Avenda Health has announced new study results showing its cancer mapping tool, Unfold AI, predicts prostate cancer spread more accurately than MRI. The study was led by Stanford and UCLA researchers. Unfold AI is the first and only FDA-approved AI-based prostate cancer decision support program.
The pilot study, titled “Prediction of Seminal Vesicle Invasion Using Artificial Intelligence Prostate Cancer Risk Mapping,” was presented at the American Urological Association’s 2025 Annual Meeting.
“We are on the road to predicting all stages of the disease,” Avenda CEO and co-founder, Shyam Natarajan, PhD, told Inside Precision Medicine.
About one in eight men in the United States alone are estimated to develop prostate cancer each year. Among the men who are treated, 20–30% experience a recurrence. Researchers are just starting to understand the key anatomical features around the prostate that need to be included in any screen to prevent recurrence.
This study showed Unfold AI significantly improves the prediction of seminal vesicle invasion (SVI), a critical factor in prostate cancer staging and prognosis, achieving a 92% accuracy rate, compared to 52% with radiologist interpretation on standard MRI.
This data builds on a previous study that examined Unfold AI’s ability to predict extracapsular extension risk. Together, these studies demonstrate the role of Unfold AI in predicting the spread of prostate cancer to other organs, improving physicians’ ability to accurately diagnose and plan treatment for patients.
Determining if prostate cancer has spread into other nearby structures, like the seminal vesicles, is critical for accurate staging and effective treatment planning, particularly for surgery and radiation. Traditional methods like MRI are largely unreliable and inaccurate, which leads to frequent misdiagnosis of SVI with MRI alone.
Researchers from Stanford University School of Medicine and UCLA’s David Geffen School of Medicine conducted a preliminary study of two cohorts of men, all of whom received MRI scans before undergoing prostate cancer surgery.
They compared physicians’ predictions of SVI based on MRI alone to predictions made by Unfold AI, which combines MRI and clinical data to create a 3D cancer map. After surgery, the team analyzed prostate specimens for SVI to evaluate the accuracy of both methods.
In the first cohort, pathology confirmed SVI in 25 of 147 patients. Unfold AI accurately identified 92% of these cases, while physicians using MRI identified 52%. The second cohort included 20 patients, 10 of whom had SVI. MRI missed four of the 10 cases, while Unfold AI missed only two. Unfold AI also produced fewer false positive rates compared to MRI in both the first and second cohorts.
“These results demonstrate how Unfold AI continues to improve the diagnosis and staging of prostate cancer, enabling the physician to recommend and deliver the best therapy to the patient,” said Natarajan.
