SimBioSys Highlights Clinical Data Demonstrating AI Digital Twin Performance Comparable to Radiologists at 43rd Annual Miami Breast Cancer Conference®

New evidence underscores TumorSight^® Viz’s ability to deliver reproducible landmark identification and measurement for early-stage breast cancer surgical planning

CHICAGO, March 5, 2026 /PRNewswire/ — SimBioSys^®, an AI-driven precision medicine company revolutionizing how cancer is understood and treated, today announced that compelling clinical data from its multi-institutional study has been selected for presentation at the Miami Breast Cancer Conference (MBCC), being held March 5–8, 2026 in Miami, FL.

The abstract, titled “An AI Digital Twin Compares Favorably to Radiologists for Landmark Identification and Measurement in Early-Stage Breast Cancer: A Retrospective, Multi-Institution Clinical Study,” will be presented as Poster #040 on Thursday, March 5, 2026. The study evaluates the accuracy of TumorSight^® Viz (v1.3), an AI-driven digital twin platform that generates patient-specific 3D representations from standard breast MRI to support anatomical assessment and surgical strategy.

“This body of clinical evidence represents an important milestone in validating how AI-generated digital twins can deliver reproducible and radiologist-comparable insight into tumor anatomy,” said Stacey Stevens, President and CEO of SimBioSys. “These findings underscore our commitment to advancing tools that support greater precision, consistency, and confidence in preoperative assessment — ultimately helping multidisciplinary teams make more informed decisions in breast cancer care.”

Key outcomes from the retrospective multi-institution analysis include:

AI performance comparable to expert radiologists — TumorSight Viz’s disease measurements fell within inter-reader variability for US-board certified, fellowship-trained breast radiologists.
High spatial concordance — TumorSight Viz achieved a 0.92 surface Dice score, indicating strong agreement between the AI’s tumor delineation and measurements confirmed by expert radiologists.
Consistent results across imaging environments — Performance remained stable regardless of MRI system manufacturer, field strength, tumor subtype, or clinical site.
Rapid quantitative output — TumorSight Viz produced landmark features and measurements in minutes per case following MRI upload.

These results highlight the potential for AI-enabled digital twin technology to provide objective, anatomy-specific insights that complement expert clinical interpretation — a critical need in surgical planning for early-stage breast cancer.

“Accurate visualization and quantitation of tumor extent are fundamental to surgical decision-making. Technologies that can reliably mirror radiologist assessments have the potential to improve clarity, reproducibility, and communication across care teams,” added Barry Rosen, MD, FACS, Breast Surgical Oncologist and Chief Medical Officer of SimBioSys.

This study adds to a growing portfolio of clinical evidence supporting the utility of AI-driven quantitative imaging tools — reinforcing SimBioSys’ mission to accelerate adoption of data-driven decision support across breast cancer care.

About SimBioSys
SimBioSys is an AI-driven precision medicine company revolutionizing how cancer is understood and treated. By converting standard medical imaging into AI-powered, decision-driving intelligence, SimBioSys empowers clinicians with clear, contextual, and actionable insights to individualize care. Its FDA-cleared TumorSight^® Viz platform and in-development TumorSight^® Risk solution combine AI and spatial biophysics to deliver greater confidence, precision, and personalization in cancer treatment. For more information, visit www.simbiosys.com.

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