Diagnostic Performance of CMR Parametric Mapping as per Modified Lake Louise Criteria in Acute Myocarditis: An Updated Systematic Review and Meta-Analysis

doi:10.21203/rs.3.rs-5026991/v1

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Diagnostic Performance of CMR Parametric Mapping as per Modified Lake Louise Criteria in Acute Myocarditis: An Updated Systematic Review and Meta-Analysis

https://doi.org/10.21203/rs.3.rs-5026991/v1

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Background

Cardiovascular Magnetic Resonance Imaging (CMR) mapping parameters—Native T1, T2 mapping, and Extracellular Volume (ECV)—are pivotal for diagnosing acute myocarditis according to the modified 2018 Lake Louise Criteria (mLLC). This systematic review and meta-analysis aim to evaluate their diagnostic performance and establish optimal thresholds for acute myocarditis diagnosis.

Methods

We systematically reviewed articles published in the past decade that utilized parametric mapping techniques for myocarditis diagnosis. Data on sensitivity, specificity, and Area Under Curve (AUC) were included, and quality assessment was conducted using the QUADAS-2 tool by two independent reviewers.

Results

Eleven studies involving 677 patients were included. Native T1 showed sensitivity of 83%, specificity of 86%, diagnostic odds ratio (DOR) of 39, and an AUC of 0.91. T2 mapping had sensitivity of 81%, specificity of 86%, DOR of 25, and an AUC of 0.89. ECV demonstrated sensitivity of 71%, specificity of 81%, DOR of 13, and an AUC of 0.83. Mean values in controls for myocarditis were: Native T1 (1039 ms ± 39.23), T2 mapping (57 ms ± 5.18), ECV (31% ± 5.60). The optimal thresholds were 1021 ms for Native T1, 54 ms for T2 mapping, and 28% for ECV generated through Receiver-operating characteristic (ROC) analysis. Native T1 exhibited the highest accuracy among the parameters assessed. Subgroup analysis indicated no significant sensitivity differences based on biopsy or clinical criteria, while Native T1 specificity varied significantly.

Conclusions

Parametric mapping, particularly Native T1, demonstrates robust diagnostic performance for myocarditis compared to T2 mapping and ECV within the mLLC framework. Integrating these CMR parameters could enhance diagnostic accuracy. Further research is essential to refine these findings and optimize diagnostic strategies for myocarditis.

myocarditis

modified Lake Louise

parametric mapping

diagnostic test

Myocarditis, an inflammatory condition of the myocardium, can arise from viral infections, autoimmune disorders, and certain medications.[1] Left untreated, it can lead to severe complications including heart failure, arrhythmias, cardiogenic shock, and dilated cardiomyopathy.[2] Diagnosing myocarditis is challenging due to its heterogeneous and atypical presentation.[3] Endomyocardial biopsy (EMB), while occasionally used, has drawbacks such as invasiveness, sampling limitations, and difficulty in capturing patchy inflammation.[4] CMR is a common non-invasive modality for detecting myocarditis, employing techniques like early gadolinium enhancement (EGE), T2-weighted images, and late gadolinium enhancement (LGE) from the classical Lake Louise Criteria to visualize myocardial inflammation.[3, 5, 6] The addition of quantitative parametric techniques, including native T1 mapping, T2 mapping, and ECV in the modified Lake Louise Criteria (mLLC), has further enhanced the diagnostic capability.[7, 8, 9] The advantages of parametric mapping include quantitative and objective myocarditis assessment and visualization of global myocardial changes.[10, 11] Several studies have proposed parametric CMR mapping as a gold standard non-invasive technique for myocarditis diagnosis.[11, 12] The values of parametric CMR mapping are influenced by field strength, vendors, and acquisition techniques, leading to a lack of universally reliable cutoff values for diagnosing myocarditis.[9, 13, 14] Our study aims to determine specific native T1 mapping, T2 mapping, and ECV cutoff values that reliably differentiate acute myocarditis from healthy controls. An accurate cut-off for parametric technique like native T1 mapping can help to differentiate acute myocarditis patients from healthy controls and narrow non-definitive diagnosis cases.[6] Both native T1 and T2 mapping are sufficient as single markers and can increase diagnostic confidence when used together.[15] Additionally, combining parametric techniques, such as native T1 and T2 mapping along with ECV, has proven beneficial in increasing sensitivity and specificity for myocarditis detection.[16] The aim of this study is also to evaluate the diagnostic performance of these single and combined mapping techniques in diagnosing myocarditis.

