Vinayak Banerjee, Shu Wang, Max Drescher, Ryan Russell, M Minhaj Siddiqui
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引用次数: 3
Abstract
In an era of powerful computing tools, radiogenomics provides a personalized, precise approach to the detection and diagnosis in patients with prostate cancer (PCa). Radiomics data are obtained through artificial intelligence (AI) and neural networks that analyze imaging, usually MRI, to assess statistical, geometrical, and textural features of images to provide quantitative data of shape, heterogeneity, and intensity of tumors. Genomics involves assessing the genomic markers that are present from tumor biopsies. In this article, we separately investigate the current landscape of radiomics and genomics within the realm of PCa and discuss the integration and validity of both into radiogenomics using the data from three papers on the topic. We also conducted a clinical trials search using the NIH's database, where we found two relevant actively recruiting studies. Although there is more research needed to be done on radiogenomics to fully adopt it as a viable diagnosis tool, its potential by providing personalized data regarding each tumor cannot be overlooked as it may be the future of PCa risk-stratification techniques.
期刊介绍:
Therapeutic Advances in Urology delivers the highest quality peer-reviewed articles, reviews, and scholarly comment on pioneering efforts and innovative studies across all areas of urology.
The journal has a strong clinical and pharmacological focus and is aimed at clinicians and researchers in urology, providing a forum in print and online for publishing the highest quality articles in this area. The editors welcome articles of current interest across all areas of urology, including treatment of urological disorders, with a focus on emerging pharmacological therapies.