Myocardial extracellular volume fraction to differentiate healthy from cardiomyopathic myocardium using dual-source dual-energy CT

Abadia, Andres F.; Assen, Marly van; Martin, Simon S.; Vingiani, Vincenzo; Griffith, L. Parkwood; Giovagnoli, Dante A; Bauer, Maximilian J.; Schoepf, U. Joseph

doi:10.1016/j.jcct.2019.09.008

Cited by 37 publications

(51 citation statements)

References 28 publications

(49 reference statements)

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“…Our results demonstrated a significant increase of ECV in acute myocarditis patients, in accordance with previous studies using CMR that underlined an elevation of this biomarker in different cardiomyopathies, including myocarditis [ 15 , 27 ]. We observed significant correlation between ECV and both troponins and BNP, which is coherent with the physiopathology of myocarditis.…”

Section: Discussionsupporting

confidence: 92%

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Diagnostic Performance of Extracellular Volume Quantified by Dual-Layer Dual-Energy CT for Detection of Acute Myocarditis

Restier

Boccalini

Congi

et al. 2021

JCM

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Background: Myocardial extracellular volume (ECV) is a marker of the myocarditis inflammation burden and can be used for acute myocarditis diagnosis. Dual-energy computed tomography (DECT) enables its quantification with high concordance with cardiac magnetic resonance (CMR). Purpose: To investigate the diagnostic performance of myocardial ECV quantified on a cardiac dual-layer DECT in a population of patients with suspected myocarditis, in comparison to CMR. Methods: 78 patients were included in this retrospective monocenter study, 60 were diagnosed with acute myocarditis and 18 patients were considered as a control population, based on the 2009 Lake and Louise criteria. All subjects underwent a cardiac DECT in acute phase consisted in an arterial phase followed by a late iodine enhancement phase at 10 min after injection (1.2 mL/kg, iodinated contrast agent). ECV was calculated using the hematocrit level measured the day of DECT examinations. Non-parametric analyses have been used to test the differences between groups and the correlations between the variables. A ROC curve has been used to identify the optimal ECV cut-off discriminating value allowing the detection of acute myocarditis cases. A p value < 0.05 has been considered as significant. Results: The mean ECV was significantly higher (p < 0.001) for the myocarditis group compared to the control (34.18 ± 0.43 vs. 30.04 ± 0.53%). A cut-off value of ECV = 31.60% (ROC AUC = 0.835, p < 0.001) allows to discriminate the myocarditis with a sensitivity of 80% and a specificity of 78% (positive predictive value = 92.3%, negative predictive value = 53.8% and accuracy = 79.5%). Conclusion: Myocardial ECV enabled by DECT allows to diagnose the acute myocarditis with a cut-off at 31.60% for a sensitivity of 80% and specificity of 78%.

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Section: Discussionsupporting

confidence: 92%

“…Hence, CT can effectively be considered as an interesting alternative to CMR. In addition, CT is more accessible and cheaper, while having a faster acquisition with a better spatial resolution, which makes it a good candidate for cardiac emergency imaging [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Diagnostic Performance of Extracellular Volume Quantified by Dual-Layer Dual-Energy CT for Detection of Acute Myocarditis

Restier

Boccalini

Congi

et al. 2021

JCM

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“…Myocardial iodine ratio was calculated as Iodine myocardium / Iodine blood (Figure 3). [10][11][12][13][14] Using 5-point Likert scales, the con dence degree for excluding CES and LIE was also evaluated being assigned a score of 1 if non-assessable, and a score of 5 if deemed of excellent quality. Left atrial area was manually traced using axial images at the image showing the maximal left atrial area, excluding the pulmonary veins and the left atrial appendage.…”

Section: Methodsmentioning

confidence: 99%

Hyperacute Incidental Late Myocardial Enhancement in Ischemic Stroke using Chest Spectral CT: Relationship with Etiology

Jj²,

Ciardi³

et al. 2021

Preprint

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PurposeHyperacute cardiac imaging of patients with acute ischemic stroke (AIS), though desirable, is impractical. Using delayed-enhancement, low-dose, non-gated, chest spectral computed tomography scans (DESCT), we explored the prevalence and patterns of incidental myocardial late iodine enhancement (LIE) and embolic sources, and the relationship with stroke etiology. MethodsSince July 2020, DESCT was performed after cerebrovascular CT angiography (CTA) among patients with suspected AIS undergoing CT using a dual-layer spectral scanner, without additional contrast administration. Images were analyzed using monoenergetic reconstructions and iodine density maps, and the myocardial extracellular volume fraction (ECV, %) was calculated. ResultsEighty consecutive patients with AIS were included. DESCT identified a cardiac thrombi in 6 patients (7.5%), and a complex aortic plaque in 4 (5%) cases; reclassifying 5 embolic strokes of uncertain source (28% of ESUS) to cardioembolic (CE, n=3) and non-CE (n=2) etiologies. LIE, most commonly ischemic (82%), was identified in 38 (48%) patients. We did not identify significant relationships between AIS etiology and the presence, pattern, and extension of LIE (p>0.05); ECV (p=0.56), severe aortic (p=0.25) or valvular (p=0.26) disease, or the extent of coronary calcification (p=0.39). Patients with evidence of major cardiovascular DESCT findings had higher rate rates of all-cause death at 90 days (42% vs. 19%, p=0.037). ConclusionIn this study, hyperacute cardiac imaging of AIS with DESCT identified a high prevalence of incidental cardiac disease predominantly involving LIE of ischemic etiology and mostly not related to the stroke etiology.

