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Researchers develop new prostate cancer prediction tool: Study

IANS  |  New York 

Researchers,, including one of an Indian-origin, have developed a novel machine-learning framework that can distinguish between low and high-risk with more precision than ever before, according to a new study.

The study conducted by the Icahn School of at Mount and Keck School of at the University of (USC), showed that the framework is intended to help physicians -- in particular, radiologists -- more accurately identify treatment options for patients, lessening the chance of unnecessary clinical intervention.

Presently, the standard methods used to assess risk are multiparametric (mpMRI), which detects prostate lesions, and the Prostate Imaging Reporting and Data System, version 2 (PI-RADS v2), a five-point scoring system that classifies lesions found on the mpMRI.

However, current tools used to predict prostate cancer progression are generally subjective in nature, leading to differing interpretations among clinicians.

The findings, published in Scientific Reports, showed that combining with radiomics -- a branch of that uses algorithms to extract large amounts of quantitative characteristics from medical images -- researchers were able to classify with high sensitivity and an even higher predictive value.

Hence, the approach has been proposed to remedy this drawback.

"By rigorously and systematically combining with radiomics, our goal is to provide radiologists and clinical personnel with a that can eventually translate to more effective and personalised patient care," said Gaurav Pandey, at the at Mount

The pathway to predicting prostate cancer progression with high accuracy is ever improving, and we believe our objective framework is a much-needed advancement, the study noted.



(This story has not been edited by Business Standard staff and is auto-generated from a syndicated feed.)

First Published: Fri, February 08 2019. 11:36 IST