The Role of T1 and T2 Mapping on Cardiovascular Magnetic Resonance Imaging in Sudden Cardiac Arrest Survivors

doi:10.21203/rs.3.rs-2643647/v1

Purpose

Etiology of sudden cardiac arrest (SCA) is identified in less than 30% of survivors without coronary artery disease. We sought to assess the diagnostic role of myocardial parametric mapping using cardiovascular magnetic resonance (CMR) in identifying SCA etiology.

Methods

Consecutive SCA survivors undergoing CMR with myocardial parametric mapping were included in the study. The determination if CMR was decisive or contributory in identifying SCA etiology was made if the diagnosis was unclear prior to CMR, and the discharge diagnosis was consistent with the CMR result. Parametric mapping was considered essential for the CMR diagnosis if the SCA etiology could have not been determined without its utilization, and contributory if the diagnosis could have been potentially based on the combination of cine and LGE imaging, without optimal assessment of the severity and prognosis of the disease (offered by parametric mapping).

Results

Of the 35 patients (mean age 46.9 ± 14.1 years; 57% males) included, diagnosis was based on CMR in 23 (66%) patients. Of those, parametric mapping was essential for the diagnosis of myocarditis and tako-tsubo cardiomyopathy (11/48%) and contributed to the diagnosis in 10 (43%) additional cases.

Conclusion

Inclusion of quantitative T1 and T2 parametric mapping in the SCA CMR protocol has the potential to increase diagnostic yield of CMR and further specify SCA etiology, especially myocarditis. CMR performed early after SCA may aid in the decision-making regarding ICD implantation.

sudden cardiac arrest

cardiovascular magnetic resonance imaging

parametric mapping

T1 and T2 mapping

Despite best efforts, the etiology of sudden cardiac arrest (SCA) is identified in only 50% of survivors and in less than 30% of those without coronary artery disease (CAD).[1, 2]. SCA might be caused by acute and transient electrical instability in the setting of acute myocardial ischemia or myocarditis, ventricular arrhythmia due to presence of ischemic or nonischemic scar, or primary electrical disease[3–5]. Clinical investigations are aimed to establish the SCA cause and its reversibility to facilitate clinical decision making, including insertion of an implantable cardioverter-defibrillator (ICD)[3, 6].

While the role of T2-weighted imaging and late gadolinium enhancement (LGE) imaging in cardiac magnetic resonance imaging (CMR) in SCA survivors has been explored, there is limited data on the role of quantitative myocardial T1 and T2 relaxation times[2, 3, 7]. Myocardial parametric mapping can be used to identify myocardial inflammation, edema, and diffuse interstitial expansion, which can aid in diagnosing myocarditis and various inflammatory and non-ischemic cardiomyopathies[2, 8].

Quantitative T2 mapping overcomes several limitations of qualitative T2-weighted imaging and provides more accurate evaluation of myocardial edema[8, 9]. The combination of quantitative T2 mapping and LGE is crucial for the differentiation between acute and potentially reversible injuries, such as myocarditis or acute ischemia, and chronic irreversible injuries such as chronic infarct or nonischemic scar[3].

Assessment of interstitial myocardial fibrosis, quantified by extracellular volume fraction (ECV) via T1 mapping, might provide prognostic information in SCA survivors. ECV elevation is associated with adverse outcomes in patients with both ischemic and nonischemic LGE across a spectrum of left ventricular function[10–13]. Importantly, ECV has been shown to be more strongly associated with adverse outcomes than nonischemic LGE, even after adjusting for left ventricle ejection fraction (LVEF)[13]. Similar associations were found in patients with CAD, dilated cardiomyopathy, and heart failure with preserved ejection fraction[12, 14–16].

The goal of our study was to evaluate the diagnostic role of T1 and T2 mapping in identifying SCA etiology and personalizing management of SCA survivors. Preliminary assessment of the prognostic role of parametric mapping was also intended.

Patients

This is a retrospective cohort study assessing the role of myocardial T1 and T2 mapping in identifying SCA etiology and assessing prognosis. Patients who presented to our institution with SCA of unclear etiology between 2016 and 2019 and underwent CMR within 4 weeks of SCA were included in the study. Patients with an acute ischemic injury and known culprit coronary artery were not included in the analysis. Aborted SCA was defined as ventricular fibrillation or hemodynamically unstable ventricular tachycardia requiring electrical or chemical cardioversion. The study was approved by The Ohio State University’s Institutional Review Board and informed consent was waived.

The electronic medical record was reviewed for demographic and clinical data as well as cardiac testing including electrocardiography (ECG), transthoracic echocardiography (TTE), coronary computed tomography angiography (CCTA), and left heart catheterization (LHC). An ischemic evaluation using LHC and CCTA was available in 33 (94%) patients.

CMR Image Acquisition & Analysis

Clinical CMR images were acquired at 1.5 T (Magnetom Avanto, Siemens Healthineers, Germany) using standardized protocols including cine imaging, pre-contrast & post-contrast T1 mapping, T2 mapping, and LGE imaging[17].

