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Magnetic resonance imaging textural analysis for detection of phenotypic patterns in Prostate Cancer patients with BRCA 1 and 2 mutations

Grant number: 21/14417-7
Support Opportunities:Regular Research Grants
Duration: March 01, 2023 - February 28, 2025
Field of knowledge:Health Sciences - Medicine - Medical Radiology
Principal Investigator:Valdair Francisco Muglia
Grantee:Valdair Francisco Muglia
Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
Associated researchers:Agma Juci Machado Traina ; Aila de Menezes Ferreira ; Daniel Guimarães Tiezzi ; Julio Cesar Nather Junior ; Leandro Machado Colli ; Rodolfo Borges dos Reis


Prostate cancer is the most prevalent cancer in men, with relevant social and economic impacts. The phenotype and course of the disease span a broad spectrum, from an indolent tumor to an aggressive metastatic carcinoma. Current clinicopathological markers are insufficient to capture this spectrum of patients, especially those at risk of treatment failure and with poor prognosis. Even with the methods currently applied for risk stratification, treatment selection, response prediction, approximately 25% of patients evolve with progressive disease, justifying the importance of better knowledge of the biological factors responsible for progression, as prerequisites for developing new ones. therapeutic strategies and improve clinical outcomes. Texture analysis by magnetic resonance (MR) is a recent, promising and objective technique that allows the identification of tissue patterns without the need for invasive methods. However, unlike conventional quantitative MRI parameters, little is known about the exact meaning of technical characteristics and their correlation with histological and genetic findings in prostate cancer. Studies report that the BRCA mutation is associated with a higher Gleason score, higher serum PSA level, higher tumor staging and grade at diagnosis, and lower overall survival, so knowledge of this mutation can affect treatment options. The aim of the study is to evaluate the ability of textural features derived from MR sequences as biomarkers of the biological behavior of prostate cancer. The study will use T2 and diffusion sequences to create textural patterns in 80 patients with prostate cancer who will have classical histological prognostic data (Gleason scale) collected and BRCA mutation sequencing. As a control group, we will have about 80 patients without gene mutation, but with similar prognosis risk stratification. The analysis of textural patterns with clinical and genomic characteristics may contribute to the individualization of prostate cancer treatment, without the need for invasive techniques. (AU)

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