Keywords: Prostate, Body
Motivation: The motivation of this study is to develop novel methods for mapping non-invasively the underlying history-morphometric features of prostate cancer.
Goal(s): The goal of this study is to develop and demonstrate radio-pathomic mapping techniques to enable noninvasive detection of prostate cancer presence and distinction from benign tissue using MRI.
Approach: Our approach was to align multiparametric MRI with digitized histology slides from prostatectomy specimens, then predict quantitative histological features from MRI intensities, and use these predicted features to classify cancer versus noncancer regions.
Results: Our models can distinguish cancerous from noncancerous prostate tissue with 70% accuracy.
Impact: This study uses radio-pathomic mapping for noninvasive prostate cancer detection, demonstrating the potential to differentiate cancerous vs benign prostate tissue using imaging surrogates of microstructural features discernible only on histology.
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