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

Abstract Background 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 limi...

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Main Authors: Aydin Eresen, Jia Yang, Junjie Shangguan, Yu Li, Su Hu, Chong Sun, Yury Velichko, Vahid Yaghmai, Al B. Benson, Zhuoli Zhang
Format: Article
Language:English
Published: BMC 2020-02-01
Series:Journal of Translational Medicine
Subjects:
Online Access:https://doi.org/10.1186/s12967-020-02246-7
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spelling doaj-35e37655c1a04489ad02b1f316951dc72021-02-14T12:10:26ZengBMCJournal of Translational Medicine1479-58762020-02-011811910.1186/s12967-020-02246-7MRI radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinomaAydin Eresen0Jia Yang1Junjie Shangguan2Yu Li3Su Hu4Chong Sun5Yury Velichko6Vahid Yaghmai7Al B. Benson8Zhuoli Zhang9Dept. of Radiology, Feinberg School of Medicine, Northwestern UniversityDept. of Radiology, Feinberg School of Medicine, Northwestern UniversityDept. of Radiology, Feinberg School of Medicine, Northwestern UniversityDept. of Radiology, Feinberg School of Medicine, Northwestern UniversityDept. of Radiology, Feinberg School of Medicine, Northwestern UniversityDept. of Radiology, Feinberg School of Medicine, Northwestern UniversityDept. of Radiology, Feinberg School of Medicine, Northwestern UniversityDept. of Radiology, Feinberg School of Medicine, Northwestern UniversityRobert H. Lurie Comprehensive Cancer Center of Northwestern UniversityDept. of Radiology, Feinberg School of Medicine, Northwestern UniversityAbstract Background 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 G12D ;LSL-Trp53 R172H ;Pdx-1-Cre (KPC) transgenic mouse model of pancreatic ductal adenocarcinoma (PDAC). Materials and methods 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. Results 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 < 0.001). Additionally, tissue-specific MRI texture features showed positive association with fibrosis percentage (r = 0.84, p < 0.002), CK19 positive percentage (r = − 0.97, p < 0.001), and Ki67 positive cells (r = 0.81, p < 0.02) as histological disease biomarkers. Conclusion Our results demonstrate that MRI texture features can be used as imaging biomarkers for early detection of therapeutic response following DC vaccination in the KPC mouse model of PDAC. Besides, MRI texture can be utilized to characterize tumor microenvironment reflected with histology analysis.https://doi.org/10.1186/s12967-020-02246-7Dendritic cell vaccineMachine learningMagnetic resonance imagingPancreatic ductal adenocarcinomaRadiomics
collection DOAJ
language English
format Article
sources DOAJ
author Aydin Eresen
Jia Yang
Junjie Shangguan
Yu Li
Su Hu
Chong Sun
Yury Velichko
Vahid Yaghmai
Al B. Benson
Zhuoli Zhang
spellingShingle Aydin Eresen
Jia Yang
Junjie Shangguan
Yu Li
Su Hu
Chong Sun
Yury Velichko
Vahid Yaghmai
Al B. Benson
Zhuoli Zhang
MRI radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinoma
Journal of Translational Medicine
Dendritic cell vaccine
Machine learning
Magnetic resonance imaging
Pancreatic ductal adenocarcinoma
Radiomics
author_facet Aydin Eresen
Jia Yang
Junjie Shangguan
Yu Li
Su Hu
Chong Sun
Yury Velichko
Vahid Yaghmai
Al B. Benson
Zhuoli Zhang
author_sort Aydin Eresen
title MRI radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinoma
title_short MRI radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinoma
title_full MRI radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinoma
title_fullStr MRI radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinoma
title_full_unstemmed MRI radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinoma
title_sort mri radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinoma
publisher BMC
series Journal of Translational Medicine
issn 1479-5876
publishDate 2020-02-01
description Abstract Background 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 G12D ;LSL-Trp53 R172H ;Pdx-1-Cre (KPC) transgenic mouse model of pancreatic ductal adenocarcinoma (PDAC). Materials and methods 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. Results 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 < 0.001). Additionally, tissue-specific MRI texture features showed positive association with fibrosis percentage (r = 0.84, p < 0.002), CK19 positive percentage (r = − 0.97, p < 0.001), and Ki67 positive cells (r = 0.81, p < 0.02) as histological disease biomarkers. Conclusion Our results demonstrate that MRI texture features can be used as imaging biomarkers for early detection of therapeutic response following DC vaccination in the KPC mouse model of PDAC. Besides, MRI texture can be utilized to characterize tumor microenvironment reflected with histology analysis.
topic Dendritic cell vaccine
Machine learning
Magnetic resonance imaging
Pancreatic ductal adenocarcinoma
Radiomics
url https://doi.org/10.1186/s12967-020-02246-7
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