Usefulness of Breath-Hold Fat-Suppressed T2-Weighted Images With Deep Learning–Based Reconstruction of the Liver

Abstract

Objectives: The aim of this study was to evaluate the usefulness of breath-hold turbo spin echo with deep learning-based reconstruction (BH-DL-TSE) in acquiring fat-suppressed T2-weighted images (FS-T2WI) of the liver by comparing this method with conventional free-breathing turbo spin echo (FB-TSE) and breath-hold half Fourier single-shot turbo spin echo with deep learning-based reconstruction (BH-DL-HASTE). Materials and Methods: The study cohort comprised 111 patients with suspected liver disease who underwent 3 T magnetic resonance imaging. Fifty-eight focal solid liver lesions ≥10 mm were also evaluated. Three sets of FS-T2WI were acquired using FB-TSE, prototypical BH-DL-TSE, and prototypical BH-DL-HASTE, respectively. In the qualitative analysis, 2 radiologists evaluated the image quality using a 5-point scale. In the quantitative analysis, we calculated the lesionto-liver signal intensity ratio (LEL-SIR). Friedman test and Dunn multiple comparison test were performed to assess differences among 3 types of FS-T2WI with respect to image quality and LEL-SIR. Results: The mean acquisition time was 4 minutes and 43 seconds ± 1 minute and 21 seconds (95% confidence interval, 4 minutes and 28 seconds to 4 minutes and 58 seconds) for FB-TSE, 40 seconds for BH-DL-TSE, and 20 seconds for BH-DL-HASTE. In the qualitative analysis, BH-DL-HASTE resulted in the fewest respiratory motion artifacts ( P < 0.0001). BH-DL-TSE and FB-TSE exhibited significantly less motion-related signal loss and clearer intrahepatic vessels than BH-DL-HASTE ( P < 0.0001). Regarding the edge sharpness of the left lobe, BH-DL-HASTE scored the highest ( P < 0.0001), and BH-DL-TSE scored higher than FB-TSE ( P = 0.0290). There were no significant differences among 3 types of FS-T2WI with respect to the edge sharpness of the right lobe ( P = 0.1290), lesion conspicuity ( P = 0.5292), and LEL-SIR ( P = 0.6026). Conclusions: BH-DL-TSE provides a shorter acquisition time and comparable or better image quality than FB-TSE, and could replace FB-TSE in acquiring FS-T2WI of the liver. BH-DL-TSE and BH-DL-HASTE have their own advantages and may be used complementarily.

Deep Learning–Accelerated Liver Diffusion-Weighted Imaging

“…14 Deep learning (DL) reconstruction was recently implemented in body MRI, and studies have reported shortened acquisition times and better image quality using DL-reconstructed T2-weighted imaging compared with conventional turbo spin echo (TSE) or half-Fourier acquisition single-shot TSE (HASTE) T2-weighted imaging. [15][16][17][18] Fewer studies have applied DL-reconstructed DWI (DL-DWI) in body imaging, likewise revealing reduced scan time and improved image quality in evaluating the liver, breast, and prostate gland. [19][20][21][22] Currently, analyses of the impact of strategies to compensate respiratory artifacts on image quality, focal lesion detection, and scan time in liver DL-DWI are lacking.…”

Ultra-High-Resolution T2-Weighted PROPELLER MRI of the Rectum With Deep Learning Reconstruction

“…10 Deep learning reconstruction (DLR), which uses a deep convolutional neural network trained to reconstruct images with higher quality, can improve the signal-to-noise ratio (SNR), sharpness, and spatial resolution of MRI and has been used effectively in various diseases. [15][16][17][18][19][20][21][22] In rectal MRI, the usefulness of DLR in predicting pathological complete response after neoadjuvant treatment has been reported. 16 However, the value of DLR in assessing local tumor extent has not been reported, and the impact of DLR on radiologists' judgments remains to be elucidated despite the direct impact of MRI-positive diagnoses on patient management.…”

“…Deep learning reconstruction (DLR), which uses a deep convolutional neural network trained to reconstruct images with higher quality, can improve the signal-to-noise ratio (SNR), sharpness, and spatial resolution of MRI and has been used effectively in various diseases 15–22 . In rectal MRI, the usefulness of DLR in predicting pathological complete response after neoadjuvant treatment has been reported 16 .…”