Quantitating myocardial fibrosis using extracellular extravascular volume determined from computed tomography myocardial perfusion imaging
Purpose Both of extracellular extravascular volume (EEV) and extracellular volume fraction (ECV) were proposed to quantify enlargement of myocardial interstitial space due to myocardium loss or fibrosis. The study aimed to investigate the feasibility of using EEV derived from myocardial computed tomography (CT) perfusion imaging (VPCT) and extracellular volume quantification with single-energy subtraction CT ($ ECV_{− SECT} $) for quantifying myocardial fibrosis. Methods In this study, 17 patients with suspected and known coronary artery disease underwent examination using a dual-source CT scanner. The $ EEV_{− VPCT} $ was derived from dynamic whole-heart myocardial perfusion imaging, and the $ ECV_{_SECT} $ was calculated from late-enhanced images 5 min after bolus contrast injection by subtracting the noncontrast baseline. The late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) imaging was used as a reference. Results In total, 11 patients and 73 segments exhibited positivity for LGE on CMR imaging. These were classified into three groups according to the segments: fibrotic segments (group I, n = 73), nonfibrotic segments in LGE-positive patients (group II, n = 103), and segments in LGE-negative patients (group III, n = 80). $ ECV_{− SECT} $, $ EEV_{− VPCT} $, myocardial blood flow (MBF), and myocardial blood volume (MBV) significantly differed among these groups (all P < 0.05). $ ECV_{− SECT} $ was significantly higher and $ EEV_{− VPCT} $, MBF, and MBV were significantly lower in fibrotic myocardial segments than in nonfibrotic ones (all P < 0.01). $ ECV_{− SECT} $ and $ EEV_{− VPCT} $ independently affected myocardial fibrosis. There was no significant correlation between $ ECV_{− SECT} $ and $ EEV_{− VPCT} $. The capability of $ EEV_{− VPCT} $ to diagnose myocardial fibrosis was equivalent to that of $ ECV_{− SECT} $ (area under the curve: 0.798 vs. 0.806, P = 0.844). $ ECV_{− SECT} $ of > 41.2% and $ EEV_{− VPCT} $ of < 10.3% indicated myocardial fibrosis. Conclusions $ EEV_{− VPCT} $ is actually first-pass distribution volume that can feasibly be used to quantify myocardial fibrosis. Furthermore, the diagnostic efficacy of $ EEV_{− VPCT} $ is comparable to that of $ ECV_{− SECT} $..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:24 |
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| Enthalten in: |
BMC medical imaging - 24(2024), 1 vom: 12. Feb. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Li, Na [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
Computed tomography |
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| Anmerkungen: |
© The Author(s) 2024 |
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| doi: |
10.1186/s12880-024-01226-3 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
SPR054741890 |
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| 100 | 1 | |a Li, Na |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Quantitating myocardial fibrosis using extracellular extravascular volume determined from computed tomography myocardial perfusion imaging |
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| 520 | |a Purpose Both of extracellular extravascular volume (EEV) and extracellular volume fraction (ECV) were proposed to quantify enlargement of myocardial interstitial space due to myocardium loss or fibrosis. The study aimed to investigate the feasibility of using EEV derived from myocardial computed tomography (CT) perfusion imaging (VPCT) and extracellular volume quantification with single-energy subtraction CT ($ ECV_{− SECT} $) for quantifying myocardial fibrosis. Methods In this study, 17 patients with suspected and known coronary artery disease underwent examination using a dual-source CT scanner. The $ EEV_{− VPCT} $ was derived from dynamic whole-heart myocardial perfusion imaging, and the $ ECV_{_SECT} $ was calculated from late-enhanced images 5 min after bolus contrast injection by subtracting the noncontrast baseline. The late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) imaging was used as a reference. Results In total, 11 patients and 73 segments exhibited positivity for LGE on CMR imaging. These were classified into three groups according to the segments: fibrotic segments (group I, n = 73), nonfibrotic segments in LGE-positive patients (group II, n = 103), and segments in LGE-negative patients (group III, n = 80). $ ECV_{− SECT} $, $ EEV_{− VPCT} $, myocardial blood flow (MBF), and myocardial blood volume (MBV) significantly differed among these groups (all P < 0.05). $ ECV_{− SECT} $ was significantly higher and $ EEV_{− VPCT} $, MBF, and MBV were significantly lower in fibrotic myocardial segments than in nonfibrotic ones (all P < 0.01). $ ECV_{− SECT} $ and $ EEV_{− VPCT} $ independently affected myocardial fibrosis. There was no significant correlation between $ ECV_{− SECT} $ and $ EEV_{− VPCT} $. The capability of $ EEV_{− VPCT} $ to diagnose myocardial fibrosis was equivalent to that of $ ECV_{− SECT} $ (area under the curve: 0.798 vs. 0.806, P = 0.844). $ ECV_{− SECT} $ of > 41.2% and $ EEV_{− VPCT} $ of < 10.3% indicated myocardial fibrosis. Conclusions $ EEV_{− VPCT} $ is actually first-pass distribution volume that can feasibly be used to quantify myocardial fibrosis. Furthermore, the diagnostic efficacy of $ EEV_{− VPCT} $ is comparable to that of $ ECV_{− SECT} $. | ||
| 650 | 4 | |a Myocardial fibrosis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Extracellular volume fraction |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Extracellular extravascular volume |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Computed tomography |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Myocardial perfusion imaging |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Zhang, Xin |4 aut | |
| 700 | 1 | |a Gu, Jin |4 aut | |
| 700 | 1 | |a Yang, Ming |4 aut | |
| 700 | 1 | |a Chen, Lina |4 aut | |
| 700 | 1 | |a Yu, Jie |4 aut | |
| 700 | 1 | |a Shi, Heshui |0 (orcid)0000-0001-7644-3711 |4 aut | |
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