A radiomic signature model to predict the chemoradiation-induced alteration in tumor-infiltrating CD8+ cells in locally advanced rectal cancer. (September 2021)

• Record Type: Journal Article
• Authors: Jeon, Seung Hyuck; Lim, Yu Jin; Koh, Jaemoon; Chang, Won Ick; Kim, Sehui; Kim, Kyubo; Chie, Eui Kyu
• Is Part Of: Radiotherapy and oncology. Volume 162(2021)
• Page Start: 124
• Page End: 131
• Publication Date: 2021-09
• Subjects: Rectal neoplasms -- Radiomics -- CD8-positive T-lymphocytes -- Chemoradiotherapy -- Radiomic score -- Neoadjuvant therapy; 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.2021.07.004
• Languages: English
• ISSNs: 0167-8140

Abstract

Highlights: This study incorporated radiomic features and immunohistochemistry of rectal cancer. The MRI-based radiomic signature predicted CD8 + TIL alterations after chemoradiation. Our results suggest the clinical utility of radiomics-immunophenotype modeling. Abstract: Background and purpose: Regarding the altered tumor immune status following cytotoxic treatment, this study aims to develop a radiomic signature to predict CD8 + tumor-infiltrating lymphocyte (TIL) density changes in chemoradiotherapy (CRT) of rectal cancer. Materials and methods: We used the magnetic resonance imaging (MRI) and immunohistochemistry data before and after neoadjuvant CRT. The discovery datasets consisted of pre-CRT dataset A1 ( n = 113), post-CRT datasets A2 ( n = 32; predominance of tumor) and A3 ( n = 20; pure fibrosis). The developed model was validated in dataset B ( n = 28). Thirty-eight radiomic features from T2-weighted MRI scans were incorporated into the least absolute shrinkage and selection operator method. Results: In pre-CRT dataset A1, the area under the receiver operating characteristic curve (AUC) values of radiomic score for predicting CD8 + TILs were 0.760 and 0.729 for training and validation subsets, respectively. A significant correlation was observed between the signature and CD8 + TIL density in the post-CRT dataset A2 (Pearson's R = −0.372, P = 0.036), whereas no association was found in dataset A3 (Pearson's R = −0.069, P = 0.77). The association was also observed in the validation dataset B (Pearson's R = −0.374, P = 0.049). In dataset A2, the radiomic score difference predicted changes in CD8 + TIL density (AUC = 0.824). Conclusion: We established the MRI-derived radiomic signature for predicting CRT-induced alterations in CD8 + TILs. This study suggests the clinical utility of radiomics-immunophenotype modeling to evaluate tumor immune status following neoadjuvant chemoradiation in rectal cancer.