CMR studies were anonymized and analyzed using Neosoft, LLC (Pewaukee, Wisconsin, United States of America). LV volumes and LVEF were measured from short-axis stacks of cine frames that covered the LV. Native and post-contrast myocardial T1 values were measured within the septum on the mid short axis (SAX) maps, and ECV was calculated using the standard formula[18]. T1 values were measured within the non-infarcted myocardium in cases with septal infarct scar. Myocardial T2 values were measured in all AHA segments on the mid SAX as well as long axis (vertical, horizontal and 3-chamber long axis) maps when available[17]. CMR reference values for the myocardium were based on institutionally established normative control data and were as follows: native T1 999 ± 31 ms, ECV 23.8 ± 2.6% and T2 56 ± 2 ms.

The presence, pattern, and extent of LGE was assessed by two level 3 trained CMR readers blinded to clinical information. LGE patterns were described as subendocardial, midwall, subepicardial, and transmural. Presence of LGE was reported according to the American Heart Association [AHA] 17-segment model[19].

The determination if CMR was decisive or contributory in identifying SCA etiology was made if the diagnosis was unclear prior to CMR, and the discharge diagnosis was consistent with the CMR result. Final SCA etiology was obtained from chart review and CMR analysis with confirmation by 2 cardiologists with adjudication by a 3rd author if in disagreement. Myocarditis on CMR was diagnosed using the updated Lake Louise criteria[20]. We followed the current criteria for defining hypertrophic cardiomyopathy, nonischemic cardiomyopathy, ischemic cardiomyopathy, and takotsubo cardiomyopathy, as published elsewhere[21–25].

Parametric mapping was considered essential for the CMR diagnosis if the SCA etiology could have not been determined without its utilization, and contributory if the diagnosis could have been potentially based on the combination of cine and LGE imaging, without optimal assessment of the severity and prognosis of the disease (offered by parametric mapping).

Follow-Up & Outcomes

Patient follow-up was performed by review of the vital status and electronic medical record including ICD interrogation and event monitor results. Follow-up duration was calculated from the date of SCA. The primary outcomes were all-cause mortality or heart transplant, and a composite arrhythmic outcomes including sudden death, VF, sustained VT, and appropriate ICD intervention.

Statistical Analysis

Categorical data are presented as frequency with percentage, and comparison between groups was performed using the chi-square or Fisher's exact test. Continuous variables were presented as mean ± standard deviation (SD) for normal distributions, and median with 25th and 75th percentiles (Q1-Q3) for non-normal distributions. Normality was tested using skewness, kurtosis, visual inspection of the histogram, QQ plot, and Shapiro-Wilk test. Continuous variable comparisons between groups were performed using the Student's t-test or the Mann-Whitney U test as appropriate. Kaplan-Meier survival curves were drawn to assess differences between groups for time to event data. Time zero was defined as the date of CMR study. A Cox regression model was used to assess the relationship of T1 elevation, T2 elevation, LGE presence, and ECV elevation with clinical outcomes. The hazard ratio and incidence rate ratio were presented as mean and 95% confidence interval. A two-sided p value of < 0.05 was considered statistically significant. The statistical analyses were performed using IBM SPSS Statistics for Windows, version 22.0 (IBM Corp., Armonk, N.Y., USA) and R software, version 4.0.3 (The R Foundation, Vienna, Austria).

Baseline Characteristics

A total of 35 patients were included in the analysis (Fig. 1). The mean age of the cohort was 46.9 ± 14.1 years, 57% male (Table 1). The most common primary arrhythmia was ventricular fibrillation/ventricular tachycardia in 33 patients (94%) followed by pulseless electrical activity in 2 patients (6%). CMR was performed within a median 5.5 (IQR: 2-7.5) days after the SCA.

CMR results

CMR findings are summarized in Table 1 for the whole cohort as well as are stratified by the primary outcome of all-cause mortality, heart transplant and arrhythmic outcomes, and detailed CMR data for each patient are presented in Supplemental Table 1. Elevation of T1 was seen in 18 (51%) patients (mean T1 1069 ± 60 ms), ECV in 16 (46%) patients (mean ECV 30 ± 7%), and T2 in 22 (63%) patients (mean T2 65 ± 10 ms). T2 was most frequently elevated in the mid inferolateral wall (12/34%) Fig. 2). LGE was present in 32 (91%) patients with a median of 5 (IQR 4–8) left ventricular segments affected (Table 1, Supplemental Table 1). The prevalence of LGE was highest in the basal (66%) to mid inferoseptal wall (63%).

Clinical impact of CMR

SCA etiology was established based on clinical data, ECG, TTE, CCTA, and LHC in 8 (23%) patients (Fig. 1, Table 1). CMR provided the most probable SCA etiology in an additional 23 (66%) patients with parametric mapping abnormalities in 21 (60%). Myocarditis (10), hypertrophic cardiomyopathy (4), nonischemic cardiomyopathy (5), ischemic cardiomyopathy (3), and takotsubo cardiomyopathy (1) were found among the 23 patients whose diagnoses were determined by CMR (Table 1, Supplemental Table 1).

