Evidence map›Paper›PMID 38893725›Full record

ArticleDiagnostics (Basel, Switzerland)2024

Deep Learning-Based High-Resolution Magnetic Resonance Angiography (MRA) Generation Model for 4D Time-Resolved Angiography with Interleaved Stochastic Trajectories (TWIST) MRA in Fast Stroke Imaging.

Bo Kyu Kim, Sung-Hye You, Byungjun Kim, Jae Ho Shin

Abstract read
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Article in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Bo Kyu KimDepartment of Radiology, Anam Hospital, Korea University College of Medicine, #126-1, 5-Ka Anam-dong, Sungbuk ku, Seoul 136-705, Republic of Korea.ORCID 0000-0001-8591-2225
Sung-Hye YouDepartment of Radiology, Anam Hospital, Korea University College of Medicine, #126-1, 5-Ka Anam-dong, Sungbuk ku, Seoul 136-705, Republic of Korea.ORCID 0000-0001-5005-9383
Byungjun KimDepartment of Radiology, Anam Hospital, Korea University College of Medicine, #126-1, 5-Ka Anam-dong, Sungbuk ku, Seoul 136-705, Republic of Korea.
Jae Ho ShinDepartment of Radiology, Anam Hospital, Korea University College of Medicine, #126-1, 5-Ka Anam-dong, Sungbuk ku, Seoul 136-705, Republic of Korea.ORCID 0000-0001-5922-5720

Funding

 This research was supported by a BRACCO 2023AN0228 This research was supported by National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT, Ministry of Science and ICT) RS-2023-00209819
6 · The paper itself

Abstract

purposeThe purpose of this study is to improve the qualitative and quantitative image quality of the time-resolved angiography with interleaved stochastic trajectories technique (4D-TWIST-MRA) using deep neural network (DNN)-based MR image reconstruction software. MATERIALS AND

methodsA total of 520 consecutive patients underwent 4D-TWIST-MRA for ischemic stroke or intracranial vessel stenosis evaluation. Four-dimensional DNN-reconstructed MRA (4D-DNR) was generated using commercially available software (SwiftMR v.3.0.0.0, AIRS Medical, Seoul, Republic of Korea). Among those evaluated, 397 (76.3%) patients received concurrent time-of-flight MRA (TOF-MRA) to compare the signal-to-noise ratio (SNR), image quality, noise, sharpness, vascular conspicuity, and degree of venous contamination with a 5-point Likert scale. Two radiologists independently evaluated the detection rate of intracranial aneurysm in TOF-MRA, 4D-TWIST-MRA, and 4D-DNR in separate sessions. The other 123 (23.7%) patients received 4D-TWIST-MRA due to a suspicion of acute ischemic stroke. The confidence level and decision time for large vessel occlusion were evaluated in these patients.

resultsIn qualitative analysis, 4D-DNR demonstrated better overall image quality, sharpness, vascular conspicuity, and noise reduction compared to 4D-TWIST-MRA. Moreover, 4D-DNR exhibited a higher SNR than 4D-TWIST-MRA. The venous contamination and aneurysm detection rates were not significantly different between the two MRA images. When compared to TOF-MRA, 4D-CE-MRA underestimated the aneurysm size (2.66 ± 0.51 vs. 1.75 ± 0.62,

conclusionDNN reconstruction may improve the qualitative and quantitative image quality of 4D-TWIST-MRA, and also enhance diagnostic performance for intracranial aneurysm and large vessel occlusion.

Indexed as

deep neural networkdenoisingMR angiography

Identifiers

PMID38893725
PMCPMC11171826

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