Abstract
Background
Strain assessed by cardiac magnetic resonance (CMR) is a key prognostic indicator in myocardial infarction. However, the strain characteristics and prognostic value in myocardial infarction with nonobstructive coronary arteries (MINOCA) with different causes are unclear. This study aims to describe left atrial (LA) and left ventricular strain in patients with MINOCA and evaluate their predictive value for major adverse cardiovascular events (MACEs) in “true MINOCA” cases.
Methods and Results
This single‐center retrospective study included patients suspected of myocardial infarction who completed CMR during hospitalization. CMR images were used to obtain LA and left ventricular strain via CMR feature tracking. True MINOCA was defined by evidence of ischemia or infarction on CMR. MACEs included all‐cause death, recurrent myocardial infarction, stroke, heart failure, atrial fibrillation, and angina pectoris. This study included 386 patients, with a median time from admission to CMR of 4 days. LA and left ventricular strains varied by pathogenesis, with the lowest strain in patients with cardiomyopathy. For patients with true MINOCA, Cox regression showed that global longitudinal strain (hazard ratio [HR], 0.90 [95% CI, 0.82–0.99]; P=0.022) and LA reservoir strain (HR, 0.95 [95% CI, 0.91–0.99]; P=0.014) were independently associated with MACEs. Kaplan–Meier analysis indicated that patients with LA reservoir strain ≤21.25% or global longitudinal strain ≤16.4% had a significantly higher MACE risk (P<0.001). Integrating global longitudinal strain and LA reservoir strain improved MACE prediction.
Conclusions
LA and left ventricular strains vary among MINOCA pathogeneses. In true MINOCA patients, global longitudinal strain and LA reservoir strains independently predict MACE risk. Integrating these strains enhances MACE prediction.
Registration
URL: https://www.clinicaltrials.gov; Unique Identifier: NCT06502899.
Keywords: cardiac magnetic resonance, left atrial strain, left ventricular strain, major adverse cardiac events, MINOCA
Subject Categories: Myocardial Infarction, Magnetic Resonance Imaging (MRI)
Nonstandard Abbreviations and Acronyms
- GLS
global longitudinal strain
- GRS
global radial strain
- IDI
integrated discrimination improvement
- LGE
late gadolinium enhancement
- MACE
major adverse cardiovascular event
- NRI
net reclassification index
Clinical Perspective.
What Is New?
In this study, true myocardial infarction with nonobstructive coronary arteries (MINOCA) was defined by evidence of ischemia or infarction on cardiac magnetic resonance; this study reported for the first time the strain characteristics of different pathogeneses of MINOCA and the relationship between strain and major adverse cardiovascular events in patients with “true MINOCA.”
What Are the Clinical Implications?
Cardiac magnetic resonance can distinguish among various potential pathogeneses, such as myocardial infarction, myocarditis, Takotsubo syndrome, and structural cardiomyopathy. In this study, it was found that LA and left ventricular strains vary among MINOCA pathogeneses, which may provide additional information for clinical understanding and differentiation of pathogeneses in patients with suspected MINOCA.
Cardiac magnetic resonance–derived LA and left ventricular strains provide significant insights into the prognosis of MINOCA. Lowered LA and left ventricular strains were independently associated with an increased risk of major adverse cardiovascular events, highlighting its potential as a prognostic biomarker; integrating LA and left ventricular strains into routine cardiac magnetic resonance evaluations may improve risk stratification and clinical decision making for patients with true MINOCA.
Myocardial infarction (MI) with nonobstructive coronary arteries (MINOCA) typically involves various underlying causes and is characterized by clinical signs of MI with normal or mildly abnormal coronary angiography (stenosis severity <50%). 1 Previous data have shown that the prevalence of MINOCA in the MI population ranges from 2.6% to 15%. 2 , 3 , 4 Despite the less severe coronary stenosis in patients with MINOCA, their prognosis is not benign, with a 1‐year mortality rate of about 4.7%. 2 It is important to note that some studies have found the mortality rate in patients with MINOCA to be comparable with, or even higher than, that of patients with obstructive MI. 5 , 6 , 7 In fact, the prognosis for MINOCA can differ markedly depending on its underlying cause, underscoring the importance of thoroughly investigating and identifying the specific pathogenesis to guide effective treatment and management strategies.
Cardiac magnetic resonance (CMR) can distinguish among various potential causes, such as MI, myocarditis, Takotsubo syndrome, and structural cardiomyopathy, with diagnostic yields reported between 33% and 92%. 8 , 9 , 10 , 11 Currently, both the European Society of Cardiology and the American Heart Association guidelines recommend using CMR for diagnosing all patients with MINOCA. 12 , 13 In our study, “true MINOCA” was defined by evidence of ischemia or infarction on CMR. 12 While CMR is widely used for risk stratification in patients with MI, studies on CMR‐related parameters and prognosis specifically for patients with true MINOCA remain limited. In recent years, myocardial strain has emerged as a major research focus, with CMR feature tracking providing an accurate and objective assessment of subtle changes in myocardial deformation. 14 Left ventricular (LV) strain has proven to be a strong predictor of major adverse cardiovascular events (MACEs), independent of left ventricular ejection fraction (LVEF) and infarct size, in patients with MI. 15 , 16 Left atrial (LA) strain has gained increasing attention as it provides a more sensitive and reliable marker of early LA structural and functional abnormalities compared with traditional parameters like LA size and better predicts cardiovascular events. 17 , 18 In a study of 1046 patients with MI, Schuster et al 19 identified LA strain as an independent predictor of MACEs, with similar results reported in another study focusing on patients with ST‐segment–elevation MI (STEMI). 20 To date, there is a lack of reported data on the strain characteristics of patients with MINOCA with different pathogeneses, and the association between strain measures and prognosis in patients with true MINOCA remains poorly understood.
