Study shows AI-assisted cancer contours reduce underestimation of prostate cancer extent, significantly improving contouring accuracy

[Graham49]

This study showed that AI-assisted cancer contours reduce underestimation of prostate cancer extent, improving contouring accuracy and negative margin rate achieved by physicians.

Artificial Intelligence Improves the Ability of Physicians to Identify Prostate Cancer Extent

Sakina Mohammed Mota , Alan Priester , Joshua Shubert , Jeremy Bong , James Sayre , Brittany Berry-Pusey , Wayne G. Brisbane , and Shyam Natarajan

doi.org/10.1097/JU.00000000...

Abstract

Purpose:

“Defining prostate cancer contours is a complex task, undermining the efficacy of interventions such as focal therapy. A multireader multicase study compared physicians’ performance using artificial intelligence (AI) vs standard-of-care methods for tumor delineation.”

Materials and Methods:

“Cases were interpreted by 7 urologists and 3 radiologists from 5 institutions with 2 to 23 years of experience. Each reader evaluated 50 prostatectomy cases retrospectively eligible for focal therapy. Each case included a T2-weighted MRI, contours of the prostate and region(s) of interest suspicious for cancer, and a biopsy report. First, readers defined cancer contours cognitively, manually delineating tumor boundaries to encapsulate all clinically significant disease. Then, after ≥ 4 weeks, readers contoured the same cases using AI software. Using tumor boundaries on whole-mount histopathology slides as ground truth, AI-assisted, cognitively-defined, and hemigland cancer contours were evaluated. Primary outcome measures were the accuracy and negative margin rate of cancer contours. All statistical analyses were performed using generalized estimating equations.”

Results:

“The balanced accuracy (mean of voxel-wise sensitivity and specificity) of AI-assisted cancer contours (84.7%) was superior to cognitively-defined (67.2%) and hemigland contours (75.9%; P < .0001). Cognitively-defined cancer contours systematically underestimated cancer extent, with a negative margin rate of 1.6% compared to 72.8% for AI-assisted cancer contours (P < .0001).”

Conclusions:

“AI-assisted cancer contours reduce underestimation of prostate cancer extent, significantly improving contouring accuracy and negative margin rate achieved by physicians. This technology can potentially improve outcomes, as accurate contouring informs patient management strategy and underpins the oncologic efficacy of treatment.”

“For patients with intermediate-risk prostate cancer (PCa), focal therapy (FT) is gaining acceptance as an alternative to prostatectomy and radiation therapy.1 Evidence is growing that FT can eradicate PCa while preserving patient quality of life.2-7 However, successful FT requires accurate contouring of cancer extent. Unfortunately, conventional cancer contouring requires surgeons to cognitively merge imaging, pathology, and clinical factors. In particular, the interpretation of MRI systematically underestimates cancer extent—sometimes severely.8-10 Patient-specific, reproducible assessment of cancer extent is a pressing and unaddressed need.”