Parametric mapping was essential for the diagnosis of myocarditis and takotsubo cardiomyopathy in 11 patients and contributed to the diagnosis in an additional 10 patients among the 23 cases with diagnoses determined by CMR. The etiology of SCA remained unknown in 4(11%) patients despite extensive testing including CMR with parametric mapping.

Parametric Mapping in Myocarditis

In the 10 myocarditis patients, T2 signal elevation (mean highest T2 of 73 ± 12 ms) and LGE were most commonly seen in the inferolateral wall consistent with prior reports (Table 1, Supplemental Table 1, Fig. 2)[20]. T1 was elevated in 6 patients (mean T1, 1084 ± 56 ms), ECV in 3 patients (mean ECV, 28.1 ± 5.6%), and left ventricular ejection fraction (LVEF) was depressed (< 50%) in 3 patients. Diagnosis was confirmed with an endomyocardial biopsy in 1 patient. One patient had influenza infection; 8 had troponin elevation (0.76, IQR 0.19–15.5, normal < 0.11 ng/L).

Parametric Mapping and in Takotsubo Cardiomyopathy

T1 (1044 ms) and ECV (28.1%) were normal in the tako-tsubo cardiomyopathy patient with myocardial edema/inflammation in the mid and apical segments (mean T2, 77 ms) that extended beyond the septal midmyocardial LGE.

Parametric Mapping in Other Etiologies of SCA

In the 4 patients with hypertrophic cardiomyopathy, native T1 was elevated in 1, and ECV in 2 patients. Two patients demonstrated T2 signal elevation, with LGE most commonly seen in the septum (Table 1, Supplemental Table 1).

Native T1 elevation was observed in 4 out of 5 patients with non-ischemic cardiomyopathy, with ECV and T2 being borderline abnormal in 1 patient. Septal and inferolateral walls were the most common locations of nonischemic LGE.

CMR based diagnosis of ischemic cardiomyopathy, was associated with native T1 and ECV elevation in 2/3 patients, whereas T2 was elevated in all 3/3 patients. Infarct scar in 2/3 patients corresponded to segments with T2 elevation and extended to other neighboring segments with no evidence of myocardial edema/inflammation.

Native T1 was elevated in 2 of 3 patients, and ECV in all 3 patients whose diagnosis of ischemic cardiomyopathy was not based on CMR. CMR of 3/3 patients was noticeable for an infarct scar that corresponded to segments with T2 elevation and extended to other neighboring segments with no evidence of myocardial edema/inflammation.

Two out of 5 patients with the primarily electric etiology of SCA (hypokalemia with QT prolongation, Brugada syndrome) presented with T1 and T2 elevation. Myocardial edema/inflammation, when present, was demonstrated in 1–2 AHA segments. ECV elevation was observed in 1 of 5 patients.

Among 4 patients with unclear SCA etiology, native T1 was elevated in 1 patient with ECV elevation in 3 patients. There was no evidence of T2 elevation.

ICD Implantation

ICD was implanted in 29 (83%) patients. ICD was not implanted in 4 (11%) patients due to reversible SCA cause, whereas 2 (6%) patients refused ICD implantation.

Primary Outcomes

Three (9%) patients were lost to follow-up. Over the median follow-up of 33.1 months (IQR 25.4–43.1) from SCA, 5 (16%) patients died or underwent a heart transplant, and 12 (38%) met the composite arrhythmic outcome (Supplemental Table 2). No significant differences in baseline characteristics, comorbidities, SCA etiology & mechanism as well as CMR parameters were demonstrated between patients that met and did not meet both primary outcomes (Table 1, Supplemental Fig. 2–3). There was no significant association between T1 elevation and all-cause mortality or heart transplant (HR: 3.25, 95% 0.36–29.7, p = 0.30), or arrhythmic outcomes (HR: 1.37, 95% CI: 0.41–4.62, p = 0.61); T2 elevation and all-cause mortality or heart transplant (HR: 1.84, 95% CI:0.19–17.7, p = 0.60), or arrhythmic outcomes (HR: 0.79, 95% CI: 0.24–2.60, p = 0.70); ECV elevation and all-cause mortality or heart transplant (HR: 0.84, 95% CI: 0.14–5.01, p = 0.84), or arrhythmic outcomes (HR: 1.23, 95% CI: 0.39–3.86, p = 0.72); (Supplemental Fig. 1).

We investigated the diagnostic role of myocardial parametric mapping in SCA survivors. Our data confirms and extends previous observations that CMR with parametric mapping has diagnostic value in assessing SCA etiology compared to non-CMR based evaluation[3, 4]. We show that parametric mapping was essential for the diagnosis in 11 patients (myocarditis and tako-tsubo) and contributed to and hence clarified the diagnosis in additional 10 patients. Our data also suggests that myocarditis may be an underdiagnosed cause of SCA in adults. We did not find any association between T1, T2, and ECV elevation and primary outcomes of all-cause mortality and heart transplant as well as arrhythmic outcomes.

