Single-breath-hold T2WI liver MRI with deep learning-based reconstruction: A clinical feasibility study in comparison to conventional multi-breath-hold T2WI liver MRI

Ruo-Fan Sheng; Li-Yun Zheng; Kai-Pu Jin; Wei Sun; Shu Liao; Meng-Su Zeng; Yong-Ming Dai

doi:10.1016/j.mri.2021.06.014

Single-breath-hold T2WI liver MRI with deep learning-based reconstruction: A clinical feasibility study in comparison to conventional multi-breath-hold T2WI liver MRI

Magn Reson Imaging. 2021 Sep:81:75-81. doi: 10.1016/j.mri.2021.06.014. Epub 2021 Jun 18.

Authors

Ruo-Fan Sheng¹, Li-Yun Zheng², Kai-Pu Jin¹, Wei Sun³, Shu Liao⁴, Meng-Su Zeng⁵, Yong-Ming Dai⁶

Affiliations

¹ Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai, 200032, China.; Shanghai Institute of Medical Imaging, Shanghai, China.
² Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai, 200032, China.; Shanghai Institute of Medical Imaging, Shanghai, China.; Central Research Institute, United Imaging Healthcare, Shanghai, China.
³ Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai, 200032, China.
⁴ Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China.
⁵ Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai, 200032, China.; Shanghai Institute of Medical Imaging, Shanghai, China.. Electronic address: mengsuzeng@163.com.
⁶ Central Research Institute, United Imaging Healthcare, Shanghai, China.

PMID: 34147594
DOI: 10.1016/j.mri.2021.06.014

Abstract

Objective: To investigate the clinical feasibility of single-breath-hold (SBH) T2-weighted (T2WI) liver MRI with deep learning-based reconstruction in the evaluation of image quality and lesion delineation, compared with conventional multi-breath-hold (MBH) T2WI.

Methods: One hundred and fifty-two adult patients with suspected liver disease were prospectively enrolled. Two independent readers reviewed images acquired with conventional MBH-T2WI and SBH-T2WI at 3.0 T MR scanner. For image quality analyses, motion artifacts scores and boundary sharpness scores were compared using nonparametric Wilcoxon matched pairs tests between MBH-T2WI and SBH-T2WI. With the reference standard, 89 patients with 376 index lesions were included for lesion analyses. The lesion detection rates were compared by chi-square test, the lesion conspicuity scores and lesion-liver contrast ratio (CR) were compared using nonparametric Wilcoxon matched pairs tests between the two sequences.

Results: For both readers, motion artifacts scores of SBH-T2WI were significantly lower than MBH-T2WI (P < 0.001). Boundary sharpness scores of SBH-T2WI were significantly higher than MBH-T2WI (P < 0.001). The lesion detection rates for SBH-T2WI were significantly higher than MBH-T2WI (P < 0.001); the differences of lesion detection rates between the two sequences were statistically significant for small (≤ 10 mm) liver lesions (P < 0.001), while not significant for larger (> 10 mm) lesions (P > 0.05). Lesion conspicuity scores were significantly higher on SBH-T2WI than MBH-T2WI in the entire cohort as well as in both stratified subgroups of lesions ≤10 mm and > 10 mm (P < 0.001 for all). CRs for focal liver lesions were also significantly higher with SBH-T2WI (P < 0.001).

Conclusion: The SBH-T2WI sequence with deep-learning based reconstruction showed promising performance as it provided significantly better image quality, lesion detectability, lesion conspicuity and contrast within a single breath-hold, compared with the conventional MBH-T2WI.

Keywords: Deep learning; Liver; Magnetic resonance imaging; T2-weighted imaging.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Artifacts
Deep Learning*
Feasibility Studies
Humans
Image Enhancement
Liver / diagnostic imaging
Liver Diseases* / diagnostic imaging
Liver Neoplasms* / diagnostic imaging
Magnetic Resonance Imaging