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Shiraishi K, Nakaura T, Uetani H, Nagayama Y, Kidoh M, Kobayashi N, Morita K, Yamahita Y, Tanaka Y, Baba H, Hirai T. Deep learning-based reconstruction and 3D hybrid profile order technique for MRCP at 3T: evaluation of image quality and acquisition time. Eur Radiol 2023; 33:7585-7594. [PMID: 37178197 DOI: 10.1007/s00330-023-09703-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 03/06/2023] [Accepted: 03/20/2023] [Indexed: 05/15/2023]
Abstract
OBJECTIVES To evaluate the image quality of the 3D hybrid profile order technique and deep-learning-based reconstruction (DLR) for 3D magnetic resonance cholangiopancreatography (MRCP) within a single breath-hold (BH) at 3 T magnetic resonance imaging (MRI). METHODS This retrospective study included 32 patients with biliary and pancreatic disorders. BH images were reconstructed with and without DLR. The signal-to-noise ratio (SNR), contrast, contrast-to-noise ratio (CNR) between the common bile duct (CBD) and periductal tissues, and full width at half maximum (FWHM) of CBD on 3D-MRCP were evaluated quantitatively. Two radiologists scored image noise, contrast, artifacts, blur, and overall image quality of the three image types using a 4-point scale. Quantitative and qualitative scores were compared using the Friedman test and post hoc Nemenyi test. RESULTS The SNR and CNR were not significantly different when under respiratory gating- and BH-MRCP without DLR. However, they were significantly higher under BH with DLR than under respiratory gating (SNR, p = 0.013; CNR, p = 0.027). The contrast and FWHM of MRCP under BH with and without DLR were lower than those under respiratory gating (contrast, p < 0.001; FWHM, p = 0.015). Qualitative scores for noise, blur, and overall image quality were higher under BH with DLR than those under respiratory gating (blur, p = 0.003; overall, p = 0.008). CONCLUSIONS The combination of the 3D hybrid profile order technique and DLR is useful for MRCP within a single BH and does not lead to the deterioration of image quality and space resolution at 3 T MRI. CLINICAL RELEVANCE STATEMENT Considering its advantages, this sequence might become the standard protocol for MRCP in clinical practice, at least at 3.0 T. KEY POINTS • The 3D hybrid profile order can achieve MRCP within a single breath-hold without a decrease in spatial resolution. • The DLR significantly improved the CNR and SNR of BH-MRCP. • The 3D hybrid profile order technique with DLR reduces the deterioration of image quality in MRCP within a single breath-hold.
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Affiliation(s)
- Kaori Shiraishi
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan
| | - Takeshi Nakaura
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan.
| | - Hiroyuki Uetani
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan
| | - Yasunori Nagayama
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan
| | - Masafumi Kidoh
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan
| | - Naoki Kobayashi
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan
| | - Kosuke Morita
- Department of Radiology, Kumamoto University Hospital, Kumamoto, Japan, Honjo 1-1-1, Kumamoto, Japan
| | - Yuichi Yamahita
- Canon Medical Systems Corporation, 70-1, Yanagi-Cho, Saiwai-Ku, Kawasaki-Shi, Kanagawa, 212-0015, Japan
| | - Yasuhito Tanaka
- Department of Gastroenterology and Hepatology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan
| | - Hideo Baba
- Department of Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan
| | - Toshinori Hirai
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, 860-8556, Japan
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Single-breath-hold T2WI MRI with artificial intelligence-assisted technique in liver imaging: As compared with conventional respiratory-triggered T2WI. Magn Reson Imaging 2022; 93:175-180. [PMID: 35987419 DOI: 10.1016/j.mri.2022.08.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 08/14/2022] [Accepted: 08/14/2022] [Indexed: 11/23/2022]
Abstract
OBJECTIVE To investigate the clinical feasibility of single-breath-hold T2-weighted (SBH-T2WI) liver MRI using Artificial Intelligence-assisted Compressed Sensing (ACS) technique in liver imaging as compared with conventional respiratory-triggered T2WI (RT-T2WI). METHODS From January 2021 to October 2021, 81 patients suspected of liver lesions were enrolled in this prospective study. The liver MRI was performed, including both RT-T2WI and ACS SBH-T2WI. Two experienced radiologists reviewed all images of each studied sequence, and recorded the lesion location and the largest diameter of the lesions. The image quality was quantitatively and qualitatively analyzed regarding signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), contrast ratio (CR), motion artifact, lesion conspicuity, liver boundary sharpness, and overall image quality. The lesion detection and image quality were compared between two sequences using the Chi-square test or Wilcoxon signed-rank test. RESULTS For lesion detection, 64 lesions were identified in 53 enrolled patients as the reference standard. The average size was 12.09 ± 7.4 mm for the benign lesions and 45.89 ± 22.01 mm for the malignant lesions. Of 64 liver lesions, ACS SBH-T2WI detected 60 lesions (93.8%), and RT-T2WI detected 58 lesions (90.6%). For image quality analysis, the motion artifact of ACS SBH-T2WI sequence was significantly reduced compared with the conventional RT-T2WI sequence (p < 0.05). The SNR, liver boundary sharpness, and overall image quality showed no statistical differences between the two sequences. While the CNR, CR, and lesion conspicuity of ACS SBH-T2WI were significantly better than RT-T2WI (all p < 0.05). CONCLUSIONS The SBH-T2WI with ACS technique showed promising performance as it provided significantly better image quality and lesion detectability with a considerable decrease in scanning time as compared with the conventional RT-T2WI.
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Sheng RF, Zheng LY, Jin KP, Sun W, Liao S, Zeng MS, Dai YM. 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; 81:75-81. [PMID: 34147594 DOI: 10.1016/j.mri.2021.06.014] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 03/23/2021] [Accepted: 06/15/2021] [Indexed: 10/21/2022]
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.
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Affiliation(s)
- Ruo-Fan Sheng
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai, 200032, China.; Shanghai Institute of Medical Imaging, Shanghai, China
| | - Li-Yun Zheng
- 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
| | - Kai-Pu Jin
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai, 200032, China.; Shanghai Institute of Medical Imaging, Shanghai, China
| | - Wei Sun
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai, 200032, China
| | - Shu Liao
- Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Meng-Su Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai, 200032, China.; Shanghai Institute of Medical Imaging, Shanghai, China..
| | - Yong-Ming Dai
- Central Research Institute, United Imaging Healthcare, Shanghai, China
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