Our findings regarding the diagnostic value of CMR are in agreement with previously published data.[3, 4] Prior reports suggest that LVEF alone has limited sensitivity and specificity for predicting SCA, since 80% of SCA occurs in the setting of LVEF > 35%[26]. In large studies on SCA survivors with inconclusive ischemic evaluation, CMR contributed to the diagnosis in 49–69% and was decisive in 28–30% of cases, depending on the definition of the study group, despite lack of utilization of parametric mapping[7, 27]. Similar to our study, dilated cardiomyopathy, myocarditis, ischemic cardiomyopathy, and hypertrophic cardiomyopathy were the most common SCA etiologies, while 31–36% of cases had unclear etiology[7, 27].

We further demonstrate that utilization of parametric mapping has potential to decrease the number of cases with unclear etiology of SCA and hence influence clinical decision-making. Myocarditis, a common SCA cause, remains underdiagnosed[28–33]. Since endomyocardial biopsy is not recommended in every case of suspected myocarditis, CMR has become the gold standard non-invasive diagnostic method enabling tissue characterization of the entire myocardium[8, 32, 34–37]. The diagnosis of myocardial inflammation is based on updated Lake Louis criteria including T1 and T2 mapping as well as late gadolinium enhancement imaging[38]. Combination of T2-weighted imaging with LGE imaging in studies on SCA survivors with inconclusive ischemic evaluation, resulted in diagnosing myocarditis in 6–13% of cases[27, 39]. Utilization of T2 mapping, that provides more accurate and quantitative assessment of myocardial edema, could potentially explain the higher percentage of myocarditis in our study (28%)[8, 9].

T2 mapping contributed to a more certain diagnosis of other etiologies by either excluding myocarditis as a cause of SCA; confirming the diagnosis suspected based on ischemic evaluation and echocardiography as in takotsubo cardiomyopathy; or assessing the acuity and potential reversibility of the process as in MINOCA and ischemic cardiomyopathy[8]. These results have the potential to influence decisions regarding ICD implantation[27].

Other studies have also shown that T2 mapping is useful not only for making the diagnosis but also for risk stratification in certain diagnoses[8]. The degree of T2 elevation is a reliable predictor of major adverse cardiac events and heart failure hospitalization in patients with myocarditis[8, 35]. T2 elevation in hypertrophic cardiomyopathy can be used as a marker for arrhythmogenicity, and in dilated cardiomyopathy to identify patients with low probability of reverse remodeling [8, 40].

ECV elevation, which was present in a significant subset of patients in our study, has been associated with adverse outcomes in various cardiomyopathy[11–16, 41]. ECV in our population was highest in hypertrophic and ischemic CMP as well as MINOCA patients.

We attempted to analyze the prognostic role of parametric mapping aware of the study limitations. Heterogeneity of included SCA etiologies is the most likely explanation of the lack of association between T1, T2, or ECV elevation and primary outcomes in our study. Our study was limited by a small sample size, which got even smaller as specific SCA etiologies were evaluated. Further studies that address specific etiologies of SCA, including our future expanded cohort, may be able to characterize association of parametric mapping abnormalities with outcome.

Limitations

This is a single center small retrospective study. SCA etiologies were determined based on clinical data, and endomyocardial biopsy was not performed in most cases to confirm CMR-based diagnosis of myocarditis. The accuracy of the endomyocardial biopsy, however, is limited by sampling error due to the patchy nature of the inflammatory process[28, 34, 42, 43].

Since myocardial edema and inflammation observed on CMR could potentially be secondary to SCA (myocardial necrosis secondary to transient hypoxemia) or cardiopulmonary resuscitation, the data must be analyzed with caution and in correspondence with typical LGE pattern[3, 20]. Since myocarditis in our study was diagnosed based on the updated Lake Louis criteria which includes T1 and T2 mapping and LGE, it is unlikely to affect results.

Distribution of SCA etiologies is not representative for the general population since only patients who survived SCA and had no clear cause of SCA were included in the study. Small sample size with very small subgroups of each SCA etiology limited analysis of the prognostic utility of parametric mapping.

To conclude, inclusion of quantitative T1 and T2 parametric mapping in the SCA CMR protocol has the potential to increase diagnostic yield of CMR and further specify SCA etiology, especially myocarditis. CMR performed early after SCA may aid in the decision-making regarding ICD implantation. Further studies are needed to investigate the prognostic role of parametric mapping in SCA survivors.

