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

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...

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Autores principales: Eresen, Aydin, Yang, Jia, Shangguan, Junjie, Li, Yu, Hu, Su, Sun, Chong, Velichko, Yury, Yaghmai, Vahid, Benson, Al B., Zhang, Zhuoli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011246/
https://www.ncbi.nlm.nih.gov/pubmed/32039734
http://dx.doi.org/10.1186/s12967-020-02246-7
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author Eresen, Aydin
Yang, Jia
Shangguan, Junjie
Li, Yu
Hu, Su
Sun, Chong
Velichko, Yury
Yaghmai, Vahid
Benson, Al B.
Zhang, Zhuoli
author_facet Eresen, Aydin
Yang, Jia
Shangguan, Junjie
Li, Yu
Hu, Su
Sun, Chong
Velichko, Yury
Yaghmai, Vahid
Benson, Al B.
Zhang, Zhuoli
author_sort Eresen, Aydin
collection PubMed
description 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.
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spelling pubmed-70112462020-02-14 MRI radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinoma Eresen, Aydin Yang, Jia Shangguan, Junjie Li, Yu Hu, Su Sun, Chong Velichko, Yury Yaghmai, Vahid Benson, Al B. Zhang, Zhuoli J Transl Med Research 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. BioMed Central 2020-02-10 /pmc/articles/PMC7011246/ /pubmed/32039734 http://dx.doi.org/10.1186/s12967-020-02246-7 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Eresen, Aydin
Yang, Jia
Shangguan, Junjie
Li, Yu
Hu, Su
Sun, Chong
Velichko, Yury
Yaghmai, Vahid
Benson, Al B.
Zhang, Zhuoli
MRI radiomics for early prediction of response to vaccine therapy in a transgenic mouse model of pancreatic ductal adenocarcinoma
title 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_short 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
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011246/
https://www.ncbi.nlm.nih.gov/pubmed/32039734
http://dx.doi.org/10.1186/s12967-020-02246-7
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