Evaluation of 3D ARFI imaging of prostate cancer: diagnostic reliability and concordance with MpMRI.

The prevalence of prostate cancer (PCa) necessitates advanced diagnostic approaches for detection and lesion characterization. Utilizing two patient cohorts (n = 85), this study analyzes a custom-designed 3D ultrasonic acoustic radiation force impulse (ARFI) elasticity imaging system alongside an Index of Suspicion (IOS) lesion ranking system to evaluate reader sensitivity, positive predictive values, inter-reader reliability, and ARFI-mpMRI concordance. The IOS system provides standardized criteria for lesion assessment, enabling consistency in stratifying PCa lesion suspicion.Three readers were trained on multiparametric ultrasound (mpUS) (combined ARFI and B-mode) prostate image volumes from 6 patients based on the IOS criteria. The readers then marked suspicious lesions in 79 patients who were retrospectively compared with histopathology-identified (Cohort I, post-radical prostatectomy) or biopsy-confirmed (Cohort II) cancerous regions.The IOS criteria stratified lesions by Gleason grade (GG), with a higher IOS correlating with more aggressive lesions. mpUS imaging was more sensitive for detecting lesions with higher GG and preferentially identified lesions with lower MR apparent-diffusion coefficients and signs of extraprostatic extension. mpUS imaging demonstrated substantial inter-reader reliability and moderate overlap with mpMRI lesions, with increasing sensitivity to higher MRI PI-RADS score lesions. mpUS imaging was less sensitive than mpMRI to lesions with lower GG.The increased sensitivity of mpUS imaging to higher GG lesions and adverse histopathological factors, along with moderate agreement with mpMRI, suggest that mpUS has the potential to guide biopsy targeting of mpMRI-visible lesions or serve as an alternative biopsy-targeting approach when mpMRI is unavailable or clinically contraindicated.

Duke Scholars

Author Kathryn Radabaugh Nightingale Biomedical Engineering

Author Mark L. Palmeri Biomedical Engineering