Radiology advances · 2026
Improved prostate diffusion imaging using deep learning denoising and phase correction with ultra-high-density coil array.
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Huang Sherry S, Wang Xinzeng, Lan Patricia, Medved Milica, Kaya Nurullah, Follante Clyve K, Stickle Yunjeong, Taylor Jonathan, Yousuf Ambereen, Engelmann Roger, Robb Fraser J L, Guidon Arnaud, Lee Grace, Oto Aytekin
Аннотация
BACKGROUND: MR diffusion-weighted imaging (DWI), especially at high b-value, is a key acquisition to help identify clinically significant prostate cancer; however, it suffers from low signal-to-noise ratio (SNR), high noise floor, and susceptibility artifact.
PURPOSE: To demonstrate the feasibility of improving DWI quality using a novel 50-channel pelvic coil in conjunction with a deep learning (DL)-based phase correction and a DL-denoising algorithm.
METHODS: In this prospective, single-center study, 24 consecutive men referred for prostate multiparametric MRI over 16 months were enrolled (age 47-79 years; mean, 68.1 years). Axial T2-weighted images and DWI were obtained using a prototype 50‑channel coil and standard clinical phased array (3 T Architect, GE HealthCare, USA). The DWI acquisitions were reconstructed with the vendor's deep learning denoising algorithm (ARDL). The same raw data were reconstructed offline using an investigational DL Phase Correction algorithm with ARDL (DLPC+ARDL). Two independent readers scored DWI and ADC series using 4 qualitative criteria. SNR and contrast-to-noise ratio (CNR) were measured on b = 1500 s/mm2 images. Combined reader scores were compared using the Wilcoxon matched‑pairs signed‑rank test, inter‑reader variability was assessed using Cohen's κ, and quantitative SNR/CNR values were compared using 2‑tailed paired t‑tests.
RESULTS: Twenty men were analyzable for qualitative and 18 for quantitative metrics (reported as mean ± SD). 50‑channel pelvic coil with DLPC+ARDL produced the highest SNR (99.70 ± 28.50) and CNR (91.68 ± 44.39), exceeding 50‑channel with ARDL alone (SNR 56.44 ± 28.50; CNR 51.11 ± 28.67), 30‑channel anterior array with ARDL (SNR 31.41 ± 13.18; CNR 26.26 ± 13.52), and DLPC + ARDL (SNR 49.4 ± 18.6; CNR 44.7 ± 18.3) (all P < .0001). Reader scores favored DLPC+ARDL in prostate border definition, peripheral/transition zone distinction, lesion conspicuity, and confidence of extraprostatic extension (all P values for DWI at b = 1500 s/mm2 < 0.0001; synthetic DWI at b = 2000 s/mm2: P = 7.5 × 10-7-0.01). Inter‑reader agreement was fair for acquired DWI (quadratic‑weighted κ = 0.34) and lower for synthetic DWI (κ = 0.19).
CONCLUSION: DWI images acquired using the 50‑channel pelvic coil and reconstructed with the DLPC + ARDL pipeline yield the highest image quality compared to ARDL only pipeline and to all 30-channel coil imaging.
PURPOSE: To demonstrate the feasibility of improving DWI quality using a novel 50-channel pelvic coil in conjunction with a deep learning (DL)-based phase correction and a DL-denoising algorithm.
METHODS: In this prospective, single-center study, 24 consecutive men referred for prostate multiparametric MRI over 16 months were enrolled (age 47-79 years; mean, 68.1 years). Axial T2-weighted images and DWI were obtained using a prototype 50‑channel coil and standard clinical phased array (3 T Architect, GE HealthCare, USA). The DWI acquisitions were reconstructed with the vendor's deep learning denoising algorithm (ARDL). The same raw data were reconstructed offline using an investigational DL Phase Correction algorithm with ARDL (DLPC+ARDL). Two independent readers scored DWI and ADC series using 4 qualitative criteria. SNR and contrast-to-noise ratio (CNR) were measured on b = 1500 s/mm2 images. Combined reader scores were compared using the Wilcoxon matched‑pairs signed‑rank test, inter‑reader variability was assessed using Cohen's κ, and quantitative SNR/CNR values were compared using 2‑tailed paired t‑tests.
RESULTS: Twenty men were analyzable for qualitative and 18 for quantitative metrics (reported as mean ± SD). 50‑channel pelvic coil with DLPC+ARDL produced the highest SNR (99.70 ± 28.50) and CNR (91.68 ± 44.39), exceeding 50‑channel with ARDL alone (SNR 56.44 ± 28.50; CNR 51.11 ± 28.67), 30‑channel anterior array with ARDL (SNR 31.41 ± 13.18; CNR 26.26 ± 13.52), and DLPC + ARDL (SNR 49.4 ± 18.6; CNR 44.7 ± 18.3) (all P < .0001). Reader scores favored DLPC+ARDL in prostate border definition, peripheral/transition zone distinction, lesion conspicuity, and confidence of extraprostatic extension (all P values for DWI at b = 1500 s/mm2 < 0.0001; synthetic DWI at b = 2000 s/mm2: P = 7.5 × 10-7-0.01). Inter‑reader agreement was fair for acquired DWI (quadratic‑weighted κ = 0.34) and lower for synthetic DWI (κ = 0.19).
CONCLUSION: DWI images acquired using the 50‑channel pelvic coil and reconstructed with the DLPC + ARDL pipeline yield the highest image quality compared to ARDL only pipeline and to all 30-channel coil imaging.