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“…However, this study did not include ischemic cardiomyopathy patients, and the ECV results were not compared with MRI-ECV. Abadia et al (12) investigated the CT-ECV of healthy myocardium, nonischemic cardiomyopathy, and ischemic cardiomyopathy, and set a threshold (a cutoff of 29.5%) to discriminate healthy participants from cardiomyopathy patients, but the CT-ECV was not compared with MRI-ECV in this work. In our study, we found a strong correlation of CT-ECV with MRI-ECV and set a cutoff value (31%) with a 83.1% sensitivity in differentiating between LGE-positive and LGE-negative segments.…”

Section: A B Cmentioning

confidence: 99%

“…After contrast injection, ECV by cardiac CT is calculated from an iodine density map (incorporating the patient's hematocrit level), thus reducing the possibility of misregistration between the pre-and postcontrast CT images and improving measurement accuracy (10). A previous study also demonstrated a threshold value of CT-ECV that distinguishes healthy myocardium from cardiomyopathy (12). However, ECV assessment among ischemic, nonischemic, and late gadolinium enhancement (LGE) negative myocardial segments using dual-layer spectral detector CT has not been studied.…”

Section: Introductionmentioning

confidence: 99%

Quantitative analysis of late iodine enhancement using dual-layer spectral detector computed tomography: comparison with magnetic resonance imaging

Liu¹,

Lin²,

Xu³

et al. 2022

Quant Imaging Med Surg

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Background: To evaluate the segmental myocardial extracellular volume (ECV) fraction and to define a threshold ECV value that can be used to distinguish positive late gadolinium enhancement (LGE) segments from negative myocardial segments using dual-layer spectral detector computed tomography (SDCT), with magnetic resonance imaging (MRI) as a reference.Methods: Fifty-six subjects with cardiac disease or suspected cardiac disease, underwent both late iodine enhancement on CT (CT-LIE) scanning and late gadolinium enhancement on MRI (MRI-LGE) scanning.Each procedure occurred within a week of the other. Global and segmental ECVs of the left ventricle were measured by CT and MRI images. According to the location and pattern of delayed enhancement on MRI image, myocardial segments were classified into 3 groups: ischemic LGE segments (group 1), nonischemicLGE segments (group 2) and negative LGE segments (group 3). The correlation and agreement between CT-ECV and MRI-ECV were compared on a per-segment basis. Receiver operating characteristic (ROC) curve analysis was performed to establish a threshold for LIE detection.Results: Among the 56 patients, 896 segments were analyzed, and of these, 73 segments were in group 1, 229 segments were in group 2, and 594 segments were in group 3. In segmental analysis, CT-ECV in group 3 (27.0%; 24.9-28.9%) was significantly lower than that in group 1 (33.2%; 30.7-36.3%) and group 2 (34.9%; 32.3-39.8%; all P<0.001). Good correlations were seen between CT-ECV and MRI-ECV for all groups (group 1: r=0.920; group 2: r=0.936; group 3: r=0.799; all P<0.001). Bland-Altman analysis between CT-ECV and MRI-ECV showed a small bias in all 3 groups (group 1: -2.1%, 95% limits of agreement −11.3-7.1%; group 2: −0.6%, 95% limits of agreement −13.1-11.9%; group 3: 1.0%, 95% limits of agreement −12.7-14.7%). CT-ECV could differentiate between LGE-positive and LGE-negative segments with 83.1% sensitivity and 93.3% specificity at a cutoff of 31%.Conclusions: ECV values derived from CT imaging showed good correlation and agreement with MR imaging findings, and CT-ECV provided high diagnostic accuracy for discriminating between LGE-positive and LGE-negative segments. Thus, cardiac CT imaging might be a suitable noninvasive imaging technique for myocardial ECV quantification. 2 Liu et al. Quantitative analysis of myocardium using dual-layer SDCT

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Myocardial extracellular volume fraction to differentiate healthy from cardiomyopathic myocardium using dual-source dual-energy CT

Cited by 37 publications

References 28 publications

Diagnostic Performance of Extracellular Volume Quantified by Dual-Layer Dual-Energy CT for Detection of Acute Myocarditis

Diagnostic Performance of Extracellular Volume Quantified by Dual-Layer Dual-Energy CT for Detection of Acute Myocarditis

Hyperacute Incidental Late Myocardial Enhancement in Ischemic Stroke using Chest Spectral CT: Relationship with Etiology

Quantitative analysis of late iodine enhancement using dual-layer spectral detector computed tomography: comparison with magnetic resonance imaging

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