Reliability of respiratory-triggered two-dimensional cine k-adaptive-t-autocalibrating reconstruction for Cartesian sampling for the assessment of biventricular volume and function in patients with repaired tetralogy of Fallot Article Swipe
Makoto Orii
,
Tsuyoshi Sugawara
,
Hidenobu Takagi
,
Satoshi Nakano
,
Hironobu Ueda
,
Yurie Takizawa
,
Jumpei Fujiwara
,
Shin Takahashi
,
Kotaro Oyama
,
Peng Lai
,
Martin Janich
,
Atsushi Nozaki
,
Kunihiro Yoshioka
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1259/bjr.20201249
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1259/bjr.20201249
Objective: To compare left ventricular (LV) and right ventricular (RV) volume, function, and image quality of a respiratory-triggered two-dimensional (2D)-cine k-adaptive-t-autocalibrating reconstruction for Cartesian sampling (2D kat-ARC) with those of the standard reference, namely, breath-hold 2D balanced steady-state free precession (2D SSFP), in patients with repaired tetralogy of Fallot (TOF). Methods: 30 patients (14 males, mean age 32.2 ± 13.9 years) underwent cardiac magnetic resonance, and 2D kat-ARC and 2D SSFP images were acquired on short-axis view. Biventricular end-diastolic volume (EDV) and end-systolic volume (ESV), stroke volume (SV), ejection fraction (EF), and LV mass (LVM) were analysed. Results: The 2D kat-ARC had significantly shorter scan time (35.2 ± 9.1 s vs 80.4 ± 16.7 s; p < 0.0001). Despite an analysis of image quality showed significant impairment using 2D kat-ARC compared to 2D SSFP cine (p < 0.0001), the two sequences demonstrated no significant difference in terms of biventricular EDV, LVESV, LVSV, LVEF, and LVM. However, the RVESV was overestimated for 2D kat-ARC compared with that for 2D SSFP (73.8 ± 43.2 ml vs 70.3 ± 44.5 ml, p = 0.0002) and the RVSV and RVEF were underestimated (RVSV = 46.2±20.5 ml vs 49.4 ± 20.4 ml, p = 0.0024; RVEF = 40.2±12.7% vs. 43.5±14.0%, p = 0.0002). Conclusion: Respiratory-triggered 2D kat-ARC cine is a reliable technique that could be used in the evaluation of LV volumes and function. Advances in knowledge: 2D cine kat-ARC is a reliable technique for the assessment LV volume and function in patients with repaired TOF.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1259/bjr.20201249
- OA Status
- green
- Cited By
- 4
- References
- 29
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3136872340
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3136872340Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1259/bjr.20201249Digital Object Identifier
- Title
-
Reliability of respiratory-triggered two-dimensional cine k-adaptive-t-autocalibrating reconstruction for Cartesian sampling for the assessment of biventricular volume and function in patients with repaired tetralogy of FallotWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
-
2021-03-18Full publication date if available
- Authors
-
Makoto Orii, Tsuyoshi Sugawara, Hidenobu Takagi, Satoshi Nakano, Hironobu Ueda, Yurie Takizawa, Jumpei Fujiwara, Shin Takahashi, Kotaro Oyama, Peng Lai, Martin Janich, Atsushi Nozaki, Kunihiro YoshiokaList of authors in order
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https://doi.org/10.1259/bjr.20201249Publisher landing page
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://www.ncbi.nlm.nih.gov/pmc/articles/8010533Direct OA link when available
- Concepts
-
Steady-state free precession imaging, Ejection fraction, Medicine, Stroke volume, Cardiology, Nuclear medicine, Internal medicine, Tetralogy of Fallot, Arc (geometry), Ventricular volume, Cardiac function curve, Magnetic resonance imaging, Radiology, Heart failure, Mathematics, Heart disease, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1, 2023: 1, 2022: 2Per-year citation counts (last 5 years)
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29Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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