Advancements in MRI-Based Radiomics and Artificial Intelligence for Prostate Cancer: A Comprehensive Review and Future Prospects

Abstract

The use of multiparametric magnetic resonance imaging (mpMRI) has become a common technique used in guiding biopsy and developing treatment plans for prostate lesions. While this technique is effective, non-invasive methods such as radiomics have gained popularity for extracting imaging features to develop predictive models for clinical tasks. The aim is to minimize invasive processes for improved management of prostate cancer (PCa). This study reviews recent research progress in MRI-based radiomics for PCa, including the radiomics pipeline and potential factors affecting personalized diagnosis. The integration of artificial intelligence (AI) with medical imaging is also discussed, in line with the development trend of radiogenomics and multi-omics. The survey highlights the need for more data from multiple institutions to avoid bias and generalize the predictive model. The AI-based radiomics model is considered a promising clinical tool with good prospects for application.

Prototype Description and Ex Vivo Evaluation of a System for Combined Endorectal Magnetic Resonance Imaging and In-Bore Biopsy of the Prostate

“…Improved liquid biopsy markers should result in a smaller but higher yield “screen positive” population requiring biopsy. Novel techniques for immediate analysis of MR images 23 and pathology specimens 24 could facilitate rapid target identification and characterization. We plan to develop software to assist users in identifying the appropriate needle channel and depth to optimally biopsy a selected target.…”

Comparative Evaluation of Machine Learning Models for Subtyping Triple-Negative Breast Cancer: A Deep Learning-Based Multi-Omics Data Integration Approach

“…Specifically, the high performance of the DL model for multi-omics data is attributed to its capacity to aggregate and analyze extensive biomolecular data 43 , while the MRI radiomics model provides a non-invasive diagnostic approach 44 . The synergy of these models holds the potential to refine the classification of TNBC, thereby enabling the formulation of more precise treatment plans for patients 45 .…”

Multiparametric magnetic resonance imaging in the active surveillance of prostate cancer: protocol, risk stratification, and surveillance

“…MRI-based radiomics, a noninvasive method, has gained popularity for extracting imaging features from PCa images and developing predictive models for clinical tasks [35]. Recent studies have explored the correlation between imaging models and genetic characteristics to better understand the inherent biological nature of PCa [36].…”