Vol. 44 (5): 882-891, September – October, 2018
Thais Caldara Mussi 1, Tatiana Martins 1, 2, Adriano Tachibana 1, Pedro Nogueira Mousessian 1, Ronaldo Hueb Baroni 1
1 Hospital Israelita Albert Einstein, São Paulo, SP, Brasil and 2 Ecoar Medicina Diagnostica, Belo Horizonte, MG, Brasil
Purpose: To identify objective and subjective criteria on multiparametric prostate MRI that can be helpful for prostate cancer detection.
Materials and Methods: Retrospective study, IRB approved, including 122 patients who had suspicious lesion on MRI and who underwent prostate biopsy with ultrasonography (US)/MRI imaging fusion. There were 60 patients with positive biopsies and 62 with negative biopsies. MRI of these patients were randomized and evaluated independently by two blinded radiologists. The following variables were analyzed in each lesion: morphology, contours, T2 signal, diffusion restriction (subjective impression and objective values), hyper-enhancement, contact with transition zone or prostatic contour, prostatic contour retraction, Likert and PIRADS classification.
Results: Apparent diffusion coefficient (ADC) value was the best predictor of positivity for prostate cancer, with mean value of 1.08 (SD 0.20) and 1.09 mm2/sec (SD 0.24) on negative biopsies and 0.81 (SD 0.22) and 0.84 mm2/sec (SD 0.22) on positive biopsies for readers 1 and 2, respectively (p < 0.001 in both analysis). For the others categorical variables evaluated the best AUC for reader 1 was subjective intensity of diffusion restriction (AUC of 0.74) and for reader 2 was hyper-enhancement (AUC of 0.65), all inferior comparing to the value of ADC map. Interobserver agreement ranged from 0.13 to 0.75, poor in most measurements, and good or excellent (kappa > 0.6) only in lesion size and ADC values.
Conclusions: Diffusion restriction with lower ADC-values is the best parameter to predict cancer on MRI prior to biopsy. Efforts to establish an ADC cutoff value would improve cancer detection, especially for less experience reader.
Keywords: Magnetic Resonance Imaging; Prostatic Neoplasms; Prostate