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Advancing Prostate Cancer Assessment: A Biparametric MRI (T2WI and DWI/ADC)-Based Radiomic Approach to Predict Tumor–Stroma Ratio

<b>Objectives:</b> This study aimed to develop and validate a biparametric MRI (bpMRI)-based radiomics model for the noninvasive prediction of tumor–stroma ratio (TSR) in prostate cancer (PCa). Additionally, we sought to explore lesion distribution patterns in the peripheral zone (PZ) and transition...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Jiangqin Ma, Xiling Gu, Zhonglin Zhang, Jun Chen, Yunfan Liu, Yang Qiu, Guangyong Ai, Xuxiang Jia, Zhenghao Li, Bo Xiang, Xiaojing He
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2025-10-01
Schriftenreihe:Diagnostics
Schlagworte:
prostate cancer
tumor–stroma ratio
radiomics
biparametric MRI
machine learning
Online-Zugang:https://www.mdpi.com/2075-4418/15/21/2722
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