High-resolution prostate diffusion MRI using eddy current-nulled convex optimized diffusion encoding and random matrix theory-based denoising

• Published in: Magma (New York, N.Y.) Vol. 37; no. 4; pp. 603 - 619
• Main Authors: Zhang, Zhaohuan, Aygun, Elif, Shih, Shu-Fu, Raman, Steven S., Sung, Kyunghyun, Wu, Holden H.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.08.2024
• Subjects: Aged; Algorithms; Basic Science - Diffusion; Biomedical Engineering and Bioengineering; Computer Appl. in Life Sciences; Diffusion Magnetic Resonance Imaging - methods; Health Informatics; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image Processing, Computer-Assisted - methods; Imaging; Male; Medicine; Medicine & Public Health; Middle Aged; Principal Component Analysis; Prostate - diagnostic imaging; Prostatic Neoplasms - diagnostic imaging; Radiology; Reproducibility of Results; Research Article; Retrospective Studies; Signal-To-Noise Ratio; Solid State Physics; Diffusion MRI; Random matrix theory; Prostate; High-resolution diffusion MRI; Denoising
• ISSN: 1352-8661; 0968-5243; 1352-8661
• DOI: 10.1007/s10334-024-01147-w

Objective To develop and evaluate a technique combining eddy current-nulled convex optimized diffusion encoding (ENCODE) with random matrix theory (RMT)-based denoising to accelerate and improve the apparent signal-to-noise ratio (aSNR) and apparent diffusion coefficient (ADC) mapping in high-resolution prostate diffusion-weighted MRI (DWI). Materials and methods Eleven subjects with clinical suspicion of prostate cancer were scanned at 3T with high-resolution (HR) (in-plane: 1.0 × 1.0 mm 2 ) ENCODE and standard-resolution (1.6 × 2.2 mm 2 ) bipolar DWI sequences (both had 7 repetitions for averaging, acquisition time [TA] of 5 min 50 s). HR-ENCODE was retrospectively analyzed using three repetitions (accelerated effective TA of 2 min 30 s). The RMT-based denoising pipeline utilized complex DWI signals and Marchenko–Pastur distribution-based principal component analysis to remove additive Gaussian noise in images from multiple coils, b-values, diffusion encoding directions, and repetitions. HR-ENCODE with RMT-based denoising (HR-ENCODE-RMT) was compared with HR-ENCODE in terms of aSNR in prostate peripheral zone (PZ) and transition zone (TZ). Precision and accuracy of ADC were evaluated by the coefficient of variation (CoV) between repeated measurements and mean difference (MD) compared to the bipolar ADC reference, respectively. Differences were compared using two-sided Wilcoxon signed-rank tests ( P  < 0.05 considered significant). Results HR-ENCODE-RMT yielded 62% and 56% higher median aSNR than HR-ENCODE ( b =  800 s/mm 2 ) in PZ and TZ, respectively ( P  < 0.001). HR-ENCODE-RMT achieved 63% and 70% lower ADC-CoV than HR-ENCODE in PZ and TZ, respectively ( P  < 0.001). HR-ENCODE-RMT ADC and bipolar ADC had low MD of 22.7 × 10 –6 mm 2 /s in PZ and low MD of 90.5 × 10 –6 mm 2 /s in TZ. Conclusions HR-ENCODE-RMT can shorten the acquisition time and improve the aSNR of high-resolution prostate DWI and achieve accurate and precise ADC measurements in the prostate.