MRI radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinoma

• Published in: Journal of translational medicine 2020-02, Vol.18 (1), p.61-61, Article 61
• Main Authors: Eresen, Aydin, Yang, Jia, Shangguan, Junjie, Li, Yu, Hu, Su, Sun, Chong, Velichko, Yury, Yaghmai, Vahid, Benson, 3rd, Al B, Zhang, Zhuoli
• Format: Article
• Language: English
• Subjects: Adenocarcinoma; Animals; Antigens; Biological markers; Biomarkers; Cancer therapies; Cancer vaccines; Carcinoma, Pancreatic Ductal - diagnostic imaging; Carcinoma, Pancreatic Ductal - therapy; Clinical trials; Cloning; Dendritic cell vaccine; Dendritic cells; Diagnosis; Diagnostic imaging; Diseases; Drug therapy; Fibrosis; Genetic engineering; Immunotherapy; Immunotherapy, Active; Invasiveness; Laboratory animals; Machine learning; Magnetic Resonance Imaging; Medical prognosis; Medical research; Methods; Mice; Mice, Transgenic; Operating systems (Software); Pancreas; Pancreatic cancer; Pancreatic ductal adenocarcinoma; Pancreatic Neoplasms - diagnostic imaging; Pancreatic Neoplasms - therapy; Quantitative analysis; Radiomics; Studies; Surgical outcomes; Testing; Transgenic mice; Tumor Microenvironment; Tumors; Vaccination; Vaccines
• ISSN: 1479-5876; 1479-5876
• DOI: 10.1186/s12967-020-02246-7

There is a lack of well-established clinical tools for predicting dendritic cell (DC) vaccination response of pancreatic ductal adenocarcinoma (PDAC). DC vaccine treatment efficiency was demonstrated using histological analysis in pre-clinical studies; however, its usage was limited due to invasiveness. In this study, we aimed to investigate the potential of MRI texture features for detection of early immunotherapeutic response as well as overall survival (OS) of PDAC subjects following dendritic cell (DC) vaccine treatment in LSL-Kras ;LSL-Trp53 ;Pdx-1-Cre (KPC) transgenic mouse model of pancreatic ductal adenocarcinoma (PDAC). KPC mice were treated with DC vaccines, and tumor growth was dynamically monitored. A total of a hundred and fifty-two image features of T2-weighted MRI images were analyzed using a kernel-based support vector machine model to detect treatment effects following the first and third weeks of the treatment. Moreover, univariate analysis was performed to describe the association between MRI texture and survival of KPC mice as well as histological tumor biomarkers. OS for mice in the treatment group was 54.8 ± 22.54 days while the control group had 35.39 ± 17.17 days. A subset of three MRI features distinguished treatment effects starting from the first week with increasing accuracy throughout the treatment (75% to 94%). Besides, we observed that short-run emphasis of approximate wavelet coefficients had a positive correlation with the survival of the KPC mice (r = 0.78, p