Purpose: Compare reader performance when adding the Hybrid Multidimensional-MRI (HM-MRI) map to multiparametric MRI (mpMRI+HM-MRI) versus mpMRI alone and inter-reader agreement in diagnosing clinically significant prostate cancers (CSPCa).
Methods: All 61 patients who underwent mpMRI (T2-, diffusion-weighted (DWI), and contrast-enhanced scans) and HM-MRI (with multiple TE/b-value combinations) before prostatectomy or MRI-fused-transrectal ultrasound-guided biopsy between August, 2012 and February, 2020, were retrospectively analyzed. Two experienced readers (R1, R2) and two less-experienced readers (less than 6-year MRI prostate experience) (R3, R4) interpreted mpMRI without/with HM-MRI in the same sitting. Readers recorded the PI-RADS 3-5 score, lesion location, and change in score after adding HM-MRI. Each radiologist's mpMRI+HM-MRI and mpMRI performance measures (AUC, sensitivity, specificity, PPV, NPV, and accuracy) based on pathology, and Fleiss' kappa inter-reader agreement was calculated and compared.
Results: Per-sextant R3 and R4 mpMRI+HM-MRI accuracy (82% 81% vs. 77%, 71%; p=.006, <.001) and specificity (89%, 88% vs. 84%, 75%; p=.009, <.001) were higher than with mpMRI. Per-patient R4 mpMRI+HM-MRI specificity improved (48% from 7%; p<.001). R1 and R2 mpMRI+HM-MRI specificity per-sextant (80%, 93% vs. 81%, 93%; p=.51,>.99) and per-patient (37%, 41% vs. 48%, 37%; p=.16, .57) remained similar to mpMRI. R1 and R2 per-patient AUC with mpMRI+HM-MRI (0.63, 0.64 vs. 0.67, 0.61; p=.33, .36) remained similar to mpMRI, but R3 and R4 mpMRI+HM-MRI AUC (0.73, 0.62) approached R1 and R2 AUC. Per-patient inter-reader agreement, mpMRI+HM-MRI Fleiss Kappa, was higher than mpMRI (0.36 [95% CI 0.26, 0.46] vs. 0.17 [95% CI 0.07, 0.27]); p=.009).
Conclusion: Adding HM-MRI to mpMRI (mpMRI+HM-MRI) improved specificity and accuracy for less-experienced readers, improving overall inter-reader agreement.
Keywords: Clinically significant prostate cancer (CSPCa); Hybrid multidimensional-MRI (HM-MRI); Multiparametric MRI (mpMRI); Prostate imaging reporting and data system (PI-RADS).
© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.