MP03-11 INSTITUTIONAL LEARNING CURVE ASSOCIATED WITH IMPLEMENTATION OF A MR/US FUSION BIOPSY PROGRAM USING PIRADS VERSION 2: FACTORS THAT INFLUENCE SUCCESS
| Autor: | Eric Weinberg, Thomas Frye, Marianne Borch, Gary Hollenberg, Hani Rashid, Edward M. Messing, Jean V. Joseph, Changyong Feng, Guan Wu, Ji Hae Park, Jacob Gantz, Matthew Truong, Ahmed Ghazi |
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| Rok vydání: | 2017 |
| Předmět: |
medicine.medical_specialty
Pathology medicine.diagnostic_test Index Lesion business.industry Urology 030232 urology & nephrology Cancer Magnetic resonance imaging medicine.disease Logistic regression 03 medical and health sciences Prostate cancer 0302 clinical medicine medicine.anatomical_structure Prostate 030220 oncology & carcinogenesis Biopsy Institutional learning medicine Radiology business |
| Zdroj: | Journal of Urology. 197 |
| ISSN: | 1527-3792 0022-5347 |
| DOI: | 10.1016/j.juro.2017.02.128 |
| Popis: | Background The purpose of this study is to assess the institutional learning curve associated with adopting FB using PI-RADS Version 2 (v2) for detecting clinically significant prostate cancer (csPCa), defined as Gleason ≥ 7 in men with prior negative biopsies and to identify patient and technical factors that predict success at detecting csPCa. Methods A total of 113 consecutive patients with at least one prior negative biopsy and a multiparametric MRI (mpMRI) exam of the prostate with a PIRADS 3 or greater index lesion underwent FB at a single academic center previously naive to FB technology. Outcomes are detection rates for Gleason 6 cancer, csPCa, and any cancer. Multiple logistic regression with model selection was used to select covariates having significant effects on the outcome. Results Prostate cancers were identified in 52% of cases in patients with prior negative prostate biopsies. Among patients diagnosed with prostate cancer, 80% were clinically significant. The detection rates of csPCa using FB when a PIRADS 3, 4, or 5 index lesion was present on mpMRI were 6%, 46%, and 66%, respectively. PI-RADS v2 score had a predictive accuracy (AUC) of 0.79 for csPCa detection. Institutional experience over time, MRI-estimated prostate volume, and PI-RADS v2 score were independent predictors of csPCa using FB. Conclusions Since FB is a highly technique-driven process, development of internal quality measures to assess the institutional learning curve and the quality of PI-RADS v2 scoring is critical with adoption of this technology. |
| Databáze: | OpenAIRE |
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