Evaluation of A Computer-Aided Detection Software for Prostate Cancer Prediction: Excellent Diagnostic Accuracy Independent of Preanalytical Factors.

Jennifer Vazzano¹, Dorota Johansson², Kun Hu³, Kristian Eurén², Stefan Elfwing², Anil Parwani⁴, Ming Zhou⁵

¹Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, Ohio.

²Inify Laboratories AB, Stockholm, Sweden (previously part of ContextVision).

³Department of Pathology, Tufts Medical Center, Tufts University School of Medicine, Boston, Massachusetts.

⁴Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, Ohio. Electronic address: anil.parwani@osumc.edu.

⁵Department of Pathology, Tufts Medical Center, Tufts University School of Medicine, Boston, Massachusetts. Electronic address: ming.zhou@tuftsmedicine.org.

PubMed DOI

Abstract

Prostate cancer (PCa) is the most common noncutaneous cancer in men in the Western world. In addition to accurate diagnosis, Gleason grading and tumor volume estimates are critical for patient management. Computer-aided detection (CADe) software can be used to facilitate the diagnosis and improve the diagnostic accuracy and reporting consistency. However, preanalytical factors such as fixation and…

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