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Review
. 2021 Feb 11;7(2):34.
doi: 10.3390/jimaging7020034.

Radiomics and Prostate MRI: Current Role and Future Applications

Giuseppe Cutaia  1 , Giuseppe La Tona  1 , Albert Comelli  2 , Federica Vernuccio  1 , Francesco Agnello  1 , Cesare Gagliardo  1 , Leonardo Salvaggio  1 , Natale Quartuccio  3 , Letterio Sturiale  3 , Alessandro Stefano  4 , Mauro Calamia  1 , Gaspare Arnone  3 , Massimo Midiri  1 , Giuseppe Salvaggio  1
Affiliations
Review

Radiomics and Prostate MRI: Current Role and Future Applications

Giuseppe Cutaia et al. J Imaging. .

Abstract

Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined to prostate cancer staging. Radiomics is the quantitative extraction and analysis of minable data from medical images; it is emerging as a promising tool to detect and categorize prostate lesions. In this paper we review the role of radiomics applied to prostate mpMRI in detection and localization of prostate cancer, prediction of Gleason score and PI-RADS classification, prediction of extracapsular extension and of biochemical recurrence. We also provide a future perspective of artificial intelligence (machine learning and deep learning) applied to the field of prostate cancer.

Keywords: Gleason score; artificial intelligence; local; multiparametric magnetic resonance imaging; neoplasm recurrence; prostate cancer.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Radiomics workflow using artificial intelligence includes 5 steps: I. acquisition of radiological images and manual segmentation of the regions of interest (ROI); II. extraction of radiomics features from ROIs; III. methods of selection and/or reduction of the most significant radiomic features; IV. Artificial intelligence models for diagnosis prediction; V. Training and validation models.
See this image and copyright information in PMC

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