Differentiating False Positive Lesions from Clinically Significant Cancer and Normal Prostate Tissue Using VERDICT MRI and Other Diffusion Models

Differentiating False Positive Lesions from Clinically Significant Cancer and Normal Prostate Tissue Using VERDICT MRI and Other Diffusion Models

False positives on multiparametric MRIs (mp-MRIs) result in many unnecessary invasive biopsies in men with clinically insignificant diseases. This study investigated whether quantitative diffusion MRI could differentiate between false positives, true positives and normal tissue non-invasively. Thirt...

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Bibliographic Details
Main Authors: Snigdha Sen, Vanya Valindria, Paddy J. Slator, Hayley Pye, Alistair Grey, Alex Freeman, Caroline Moore, Hayley Whitaker, Shonit Punwani, Saurabh Singh, Eleftheria Panagiotaki
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Diagnostics
Subjects:
prostate cancer
diffusion MRI
false positives
biophysical modeling
deep learning
Online Access:https://www.mdpi.com/2075-4418/12/7/1631

Internet

https://www.mdpi.com/2075-4418/12/7/1631

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