We conducted a systematic review and meta-analysis to assess the diagnostic performance of parametric CMR parameters—Native T1, T2 mapping, and ECV for myocarditis diagnosis (individual or combined) and provide their respective cut-off values in acute myocarditis cases. The study adhered to PRISMA guidelines, and the protocol was registered in PROSPERO (CRD42023484275).

1. Study search and selection criteria

Two reviewers (L.G. and R.S.) independently searched PubMed and Google Scholar for relevant studies using predefined keywords: including ["myocarditis" AND “magnetic resonance imaging” AND “Lake Louise Criteria AND "Modified Lake Louise Criteria,” AND "New Lake Louise Criteria," AND "2018 Lake Louise Criteria") AND “ECV”]. Studies from 2014 to 2024 were included. Inclusion criteria encompassed prospective and retrospective studies evaluating the diagnostic accuracy of the three parametric CMR techniques: Native T1, T2 mapping and ECV compared to EMB or accurate clinical assessment as reference. Despite the introduction of the mLLC in 2018, our inclusive approach considered studies dating back to 2014, as many authors had incorporated mapping techniques and ECV in their research even before the formal introduction of the mLLC in 2018. Exclusion criteria eliminated case reports, reviews, and studies lacking sufficient data on calculating sensitivity or specificity. Disagreements were resolved through discussion or involvement of a third reviewer (M.U.). Risk of bias was assessed using QUADAS-2 forms. (Fig. 1)

2. Statistical Analysis

The meta-analysis was performed using R version 4.3.2. Pooled Diagnostic Odds Ratios (DORs) and 95% Confidence Intervals (CIs) were calculated for single parametric techniques and, if available, for combined parametric mapping. Diagnostic accuracy was evaluated using the AUC from Summary Receiver Operating Characteristic (SROC) curves. A univariate random-effects model assessed pooled sensitivity and specificity, and statistical heterogeneity was evaluated using the I² statistic, with significant heterogeneity defined as I² > 60%. ROC analysis was performed to calculate the optimal thresholds of native T1, T2 mapping, and ECV along with their respective AUC, sensitivities and specificities. Pooled mean native T1, T2 mapping, and ECV values were calculated by combining means and standard deviations from multiple studies, and optimal thresholds were calculated by Receiver operating curves (ROC). Subgroup analyses were conducted based on study reference standards. Funnel plots and Egger's regression test were used to inspect and test for publication bias. Continuous variables were expressed as means ± standard deviations, and categorical values as numbers and percentages.

Search results

A total of 1199 articles were initially identified, with 180 undergoing full-text review. Ultimately, 11 studies from 2014 to 2022 were included in the meta-analysis. These comprised seven prospective and four retrospective designs, primarily conducted in Germany. (Table 1) (Table 2)

Table 1: Summary of study characteristics, demography of included studies.

Author (First Author)

Year

Study design

Baseline characteristics of patients

Reference Standard

Age

Male (%)

Presentation

Huber

2018

Retrospective cohort with case-control element

45(29-61)

60/40

Acute

CLINICAL

Radunski

2014

Retrospective case control

76/24

125

Acute

CLINICAL

Isaaki

2021

Retrospective case control

17(14-20)

77/23

Acute

EMB

Palmisano

2020

Prospective case control

39(28-46)

51/49

Acute

CLINICAL

Luetkens

2015

Prospective case control

44.9(26.2-63.17)

50/50

Acute

CLINICAL

2021

Retrospective cohort with case-control element

32 (18-50

71.2/28.8

Acute

EMB

Lurz

2016

Prospective cohort with case-control element

83/17

129

Acute

EMB

Knobelsdorff-Brenkenhoff

2017

Prospective cohort with case-control element

24.5

78/22

Acute

CLINICAL

Luetkens

2019

Prospective cohort with case-control element

41(23-64)

72.5/27.5

Acute

CLINICAL

Dabir

2019

Prospective cohort with case-control element

38(22-54)

77/23

Acute

CLINICAL

Brendel

2022

Prospective cohort with case-control element

48 (30–63)

44/56

Acute

EMB

Ms: millisecond

T1: Native T1

Acute myocarditis: patients presenting with symptoms within 28 days.

