AUTHOR=Guerrisi Antonino , Russillo Michelangelo , Loi Emiliano , Ganeshan Balaji , Ungania Sara , Desiderio Flora , Bruzzaniti Vicente , Falcone Italia , Renna Davide , Ferraresi Virginia , Caterino Mauro , Solivetti Francesco Maria , Cognetti Francesco , Morrone Aldo TITLE=Exploring CT Texture Parameters as Predictive and Response Imaging Biomarkers of Survival in Patients With Metastatic Melanoma Treated With PD-1 Inhibitor Nivolumab: A Pilot Study Using a Delta-Radiomics Approach JOURNAL=Frontiers in Oncology VOLUME=11 YEAR=2021 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.704607 DOI=10.3389/fonc.2021.704607 ISSN=2234-943X ABSTRACT=
In the era of artificial intelligence and precision medicine, the use of quantitative imaging methodological approaches could improve the cancer patient’s therapeutic approaches. Specifically, our pilot study aims to explore whether CT texture features on both baseline and first post-treatment contrast-enhanced CT may act as a predictor of overall survival (OS) and progression-free survival (PFS) in metastatic melanoma (MM) patients treated with the PD-1 inhibitor Nivolumab. Ninety-four lesions from 32 patients treated with Nivolumab were analyzed. Manual segmentation was performed using a free-hand polygon approach by drawing a region of interest (ROI) around each target lesion (up to five lesions were selected per patient according to RECIST 1.1). Filtration-histogram-based texture analysis was employed using a commercially available research software called TexRAD (Feedback Medical Ltd, London, UK;