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Prostate cancer diagnostic tests have witnessed significant technological advancements in recent years. These advancements are intended to improve the accuracy and effectiveness of cancer diagnostics, staging, and treatment options. Several biomarkers, such as prostate-specific antigen (PSA), have been used for prostate cancer screening and monitoring. However, novel biomarkers such as prostate cancer antigen 3 (PCA3), TMPRSS2-ERG fusion, and 4Kscore are developed to improve diagnostic accuracy and risk stratification. These biomarkers can be combined with other clinical information to enhance personalized treatment decisions.
Healthcare professionals are employing artificial intelligence and machine learning techniques to analyse medical imaging data and assist in prostate cancer diagnosis. These algorithms are helping radiologists and urologists identify suspicious regions on mpMRI, improve biopsy targeting, and aid in risk stratification.
Furthermore, advances in genomic sequencing technologies have allowed for comprehensive genomic profiling of prostate tumours. By analysing the genomic alterations, researchers are identifying specific genetic mutations or alterations that drive the development and progression of prostate cancer. This data is proving to be significant in selecting targeted therapies and personalized treatment approaches. As a result, technological advancements hold promise in improving prostate cancer diagnosis & treatment procedures efficiently.