This study aimed to characterize LA and LV strains in patients with MINOCA with varying pathogeneses and to assess their predictive value for patients with MACEs in true MINOCA.
METHODS
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Study Population
This single‐center retrospective study included patients suspected of MI who underwent coronary angiography at the Affiliated Hospital of Xuzhou Medical University between January 2019 and June 2024. The Strengthening the Reporting of Observational Studies in Epidemiology cohort reporting guidelines was used in our study. 21 The inclusion criteria were a complete CMR examination during hospitalization, coronary angiography results showing coronary artery stenosis of <50%, and a peak high‐sensitivity troponin T value exceeding the 99th percentile. Exclusion criteria included missing or poor‐quality CMR images. In total, 386 patients were included, of which 131 were identified as having true MINOCA (Figure 1).
Figure 1. Study flowchart.
AMI indicates acute myocardial infarction; CAG, coronary angiography; CMR, cardiac magnetic resonance; MI, myocardial infarction; MINOCA, myocardial infarction with nonobstructive coronary arteries; and TS, Takotsubo syndrome.
This study was reviewed and approved by the institutional review board of the Affiliated Hospital of Xuzhou Medical University (No. XYFY2024‐KL189‐01), which waived the informed consent requirement due to the retrospective nature of the study and lack of patient harm.
Clinical Data Collection
For each patient, we collected demographic and baseline clinical data, including age, sex, and cardiovascular risk factors (smoking, hypertension, diabetes, and stroke) through a review of electronic medical records. We also documented discharge medications, including antiplatelet drugs, β blockers, renin–angiotensin–aldosterone system inhibitors, and statins. During hospitalization, blood samples were collected for standard analysis, including estimated glomerular filtration rate, lipids, fasting blood glucose, high‐sensitivity C‐reactive protein, NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide), and hs‐TnT, with high‐sensitivity C‐reactive protein, NT‐proBNP, and high‐sensitivity troponin T measured at their peak values during the hospital stay.
CMR Protocol and Related Parameters
CMR was performed on 3.0 T systems (Ingenia, Philips, The Netherlands). Our previously published papers have described the CMR protocol and CMR‐related parameters. 22 , 23 A balanced turbo field echo sequence was adopted. Scan parameters: slice thickness=7 mm, no interlayer gap; echo time=1.47 milliseconds, repetition time=2.94 milliseconds; flip angle=60°, field of view=300×300 mm, matrix=280×240 mm, and voxel size=1.22×1.22×8.0 mm3. CMR images (cine imaging, late gadolinium enhancement [LGE], T2 or T1 imaging) were acquired. The CVI42 (cvi42 version 5.13.5; Circle Cardiovascular Imaging, Canada) was used for image analysis. CMR image analysis was performed independently by 2 experienced doctors who were unknown in this study, and each patient was measured twice at different times. End‐diastolic volume, end‐systolic volume, and LVEF were automatically obtained and corrected for body surface area. The LA structure was analyzed by automatically tracing the LA border. The biplane method was used to calculate atrial volume, LA volume=(0.85×4‐chamber LA area×2‐chamber LA area)/shortest length of the LA vertical axis on 2 or 4 chambers with body surface area correction. LA ejection fraction=[(LAmax−LAmin)/LAmax]×100%. CMR feature tracking was used to obtain the strains, including LA reservoir strain, LA conduit strain, LA booster strain and LV global longitudinal strain (GLS), global circumferential strain, and global radial strain (GRS) (Figures 2 and 3). The reliability of strain acquisition using CMR feature tracking is shown in Table S1. All strains were analyzed by taking absolute values. Microvascular obstruction was observed from the LGE images. Microvascular obstruction was identified on LGE images as regions of hypoenhancement within areas of hyperenhancement. 24 LGE% was expressed as a percentage of the total LV myocardial mass.
Figure 2. Left ventricular strain measurements using cardiac magnetic resonance feature tracking.
Figure 3. Left atrial strain measurements using cardiac magnetic resonance feature tracking.
