Combination of Peri-Tumoral and Intra-Tumoral Radiomic Features on Bi-Parametric MRI Accurately Stratifies Prostate Cancer Risk: A Multi-Site Study

Combination of Peri-Tumoral and Intra-Tumoral Radiomic Features on Bi-Parametric MRI Accurately Stratifies Prostate Cancer Risk: A Multi-Site Study

<i>Background:</i> Prostate cancer (PCa) influences its surrounding habitat, which tends to manifest as different phenotypic appearances on magnetic resonance imaging (MRI). This region surrounding the PCa lesion, or the peri-tumoral region, may encode useful information that can complem...

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Bibliographic Details
Main Authors: Ahmad Algohary, Rakesh Shiradkar, Shivani Pahwa, Andrei Purysko, Sadhna Verma, Daniel Moses, Ronald Shnier, Anne-Maree Haynes, Warick Delprado, James Thompson, Sreeharsha Tirumani, Amr Mahran, Ardeshir R Rastinehad, Lee Ponsky, Phillip D. Stricker, Anant Madabhushi
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Cancers
Subjects:
radiomics
prostate cancer
MRI
artificial intelligence
PIRADS
machine learning
Online Access:https://www.mdpi.com/2072-6694/12/8/2200

Internet

https://www.mdpi.com/2072-6694/12/8/2200

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