Early Prediction of Cardiac Complications in Acute Myocarditis by Means of Extracellular Volume Quantification With the Use of Dual-Energy Computed Tomography

Congi, Anaelle; Ziegler, Arthur; Tomasevic, Danka; Tatard-Leitman, Valerie M.; Broussaud, Thomas; Boccalini, Sara; Bensalah, M.; Rouvière, Anne-Sophie; Bonnefoy‐Cudraz, Eric; Bochaton, Thomas; Boussel, Loîc; Douek, Philippe

doi:10.1016/j.jcmg.2021.04.008

Cited by 12 publications

(3 citation statements)

References 4 publications

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“…This is not a surprising finding, considering the high concordance between these modalities for ECV quantification as demonstrated by recent comparative studies which permits the use of this biomarker for multiple prospects [8,11,14,21]. Hence, we showed recently that ECV enabled by DECT allows a prediction of cardiac complications in acute myocarditis [34]. In this recent study, the cut-off suggested was of 39.5% which is highlighting a higher myocarditis inflammation burden that is consequently at risk.…”

Section: Discussionsupporting

confidence: 57%

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: 57%

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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“…To identify reliable predictors and address collinearity among independent variables, we will employ the LASSO regression analysis 24. As the outcome event pertains to myocarditis development in children, we will use multiple logistic regression analyses18 25–29 to construct an early prediction model for myocarditis. This model estimates the probability of myocarditis by assessing the child’s condition during a visit.…”

Section: Discussionmentioning

confidence: 99%

Establishment and validation of a prediction model for myocarditis in Chinese children below 14 years old: a protocol for a retrospective cohort study

Wu,

Ji,

Huang

et al. 2023

BMJ Open

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IntroductionPaediatric myocarditis, a rare inflammatory disease, often presents without clear early symptoms. Although cardiac troponin I levels can aid in diagnosing myocarditis, they are not definitive indicators. Troponin I levels frequently fluctuate within and outside the reference range, potentially causing misinterpretations by clinicians. Although a negative troponin I result is valuable for excluding myocarditis, its specificity is low. Moreover, the clinical diagnosis of paediatric myocarditis is exceptionally challenging, and accurate early-stage diagnosis and treatment pose difficulties. Currently, the Dallas criteria, involving cardiac biopsy, serves as the gold standard for myocarditis diagnosis. However, this method has several drawbacks and is unsuitable for children, resulting in its limited use.Methods and analysisIn this study, we will employ multiple logistic regression analysis to develop a predictive model for early childhood myocarditis. This model will assess the patient’s condition at onset and provide the probability of a myocarditis diagnosis. Model performance will be evaluated for accuracy and calibration, and the results will be presented through receiver operating characteristic (ROC) curves and calibration plots. Clinical decision curve analysis, in conjunction with ROC curve analysis, will be employed to determine the optimal cut-off value and calculate the net clinical benefit value for assessing clinical effectiveness. Finally, internal model validation will be conducted using bootstrapping.Ethics and disseminationApproval from the Clinical Research Ethics Committee of The Third Affiliated Hospital of Wenzhou Medical University has been obtained. The research findings will be disseminated through presentations at scientific conferences and publication in peer-reviewed journals.

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“…ECV has shown to be capable of detecting subtle myocardial alternations including fibrosis and therefore is especially beneficial when LGE is not attainable [ 25 , 27 ]. Furthermore, ECV has proven to be an independent CMR parameter robustly associated with outcome in myocardial fibrosis [ 28 ], and to be the best imaging biomarker of acute myocarditis burden also in dual-energy computed tomography (DECT), allowing an early prediction of the occurrence of cardiac complications [ 29 , 30 ].…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Cardiac Magnetic Resonance to Detect Subacute Myocarditis

Brendel

Klingel

Kübler

et al. 2022

JCM

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(1) Background: Compared to acute myocarditis in the initial phase, detection of subacute myocarditis with cardiac magnetic resonance (CMR) parameters can be challenging due to a lower degree of myocardial inflammation compared to the acute phase. (2) Objectives: To systematically evaluate non-invasive CMR imaging parameters in acute and subacute myocarditis. (3) Methods: 48 patients (age 37 (IQR 28–55) years; 52% female) with clinically suspected myocarditis were consecutively included. Patients with onset of symptoms ≤2 weeks prior to 1.5T CMR were assigned to the acute group (n = 25, 52%), patients with symptom duration >2 to 6 weeks were assigned to the subacute group (n = 23, 48%). CMR protocol comprised morphology, function, 3D-strain, late gadolinium enhancement (LGE) imaging and mapping (T1, ECV, T2). (4) Results: Highest diagnostic performance in the detection of subacute myocarditis was achieved by ECV evaluation either as single parameter or in combination with T1 mapping (applying a segmental or global increase of native T1 > 1015 ms and ECV > 28%), sensitivity 96% and accuracy 91%. Compared to subacute myocarditis, acute myocarditis demonstrated higher prevalence and extent of LGE (AUC 0.76) and increased T2 (AUC 0.66). (5) Conclusions: A comprehensive CMR approach allows reliable diagnosis of clinically suspected subacute myocarditis. Thereby, ECV alone or in combination with native T1 mapping indicated the best performance for diagnosing subacute myocarditis. Acute vs. subacute myocarditis is difficult to discriminate by CMR alone, due to chronological connection and overlap of pathologic findings.

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Early Prediction of Cardiac Complications in Acute Myocarditis by Means of Extracellular Volume Quantification With the Use of Dual-Energy Computed Tomography

Cited by 12 publications

References 4 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

Establishment and validation of a prediction model for myocarditis in Chinese children below 14 years old: a protocol for a retrospective cohort study

Comprehensive Cardiac Magnetic Resonance to Detect Subacute Myocarditis

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