Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise
Abstract This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-speci...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ha, Hojin [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
4D phase-contrast magnetic resonance imaging (PC-MRI) |
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| Anmerkung: |
© The Visualization Society of Japan 2018 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of visualization - Berlin : Springer, 1998, 22(2018), 2 vom: 21. Nov., Seite 245-257 |
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| Übergeordnetes Werk: |
volume:22 ; year:2018 ; number:2 ; day:21 ; month:11 ; pages:245-257 |
| Links: |
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| DOI / URN: |
10.1007/s12650-018-0536-9 |
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| Katalog-ID: |
SPR026584867 |
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| 245 | 1 | 0 | |a Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise |
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| 520 | |a Abstract This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5–3.0 mm and noise levels of 0.1–50 cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2–4 years old) had the errors of ± 0.057, ± 0.145 and ± 0.210 at the voxel sizes of 1.0 mm, 2.0 mm, and 3.0 mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to ± 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels. Graphical abstract | ||
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| 650 | 4 | |a 4D flow MRI |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Blood flow distribution |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Computational fluid dynamics (CFD) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Fontan circulation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Hemodynamics |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Lee, Sang Joon |4 aut | |
| 700 | 1 | |a Kim, Namkug |4 aut | |
| 700 | 1 | |a Yang, Dong Hyun |4 aut | |
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10.1007/s12650-018-0536-9 doi (DE-627)SPR026584867 (SPR)s12650-018-0536-9-e DE-627 ger DE-627 rakwb eng Ha, Hojin verfasserin aut Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Visualization Society of Japan 2018 Abstract This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5–3.0 mm and noise levels of 0.1–50 cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2–4 years old) had the errors of ± 0.057, ± 0.145 and ± 0.210 at the voxel sizes of 1.0 mm, 2.0 mm, and 3.0 mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to ± 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels. Graphical abstract 4D phase-contrast magnetic resonance imaging (PC-MRI) (dpeaa)DE-He213 4D flow MRI (dpeaa)DE-He213 Blood flow distribution (dpeaa)DE-He213 Computational fluid dynamics (CFD) (dpeaa)DE-He213 Fontan circulation (dpeaa)DE-He213 Hemodynamics (dpeaa)DE-He213 Kang, Heejun aut Huh, Hyungkyu aut Choi, Woorak aut Koo, Hyun Jung aut Kwon, Jaeyoung aut Park, Kyoung Jin aut Cho, Young Chul aut Lee, Sang Joon aut Kim, Namkug aut Yang, Dong Hyun aut Enthalten in Journal of visualization Berlin : Springer, 1998 22(2018), 2 vom: 21. Nov., Seite 245-257 (DE-627)357174291 (DE-600)2094841-4 1875-8975 nnns volume:22 year:2018 number:2 day:21 month:11 pages:245-257 https://dx.doi.org/10.1007/s12650-018-0536-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 22 2018 2 21 11 245-257 |
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10.1007/s12650-018-0536-9 doi (DE-627)SPR026584867 (SPR)s12650-018-0536-9-e DE-627 ger DE-627 rakwb eng Ha, Hojin verfasserin aut Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Visualization Society of Japan 2018 Abstract This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5–3.0 mm and noise levels of 0.1–50 cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2–4 years old) had the errors of ± 0.057, ± 0.145 and ± 0.210 at the voxel sizes of 1.0 mm, 2.0 mm, and 3.0 mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to ± 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels. Graphical abstract 4D phase-contrast magnetic resonance imaging (PC-MRI) (dpeaa)DE-He213 4D flow MRI (dpeaa)DE-He213 Blood flow distribution (dpeaa)DE-He213 Computational fluid dynamics (CFD) (dpeaa)DE-He213 Fontan circulation (dpeaa)DE-He213 Hemodynamics (dpeaa)DE-He213 Kang, Heejun aut Huh, Hyungkyu aut Choi, Woorak aut Koo, Hyun Jung aut Kwon, Jaeyoung aut Park, Kyoung Jin aut Cho, Young Chul aut Lee, Sang Joon aut Kim, Namkug aut Yang, Dong Hyun aut Enthalten in Journal of visualization Berlin : Springer, 1998 22(2018), 2 vom: 21. Nov., Seite 245-257 (DE-627)357174291 (DE-600)2094841-4 1875-8975 nnns volume:22 year:2018 number:2 day:21 month:11 pages:245-257 https://dx.doi.org/10.1007/s12650-018-0536-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 22 2018 2 21 11 245-257 |