CMR Reclassification
Combined with relevant definitions, reclassification was performed on the basis of the presence of wall motion abnormalities on CMR, LGE images, T2‐weighted imaging or T1 imaging. All patients were classified as true MINOCA, myocarditis, Takotsubo syndrome, cardiomyopathy (other nonischemic cardiomyopathies, including dilated cardiomyopathy, hypertrophic cardiomyopathy, arrhythmogenic cardiomyopathy, etc), and normal. The specific definitions were as follows. True MINOCA was characterized by LGE or myocardial edema in the subendocardial or transmural region of the coronary territory, which was the evidence of ischemia or infarct by CMR criteria. 12 Takotsubo syndrome was identified by the presence of a focal wall motion abnormality not corresponding to a specific vascular territory, particularly in the mid or apical myocardium, along with the presence of myocardial edema but the absence of LGE. 25 Normal wall motion without any T2‐weighted or T1 imaging or LGE abnormality was classified as normal. Myocarditis was diagnosed according to the 2018 Lake Louise criteria. 26 Cardiomyopathy was diagnosed according to relevant definitions. 27
Clinical Outcomes and Follow‐Up
Patients were followed up from the time of discharge through outpatient visits or telephone contact using a standardized questionnaire. If the patient could not be contacted, information was collected through the patient's family or physician. The primary follow‐up end point was MACE, defined as all‐cause death, recurrent MI, stroke, heart failure, atrial fibrillation, or angina pectoris. Recurrent MI was diagnosed according to current European Society of Cardiology guidelines. 28 Stroke was defined as neurological dysfunction and cerebrovascular injury caused by cerebral ischemia or cerebral hemorrhage. 29 All patients who were lost to follow‐up were confirmed to be dead through the local official household registry.
Statistical Analysis
Statistical analysis was performed using SPSS 27.0 (IBM, Chicago, IL) and R (Lucent Technologies, Murray Hill, NJ). Continuous variables with a normal distribution were presented as mean±SD and analyzed using Student's t test. Nonnormally distributed continuous variables were reported as median (quartiles 25 to 75) and analyzed with the Mann–Whitney U test. Categorical variables were expressed as frequencies and percentages and analyzed using the χ 2 test. Cox proportional hazards regression models explored the association between LA and LV strains and MACEs. Variables with a P<0.1 from univariable analysis were included in the multivariable models using a stepwise forward selection method. Specifically, model 1 includes LGE%, LVEF, LA ejection fraction, body mass index, NT‐proBNP, high‐density leptin cholesterol, and STEMI. Model 2 includes LGE%, LVEF, LA ejection fraction, body mass index, NT‐proBNP, high‐density leptin cholesterol, STEMI, GLS, and LA reservoir strain. Visualization of Schoenfeld residuals was used to test the proportional hazard assumptions, and no assumption violation was observed. The receiver operating characteristic (ROC) was used to assess the ability of LA strain and LV strain to identify MACEs. The net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to evaluate the improvement in the discrimination and reclassification abilities of the model with LA strain or LV strain. Based on the cutoff values obtained from the ROC, all patients were divided into 2 groups and analyzed for the Kaplan–Meier curve. All P values were from 2‐sided tests, and the results were considered statistically significant at P<0.05.
RESULTS
Study Participants
A total of 386 participants were enrolled, with a median of 4 (3–5) days between admission and CMR. The cohort included 131 cases of true MINOCA, 84 cases of myocarditis, 49 cases of Takotsubo syndrome, 49 cases of cardiomyopathy, and 73 normal findings. Significant differences were observed among these groups in terms of LV–end‐diastolic volume index, LV–end‐systolic volume index, LVEF, LA ejection fraction, age, LGE, estimated glomerular filtration rate, hs‐TnT, NT‐proBNP, and high‐sensitivity C‐reactive protein levels. Additionally, there were notable differences in the percentages of stroke, male sex, smoking, purinergic receptor P2Y, G protein–coupled 12 inhibitors, aspirin, statins, angiotensin‐converting enzyme inhibitors/angiotensin II receptor blockers/sacubitril/valsartan, and β blockers. Furthermore, significant differences were found in LA reservoir strain, LA conduit strain, LA booster strain, GLS, global circumferential strain, and GRS among the group, with patients with cardiomyopathy exhibiting the lowest strain values (Table 1).
Table 1.
Characteristics of Participants
