Performance of an AI-powered visualization software platform for precision surgery in breast cancer patients.

Michelle Weitz¹, J R Pfeiffer¹, Snehal Patel¹, Matthew Biancalana¹, Arda Pekis¹, Vignesh Kannan¹, Evandros Kaklamanos¹, Amanda Parker¹, Jesse E Bucksot¹, José Rubio Romera¹, Ryan Alvin¹, Yuhan Zhang¹, Andrew T Stefka¹, Dorys Lopez-Ramos¹, Joseph R Peterson¹, Anuja K Antony¹, Kathryn W Zamora², Stefanie Woodard³

¹SimBioSys, Inc., Chicago, IL, USA.

²Department of Radiology, University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA.

³Department of Radiology, University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA. swoodard@uabmc.edu.

PubMed PMC DOI PDF

Abstract

Surgery remains the primary treatment modality in the management of early-stage invasive breast cancer. Artificial intelligence (AI)-powered visualization platforms offer the compelling potential to aid surgeons in evaluating the tumor's location and morphology within the breast and accordingly optimize their surgical approach. We sought to validate an AI platform that employs dynamic contrast-enh…

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