Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study. (March 2022)

• Record Type: Journal Article
• Authors: Fontaine, Pierre; Andrearczyk, Vincent; Oreiller, Valentin; Abler, Daniel; Castelli, Joel; Acosta, Oscar; De Crevoisier, Renaud; Vallières, Martin; Jreige, Mario; Prior, John O.; Depeursinge, Adrien
• Is Part Of: Clinical and translational radiation oncology. Volume 33(2022)
• Page Start: 153
• Page End: 158
• Publication Date: 2022-03
• Subjects: Radiomics -- Head and neck cancer -- Survival analysis; Cancer -- Radiotherapy -- Periodicals; Oncology -- Periodicals; Cancer -- Radiotherapy; Oncology; Radiation Oncology; Neoplasms -- radiotherapy; Translational Medical Research; Periodicals; Electronic journals; Periodicals; 616.9940642
• DOI: 10.1016/j.ctro.2022.01.003
• Languages: English
• ISSNs: 2405-6308

Abstract

Highlights: PET images features are more stable across different delineation of the same target. Shape family features are more stable. The survival model based on Dedicated contours achieved better performance for predicting PFS. Abstract: A vast majority of studies in the radiomics field are based on contours originating from radiotherapy planning. This kind of delineation ( e.g. Gross Tumor Volume, GTV) is often larger than the true tumoral volume, sometimes including parts of other organs ( e.g. trachea in Head and Neck, H&N studies) and the impact of such over-segmentation was little investigated so far. In this paper, we propose to evaluate and compare the performance between models using two contour types: those from radiotherapy planning, and those specifically delineated for radiomics studies. For the latter, we modified the radiotherapy contours to fit the true tumoral volume. The two contour types were compared when predicting Progression-Free Survival (PFS) using Cox models based on radiomics features extracted from FluoroDeoxyGlucose-Positron Emission Tomography (FDG-PET) and CT images of 239 patients with oropharyngeal H&N cancer collected from five centers, the data from the 2020 HECKTOR challenge. Using Dedicated contours demonstrated better performance for predicting PFS, where Harell's concordance indices of 0 . 61 and 0 . 69 were achieved for Radiotherapy and Dedicated contours, respectively. Using automatically Resegmented contours based on a fixed intensity range was associated with a C-index of 0.63. These results illustrate the importance of using clean dedicated contours that are close to the true tumoral volume in radiomics studies, even when tumor contours are already available from radiotherapy treatment planning