| True MINOCA (n=131) | TS (n=49) | Myocarditis (n=84) | Normal (n=73) | Cardiomyopathy (n=49) | P value | |
|---|---|---|---|---|---|---|
| Age, y | 54.50±11.35 | 56.88±11.64 | 48.75±11.23 | 51.81±11.85 | 56.55±12.40 | <0.001 |
| Body mass index, kg/m2 | 25.23±2.72 | 25.07±2.97 | 25.34±3.12 | 24.80±3.04 | 25.54±2.37 | 0.664 |
| Male sex, n (%) | 60 (45.8) | 4 (8.2) | 64 (76.2) | 37 (50.7) | 35 (71.4) | <0.001 |
| Smoking, n (%) | 57 (43.5) | 4 (8.2) | 36 (42.9) | 22 (30.1) | 19 (38.8) | <0.001 |
| Hypertension, n (%) | 56 (42.7) | 25 (51.0) | 34 (40.5) | 26 (35.6) | 23 (46.9) | 0.492 |
| Diabetes, n (%) | 18 (13.7) | 5 (10.2) | 12 (14.3) | 9 (12.3) | 9 (18.4) | 0.818 |
| Stroke, n (%) | 15 (11.5) | 3 (6.1) | 6 (7.1) | 4 (5.5) | 9 (18.4) | 0.132 |
| SBP, mm Hg | 130.66±16.08 | 129.57±17.94 | 131.08±18.84 | 132.23±18.93 | 125.63±18.97 | 0.345 |
| DBP, mm Hg | 81.37±12.35 | 79.94±10.35 | 81.04±13.12 | 80.32±11.94 | 78.55±11.39 | 0.695 |
| Heart rate, bpm | 75.17±13.59 | 73.57±10.85 | 77.45±12.42 | 74.88±12.28 | 77.57±12.5 | 0.33 |
| Triglycerides, mmol/L | 1.59±0.87 | 1.59±1.08 | 1.59±1.12 | 1.78±1.48 | 1.72±0.91 | 0.732 |
| Total cholesterol, mmol/L | 4.32±1.10 | 4.45±1.46 | 4.36±1.01 | 4.12±1.13 | 4.30±1.04 | 0.561 |
| LDL‐C, mmol/L | 2.57±0.88 | 2.57±1.27 | 2.52±0.89 | 2.38±1.01 | 2.42±0.90 | 0.648 |
| HDL‐C, mmol/L | 1.06±0.30 | 1.06±0.20 | 1.10±0.25 | 1.07±0.24 | 1.07±0.26 | 0.903 |
| Fasting blood glucose, mmol/L | 6.33±2.48 | 6.11±2.13 | 6.36±2.24 | 6.29±2.22 | 6.59±2.60 | 0.901 |
| eGFR, mL/min per 1.73 m2 | 111.07±14.12 | 113.53±12.42 | 112.61±10.59 | 113.25±11.49 | 106.65±15.56 | 0.039 |
| hs‐TnT, ng/L | 334.6 (130.8–750.3) | 430.9 (203.4–770.5) | 631.4 (256.7–883.7) | 63.6 (45.8–132.3) | 150.5 (69.0–403.5) | <0.001 |
| NT‐proBNP, pg/mL | 592.3 (205.7–1139.0) | 466.0 (264.8–990.5) | 710.8 (348.5–2011.5) | 242.2 (157.0–645.8) | 793.3 (350.4–2118.3) | <0.001 |
| hs‐CRP, mg/L | 4.50 (1.50–14.60) | 4.60 (1.70–13.10) | 20.05 (5.00–47.08) | 3.30 (1.15–7.70) | 5.90 (1.35–17.50) | <0.001 |
| LVEF, % | 55.91±9.34 | 53.42±6.47 | 54.98±9.78 | 62.80±7.74 | 49.43±10.60 | <0.001 |
| LV‐EDVi, mL/m2 | 76.23±18.99 | 73.60±15.39 | 80.44±22.14 | 72.64±16.61 | 83.63±21.48 | 0.011 |
| LV‐ESVi, mL/m2 | 40.82±14.51 | 34.76±8.38 | 46.54±20.08 | 33.59±13.77 | 49.62±18.84 | <0.001 |
| LA‐EDVi, mL/m2 | 19.35±11.45 | 18.65±6.41 | 19.64±9.90 | 17.45±7.81 | 22.25±10.90 | 0.106 |
| LA‐ESVi, mL/m2 | 34.24±14.51 | 32.13±10.86 | 33.79±13.31 | 33.75±11.67 | 36.60±15.54 | 0.586 |
| GLS, % | 17.21±3.89 | 15.14±3.47 | 16.25±4.52 | 20.44±4.16 | 12.64±4.29 | <0.001 |
| GCS, % | 19.07±4.36 | 18.12±3.64 | 17.89±4.56 | 21.71±4.67 | 15.87±4.73 | <0.001 |
| GRS, % | 27.77±6.24 | 27.52±4.55 | 27.53±6.28 | 30.36±6.95 | 24.15±6.39 | <0.001 |
| LA reservoir strain, % | 24.48±9.32 | 26.29±8.97 | 24.91±8.27 | 30.80±10.28 | 20.01±8.71 | <0.001 |
| LA booster strain, % | 12.28±5.33 | 11.90±5.39 | 11.32±5.64 | 13.57±6.42 | 9.44±5.68 | 0.002 |
| LA conduit strain, % | 12.21±5.78 | 14.40±6.52 | 13.60±5.60 | 17.23±6.42 | 10.57±6.24 | <0.001 |
| LAEF, % | 56.44±10.87 | 58.72±8.16 | 57.01±10.69 | 62.62±9.79 | 52.50±12.42 | <0.001 |
| LGE, n (%) | 128 (97.7) | 0 (0) | 78 (92.9) | 0 (0) | 29 (59.2) | <0.001 |
| LGE% | 13.93 (8.83–22.86) | 0 (0–0) | 15.25 (9.58–22.66) | 0 (0–0) | 16.81 (0–33.13) | <0.001 |
| LV mass index, g/m2 | 64.19±17.90 | 57.78±12.56 | 60.11±12.62 | 60.74±15.26 | 63.70±15.54 | 0.075 |
| P2Y12 inhibitors, n (%) | 79 (60.3) | 0 (0) | 1 (1.2) | 9 (12.3) | 1 (2.0) | <0.001 |
| Aspirin, n (%) | 124 (94.7) | 2 (4.1) | 10 (11.9) | 43 (58.9) | 13 (26.5) | <0.001 |
| Statins, n (%) | 122 (93.1) | 3 (6.1) | 8 (9.5) | 39 (53.4) | 8 (16.3) | <0.001 |
| ACEI/ARB/sacubitril/valsartan, n (%) | 97 (74.0) | 11 (22.4) | 23 (27.4) | 42 (57.5) | 31 (63.3) | <0.001 |
| β blockers, n (%) | 92 (70.2) | 17 (34.7) | 41 (48.8) | 33 (45.2) | 31 (63.3) | <0.001 |
ACEI indicates angiotensin‐converting enzyme inhibitor; ARB, angiotensin II receptor blocker; DBP, diastolic blood pressure; EDVi, end‐diastolic volume index; eGFR, estimated glomerular filtration rate; ESVi, end‐systolic volume index; GCS, global circumferential strain; GLS, global longitudinal strain; GRS, global radial strain; HDL‐C, high‐density lipoprotein cholesterol; hs‐CRP, high sensitivity C‐reactive protein; hs‐TnT, high sensitivity troponin T; LA, left atrial; LAEF, left atrial ejection fraction; LDL‐C, low‐density lipoprotein cholesterol; LGE, late gadolinium enhanced; LV, left ventricular; LVEF, left ventricular ejection fraction; MINOCA, myocardial infarction with nonobstructive coronary arteries; NT‐proBNP, N‐terminal pro‐B‐type natriuretic peptide; P2Y12, purinergic receptor P2Y, G protein coupled 12; and SBP, systolic blood pressure.
