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Using pre-operative MRI data, an AI algorithm can help predict recurrence better than existing models.
An artificial intelligence (AI) tool, developed using MRI data, could soon top the list of strategies used to determine which men are most likely to experience a prostate cancer recurrence.
Together with a small group of institutions, Case Western Reserve University has developed RadClip, an AI tool that is designed to make it easier for providers target patients with better treatment options. The team, led by Case Western doctoral Lin Li, published the details of their development recently in The Lancet’s EBioMedicine.
“This tool can help urologists, oncologists, and surgeons create better treatment plans so that their patients can have the most precise treatment,” said Li, who is working on her doctorate from Case Western’s Center for Computational Imaging and Personalized Diagnostics (CCIPD).
Being able to pinpoint which men might have a recurrence or who might die from prostate cancer is vital because it helps providers deliver additional therapy to those men earlier. RadClip can help with these predictions, she said, and it can also identify, on pre-operative MRI, the small heterogeneity and texture pattern differences both inside and outside the tumor area. This way, she added, estimating and predicting post-surgical outcomes is easier.
To accomplish this, RadClip uses AI algorithms to examine MRI scan and molecular data culled from Cleveland Clinic, University Hospitals, and Louis Stokes Cleveland Veterans Administration Medical Center. For this multi-institutional study, Li’s team applied RadClip to pre-operative MRI scans from nearly 200 patients who had undergone radical prostatectomy.
“We’re bringing together and connecting a variety of information, from radiologic scans like MRI to digitized pathology specimen slides and genomic data, for providing a more comprehensive characterization of the disease,” said senior study author Anat Madabhushi, CCIPD director and Donnell Institute biomedical engineering professor at Case Western.
The team, then, compared its results to other predictive strategies, including Cancer of the Prostate Risk Assessment (CAPRA) score and the genomic-based Decipher ® Prostate Cancer Test. Their analysis showed that RadClip gleans superior prognostic information to these tools.
“Genomic-based tests cost several thousand dollars and involve destructive testing of the tissue,” Madabhushi said. “Prognostic predictions from an MRI scan provide a non-invasive method for making both short-term and long-term decisions on treatment.”
The information gathered with RadClip offers several benefits to both prostate surgery and post-operative management, Li said. Surgeons can use the predictive data about cancer existence and extent collected from pre-operative MRI to determine how much tissue to remove, and oncologists can use the estimates of recurrence to target patients who need post-surgical adjuvant treatment, including radiation therapy or chemotherapy.
“Having this information before surgery,” she said, “provides surgeons and oncologists the time and space to adjust treatment plans and come up with a plan that’s best suited to the patient.”
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