FDA Grants Clearance to AI-Powered Prognostic Tool for Breast Cancer Recurrence Risk

SimBioSys®, an AI-driven precision medicine company, has received U.S. Food and Drug Administration (FDA) 510(k) clearance for TumorSight® Risk, an AI-powered, MRI-derived prognostic tool for assessing recurrence risk in women with early-stage breast cancer. This innovative software synthesizes routinely collected breast MRI, pathology, and clinical data to establish individualized prognoses for five and ten years. The tool specifically targets women with hormone receptor-positive (HR+), HER2-negative Stage I–IIIA breast cancer, a category that accounts for around 75% of breast cancer cases in the United States.

Stacey Stevens, President and CEO of SimBioSys, highlighted the significance of this clearance, stating, "For the first time, clinicians can leverage the detailed biological and spatial information from a patient's breast MRI, alongside standard pathology and clinical data, to gain personalized insight into recurrence risk." The ability to provide rapid access to this information within existing clinical workflows is expected to enhance treatment decision-making for both clinicians and patients.

TumorSight Risk utilizes spatial AI modeling to analyze tumor characteristics, the surrounding tissue context, and clinical factors. The software produces a score ranging from zero to 100, along with risk classifications (high-, intermediate-, or low-risk). Notably, it operates within the existing care framework, requiring no additional procedures or specialized hardware.

The tool is intended to serve as a prognostic indicator of recurrence-free survival for adult women diagnosed with HR-positive, HER2-negative Stage I–IIIA breast cancer, and should be used in conjunction with other relevant clinical factors when planning treatment.

The clearance is supported by a comprehensive multicenter validation study involving 2,129 patients from notable institutions including Mayo Clinic, Emory University, Stanford Medicine, and Mercy Medical Cedar Rapids. Preliminary findings reveal that TumorSight Risk successfully stratifies patients according to recurrence-free survival. Patients identified as high risk presented a 3.3-fold increased recurrence risk compared to those classified as low risk. Moreover, each 10-point increase in the score correlated with a 22% increase in relative recurrence risk.

The estimated recurrence risk at five years varied significantly, ranging from 2.2% for patients with the lowest scores to 13.6% for those with the highest. Long-term outcomes at ten years showed recurrence risks from 6.2% to 34.2% across these score groups. Notably, the prognostic score retained significance even after adjusting for standard prognostic indicators.

Dr. Matthew Goetz from Mayo Clinic emphasized the importance of accurately defining recurrence risk for treatment individualization in early-stage, HR-positive breast cancer. He noted that MRI-derived risk assessments can provide valuable prognostic information beyond traditional clinicopathologic factors.

TumorSight Risk is positioned to complement existing assessment methods, particularly for patients historically underrepresented in genomic testing, and aims to facilitate more informed treatment discussions between clinicians and patients regarding options such as chemotherapy and prolonged endocrine therapy.

This development marks a significant advancement in the integration of AI with standard medical imaging, aiming to offer a more personalized approach to breast cancer treatment.