Effect of Deep Learning Reconstruction on Respiratory-triggered T2-weighted MR Imaging of the Liver: A Comparison between the Single-shot Fast Spin-echo and Fast Spin-echo Sequences.

artifacts deep learning liver magnetic resonance imaging spin echo imaging

Journal

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
ISSN: 1880-2206
Titre abrégé: Magn Reson Med Sci
Pays: Japan
ID NLM: 101153368

Informations de publication

Date de publication:
01 Apr 2024
Historique:
medline: 2 4 2024
pubmed: 30 3 2023
entrez: 29 3 2023
Statut: ppublish

Résumé

To compare the effects of deep learning reconstruction (DLR) on respiratory-triggered T2-weighted MRI of the liver between single-shot fast spin-echo (SSFSE) and fast spin-echo (FSE) sequences. Respiratory-triggered fat-suppressed liver T2-weighted MRI was obtained with the FSE and SSFSE sequences at the same spatial resolution in 55 patients. Conventional reconstruction (CR) and DLR were applied to each sequence, and the SNR and liver-to-lesion contrast were measured on FSE-CR, FSE-DLR, SSFSE-CR, and SSFSE-DLR images. Image quality was independently assessed by three radiologists. The results of the qualitative and quantitative analyses were compared among the four types of images using repeated-measures analysis of variance or Friedman's test for normally and non-normally distributed data, respectively, and a visual grading characteristics (VGC) analysis was performed to evaluate the image quality improvement by DLR on the FSE and SSFSE sequences. The liver SNR was lowest on SSFSE-CR and highest on FSE-DLR and SSFSE-DLR (P < 0.01). The liver-to-lesion contrast did not differ significantly among the four types of images. Qualitatively, noise scores were worst on SSFSE-CR but best on SSFSE-DLR because DLR significantly reduced noise (P < 0.01). In contrast, artifact scores were worst both on FSE-CR and FSE-DLR (P < 0.01) because DLR did not reduce the artifacts. Lesion conspicuity was significantly improved by DLR compared with CR in the SSFSE (P < 0.01) but not in FSE sequences for all readers. Overall image quality was significantly improved by DLR compared with CR for all readers in the SSFSE (P < 0.01) but only one reader in the FSE (P < 0.01). The mean area under the VGC curve values for the FSE-DLR and SSFSE-DLR sequences were 0.65 and 0.94, respectively. In liver T2-weighted MRI, DLR produced more marked improvements in image quality in SSFSE than in FSE.

Identifiants

pubmed: 36990740
doi: 10.2463/mrms.mp.2022-0111
pmc: PMC11024712
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

214-224

Auteurs

Kengo Kiso (K)

Department of Radiology, Osaka University Graduate School of Medicine.

Takahiro Tsuboyama (T)

Department of Radiology, Osaka University Graduate School of Medicine.

Hiromitsu Onishi (H)

Department of Radiology, Osaka University Graduate School of Medicine.

Kazuya Ogawa (K)

Department of Radiology, Osaka University Graduate School of Medicine.

Atsushi Nakamoto (A)

Department of Radiology, Osaka University Graduate School of Medicine.

Mitsuaki Tatsumi (M)

Department of Radiology, Osaka University Graduate School of Medicine.

Takashi Ota (T)

Department of Radiology, Osaka University Graduate School of Medicine.

Hideyuki Fukui (H)

Department of Radiology, Osaka University Graduate School of Medicine.

Keigo Yano (K)

Department of Radiology, Osaka University Graduate School of Medicine.

Toru Honda (T)

Department of Radiology, Osaka University Graduate School of Medicine.

Shinji Kakemoto (S)

Department of Radiology, Osaka University Graduate School of Medicine.

Yoshihiro Koyama (Y)

Department of Radiology, Osaka University Hospital.

Hiroyuki Tarewaki (H)

Department of Radiology, Osaka University Hospital.

Noriyuki Tomiyama (N)

Department of Radiology, Osaka University Graduate School of Medicine.

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