Characterization of prostate lesions as benign or malignant at multiparametric MR imaging: comparison of three scoring systems in patients treated with radical prostatectomy

Abstract

Purpose: To compare the subjective Likert score to the Prostate Imaging Reporting and Data System (PIRADS) and morphology-location-signal intensity (MLS) scores for categorization of prostate lesions as benign or malignant at multiparametric magnetic resonance (MR) imaging.

Materials and methods: Two hundred fifteen patients who underwent T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced multiparametric MR imaging of the prostate before radical prostatectomy were included in a prospective database after they signed the institutional review board-approved forms. Senior readers 1 and 2 prospectively noted the location, shape, and signal intensity of lesions on MR images from individual pulse sequences and scored each for likelihood of malignancy by using a Likert scale (range, 1-5). A junior reader (reader 3) retrospectively reviewed the database and did the same analysis. The MLS score (range, 1-13) was computed by using the readers' descriptions of the lesions. Then, the three readers again scored the lesions they described by using the PIRADS score (range, 3-15). MLS and PIRADS scores were compared with the Likert score by using their areas under the receiver operating characteristic curves.

Results: Areas under the receiver operating characteristic curves of the Likert, MLS, and PIRADS scores were 0.81, 0.77 (P = .03), and 0.75 (P = .01) for reader 1; 0.88, 0.74 (P < .0001), and 0.76 (P < .0001) for reader 2; and 0.81, 0.78 (P = .23), and 0.75 (P = .01) for reader 3. For diagnosing cancers with Gleason scores greater than or equal to 7, the Likert score was significantly more accurate than the others, except for the MLS score for reader 3. Weighted κ values were 0.470-0.524, 0.405-0.430, and 0.378-0.441 for the Likert, MLS, and PIRADS scores, respectively.

Conclusion: The Likert score allowed significantly more accurate categorization of prostate lesions on MR images than did the MLS and PIRADS scores.