Comparison of a Deep Learning‐Accelerated vs. Conventional <scp>T2</scp> ‐Weighted Sequence in Biparametric <scp>MRI</scp> of the Prostate
Angela Tong, Barun Bagga, Robert Petrocelli, Paul Smereka, Abhinav Vij, Kun Qian, Robert Grimm, Ali Kamen, Mahesh Keerthivasan, Mahesh Keerthivasan, Dominik Nickel, Heinrich von Busch, Hersh Chandarana
Abstract
BACKGROUND: Demand for prostate MRI is increasing, but scan times remain long even in abbreviated biparametric MRIs (bpMRI). Deep learning can be leveraged to accelerate T2-weighted imaging (T2WI). PURPOSE: To compare conventional bpMRIs (CL-bpMRI) with bpMRIs including a deep learning-accelerated T2WI (DL-bpMRI) in diagnosing prostate cancer. STUDY TYPE: Retrospective. POPULATION: Eighty consecutive men, mean age 66 years (47-84) with suspected prostate cancer or prostate cancer on active surveillance who had a prostate MRI from December 28, 2020 to April 28, 2021 were included. Follow-up included prostate biopsy or stability of prostate-specific antigen (PSA) for 1 year. FIELD STRENGTH AND SEQUENCES: . ASSESSMENT: CL-bpMRI and DL-bpMRI including the same conventional diffusion-weighted imaging (DWI) were presented to three radiologists (blinded to acquisition method) and to a deep learning computer-assisted detection algorithm (DL-CAD). The readers evaluated image quality using a 4-point Likert scale (1 = nondiagnostic, 4 = excellent) and graded lesions using Prostate Imaging Reporting and Data System (PI-RADS) v2.1. DL-CAD identified and assigned lesions of PI-RADS 3 or greater. STATISTICAL TESTS: Quality metrics were compared using Wilcoxon signed rank test, and area under the receiver operating characteristic curve (AUC) were compared using Delong's test. SIGNIFICANCE: P = 0.05. RESULTS: Eighty men were included (age: 66 ± 9 years; 17/80 clinically significant prostate cancer). Overall image quality results by the three readers (CL-T2, DL-T2) are reader 1: 3.72 ± 0.53, 3.89 ± 0.39 (P = 0.99); reader 2: 3.33 ± 0.82, 3.31 ± 0.74 (P = 0.49); reader 3: 3.67 ± 0.63, 3.51 ± 0.62. In the patient-based analysis, the reader results of AUC are (CL-bpMRI, DL-bpMRI): reader 1: 0.77, 0.78 (P = 0.98), reader 2: 0.65, 0.66 (P = 0.99), reader 3: 0.57, 0.60 (P = 0.52). Diagnostic statistics from DL-CAD (CL-bpMRI, DL-bpMRI) are sensitivity (0.71, 0.71, P = 1.00), specificity (0.59, 0.44, P = 0.05), positive predictive value (0.23, 0.24, P = 0.25), negative predictive value (0.88, 0.88, P = 0.48). CONCLUSION: Deep learning-accelerated T2-weighted imaging may potentially be used to decrease acquisition time for bpMRI. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.