Baseline Characteristics of Patients With True MINOCA
In the true MINOCA group, during a median follow‐up of 26.5 months, 43 (32.8%) patients experienced MACEs (Table S2). Compared with the non‐MACE group, those with MACEs exhibited higher LGE%, NT‐proBNP, and high‐sensitivity C‐reactive protein, as well as a higher proportion of STEMI cases. Additionally, they demonstrated lower values for LA reservoir strain, LA conduit strain, LA booster strain, GLS, global circumferential strain, GRS, and LVEF (Table 2).
Table 2.
Characteristics of Participants With and Without MACEs
| Non‐MACE (n=88) | MACE (n=43) | P value | |
|---|---|---|---|
| LV‐EDVi, mL/m2 | 74.71±18.36 | 79.36±20.07 | 0.189 |
| LV‐ESVi, mL/m2 | 39.09±12.10 | 44.36±18.15 | 0.051 |
| LGE% | 12.09 (8.05–18.31) | 19.95 (11.97–32.09) | <0.001 |
| LV mass index, g/m2 | 63.63±16.27 | 65.35±21.00 | 0.608 |
| LA‐EDVi, mL/m2 | 18.40±10.94 | 21.31±12.33 | 0.173 |
| LA‐ESVi, mL/m2 | 33.60±13.96 | 35.56±15.66 | 0.469 |
| GLS, % | 18.07 ± 3.85 | 15.45 ± 3.37 | <0.001 |
| GCS, % | 19.72±3.98 | 17.74±4.85 | 0.015 |
| GRS, % | 28.63±5.65 | 26.02±7.04 | 0.024 |
| LA reservoir strain, % | 26.17±8.98 | 21.02±9.15 | 0.003 |
| LA booster strain, % | 13.10±5.10 | 10.58±5.44 | 0.010 |
| LA conduit strain, % | 13.07±5.59 | 10.44±5.82 | 0.014 |
| LVEF, % | 57.05±9.25 | 53.57±9.19 | 0.045 |
| LAEF, % | 57.72±10.57 | 53.83±11.13 | 0.055 |
| Age, y | 53.93±11.63 | 55.67±10.79 | 0.411 |
| Male, n (%) | 38 (43.18) | 22 (51.16) | 0.389 |
| Body mass index, kg/m2 | 25.53±2.83 | 24.63±2.41 | 0.076 |
| SBP, mm Hg | 131.72±15.53 | 128.51±17.13 | 0.286 |
| DBP, mm Hg | 81.99±12.16 | 80.09±12.78 | 0.411 |
| Heart rate, bpm | 75.39±14.28 | 74.72±12.23 | 0.794 |
| Triglycerides, mmol/L | 1.55±0.66 | 1.67±1.19 | 0.549 |
| Total cholesterol, mmol/L | 4.27±1.08 | 4.42±1.14 | 0.478 |
| LDL‐C, mmol/L | 2.56±0.81 | 2.60±1.00 | 0.794 |
| HDL‐C, mmol/L | 1.04 ± 0.22 | 1.12 ± 0.43 | 0.133 |
| Fasting blood glucose, mmol/L | 6.31±2.51 | 6.38±2.44 | 0.881 |
| eGFR, mL/min per 1.73 m2 | 111.12±13.19 | 110.99±16.02 | 0.960 |
| hs‐TnT, ng/L | 330.00 (133.95–643.25) | 371.50 (134.85–897.20) | 0.383 |
| NT‐proBNP, pg/mL | 519.85 (180.93–910.12) | 704.91 (379.20–1258.10) | 0.019 |
| hs‐CRP, mg/L | 4.20 (1.20–14.07) | 8.50 (2.65–21.00) | 0.041 |
| Microvascular obstruction, n (%) | 4 (4.55) | 6 (13.95) | 0.120 |
| STEMI, n (%) | 4 (4.55) | 10 (23.26) | 0.002 |
| Smoking, n (%) | 37 (42.05) | 20 (46.51) | 0.628 |
| Hypertension, n (%) | 41 (46.59) | 15 (34.88) | 0.203 |
| Diabetes, n (%) | 9 (10.23) | 9 (20.93) | 0.095 |
| Stroke, n (%) | 9 (10.23) | 6 (13.95) | 0.736 |
| Killip class, n (%) | 0.438 | ||
| I | 85 (96.59) | 40 (93.02) | |
| II | 2 (2.27) | 3 (6.98) | |
| III | 1 (1.14) | 0 (0.00) | |
| IV | 0 (0.00) | 0 (0.00) | |
| P2Y12 inhibitors, n (%) | 57 (64.77) | 22 (51.16) | 0.135 |
| Aspirin, n (%) | 84 (95.45) | 40 (93.02) | 0.867 |
| Statins, n (%) | 83 (94.32) | 39 (90.70) | 0.688 |
| ACEI/ARB/sacubitril/valsartan, n (%) | 67 (76.14) | 30 (69.77) | 0.435 |
| β blockers, n (%) | 63 (71.59) | 29 (67.44) | 0.626 |
