Advancements in MRI-based radiomics and artificial intelligence for prostate cancer: A comprehensive review and future prospects

Chaddad, Ahmad, Tan, Guina, Liang, Xiaojuan, Hassan, Lama, Rathore, Saima, Desrosiers, Christian, Katib, Yousef et Niazi, Tamim. 2023. « Advancements in MRI-based radiomics and artificial intelligence for prostate cancer: A comprehensive review and future prospects ». Cancers, vol. 15, nº 15.
Compte des citations dans Scopus : 4.

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Résumé

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.

Type de document:	Article publié dans une revue, révisé par les pairs
Professeur:	Professeur Desrosiers, Christian
Affiliation:	Génie logiciel et des technologies de l'information
Date de dépôt:	30 août 2023 19:39
Dernière modification:	16 oct. 2023 19:20
URI:	https://espace2.etsmtl.ca/id/eprint/27511

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