Table 2: CMR characteristics of included studies

Study ID	Native T1 Control		Native T1 Cases	T2 Control				T2 Cases		ECV Control			ECV Cases	Native T1 mapping technique		T2 mapping technique			Vendor	Magnet strength
Huber 2028	965 (940-990)		1044 (981-1107)	48 (46-50)				53 (49-57)		22 (19-25)			24 (17-31)	MOLLI		bSSFP			Siemens	1.5 T
Radunski 2014	1051 (1010-1063)		1098 (1057-1139)	55 (54-60)				61 (58-65)		25 (24-27)			31 (28-34)	MOLLI		N/A			Philips	1.5 T
Isaaki 2021	962 (945-979)		1031 (985-1077)	51 (49-53)				58 (53-63)		26.5 (23.7-29.3)			29.2 (23.3-35.1)	MOLLI		GraSE			Philips	1.5 T
Palmisano 2020	1008 (988-1033)		1093 (1050-1201)	47 (46-47.6)				55 (52-59)		25 (24-26)			30 (27-32)	MOLLI		N/A			Philips	1.5 T
Luetkens 2015	966.9 (939.1-994.7)		1048.6 (996.7-1100.5)	52.42 (49.86-54.98)				60.43 (52.96-67.9)		27.68 (21.86-33.5)			34.47 (25.95-43.99)	MOLLI/ShMOLLI		GraSE			Philips	1.5 T
Li 2021	1195 (1152-1238)		1252 (1210-1294)	54.5 (50.8-58.2)				63.2 (57.1-69.3)		29.3 (25.2-33.4)			32.7 (29.4-36)	MOLLI		GraSE			Philips	3 T
Lurz 2016	1044 (1002-1086)		1113 (1046-1180)	56.9 (49.7-64.1)				62.2 (57.7-66.7)		31.8 (26.9-36.7)			37.2 (30.7-43.7)	MOLLI		N/A			Philips	1.5 T
Knobelsdorff-Brenkenhoff 2017		975 (957-1004)		1004 (988-1048)			50.2 (49.2-52)			55.1 (53.3-57.2)	24 (24-25)		26 (25-28)	MOLLI		bSSFP			Philips	1.5 T
Luetkens 2019		965.8 (940.7-990.9)			1047.0 (993.2-1100.8)	52.8 (50.4-55.2)			61.8 (53.6-70)			26.1 (21.9-30.3)	28.6 (23.3-33.9)		MOLLI		GraSE	Philips		1.5 T
Dabir 2019		958.9 (936.4-981.4)			1027.2 (977.9-1076.5)	51.6 (49.7-53.5)			58 (52-64)			27.7 (24.5-30.9)	32 (25.6-38.4)		MOLLI		GraSE	Philips		1.5 T
Brendel 2022		1015 (1015-1015)			1069 (1024-1127)	50 (50-50)			53 (52-56)			30 (30-30)	33 (31-35)		MOLLI		bSSFP	Philips
Optimal Diagnostic Thresholds*		Native T1 Threshold=1021 ms ROC AUC=0.82 Sensitivity=91% Specificity=73%				T2 mapping threshold=54 ms ROC AUC=0.93 Sensitivity=82% Specificity=82%						ECV threshold=28% ROC AUC=0.79 Sensitivity=82% Specificity=73%

*Optimal diagnostic thresholds were determined using ROCs curve

Diagnostic accuracy results

Pooled mean T1 time was 1075.16±64.22 ms, and pooled mean T2 time was 58.25±3.58 ms for myocarditis cases. ECV cutoffs ranged from 22% to 34.47%, and post-contrast T1 timing ranged from 10 to 15 minutes. Out of the eleven studies, only two studies had Siemens as a vendor.¹⁷^,⁸ Ten studies utilized MOLLI (Modified Look-Locker Inversion recovery) for native T1 mapping, with one using both ShMOLLI (Shortened Modified Look-Locker Inversion recovery) and MOLLI. We had five studies utilizing GraSE (Gradient and Spin Echo), three using bSSFP (balanced Steady-state free precession) as a T2 mapping technique and three studies did not report the T2 mapping technique utilized. Diagnostic accuracy for Native T1, T2 mapping, and ECV was reported in all studies (Table 3). Native T1 demonstrated the highest sensitivity (83%) and specificity (86%) among the evaluated parameters, with an inconsistency (I-square I2) of 69% for sensitivity and 75% for specificity. It also had a DOR of 39 and an AUC of 0.91. T2 mapping showed similar sensitivity (81%) and specificity (86%) with I2 of 72.2% and 69% respectively, and a DOR of 25 with an AUC of 0.89. ECV exhibited moderate sensitivity (71%) and specificity (81%) with I2 of 72% and 37%, along with a lower DOR of 13 and an AUC of 0.83. (Figure 2, 3, 4, 5)