Disclosures: N/A

Acknowledgments: N/A

Carter-Monroe N, Virmani R (2011). Current Trends in the Classification of Sudden Cardiac Death Based on Autopsy Derived Data: A Review of Investigations Into the Etiology of Sudden Cardiac Death. Revista Española de Cardiología (English Edition) 64(1):10–2. doi: 10.1016/j.recesp.2010.09.004.
Zareba W, Zareba KM (2017). Cardiac Magnetic Resonance in Sudden Cardiac Arrest Survivors. Circ Cardiovasc Imaging. doi: 10.1161/CIRCIMAGING.117.007290.
Zorzi A, Susana A, de Lazzari M, Migliore F, Vescovo G, Scarpa D, et al (2018). Diagnostic value and prognostic implications of early cardiac magnetic resonance in survivors of out-of-hospital cardiac arrest. Heart Rhythm 15(7):1031–41. doi: 10.1016/j.hrthm.2018.02.033.
Ojrzyńska-Witek N, Marczak M, Mazurkiewicz Ł, Petryka-Mazurkiewicz J, Miłosz-Wieczorek B, Grzybowski J, et al (2022). Sudden cardiac arrest: Focus on cardiac magnetic resonance. Kardiol Pol 80(1):87–9. DOI: 10.33963/KP.a2021.0151.
Zaremba T, Brøndberg AK, Jensen HK, Kim WY (2018). Cardiac magnetic resonance characteristics in young survivors of aborted sudden cardiac death. Eur J Radiol 105:141–7. doi: 10.1016/j.ejrad.2018.06.004.
Swoboda P, Kidambi A, Uddin A, McDiarmid A, Ripley D, Greenwood J, et al (2014). Cardiovascular Magnetic Resonance is Valuable in the Investigation of Aborted Sudden Cardiac Death. Heart 100(Suppl 3):A71.2-A72. doi: 10.1136/heartjnl-2014-306118.125
Rodrigues P, Joshi A, Williams H, Westwood M, Petersen SE, Zemrak F, et al (2017). Diagnosis and Prognosis in Sudden Cardiac Arrest Survivors Without Coronary Artery Disease: Utility of a Clinical Approach Using Cardiac Magnetic Resonance Imaging. Circ Cardiovasc Imaging Dec;10(12):e006709. doi: 10.1161/CIRCIMAGING.117.006709.
O’Brien AT, Gil KE, Varghese J, Simonetti OP, Zareba KM (2022). T2 mapping in myocardial disease: a comprehensive review. Journal of Cardiovascular Magnetic Resonance 24,33. doi: 10.1186/s12968-022-00866-0.
Giri S, Chung YC, Merchant A, Mihai G, Rajagopalan S, Raman S v., et al (2009). T2 quantification for improved detection of myocardial edema. Journal of Cardiovascular Magnetic Resonance 11(1):56. doi: 10.1186/1532-429X-11-56.
Wong TC, Piehler KM, Kang IA, Kadakkal A, Kellman P, Schwartzman DS, et al (2014). Myocardial extracellular volume fraction quantified by cardiovascular magnetic resonance is increased in diabetes and associated with mortality and incident heart failure admission. Eur Heart J 35(10):657–64. doi: 10.1093/eurheartj/eht193.
Schelbert EB, Piehler KM, Zareba KM, Moon JC, Ugander M, Messroghli DR, et al (2015). Myocardial fibrosis quantified by extracellular volume is associated with subsequent hospitalization for heart failure, death, or both across the spectrum of ejection fraction and heart failure stage. J Am Heart Assoc 4(12). doi: 10.1161/JAHA.115.002613.
Cheng RK, Masri SC (2019). Extracellular Volume as an Imaging Biomarker for Incident Heart Failure. Circ Cardiovasc Imaging 12(12):10152. doi: 10.1161/CIRCIMAGING.119.010152.
Schelbert EB, Piehler KM, Zareba KM, Moon JC, Ugander M, Messroghli DR, et al (2015). Myocardial Fibrosis Quantified by Extracellular Volume Is Associated With Subsequent Hospitalization for Heart Failure, Death, or Both Across the Spectrum of Ejection Fraction and Heart Failure Stage. J Am Heart Assoc 4(12). doi: 10.1161/JAHA.115.002613.
Laohabut I, Songsangjinda T, Kaolawanich Y, Yindeengam A, Krittayaphong R (2021). Myocardial Extracellular Volume Fraction and T1 Mapping by Cardiac Magnetic Resonance Compared Between Patients With and Without Type 2 Diabetes, and the Effect of ECV and T2D on Cardiovascular Outcomes. Front Cardiovasc Med 7;0:1725. doi: 10.3389/fcvm.2021.771363.
Youn JC, Hong YJ, Lee HJ, Han K, Shim CY, Hong GR, et al (2017). Contrast-enhanced T1 mapping-based extracellular volume fraction independently predicts clinical outcome in patients with non-ischemic dilated cardiomyopathy: a prospective cohort study. Eur Radiol 27(9):3924–33. doi: 10.1007/s00330-017-4817-9.