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10.1007/s12650-018-0536-9 doi (DE-627)SPR026584867 (SPR)s12650-018-0536-9-e DE-627 ger DE-627 rakwb eng Ha, Hojin verfasserin aut Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Visualization Society of Japan 2018 Abstract This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5–3.0 mm and noise levels of 0.1–50 cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2–4 years old) had the errors of ± 0.057, ± 0.145 and ± 0.210 at the voxel sizes of 1.0 mm, 2.0 mm, and 3.0 mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to ± 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels. Graphical abstract 4D phase-contrast magnetic resonance imaging (PC-MRI) (dpeaa)DE-He213 4D flow MRI (dpeaa)DE-He213 Blood flow distribution (dpeaa)DE-He213 Computational fluid dynamics (CFD) (dpeaa)DE-He213 Fontan circulation (dpeaa)DE-He213 Hemodynamics (dpeaa)DE-He213 Kang, Heejun aut Huh, Hyungkyu aut Choi, Woorak aut Koo, Hyun Jung aut Kwon, Jaeyoung aut Park, Kyoung Jin aut Cho, Young Chul aut Lee, Sang Joon aut Kim, Namkug aut Yang, Dong Hyun aut Enthalten in Journal of visualization Berlin : Springer, 1998 22(2018), 2 vom: 21. Nov., Seite 245-257 (DE-627)357174291 (DE-600)2094841-4 1875-8975 nnns volume:22 year:2018 number:2 day:21 month:11 pages:245-257 https://dx.doi.org/10.1007/s12650-018-0536-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 22 2018 2 21 11 245-257 |
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10.1007/s12650-018-0536-9 doi (DE-627)SPR026584867 (SPR)s12650-018-0536-9-e DE-627 ger DE-627 rakwb eng Ha, Hojin verfasserin aut Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Visualization Society of Japan 2018 Abstract This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5–3.0 mm and noise levels of 0.1–50 cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2–4 years old) had the errors of ± 0.057, ± 0.145 and ± 0.210 at the voxel sizes of 1.0 mm, 2.0 mm, and 3.0 mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to ± 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels. Graphical abstract 4D phase-contrast magnetic resonance imaging (PC-MRI) (dpeaa)DE-He213 4D flow MRI (dpeaa)DE-He213 Blood flow distribution (dpeaa)DE-He213 Computational fluid dynamics (CFD) (dpeaa)DE-He213 Fontan circulation (dpeaa)DE-He213 Hemodynamics (dpeaa)DE-He213 Kang, Heejun aut Huh, Hyungkyu aut Choi, Woorak aut Koo, Hyun Jung aut Kwon, Jaeyoung aut Park, Kyoung Jin aut Cho, Young Chul aut Lee, Sang Joon aut Kim, Namkug aut Yang, Dong Hyun aut Enthalten in Journal of visualization Berlin : Springer, 1998 22(2018), 2 vom: 21. Nov., Seite 245-257 (DE-627)357174291 (DE-600)2094841-4 1875-8975 nnns volume:22 year:2018 number:2 day:21 month:11 pages:245-257 https://dx.doi.org/10.1007/s12650-018-0536-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 22 2018 2 21 11 245-257 |
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10.1007/s12650-018-0536-9 doi (DE-627)SPR026584867 (SPR)s12650-018-0536-9-e DE-627 ger DE-627 rakwb eng Ha, Hojin verfasserin aut Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Visualization Society of Japan 2018 Abstract This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5–3.0 mm and noise levels of 0.1–50 cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2–4 years old) had the errors of ± 0.057, ± 0.145 and ± 0.210 at the voxel sizes of 1.0 mm, 2.0 mm, and 3.0 mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to ± 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels. Graphical abstract 4D phase-contrast magnetic resonance imaging (PC-MRI) (dpeaa)DE-He213 4D flow MRI (dpeaa)DE-He213 Blood flow distribution (dpeaa)DE-He213 Computational fluid dynamics (CFD) (dpeaa)DE-He213 Fontan circulation (dpeaa)DE-He213 Hemodynamics (dpeaa)DE-He213 Kang, Heejun aut Huh, Hyungkyu aut Choi, Woorak aut Koo, Hyun Jung aut Kwon, Jaeyoung aut Park, Kyoung Jin aut Cho, Young Chul aut Lee, Sang Joon aut Kim, Namkug aut Yang, Dong Hyun aut Enthalten in Journal of visualization Berlin : Springer, 1998 22(2018), 2 vom: 21. Nov., Seite 245-257 (DE-627)357174291 (DE-600)2094841-4 1875-8975 nnns volume:22 year:2018 number:2 day:21 month:11 pages:245-257 https://dx.doi.org/10.1007/s12650-018-0536-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 22 2018 2 21 11 245-257 |
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Enthalten in Journal of visualization 22(2018), 2 vom: 21. Nov., Seite 245-257 volume:22 year:2018 number:2 day:21 month:11 pages:245-257 |
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4D phase-contrast magnetic resonance imaging (PC-MRI) 4D flow MRI Blood flow distribution Computational fluid dynamics (CFD) Fontan circulation Hemodynamics |
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Ha, Hojin @@aut@@ Kang, Heejun @@aut@@ Huh, Hyungkyu @@aut@@ Choi, Woorak @@aut@@ Koo, Hyun Jung @@aut@@ Kwon, Jaeyoung @@aut@@ Park, Kyoung Jin @@aut@@ Cho, Young Chul @@aut@@ Lee, Sang Joon @@aut@@ Kim, Namkug @@aut@@ Yang, Dong Hyun @@aut@@ |
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2018-11-21T00:00:00Z |
