MP64-05 THE APPLICATION OF MINIMAL SCORE OF APPARENT DIFFUSION COEFFICIENT (ADC) IN PROSTATE MRI TO PREDICT THE PROSTATE CANCER MICROENVIRONMENT

Abstract

You have accessJournal of UrologyProstate Cancer: Basic Research & Pathophysiology II1 Apr 2018MP64-05 THE APPLICATION OF MINIMAL SCORE OF APPARENT DIFFUSION COEFFICIENT (ADC) IN PROSTATE MRI TO PREDICT THE PROSTATE CANCER MICROENVIRONMENT Manabu Kato, Placencio Veronica, Kenichiro Ishii, Kohei Nishikawa, Kiminobu Arima, Yoshihumi Hirokawa, Masatoshi Watanabe, and Yoshiki Sugimura Manabu KatoManabu Kato More articles by this author , Placencio VeronicaPlacencio Veronica More articles by this author , Kenichiro IshiiKenichiro Ishii More articles by this author , Kohei NishikawaKohei Nishikawa More articles by this author , Kiminobu ArimaKiminobu Arima More articles by this author , Yoshihumi HirokawaYoshihumi Hirokawa More articles by this author , Masatoshi WatanabeMasatoshi Watanabe More articles by this author , and Yoshiki SugimuraYoshiki Sugimura More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.2050AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Multi-parametric MRI and the mapping with Apparent Diffusion Coefficient (ADC) reinforce the accuracy for local detection of prostate cancer. It has been hard to predict the conditions of tumor microenvironment before the treatment. In this prostate tumor microenvironment, cancer-associated fibroblasts plays important role for cancer progression and invasion, and these components shows tendency of high expression for specific protein markers including Vimentin, CD105 and TNC-C. On the other hand, aSMA is commonly used as a marker of smooth muscle cells and expressed in the stroma area surrounding normal prostate grounds. In this study, we examined the MRI predictive availability for evaluation of prostate cancer microenvironment by comparing the pre-operation MRI images with the findings of immunohistochemistry (IHC) of prostate cancer surgical specimens. METHODS 44 cases were analyzed that are surgically operated with robot-assisted radical prostatectomy performed from February to September in 2016. Preoperative MRI have been conducted for all 44 cases, and the prostate cancer local diagnoses (Region of Interest: ROI) were determined by radiologists using MRI T2 weighed image and Diffusion Weighed Image (DWI), then finally the scores of ADC were calculated. IHC for aSMA, vimentin, CD105, and Tenascin-C (TNC-C) were conducted and classified into three group (none stained, weakly stained, strongly stained) to check the relation of those IHC findings to MRI ADC score before the treatment. RESULTS The average of minimum ADC scores in ROC of these prostate cancer patients before surgery was 0.779 (SD=0.173). IHC comparison were made according to the cut off value of the minimum ADC scores between more (n=18, group A) and less (n=26, group B) than 0.800. 66% (12/18) patients showed strongly stained findings for aSMA in group A. Meanwhile, vimentin, CD105, and TNC-C showed strong stained in B group, 22.2% (4/18) and 61.5% (16/26), 22.2% (4/18) and 0% (0/26), and, 33.3% (6/18) and 76.9% (20/26) in group A and B, respectively.(Conclusions) CONCLUSIONS To use these multi-parametric MRI findings, especially pretreatment ADC scores, our results suggested postoperative IHC findings and more to address, tumor microenvironment could be predicted. The more various treatment selection have been and could be applied to prostate cancer, such as upfront chemotherapy and wide resection for surrounding tissues, the more precise procedure are needed to predict tumor microenvironment in order to detect potentially aggressive prostate cancer. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e851-e852 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Manabu Kato More articles by this author Placencio Veronica More articles by this author Kenichiro Ishii More articles by this author Kohei Nishikawa More articles by this author Kiminobu Arima More articles by this author Yoshihumi Hirokawa More articles by this author Masatoshi Watanabe More articles by this author Yoshiki Sugimura More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...