Schelbert EB, Fridman Y, Wong TC, Abu Daya H, Piehler KM, Kadakkal A, et al (2017). Temporal Relation Between Myocardial Fibrosis and Heart Failure With Preserved Ejection Fraction: Association With Baseline Disease Severity and Subsequent Outcome. JAMA Cardiol 2(9):995–1006. doi: 10.1001/jamacardio.2017.2511.
Kramer CM, Barkhausen J, Bucciarelli-Ducci C, Flamm SD, Kim RJ, Nagel E (2020). Standardized cardiovascular magnetic resonance imaging (CMR) protocols: 2020 update. Journal of Cardiovascular Magnetic 22(1):1–18. https://doi.org/10.1186/s12968-020-00607-1.
Haaf P, Garg P, Messroghli DR, Broadbent DA, Greenwood JP, Plein S (2016). Cardiac T1 Mapping and Extracellular Volume (ECV) in clinical practice: A comprehensive review. Journal of Cardiovascular Magnetic Resonance 18(1):1–12. doi: 10.1186/s12968-016-0308-4.
Cerqueira MD, Weissman NJ, Dilsizian V, Jacobs AK, Kaul S, Laskey WK, et al (2002). Standardized Myocardial Segmentation and Nomenclature for Tomographic Imaging of the Heart. Circulation 105(4):539–42. doi: 10.1161/hc0402.102975.
Aquaro GD, Perfetti M, Camastra G, Monti L, Dellegrottaglie S, Moro C, et al (2017). Cardiac MR With Late Gadolinium Enhancement in Acute Myocarditis With Preserved Systolic Function: ITAMY Study. J Am Coll 70(16):1977–87. doi: 10.1016/j.jacc.2017.08.044.
Maron BJ, Maron MS (2016). LGE Means Better Selection of HCM Patients for Primary Prevention Implantable Defibrillators. JACC: Cardiovascular Imaging 9 (12) 1403–1406.https://doi.org/10.1016/j.jcmg.2016.01.032.
Bozkurt B, Colvin M, Cook J, Cooper LT, Deswal A, Fonarow GC, et al (2016). Current Diagnostic and Treatment Strategies for Specific Dilated Cardiomyopathies: A Scientific Statement from the American Heart Association. Circulation 134:e579–e646. https://doi.org/10.1161/CIR.0000000000000455.
Maron BJ, Towbin JA, Thiene G, Antzelevitch C, Corrado D, Arnett D, et al (2006). Contemporary definitions and classification of the cardiomyopathies: An American Heart Association Scientific Statement from the Council on Clinical Cardiology, Heart Failure and Transplantation Committee; Quality of Care and Outcomes Research and Functional Genomics and Translational Biology Interdisciplinary Working Groups; and Council on Epidemiology and Prevention. Circulation 113(14):1807–16. doi: 10.1161/CIRCULATIONAHA.106.174287.
Singh T, Khan H, Gamble DT, Scally C, Newby DE, Dawson D (2022). Takotsubo Syndrome: Pathophysiology, Emerging Concepts, and Clinical Implications. Circulation 145(13):1002–19. doi: 10.1161/CIRCULATIONAHA.121.055854.
Thavendiranathan P, Walls M, Giri S, Verhaert D, Rajagopalan S, Moore S, et al (2012). Improved detection of myocardial involvement in acute inflammatory cardiomyopathies using T2 mapping. Circ Cardiovasc Imaging 5(1):102–10. doi: 10.1161/CIRCIMAGING.111.967836.
Wu KC (2017). Sudden Cardiac Death Substrate Imaged by Magnetic Resonance Imaging: From Investigational Tool to Clinical Applications. Circ Cardiovasc Imaging 10(7):e005461. doi: 10.1161/CIRCIMAGING.116.005461.
Baritussio A, Zorzi A, Ghosh Dastidar A, Susana A, Mattesi G, Rodrigues JCL, et al (2017). Out of hospital cardiac arrest survivors with inconclusive coronary angiogram: Impact of cardiovascular magnetic resonance on clinical management and decision-making. Resuscitation 116:91–7. doi: 10.1016/j.resuscitation.2017.03.039.
Tschöpe C, Ammirati E, Bozkurt B, Caforio ALP, Cooper LT, Felix SB, et al (2021). Myocarditis and inflammatory cardiomyopathy: current evidence and future directions. Nat Rev Cardiol 18(3):169-193. doi: 10.1038/s41569-020-00435-x.
von Knobelsdorff-Brenkenhoff F, Schüler J, Dogangüzel S, Dieringer MA, Rudolph A, Greiser A, et al (2017). Detection and Monitoring of Acute Myocarditis Applying Quantitative Cardiovascular Magnetic Resonance. Circ Cardiovasc Imaging 10(2):1–10. doi: 10.1161/CIRCIMAGING.116.005242.