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Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5–3.0 mm and noise levels of 0.1–50 cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2–4 years old) had the errors of ± 0.057, ± 0.145 and ± 0.210 at the voxel sizes of 1.0 mm, 2.0 mm, and 3.0 mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to ± 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels. 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Ha, Hojin |
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Ha, Hojin misc 4D phase-contrast magnetic resonance imaging (PC-MRI) misc 4D flow MRI misc Blood flow distribution misc Computational fluid dynamics (CFD) misc Fontan circulation misc Hemodynamics Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise |
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Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise 4D phase-contrast magnetic resonance imaging (PC-MRI) (dpeaa)DE-He213 4D flow MRI (dpeaa)DE-He213 Blood flow distribution (dpeaa)DE-He213 Computational fluid dynamics (CFD) (dpeaa)DE-He213 Fontan circulation (dpeaa)DE-He213 Hemodynamics (dpeaa)DE-He213 |
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Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise |
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Ha, Hojin Kang, Heejun Huh, Hyungkyu Choi, Woorak Koo, Hyun Jung Kwon, Jaeyoung Park, Kyoung Jin Cho, Young Chul Lee, Sang Joon Kim, Namkug Yang, Dong Hyun |
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accuracy evaluation of blood flow distribution in the fontan circulation: effects of resolution and velocity noise |
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Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise |
| abstract |
Abstract This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5–3.0 mm and noise levels of 0.1–50 cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2–4 years old) had the errors of ± 0.057, ± 0.145 and ± 0.210 at the voxel sizes of 1.0 mm, 2.0 mm, and 3.0 mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to ± 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels. Graphical abstract © The Visualization Society of Japan 2018 |
| abstractGer |
Abstract This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5–3.0 mm and noise levels of 0.1–50 cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2–4 years old) had the errors of ± 0.057, ± 0.145 and ± 0.210 at the voxel sizes of 1.0 mm, 2.0 mm, and 3.0 mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to ± 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels. Graphical abstract © The Visualization Society of Japan 2018 |
| abstract_unstemmed |
Abstract This study analyzes the accuracy of the Fontan circulation using four-dimensional (4D) flow magnetic resonance imaging (MRI) for a variety of spatial resolution and noise scenarios. Using the results of computational fluid dynamics (CFD) as ground truth, hemodynamics in twelve patient-specific Fontan circulations were simulated as 4D flow MRIs, for voxel sizes of 0.5–3.0 mm and noise levels of 0.1–50 cm/s. In each case, three-dimensional streamline tracers were emitted at 1000 randomly sampled points from the inferior vena cava and superior vena cava planes, and the blood flow distribution from the vena cava to pulmonary arteries was quantified. The error of the flow distribution in 4D flow MRI was obtained by substituting the value obtained from 4D flow MRI into that obtained from CFD. Increasing the voxel size in 4D flow MRI affected the accuracy of the flow distribution estimation. The 4D flow MRI assessment of the flow distribution ratio in Fontan patients (2–4 years old) had the errors of ± 0.057, ± 0.145 and ± 0.210 at the voxel sizes of 1.0 mm, 2.0 mm, and 3.0 mm, respectively. Increasing velocity noise increased the missing fraction of the tracers, increasing the mean error of the flow distribution ratio to 0.490 at the missing fractions above 70%. Using the missing fraction of 20% as a cutoff condition for the dataset, the error ratio in the analysis was confined to ± 0.2. Assessment of the flow distribution using 4D flow MRI is sensitive to spatial resolution and velocity noise levels. Graphical abstract © The Visualization Society of Japan 2018 |
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| title_short |
Accuracy evaluation of blood flow distribution in the Fontan circulation: effects of resolution and velocity noise |
| url |
https://dx.doi.org/10.1007/s12650-018-0536-9 |
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| author2 |
Kang, Heejun Huh, Hyungkyu Choi, Woorak Koo, Hyun Jung Kwon, Jaeyoung Park, Kyoung Jin Cho, Young Chul Lee, Sang Joon Kim, Namkug Yang, Dong Hyun |
| author2Str |
Kang, Heejun Huh, Hyungkyu Choi, Woorak Koo, Hyun Jung Kwon, Jaeyoung Park, Kyoung Jin Cho, Young Chul Lee, Sang Joon Kim, Namkug Yang, Dong Hyun |
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| doi_str |
10.1007/s12650-018-0536-9 |
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2024-07-03T21:41:11.065Z |
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| score |
7.4028378 |