Researchers at the Icahn School of Medicine at Mount Sinai have developed an advanced artificial intelligence (AI)-driven tool to improve the management and prognosis of prostate cancer.
Recent progress in AI, especially with advances in deep learning techniques, has accelerated the creation of new technologies that use medical images to predict diseases more accurately.
The tool is called PATHOMIQ_PRAD and it is designed for patients with intermediate-risk prostate cancer, uses deep learning to extract morphological features from datasets derived from biopsy or surgical haematoxylin- and eosin-stained whole-slide images.
The technology aims to identify those at higher risk of rapid disease progression and provide more timely, accurate predictions for earlier interventions and more targeted, personalized, treatment plans. Estimates for prostate cancer in the U.S. for 2024 are about 299,010 new cases, with about 35,250 deaths.
According to researcher Ash Tewari: “About 60 percent of patients in the intermediate-risk group don’t have a clear treatment plan, and around 30 to 50 percent see their cancer progress after the first round of therapy. We’re finding that some of these patients are at higher risk for rapid progression, so identifying them early is critical.”
Tewari adds: “We developed this tool to analyse samples from biopsies or surgeries, providing a clearer understanding of which patients may require more aggressive treatment earlier to improve their outcomes. PATHOMIQ_PRAD has the potential to become a routine part of clinical decision-making.”
The new tool has an ability to analyse specific regions of tissue that may hold clues to previously undiscovered drivers of prostate cancer progression.
PATHOMIQ_PRAD scores range from 0 to 1, with higher scores indicating high-risk features. The study analyzed large datasets to classify patients into high- and low-risk groups using pre-determined PATHOMIQ_PRAD clinical cut offs of 0.45 for BCR and 0.55 for metastasis. These limits were based on things like the chances of cancer returning or spreading. The study found that the tool outperformed existing benchmark cancer outcomes over the next five years compared to other current tools.
The researchers plan to conduct large-scale clinical validation studies with a more diverse patient population. They also aim to pursue regulatory approval to develop PATHOMIQ_PRAD as a Lab Developed Test, allowing its use in CLIA-certified labs.
The researchers are also integrating the tool with advanced genomic profiling techniques, such as spatial transcriptomics and mass cytometry, to enhance understanding of the biology behind the regions identified by PATHOMIQ_PRAD.
The findings have been reported in the journal European Urology. The paper is titled “A novel artificial intelligence–powered tool for precise risk stratification of prostate cancer progression in patients with clinical intermediate risk”.