Grun S, Schumm J, Greulich S, Wagner A, Schneider S, Bruder O, et al (2012). Long-term follow-up of biopsy-proven viral myocarditis: Predictors of mortality and incomplete recovery. J Am Coll Cardiol 59(18):1604–15. doi: 10.1016/j.jacc.2012.01.007.
Spieker M, Katsianos E, Gastl M, Behm P, Horn P, Jacoby C, et al (2018). T2 mapping cardiovascular magnetic resonance identifies the presence of myocardial inflammation in patients with dilated cardiomyopathy as compared to endomyocardial biopsy. Eur Heart J Cardiovasc Imaging 19(5):574–82. doi: 10.1093/ehjci/jex230.
Løgstrup BB, Nielsen JM, Kim WY, Poulsen SH (20160. Myocardial oedema in acutemyocarditis detected by echocardiographic 2Dmyocardial deformation analysis. Eur Heart J Cardiovasc Imaging 17(9):1018–26. doi: 10.1093/ehjci/jev302.
Ruppert V, Meyer T, Pankuweit S, Möller E, Funck RC, Grimm W, et al (2008). Gene expression profiling from endomyocardial biopsy tissue allows distinction between subentities of dilated cardiomyopathy. Journal of Thoracic and Cardiovascular Surgery 136(2): 360-369.e1. doi: 10.1016/j.jtcvs.2008.03.016
Ammirati E, Frigerio M, Adler ED, Basso C, Birnie DH, Brambatti M, et al (2020). Management of Acute Myocarditis and Chronic Inflammatory Cardiomyopathy: An Expert Consensus Document. Circ Heart Fail 13(11):e007405. doi: 10.1161/CIRCHEARTFAILURE.120.007405.
Spieker M, Haberkorn S, Gastl M, Behm P, Katsianos S, Horn P, et al (2017). Abnormal T2 mapping cardiovascular magnetic resonance correlates with adverse clinical outcome in patients with suspected acute myocarditis. Journal of Cardiovascular Magnetic Resonance 19(1): 38. doi: 10.1186/s12968-017-0350-x.
P Caforio AL, Pankuweit S, Arbustini E, Basso C, Gimeno-Blanes J, Felix SB, et al (2013). Current state of knowledge on aetiology, diagnosis, management, and therapy of myocarditis: a position statement of the European Society of Cardiology Working Group on Myocardial and Pericardial Diseases. 34(33):2636-48, 2648a-2648d. doi: 10.1093/eurheartj/eht210.
Dass S, Suttie JJ, Piechnik SK, Ferreira VM, Holloway CJ, Banerjee R, et al (2012). Myocardial tissue characterization using magnetic resonance noncontrast T1 mapping in hypertrophic and dilated cardiomyopathy. Circ Cardiovasc Imaging 5(6):726–33. doi: 10.1161/CIRCIMAGING.112.976738.
Ferreira VM, Schulz-Menger J, Holmvang G, Kramer CM, Carbone I, Sechtem U, et al (2018). Cardiovascular Magnetic Resonance in Nonischemic Myocardial Inflammation: Expert Recommendations. J Am Coll Cardiol 72(24):3158–76. doi: 10.1016/j.jacc.2018.09.072.
Rodrigues P, Joshi A, Williams H, Westwood M, Petersen SE, Zemrak F, et al (2017). Diagnosis and Prognosis in Sudden Cardiac Arrest Survivors Without Coronary Artery Disease: Utility of a Clinical Approach Using Cardiac Magnetic Resonance Imaging. Circ Cardiovasc Imaging 10(12):e006709. doi: 10.1161/CIRCIMAGING.117.006709.
Baig M, Galazka P, Dakwar O, Syed SA, Sawlani R, Shahir K, et al (2021). Prevalence of myocardial edema with T2 mapping in hypertrophic cardiomyopathy. J Am Coll Cardiol 77 (18_Supplement_1):1303.https://doi.org/10.1016/S0735-1097(21)02661-9
Wong TC, Piehler KM, Kang IA, Kadakkal A, Kellman P, Schwartzman DS, et al (2014). Myocardial extracellular volume fraction quantified by cardiovascular magnetic resonance is increased in diabetes and associated with mortality and incident heart failure admission. Eur Heart J 35(10):657–64. doi: 10.1093/eurheartj/eht193.
Bönner F, Spieker M, Haberkorn S, Jacoby C, Flögel U, Schnackenburg B, et al. Myocardial T2 Mapping Increases Noninvasive Diagnostic Accuracy for Biopsy-Proven Myocarditis. JACC: Cardiovascular Imaging 9:1467–9. doi: 10.1016/j.jcmg.2015.11.014.
Lurz P, Luecke C, Eitel I, Föhrenbach F, Frank C, Grothoff M, et al (2016). Comprehensive Cardiac Magnetic Resonance Imaging in Patients with Suspected Myocarditis the MyoRacer-Trial. J Am Coll Cardiol 67(15):1800–11. doi: 10.1016/j.jacc.2016.02.013.

