Evidence map›Paper›PMID 41546797›Full record

ArticleJapanese journal of radiology2026

SnapShot Freeze 2.0, a second-generation motion-correction algorithm, improves mitral valve image quality in preoperative cardiac computed tomography for mitral regurgitation.

Hiromi Hashimura, Kentaro Nishiuchi, Yu Izawa, Kei Honde, Kazuki Ishikawa, Hiroaki Takahashi, Takamichi Murakami

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Article in Japanese journal of radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Hiromi HashimuraDepartment of Radiology, Kobe University Hospital, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, Hyogo, 650-0017, Japan. hsmr@med.kobe-u.ac.jp.ORCID http://orcid.org/0009-0003-7520-7225
Kentaro NishiuchiDepartment of Radiology, Kobe University Hospital, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, Hyogo, 650-0017, Japan.
Yu IzawaDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, Kobe, Japan.
Kei HondeDivision of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, Kobe, Japan.
Kazuki IshikawaCenter for Radiology and Radiation Oncology, Kobe University Hospital, Kobe, Japan.
Hiroaki TakahashiDepartment of Cardiovascular Surgery, Kobe University Graduate School of Medicine, Kobe, Japan.
Takamichi MurakamiDepartment of Radiology, Kobe University Hospital, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-cho, Chuo-ku, Kobe, Hyogo, 650-0017, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreoperative cardiac CT for mitral valve assessment is crucial, and improvement of image quality using motion-correction algorithms remains unreported. MATERIALS AND

methodsWe retrospectively analyzed 141 datasets from 47 patients with mitral regurgitation, reconstructing images acquired using a CT scanner with 16-cm z-axis coverage with prospective electrocardiography gating utilizing standard (STD), SnapShot Freeze 1.0 (SSF), and SnapShot Freeze 2.0 (SSF2) algorithms. Two radiologists blinded to reconstruction methods, cardiac cycle, and patient information evaluated image quality for mitral valve leaflets (A1-P3) using a five-point Likert scale, assessing 20 cardiac phases for the A2/P2 and systolic phases for all leaflets.

resultsImage quality scored significantly higher using SSF2 compared to STD or SSF reconstruction for all 20 cardiac phases of the A2/P2 and the systolic phase of all leaflets (P < 0.05). STD and SSF scores did not differ significantly but were higher in atrial fibrillation than sinus rhythm, a difference not observed with SSF2. No reconstruction method showed significant correlation between heart rate and image quality. The mean systolic phase contributing most to mitral regurgitation diagnosis was 27.7% of the R-R interval. Interobserver agreement was excellent (weighted kappa = 0.956 for A2/P2; 0.915 for A1/P1, A2/P2, and A3/P3).

conclusionsMitral valve image quality in preoperative cardiac CT for mitral regurgitation improved significantly using SSF2 reconstruction compared to STD and SSF. Reflected across different cardiac phases and influenced by neither heart rhythm nor rate, findings suggest the robustness of SSF2 for use in various clinical scenarios and to aid surgical planning.

Indexed as

AlgorithmsMitral ValveMitral Valve InsufficiencyPreoperative CareRadiographic Image Interpretation, Computer-AssistedTomography, X-Ray ComputedAdultAgedAged, 80 and overCardiac-Gated Imaging TechniquesFemaleHumansMaleMiddle AgedRetrospective StudiesComputed tomography angiographyMitral regurgitationMitral valveMitral valve plastyMotion-correction algorithm

Identifiers

PMID41546797
PMCPMC13222163

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.