ACEI indicates angiotensin–converting enzyme inhibitor; ARB, angiotensin II receptor blocker; DBP, diastolic blood pressure; EDVi, end‐diastolic volume index; eGFR, estimated glomerular filtration rate; ESVi, end‐systolic volume index; GCS, global circumferential strain; GLS, global longitudinal strain; GRS, global radial strain; HDL‐C, high‐density lipoprotein cholesterol; hs‐CRP, high sensitivity C‐reactive protein; hs‐TnT, high sensitivity troponin T; LA, left atrial; LDL‐C, low‐density lipoprotein cholesterol; LGE, late gadolinium enhanced; LV, left ventricular; LVEF, left ventricular ejection fraction; LAEF, left atrial ejection fraction; MACE, major adverse cardiovascular event; NT‐proBNP, N‐terminal pro‐B‐type natriuretic peptide; P2Y12, purinergic receptor P2Y, G protein coupled 12; SBP, systolic blood pressure; and STEMI, ST‐segment–elevation myocardial infarction.
Value of LA Strain and LV Strain for Identifying MACEs
ROC analysis was used to analyze the predictive value of LA strain and LV strain for MACEs. All measured LA and LV strain parameters effectively identified MACE (P<0.05), with LA reservoir strain and GLS showing the highest area under the curve (AUC). Specifically, the AUC for the LA reservoir strain was 0.674 (P=0.001) with a cutoff value of 21.25%, while GLS had an AUC of 0.714 (P<0.001) with a cutoff value of 16.4% (Figure 4, Table 3).
Figure 4. Receiver operating characteristic analysis of left ventricular strain and LA strain for MACEs.
AUC indicates area under the curve; GCS, global circumferential strain; GLS, global longitudinal strain; GRS, global radial strain; LA, left atrial; and MACEs, major adverse cardiovascular events.
Table 3.
ROC of Parameters for MACEs
| AUC | 95% CI | P value | Cutoff | Sensitivity | Specificity | |
|---|---|---|---|---|---|---|
| GLS, % | 0.714 | 0.621–0.808 | <0.001 | 16.4 | 0.698 | 0.693 |
| GCS, % | 0.660 | 0.559–0.760 | 0.003 | 18.15 | 0.558 | 0.727 |
| GRS, % | 0.620 | 0.516–0.725 | 0.026 | 27.4 | 0.535 | 0.705 |
| LA reservoir strain, % | 0.674 | 0.574–0.775 | 0.001 | 21.25 | 0.605 | 0.727 |
| LA booster strain, % | 0.639 | 0.537–0.742 | 0.010 | 11.95 | 0.628 | 0.602 |
| LA conduit strain, % | 0.651 | 0.546–0.755 | 0.005 | 9.7 | 0.581 | 0.705 |
AUC indicates area under the curve; GCS, global circumferential strain; GLS, global longitudinal strain; GRS, global radial strain; LA, left atrial; MACE, major adverse cardiovascular event; and ROC, receiver operating characteristic.
Relationship Between MACEs and Strain in Patients With True MINOCA
Cox regression analysis was used to explore the variables associated with MACEs. The univariable analysis showed that LGE%, GLS, global circumferential strain, GRS, LA reservoir strain, LA booster strain, LA conduit strain, LVEF, and STEMI were associated with MACEs. Due to collinearity among LA strain and LV strain measures, and based on the previous ROC AUC results, only LA reservoir strain and GLS were included in subsequent analyses. After adjusting for variables with a P<0.1 from the univariable analysis except GLS and LA reservoir strain (model 1), it was found that LGE% and LVEF were independently associated with MACEs. Further adjustments, incorporating all variables with a P<0.1 from the univariable analysis (model 2), demonstrated that LGE%, GLS (hazard ratio [HR], 0.90 [95% CI, 0.82–0.99]; P=0.022), and LA reservoir strain (HR, 0.95 [95% CI, 0.91–0.99]; P=0.014) were independently associated with MACEs (Table 4).
Table 4.
