Vol. 44 (5): 882-891, September – October, 2018

doi: 10.1590/S1677-5538.IBJU.2018.0038


ORIGINAL ARTICLE

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

ABSTRACT

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

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