Table 3: Diagnostic accuracies and heterogeneity indices of individual mapping parameters Native T1, T2 mapping and ECV

Parameter	Sensitivity	Inconsistency (I-square)	Specificity	Inconsistency (I-square)	Diagnostic Odds Ratio (DOR)	Area Under Curve (AUC)
Native T1	83%	69%	86%	75%	39	0.91
T2	81%	72%	86%	69%	25	0.89
ECV	71%	72%	81%	37%	13	0.83

The optimal cut-off for native T1 mapping was 1021 ms (ROC AUC=0.82, Sensitivity=91%, Specificity=73%). For ECV, the threshold was 28% (ROC AUC=0.79, Sensitivity=82%, Specificity=73%) and T2 mapping had an optimal threshold of 54 ms (ROC AUC=0.93, Sensitivity=82%, Specificity=82%). (Figure 6)

Subgroup analyses revealed no significant differences in diagnostic accuracy based on clinical criteria or EMB reference standards. Meta-regression showed no significant sensitivity differences for Native T1, T2, and ECV (P-value>0.05), though Native T1 mapping specificity varied significantly (P-value<0.05). (Table 4) Funnel plot examination and Egger’s test indicated no significant publication bias for T1, T2, and ECV parameters (p > 0.05 for all on Egger’s test).

Table 4: Results of meta-regression and subgroup analyses based on reference standard of studies.

Mapping technique	Approach	Study number	sensitivity	p-value	specificity	p-value
Native T1	Clinical	7	79% (70-87)	0.77	92% (87-96)	0.001
Native T1	EMB	4	88% (82-93)	0.77	70% (50-84)	0.001
T2	Clinical	7	78% (67-87)	0.205	90% (84-93)	0.076
T2	EMB	4	85% (79-90)	0.205	77% (56-90)	0.076
ECV	Clinical	7	67% (55-78)	0.174	84% (78-89)	0.102
ECV	EMB	4	81% (64-91)	0.174	74% (62-84)	0.102

Study quality assessment and integrated diagnostic performance of different CMR approaches

Overall study quality was moderate and acceptable per QUADAS-2, with one study showing high risk of bias due to non-uniform EMB performance, case control selection. (Figure 7) (Table 5). Five studies investigated combined CMR approaches, with various combinations showing high sensitivity, specificity, and AUC (Table 6).

Table 5: Quality Assessment (QADAS-2)

Study Number	Study ID	Domain 1	Domain 2	Domain 3	Domain 4	Overall Risk of Bias
1	Huber 2018	Low	Low	Low	Low	Low
2	Radunski 2014	Low	Low	Low	Low	Low
3	Isaak 2021	Low	Low	Low	Low	Low
4	Palmisano 2020	Low	Low	Low	Unclear	Low
5	Luetkens 2015	Low	Low	Low	Unclear	Low
6	Li 2021	Low	Low	Low	Low	Low
7	Lurz 2016	Low	Low	Low	Low	Low
8	Knobelsdorff-Brenkenhoff 2017	Low	Low	Low	Low	Low
9	Luetkens 2019	Low	Low	Low	Unclear	Low
10	Dabir 2019	Low	Low	Low	Low	Low
11	Brendel 2022	Low	Unclear	High	Low	High

Domain 1: Was the patient population representative of the population under investigation, with clear criteria for patient inclusion and exclusion, enrollment through consecutive or random sampling, and balanced reporting of patient demographics (age, gender) across study groups? , Domain 2: Were the CMR parameters (T1, T2, ECV) described in sufficient detail, with consistency in the application and interpretation of CMR techniques across studies, blinded assessment of CMR parameters to the reference standard results, and a pre-specified threshold for abnormal CMR findings?, Domain 3: Was endomyocardial biopsy deemed an appropriate reference standard for myocarditis diagnosis, with blinded interpretation of biopsy findings to CMR parameter results, consistency in the application of clinical criteria across studies, and uniform timing of clinical criteria utilization in relation to symptom presentation?, Domain 4: Was there inclusion of all eligible patients in the analysis, with consistent intervals between symptom presentation and CMR testing, CMR testing and the reference standard (EMB/clinical criteria), and analysis of patients in the groups to which they were initially assigned?