Univariable and Multivariable Cox Proportional Hazards Model for MACEs
| Univariable | Multivariable | |||||
|---|---|---|---|---|---|---|
| HR (95% CI) | P value | Model 1 | Model 2 | |||
| HR (95% CI) | P value | HR (95% CI) | P value | |||
| LGE% | 1.04 (1.02–1.06) | <0.001 | 1.04 (1.02–1.06) | <0.001 | 1.03 (1.01–1.05) | 0.006 |
| LV mass index, g/m2 | 1.00 (0.99–1.02) | 0.590 | ||||
| LV‐EDVi, mL/m2 | 1.01 (0.99–1.02) | 0.316 | ||||
| LV‐ESVi, mL/m2 | 1.01 (1.00–1.03) | 0.132 | ||||
| LA‐EDVi, mL/m2 | 1.01 (0.99–1.04) | 0.301 | ||||
| LA‐ESVi, mL/m2 | 1.00 (0.98–1.02) | 0.738 | ||||
| GLS, % | 0.86 (0.79–0.93) | <0.001 | Not in model | 0.90 (0.82–0.99) | 0.022 | |
| GCS, % | 0.90 (0.83–0.97) | 0.006 | Not in model | Not in model | ||
| GRS, % | 0.93 (0.89–0.98) | 0.004 | Not in model | Not in model | ||
| LA reservoir strain, % | 0.94 (0.90–0.98) | 0.002 | Not in model | 0.95 (0.91–0.99) | 0.014 | |
| LA booster strain, % | 0.90 (0.85–0.97) | 0.003 | Not in model | Not in model | ||
| LA conduit strain, % | 0.94 (0.88–0.99) | 0.049 | Not in model | Not in model | ||
| LVEF, % | 0.97 (0.94–1.00) | 0.028 | 0.964 (0.935–0.994) | 0.018 | ||
| LAEF, % | 0.97 (0.95–1.00) | 0.072 | ||||
| Age, y | 1.00 (0.98–1.03) | 0.785 | ||||
| Male sex, n (%) | 1.32 (0.73–2.40) | 0.366 | ||||
| Body mass index, kg/m2 | 0.90 (0.80–1.00) | 0.054 | ||||
| SBP, mm Hg | 0.99 (0.97–1.01) | 0.155 | ||||
| DBP, mm Hg | 0.99 (0.96–1.01) | 0.309 | ||||
| Heart rate, bpm | 1.00 (0.97–1.02) | 0.684 | ||||
| hs‐TnT, ng/L | 1.31 (0.70–2.43) | 0.408 | ||||
| NT‐proBNP, pg/mL | 1.86 (0.96–3.61) | 0.063 | ||||
| hs‐CRP, mg/L | 1.01 (1.00–1.02) | 0.291 | ||||
| Triglycerides, mmol/L | 1.06 (0.77–1.47) | 0.695 | ||||
| Total cholesterol, mmol/L | 1.00 (0.74–1.36) | 0.991 | ||||
| LDL‐C, mmol/L | 0.95 (0.64–1.40) | 0.814 | ||||
| HDL‐C, mmol/L | 1.91 (0.94–3.89) | 0.084 | ||||
| Fasting blood glucose, mmol/L | 0.99 (0.89–1.12) | 0.947 | ||||
| eGFR, mL/min per 1.73 m2 | 1.00 (0.98–1.02) | 0.902 | ||||
| Microvascular obstruction, n (%) | 2.01 (0.84–4.77) | 0.115 | ||||
| STEMI, n (%) | 2.96 (1.45–6.05) | 0.003 | ||||
| Smoking, n (%) | 1.25 (0.68–2.28) | 0.473 | ||||
| Hypertension, n (%) | 0.66 (0.35–1.24) | 0.199 | ||||
| Diabetes, n (%) | 1.83 (0.88–3.82) | 0.109 | ||||
| Stroke, n (%) | 1.19 (0.50–2.83) | 0.691 | ||||
Model 1: Adjusting all variables with a P<0.1 in univariate analysis excluded LA strain and LV strain. Model 2: Adjusting all variables with a P<0.1 in univariate analysis excluded GCS, GRS, LA booster strain, and LA conduit strain. ACEI indicates angiotensin‐converting enzyme inhibitor; ARB, angiotensin II receptor blocker; DBP, diastolic blood pressure; EDVi, end‐diastolic volume index; eGFR, estimated glomerular filtration rate; ESVi, end‐systolic volume index; GCS, global circumferential strain; GLS, global longitudinal strain; GRS, global radial strain; HDL‐C, high‐density lipoprotein cholesterol; hs‐CRP, high sensitivity C‐reactive protein; hs‐TnT, high sensitivity troponin T; LA, left atrial; LAEF, left atrial ejection fraction; LDL‐C, low‐density lipoprotein cholesterol; LGE, late gadolinium enhanced; LV, left ventricular; LVEF, left ventricular ejection fraction; MACE, major adverse cardiovascular event; NT‐proBNP, N‐terminal pro‐B‐type natriuretic peptide; SBP, systolic blood pressure; and STEMI, ST‐segment–elevation myocardial infarction.
Patients were grouped according to the cutoff value of the ROC. The Kaplan–Meier curves revealed that patients with LA reservoir strain ≤21.25% or GLS ≤16.4% had a significantly higher long‐term risk of MACEs than those with LA reservoir strain >21.25% or GLS > 16.4%. Additionally, when patients were divided into 4 groups, those with LA reservoir strain ≤21.25% and GLS ≤16.4% exhibited the highest long‐term risk of MACEs, with both comparisons showing a log‐rank P value <0.001 (Figure 5).
