Is possible to rule out clinically significant prostate cancer using PI-RADS v2 for the assessment of prostate MRI?
Int. braz. j. urol; 45 (4), 2019
Publication year: 2019
ABSTRACT Objectives To evaluate the diagnostic performance and interobserver agreement of PI-RADS v2. Materials and Methods In this Institutional Review Board approved single-center retrospective study, 98 patients with clinically suspected PCa who underwent 3-T multiparametric MRI followed by MRI/TRUS fusion-guided prostate biopsy were included from June 2013 to February 2015. Two radiologists (R1 and R2) with 8 and 1 years of experience in abdominal radiology reviewed the MRI scans and assigned PI-RADS v2 scores in all prostate zones. PI-RADS v2 were compared to MRI/TRUS fusion-guided biopsy results, which were classified as negative, PCa, and significant PCa (sPCa). Results Sensitivity, specificity, NPV, PPV and accuracy for PCa was 85.7% (same for all metrics) for R1 and 81.6%, 79.6%, 81.2%, 80.0% and 80.6% for R2. For detecting sPCa, the corresponding values were 95.3%, 85.4%, 95.9%, 83.7% and 89.8% for R1 and 93.0%, 81.8%, 93.7%, 86.7% and 86.7% for R2. There was substantial interobserver agreement in assigning PI-RADS v2 score as negative (1, 2, 3) or positive (4, 5) (Kappa=0.78). On multivariate analysis, PI-RADS v2 (p <0.001) was the only independent predictor of sPCa compared with age, abnormal DRE, prostate volume, PSA and PSA density. Conclusions Our study population demonstrated that PI-RADS v2 had high diagnostic accuracy, substantial interobserver agreement, and it was the only independent predictor of sPCa.
Brasil, Biopsia Guiada por Imagen/métodos, Modelos Logísticos, Imagen por Resonancia Magnética/métodos, Persona de Mediana Edad, Clasificación del Tumor, Variaciones Dependientes del Observador, Antígeno Prostático Específico/sangre, Neoplasias de la Próstata/diagnóstico por imagen, Neoplasias de la Próstata/patología, Valores de Referencia, Reproducibilidad de los Resultados, Estudios Retrospectivos, Medición de Riesgo, Factores de Riesgo, Sensibilidad y Especificidad, Estadísticas no Paramétricas