Computer Extracted Nuclear Features From Tumor And Benign Regions Of Feulgen And H&E Images To Help Predict Recurrence In Prostate Cancer Patients Following Radical Prostatectomy.
JOURNAL OF CLINICAL ONCOLOGY(2017)
摘要
e16556Background: Following radical prostatectomy, around 30% of prostate cancer (PCa) patients experience biochemical recurrence (BCR). Hu0026E highlights nuclear morphology and Feulgen reflects nuclear DNA content, a feature linked to PCa presence and aggressiveness. In this work we sought to explore whether computer extracted measurements of tumor morphology and tumor adjacent benign regions on Hu0026E and Feulgen tissue images could predict BCR. Methods: We used 108 patients (59 BCR and 49 non-recurrence (NR)) and each patient had 242 QH features calculated from both the tumor and benign region of stained TMA core images. Feature selection was performed on a training set (30 BCR, 24 NR) to select the 10 most discriminating tumor and tumor adjacent benign features of each stain. A random forest classifier was trained with features so identified and validated on a test set (29 BCR, 25 NR) to predict BCR. Predictions were displayed using Kaplan-Meier analysis and area under the ROC curve (AUC). Results: The most...
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关键词
prostate cancer,radical prostatectomy,prostate cancer patients,nuclear features
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