Table 1. Baseline clinical and imaging characteristics of Sudden Cardiac Arrest Survivors.

Abbreviations: BSA - body surface area; SCA – sudden cardiac arrest; MINOCA - myocardial infarction with non-obstructive coronary arteries; CMR – cardiovascular magnetic resonance; LVEDVI – left ventricular end-diastolic volume index; LVESVI - left ventricular end-systolic volume index; LVEF – left ventricular ejection fraction; LGE – late gadolinium enhancement imaging; AHA – American Heart Association.

Continuous variables are expressed as mean ± standard deviation with normal distribution and median and interquartile range (25th-75th percentiles) with non-normal distribution. Categorical variables are presented as n (%).

*Calculated from the cohort having primary outcome data (all-cause mortality, heart transplant and arrhythmic outcomes)

Characteristic	Whole cohort (n=35)	Primary Outcome*		P value
Characteristic	Whole cohort (n=35)	Yes (n=15)	No (n=17)	P value
Age, mean (SD), y	46.9 ± 14.1	50.4 ± 15.0	46.1 ± 13.3	0.39
Male, No. (%)	20 (57)	9 (60.0)	8 (47.1)	0.46
BSA, mean (SD), m²	2.1±0.3	2.1 ± 0.4	2.0 ± 0.2	0.32
Obesity, No. (%)	13 (37)	7 (46.7)	5 (29.4)	0.31
Hypertension, No. (%)	24 (69)	13 (86.7)	10 (58.8)	0.12
Hyperlipidemia, No. (%)	14 (40)	6 (40.0)	6 (35.3)	0.78
Diabetes mellitus, No. (%)	6 (17)	2 (13.3)	3 (17.6)	0.99
Atrial fibrillation, No. (%)	6 (17)	2 (13.3)	4 (23.5)	0.66
Coronary artery disease, No. (%)	16 (46)
Stroke, No. (%)	4 (11)	2 (13.3)	2 (11.8)	0.99
Chronic kidney disease, No. (%)	4 (11)	2 (13.3)	2 (11.8)	0.99
Chronic obstructive pulmonary disease, No. (%)	2 (6)	2 (13.3)	0 (0.0)	0.21
SCA mechanism, No. (%)
Ventricular fibrillation/ventricular tachycardia	33 (94)	14 (93.3)	16 (94.1)	0.99
Pulseless electrical activity	2 (6)	1 (6.7)	1 (5.9)	0.99
Suspected SCA etiology, No. (%)				0.65
*Suspected SCA etiology by CMR, No. (%)*
Myocarditis (parametric mapping essential for the diagnosis)	10 (29)	4 (27)	5 (29)
Hypertrophic cardiomyopathy	4 (11)	1 (7)	3 (18)
Non-ischemic cardiomyopathy	5 (14)	2 (13)	3 (18)
Ischemic cardiomyopathy	3 (9)	3 (20.0)	0 (0.0)
Tako-tsubo cardiomyopathy (parametric mapping essential for the diagnosis)	1 (3)	0 (0)	1 (6)
*Suspected SCA etiology based on other tests, No. (%)*
Ischemic cardiomyopathy	3 (9)	1 (7)	1 (6)
Primarily electric etiology	5 (14)	3 (20)	2 (12)
Unclear cause	4 (11)	1 (7)	2 (12)
CMR parameters, mean (SD)
LVEDVI, mean (SD), ml/m2	87 (27)	91 (23)	85 (30)	0.52
LVESVI, mean (SD), ml/m2	51 (25)	55 (25)	49 (27)	0.52
LVEF, mean (SD), %,	49 (13)	46 (14)	52 (13)	0.20
T1 elevation, No. (%)	18 (51%)	10 (66.7)	7 (41.2)	0.15
Mean T1, mean (SD), ms	1069 ± 60	1085 ± 63	1059 ± 57	0.22
ECV, mean (SD), %	30 ± 7	30 ± 7	29 ± 7	0.69
T2 elevation, No. (%)	22 (63%)	9 (60.0)	11 (64.7)	0.78
Mean T2, mean (SD), ms	65 ± 10	64 ± 10	65 ± 11	0.71
LGE presence, No. (%)	32 (91)	13 (86.7)	16 (94.1)	0.59
LGE midwall, No. (%)	24 (69)	8 (53.3)	15 (88.2)	0.03
LGE subepicardial, No. (%)	7 (20)	2 (13.3)	4 (23.5)	0.66
LGE subendocardial, No. (%)	7 (20)	4 (26.7)	2 (11.8)	0.38
LGE transmural, No. (%)	4 (11.4)	3 (20.0)	1 (5.9)	0.32
AHA segments, median (IQR)	5 (4-8)	4 (3-7)	5 (4-10)	0.22

No competing interests reported.

SupplementSCAmappingfinal.docx

The Role of T1 and T2 Mapping on Cardiovascular Magnetic Resonance Imaging in Sudden Cardiac Arrest Survivors

Status:

Journal Publication

Version 1

Abstract

Purpose

Methods

Results

Conclusion

Figures

Introduction

Materials & Methods

Patients

CMR Image Acquisition & Analysis

Follow-Up & Outcomes

Statistical Analysis

Results

Baseline Characteristics

CMR results

Clinical impact of CMR

Parametric Mapping in Myocarditis

Parametric Mapping and in Takotsubo Cardiomyopathy

Parametric Mapping in Other Etiologies of SCA

ICD Implantation

Primary Outcomes

Discussion

Limitations

Conclusions

Declarations

References

Table 1

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1