Julie Y An1, Stephanie A Harmon2, Sherif Mehralivand3,4,5, Marcin Czarniecki3, Clayton P Smith3, Julie A Peretti1, Bradford J Wood1, Peter A Pinto4, Peter L Choyke3, Joanna H Shih6, Baris Turkbey7. 1. Center for Interventional Oncology, NIH Clinical Center, National Institutes of Health, 10 Center Drive, Bethesda, MD, USA. 2. Clinical Research Directorate/Clinical Monitoring Research Program, Leidos Biomedical Research, Inc, NCI Campus at Frederick, 1050 Boyle Street, Frederick, MD, USA. 3. Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Drive, Room B3B85, Bethesda, MD, 20892, USA. 4. Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD, USA. 5. Department of Urology and Pediatric Urology, University Medical Center, Mainz, Germany. 6. Biometric Research Program, National Cancer Institute, National Institutes of Health, 6130 Executive Plaza, Rockville, MD, USA. 7. Molecular Imaging Program, National Cancer Institute, National Institutes of Health, 10 Center Drive, Room B3B85, Bethesda, MD, 20892, USA. turkbeyi@mail.nih.gov.
Abstract
PURPOSE: The purpose of the study was to determine if the ≥ 15 mm threshold currently used to define PIRADS 5 lesions is the optimal size threshold for predicting high likelihood of clinically significant (CS) cancers. MATERIALS: Three hundred and fifty-eight lesions that may be changed from category 4 to 5 or vice versa on the basis of the size criterion (category 4: n = 288, category 5: n = 70) from 255 patients were evaluated. Kendall's tau-b statistic accounting for inter-lesion correlation, generalized estimation equation logistic regression, and receiver operating curve analysis evaluated two lesion size-metrics (lesion diameter and relative lesion diameter-defined as lesion diameter/prostate volume) for ability to identify CS (Gleason grade ≥ 3 + 4) cancer at targeted biopsy. Optimal cut-points were identified using the Youden index. Analyses were performed for the whole prostate (WP) and zone-specific sub-cohorts of lesions in the peripheral and transition zones (PZ and TZ). RESULTS: Lesion diameter showed a modest correlation with Gleason grade (WP: τB = 0.21, p < 0.0001; PZ: τB = 0.13, p = 0.02; TZ: τB = 0.32, p = 0.001), and association with CS cancer detection (WP: AUC = 0.63, PZ: AUC = 0.59, TZ: AUC = 0.74). Empirically derived thresholds (WP: 14 mm, PZ: 13 mm, TZ: 16 mm) performed similarly to the current ≥ 15 mm standard. Lesion relative lesion diameter improved identification of CS cancers compared to lesion diameter alone (WP: τB = 0.30, PZ: τB = 0.24, TZ: τB = 0.42, all p < 0.0001). AUC also improved for WP and PZ lesions (WP: AUC = 0.70, PZ: AUC = 0.68, and TZ: AUC = 0.74). CONCLUSIONS: The current ≥ 15 mm diameter threshold is a reasonable delineator of PI-RADS category 4 and category 5 lesions in the absence of extraprostatic extension to predict CS cancers. Additionally, relative lesion diameter can improve identification of CS cancers and may serve as another option for distinguishing category 4 and 5 lesions.
PURPOSE: The purpose of the study was to determine if the ≥ 15 mm threshold currently used to define PIRADS 5 lesions is the optimal size threshold for predicting high likelihood of clinically significant (CS) cancers. MATERIALS: Three hundred and fifty-eight lesions that may be changed from category 4 to 5 or vice versa on the basis of the size criterion (category 4: n = 288, category 5: n = 70) from 255 patients were evaluated. Kendall's tau-b statistic accounting for inter-lesion correlation, generalized estimation equation logistic regression, and receiver operating curve analysis evaluated two lesion size-metrics (lesion diameter and relative lesion diameter-defined as lesion diameter/prostate volume) for ability to identify CS (Gleason grade ≥ 3 + 4) cancer at targeted biopsy. Optimal cut-points were identified using the Youden index. Analyses were performed for the whole prostate (WP) and zone-specific sub-cohorts of lesions in the peripheral and transition zones (PZ and TZ). RESULTS: Lesion diameter showed a modest correlation with Gleason grade (WP: τB = 0.21, p < 0.0001; PZ: τB = 0.13, p = 0.02; TZ: τB = 0.32, p = 0.001), and association with CS cancer detection (WP: AUC = 0.63, PZ: AUC = 0.59, TZ: AUC = 0.74). Empirically derived thresholds (WP: 14 mm, PZ: 13 mm, TZ: 16 mm) performed similarly to the current ≥ 15 mm standard. Lesion relative lesion diameter improved identification of CS cancers compared to lesion diameter alone (WP: τB = 0.30, PZ: τB = 0.24, TZ: τB = 0.42, all p < 0.0001). AUC also improved for WP and PZ lesions (WP: AUC = 0.70, PZ: AUC = 0.68, and TZ: AUC = 0.74). CONCLUSIONS: The current ≥ 15 mm diameter threshold is a reasonable delineator of PI-RADS category 4 and category 5 lesions in the absence of extraprostatic extension to predict CS cancers. Additionally, relative lesion diameter can improve identification of CS cancers and may serve as another option for distinguishing category 4 and 5 lesions.
Entities:
Keywords:
Biopsy; Multi-parametric MRI; PI-RADS version 2; PSA; Prostate cancer; Prostate imaging reporting and data system
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