Stratified assessment of an FDA-cleared deep learning algorithm for automated detection and contouring of metastatic brain tumors in stereotactic radiosurgery.

Jen-Yeu Wang¹, Vera Qu¹, Caressa Hui¹, Navjot Sandhu¹, Maria G Mendoza¹, Neil Panjwani¹, Yu-Cheng Chang², Chih-Hung Liang², Jen-Tang Lu², Lei Wang¹, Nataliya Kovalchuk¹, Michael F Gensheimer¹, Scott G Soltys¹, Erqi L Pollom³

¹Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, CA, 94305, USA.

²Vysioneer Inc, Cambridge, MA, USA.

³Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, CA, 94305, USA. erqiliu@stanford.edu.

PubMed PMC DOI PDF

Abstract

PURPOSE: Artificial intelligence-based tools can be leveraged to improve detection and segmentation of brain metastases for stereotactic radiosurgery (SRS). VBrain by Vysioneer Inc. is a deep learning algorithm with recent FDA clearance to assist in brain tumor contouring. We aimed to assess the performance of this tool by various demographic and clinical characteristics among patients with brain…

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