Lina Zhu1, Ge Gao1, Yi Liu1, Chao Han1, Jing Liu1, Xiaodong Zhang1, Xiaoying Wang2. 1. Department of Radiology, Peking University First Hospital, No. 8 Xishiku Street, Xicheng District, Beijing 100034, China. 2. Department of Radiology, Peking University First Hospital, No. 8 Xishiku Street, Xicheng District, Beijing 100034, China. Electronic address: wangxiaoying@bjmu.edu.cn.
Abstract
OBJECTIVES: To evaluate the feasibility of integrating computer-aided diagnosis (CAD) with structured reports of prostate multiparametric MRI (mpMRI). METHODS: This retrospective study enrolled 153 patients who underwent prostate mpMRI for the purpose of targeted biopsy; patients were divided into a group with clinically significant prostate cancer (csPCa, Gleason score ≥ 3 + 4, n = 89) and a group with non-csPCa (n = 64). Ten inexperienced radiologists retrospectively evaluated these cases (single reader per case) twice using structured reports, and they were blinded to the pathologic results. Initially, the readers interpreted mpMRI without CAD. Six weeks later, they evaluated the same cases again with CAD assistance. At each time of image interpretation, lesions detected by the readers were marked on the prostate vector map in structured reports, and a PI-RADS score was given to each lesion. Diagnostic efficacy and reading time were evaluated for the two reading sessions. RESULTS: With the assistance of CAD, the overall diagnostic efficacy was improved, i.e., the AUC increased from 0.83 to 0.89 (p = 0.018). Specifically, per-patient sensitivity (84.3% vs. 93.3%) and per-lesion sensitivity (76.7% vs. 88.8%) were significantly improved (all p < 0.05). Per-patient specificity with CAD (65.6%) was higher than that without CAD (56.3%), but statistical significance was not reached (p = 0.238). The reading time for each case decreased from 10.9 min to 7.8 min (p < 0.001). CONCLUSIONS: It is feasible to integrate CAD with structured reports of prostate mpMRI. This reading paradigm can improve the diagnostic sensitivity of csPCa detection and reduce reading time among inexperienced radiologists.
OBJECTIVES: To evaluate the feasibility of integrating computer-aided diagnosis (CAD) with structured reports of prostate multiparametric MRI (mpMRI). METHODS: This retrospective study enrolled 153 patients who underwent prostate mpMRI for the purpose of targeted biopsy; patients were divided into a group with clinically significant prostate cancer (csPCa, Gleason score ≥ 3 + 4, n = 89) and a group with non-csPCa (n = 64). Ten inexperienced radiologists retrospectively evaluated these cases (single reader per case) twice using structured reports, and they were blinded to the pathologic results. Initially, the readers interpreted mpMRI without CAD. Six weeks later, they evaluated the same cases again with CAD assistance. At each time of image interpretation, lesions detected by the readers were marked on the prostate vector map in structured reports, and a PI-RADS score was given to each lesion. Diagnostic efficacy and reading time were evaluated for the two reading sessions. RESULTS: With the assistance of CAD, the overall diagnostic efficacy was improved, i.e., the AUC increased from 0.83 to 0.89 (p = 0.018). Specifically, per-patient sensitivity (84.3% vs. 93.3%) and per-lesion sensitivity (76.7% vs. 88.8%) were significantly improved (all p < 0.05). Per-patient specificity with CAD (65.6%) was higher than that without CAD (56.3%), but statistical significance was not reached (p = 0.238). The reading time for each case decreased from 10.9 min to 7.8 min (p < 0.001). CONCLUSIONS: It is feasible to integrate CAD with structured reports of prostate mpMRI. This reading paradigm can improve the diagnostic sensitivity of csPCa detection and reduce reading time among inexperienced radiologists.