AUTHOR=Qin Xiaoyan , Lv Jian , Zhang Jianmei , Mu Ronghua , Zheng Wei , Liu Fuzhen , Huang Bingqin , Li Xin , Yang Peng , Deng Kan , Zhu Xiqi 

TITLE=Amide proton transfer imaging has added value for predicting extraprostatic extension in prostate cancer patients

JOURNAL=Frontiers in Oncology

VOLUME=Volume 14 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2024.1327046

DOI=10.3389/fonc.2024.1327046

ISSN=2234-943X

ABSTRACT=Background: Prostate cancer invades the capsule is a key factor in selecting appropriate treatment methods. Accurate preoperative prediction of extraprostatic extension (EPE) can help achieve precise selection of treatment plans.The aim of this study is to verify the diagnostic efficacy of tumor size, length of capsular contact (LCC), apparent diffusion coefficient (ADC), and Amide proton transfer (APT) value in predicting EPE. Additionally, the study aims to investigate the potential additional value of APT for predicting EPE. Method: This study include 47 tumor organ confined patients (age, 64.16±9.18) and 50 EPE patients (age, 61.51±8.82). The difference of tumor size, LCC, ADC and APT value between groups were compared. Binary logistic regression was used to screen the EPE predictors. The receiver operator characteristic curve analysis was performed to assess the diagnostic performance of variables for predicting EPE. The diagnostic efficacy of combined models ( model I: ADC+LCC+tumor size; model II: APT+LCC+tumor size; and model III: APT +ADC+LCC+tumor size) were also analyzed. Results: APT, ADC, tumor size and the LCC were independent predictors of EPE. The area under the curve (AUC) of APT, ADC, tumor size and the LCC were 0.752, 0.665, 0.700 and 0.756, respectively. The AUC of model I, model II , and model III were 0.803, 0.845 and 0.869, respectively. The cutoff value of APT, ADC, tumor size We aim to verify the diagnostic efficacy of tumor size, length of capsular contact (LCC), apparent diffusion coefficient (ADC), Amide proton transfer (APT) value and their combined models for predicting EPE.