Table 6: Results of diagnostic values of combined parametric mapping techniques

S.N.	Author	Combination	Sensitivity	Specificity
1.	Radunski et al	LGE+ECV	94% (88-98)	71% (48-89)
2.	Isaak et al	T1+T2 mapping	85% (64–96)	100% (79–100)
3.	Li et al	T1+T2 mapping LGE + T2 mapping	a. 82.2% b. 79.5%
4.	Brenkenhoff et al	a. T1+T2 b. T2+ECV c. T1+LGE d. T2+LGE e. T1+T2+LGE	a.77.8% (52.4-93.6) b.82.4% (56.6-96.2) c.72.2% (46.5-90.3) d.66.7% (41-86.7) e. 66.7% (41-86.7)	a. 94.4% (72.7-99.9) b.94.4% (72.7-99.9) c.100% (81.5-100) d. 100% (81.5-100) e. 100% (81.5-100)
5.	Brendel et al	T1 + ECV T2 + ECV	a. 96% b. 83%	a. 83% b. 92%

All the combinations are based on Native T1 mapping.

Our study focused on evaluating the diagnostic accuracies of individual parametric mapping techniques for acute myocarditis. Prolonged T1 values, attributed to cellular edema, increased extracellular space, inflammation, and myocyte necrosis, are consistently observed in myocarditis cases.[18, 19] Native T1 mapping showed the highest accuracy among the studied techniques, consistently demonstrating good diagnostic performance (AUC 0.90, DOR 39) compared to T2 mapping (AUC 0.88, DOR 25) and ECV (AUC 0.83, DOR 13). This aligns with findings by several other studies indicating superior diagnostic efficacy of T1 mapping techniques over original LLC 2009 techniques (T2-Weighted imaging, LGE, and EGE).[15, 20, 18, 19]

It is well known that native T1 values can be affected by mapping sequence used and field strength.²¹ In the current study, however, we found relative uniformity among the studies included in the meta-analysis with respect to these parameters. Ten of eleven studies used the MOLLI sequence, and ten studies used a 1.5 T strength magnet. Hence the inter-study variation in Native T1 values in the current study are likely secondary to other factors. Caution should be taken in applying the current results if not using MOLLI on a 1.5T scanner. For native T1 mapping an optimal cut-off of 1021 ms (ROC AUC = 0.82, Sensitivity = 91%, Specificity = 73%) was found. However, this is a statistical threshold, and its clinical significance still needs to be completely determined.

ECV, derived from pre- and post-contrast T1 and hematocrit values, exhibited promise with an AUC of 0.83. However, it is well known that edema itself elevates ECV, which may make the utility of ECV even less reliable among the hyper acute and acute phase of inflammation.[21] A median time of less than 14 days from symptom onset to CMR acquisition in our analysis likely contributed to ECV's lower sensitivity, as observed in study by Luetkens et al.[7] ECV values vary with CMR sequences but remain unaffected by field strength, distinguishing them from native T1 and T2 mapping.[22] Li et al. reported an ECV of 32.7% (29.4–36) for acute myocarditis cases, and 29.3% (25.2–33.4) for controls (p < 0.01) using a 3T magnet. In comparison, Dabir et al. found an ECV of 32% (25.6–38.4) for myocarditis patients and 27.7% ( 24.5–30.9) for controls (p = 0.01) using a 1.5 T magnet.[14, 20] ECV had an optimal threshold of 28% (ROC AUC = 0.79, Sensitivity = 82%, Specificity = 73%) however it is a statistical measure.

Myocardial T2 relaxation time emerged as a promising marker, with significantly elevated values in patients during acute presentation compared to controls. Myocardial T2 relaxation time, closely linked to free tissue water content, with significantly elevated values in acute myocarditis patients.[20] In our study, T2 mapping demonstrated comparable diagnostic efficacy to native T1, with an AUC of 0.88. Variations in T2 mapping techniques and thresholds necessitate consideration of acquisition types, patient populations, and clinical contexts.[23, 24] A statistical analysis identified an optimal threshold of 54 ms for detecting myocarditis using T2 mapping, with a ROC AUC of 0.93, 82% sensitivity, and 82% specificity.

This meta-analysis includes combined mapping techniques from recent studies. This combined approach is most reflective of clinical practice. Five studies reported enhanced diagnostic outcomes by use of several different integrated mapping techniques, such as native T1 + T2, native T1 + ECV.[17, 25, 26, 20, 16] A study by Li et al. demonstrated high diagnostic performance when combining native T1 + T2 mapping over a single parameter of mLLC.[20] A small number of studies precluded a pooled analysis in our meta-analysis. Subgroup analysis with fewer than 4 studies would be unreliable due to low statistical power to detect true differences between subgroups. The study supports the notion that native T1 and T2 mapping allow for a reliable distinction between injured and normal myocardium but may struggle to discriminate between acute myocarditis and other noninflammatory cardiomyopathy or myocarditis with a chronic presentation.

