pixel -- CEA carcinoembryonic antigen -- CI confidence interval; Computed tomography -- Texture analysis -- Prognostic value -- Neoadjuvant therapy -- Rectal cancer; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2019.03.011
• Languages: English
• ISSNs: 0167-8140

Abstract

Highlights: We assessed baseline-CT texture analysis's value in predicting downstaging in rectal cancer. A multivariable prognostic model including Radscore and clinical factors was created. CT-derived texture analysis helps offer personalized treatment for cancer patients. 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.