The diagnostic accuracy of parametric mapping techniques has been established to be superior to older techniques. Available parametric mapping evaluations demonstrate that at least one of the main modified LL criteria can effectively diagnose myocarditis with little less accuracy as an alternative to EMB (Sensitivity 88% for EMB > 80% for parametric mapping in CMR).[27]

Limitations

The results of this meta-analysis should be interpreted cautiously due to possible selection and reference biases. Most studies included in our analysis exhibited variability in population, study design, patient characteristics, observer interpretations, and CMR acquisition protocols. EMB was utilized as reference in four studies, while the other studies relied on clinical diagnoses and case-control designs. Some studies did not report local normal data for Native T1 mapping, potentially affecting diagnostic accuracy. Variations in T2 mapping techniques (Gradient and Spin Echo or Steady-state free precession) and CMR vendors (Philips or Siemens) at 1.5 T field strength may limit generalizability. The small number of studies on updated LLC combined mapping parameters precluded a reliable sensitivity analysis, particularly for combined T1 and T2 mapping techniques.

Clinical Implications and Future Directions

Our investigation underscores Native T1 mapping as the most effective modality for diagnosing acute myocarditis, with T2 mapping and ECV presenting viable alternatives. Future studies should refine diagnostic protocols based on patient presentation timing, standardize CMR methods across large, matched cohorts, and consider diagnostic network meta-analyses to optimize approaches. This approach aims to reduce diagnostic costs and clinical workload associated with myocarditis, facilitating more precise and efficient diagnosis.

The utilization of CMR based parametric mapping emerges as a valuable diagnostic strategy for acute myocarditis with native T1 mapping exhibiting highest diagnostic accuracy across the board, followed by T2 mapping and ECV. The pooled optimal threshold values of each native T1, T2 mapping, and ECV obtained from ROC aid in adequate diagnosis of myocarditis. We recommend further studies to explore the diagnostic performance of combined parametric mapping techniques.

Acknowledgment

We would like to express our sincere gratitude to all the researchers and clinicians whose work contributed to the studies included in this systematic review and meta-analysis. Additionally, we extend our appreciation to Dr. Alireza Ghodsi for his contribution in literature search. We also acknowledge the contributions of the PROSPERO team for their assistance with study registration.

Author contributions

LG conceived and designed the study, conducted literature search, performed data extraction and analysis, and drafted the manuscript. RS conducted literature search, performed data extraction, and contributed to the interpretation of results. AM participated in the study design, conducted literature search, contributed to the interpretation of results, and provided critical feedback on the manuscript. BV assisted in the study design, conducted literature search, and contributed to the interpretation of results. YL contributed to the study design, performed data extraction and analysis, contributed to the interpretation of results, and provided valuable input during manuscript preparation. JA participated in the study design and provided critical revisions to the manuscript. SZ participated in the study design and provided critical revisions to the manuscript. MU supervised the study, provided guidance on study design and methodology, contributed to the interpretation of results, critically reviewed the manuscript for intellectual content.

AUC: Area Under Curve

bSSFP: Balanced Steady-state Free Precession

CMR: Cardiovascular Magnetic Resonance Imaging

DOR: Diagnostic Odds Ratio

ECV: Extracellular Volume

EMB: Endomyocardial Biopsy

EGE: Early Gadolinium Enhancement

GraSE: Gradient and Spin Echo

LLC: Lake Louise Criteria

LGE: Late Gadolinium Enhancement

mLLC: Modified Lake Louise Criteria

MOLLI: Modified Look-Locker Inversion recovery

ms: milliseconds

PPV: Positive Predictive Value

PROSPERO: International Prospective Register of Systematic Reviews

QUADAS-2: Quality Assessment of Diagnostic Accuracy Studies

ROC: Receiver-operating Characteristic

SD: Standard Deviation

ShMOLLI: Shortened Modified Look-Locker Inversion recovery

SROC: Summary Receiver Operating Characteristic

T2: T2 mapping

T1: Native T1 mapping

1.5T: 1.5 Tesla

3T: 3 Tesla

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Diagnostic Performance of CMR Parametric Mapping as per Modified Lake Louise Criteria in Acute Myocarditis: An Updated Systematic Review and Meta-Analysis

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Introduction

Methods

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Results

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