Figure 5. Kaplan–Meier curve for patients based on the cutoff values of GLS and LA reservoir strain.
A, Kaplan–Meier curve of LA reservoir strain for MACEs. B, Kaplan–Meier curve of GLS for MACEs. C, Kaplan–Meier curve of LA reservoir strain and GLS for MACEs. GLS indicates global longitudinal strain; LA, left atrial; and MACEs, major adverse cardiovascular events.
Incremental Value of GLS and LA Reservoir Strain for Predicting MACE
The AUC of LGE combined with GLS for predicting MACEs was 0.784 (P<0.001). The AUC of LGE combined with LA reservoir strain for predicting MACEs was 0.754 (P<0.001). When all 3 parameters were combined, the AUC for MACEs was 0.787 (P<0.001) (Figure 6, Table 5).
Figure 6. Receiver operating characteristic analysis of combined parameters for MACEs.
AUC indicates area under the curve; GLS, global longitudinal strain; LA, left atrial; LGE, late gadolinium enhancement; and MACEs, major adverse cardiovascular events.
Table 5.
ROC of Combined Parameters for MACE
| AUC | 95% CI | P value | Sensitivity | Specificity | |
|---|---|---|---|---|---|
| LGE | 0.704 | 0.606–0.801 | <0.001 | 0.651 | 0.727 |
| LGE+GLS | 0.784 | 0.698–0.869 | <0.001 | 0.721 | 0.818 |
| LGE+LA reservoir strain | 0.751 | 0.663–0.839 | <0.001 | 0.791 | 0.625 |
| LGE+GLS+LA reservoir strain | 0.787 | 0.709–0.866 | <0.001 | 0.930 | 0.523 |
AUC indicates area under the curve; GLS, global longitudinal strain; LA, left atrial; LGE, late gadolinium enhancement; MACE, major adverse cardiovascular event; and ROC, receiver operating characteristic.
Subsequently, the NRI and IDI were calculated, revealing that incorporating GLS or LA reservoir strain into the model that includes LGE% significantly improved the discrimination and reclassification accuracy for MACEs (P<0.05). When both the LA reservoir strain and GLS were included in the model, the NRI was >0 (NRI, 0.618 [95% CI, 0.2694–0.9674]; P<0.001), and the IDI value was improved by 9.0% (IDI, 0.090 [95% CI, 0.0368–0.1429]; P<0.001), suggesting that the integration of GLS or LA reservoir strain could significantly improve the ability of the model to predict MACEs (Table 6).
Table 6.
Discrimination Accuracy and Reclassification of LA and LV Strains for MACEs
| NRI | IDI | |||
|---|---|---|---|---|
| Estimate (95% CI) | P value | Estimate (95% CI) | P value | |
| LGE | Reference | … | Reference | … |
| LGE+GLS | 0.504 (0.1494–0.8580) | 0.005 | 0.064 (0.0218–0.1070) | 0.003 |
| LGE+LA reservoir strain | 0.552 (0.2029–0.9018) | 0.002 | 0.056 (0.0123–0.0995) | 0.012 |
| LGE+GLS+LA reservoir strain | 0.618 (0.2694–0.9674) | <0.001 | 0.090 (0.0368–0.1429) | <0.001 |
GLS indicates global longitudinal strain; IDI, integrated discrimination improvement; LA, left atrial; LGE, late gadolinium enhancement; LV, left ventricular; MACE, major adverse cardiovascular event; and NRI, net reclassification index.
DISCUSSION
To the best of our knowledge, this study reported for the first time the strain characteristics of different pathogeneses of MINOCA and the relationship between strain and MACEs in patients with true MINOCA. The main findings were as follows: Among the various pathogeneses of MINOCA, the strain was lowest in cardiomyopathy; reduced LA reservoir strain and GLS were found to be independent risk factors for MACEs in patients with true MINOCA; patients with an LA reservoir strain ≤21.25% or GLS ≤16.4% had a significantly higher long‐term risk of MACEs, and incorporating LA reservoir strain or GLS into the evaluation significantly improved the prediction of MACE.
MINOCA is not a benign process and is often accompanied by a higher risk of MACEs. 2 In our study, we found that 32.8% of patients with MINOCA experienced MACEs. The current clinical treatment and management of patients with MINOCA remains challenging due to its diagnosis often encompassing multiple pathogeneses. Therefore, investigating and identifying the specific underlying causes of MINOCA is critical for developing appropriate treatment strategies. 30 Given the elevated risk of MACEs in this population, it is imperative for clinicians to adopt a comprehensive and individualized approach to the care of patients with MINOCA, which includes close monitoring and targeted therapies based on the identified pathogeneses.
Recent guideline statements from the European Society of Cardiology and American Heart Association strongly recommend CMR imaging for evaluating patients with suspected MINOCA. 12 , 13 In a previous prospective study, the median time from admission to CMR was 4 (2–6) days, and CMR confirmed the diagnosis in 79% of cases. 11 Similarly, in our study, the median time from admission to CMR was 4 (3–5) days, and the CMR definitively diagnosed 81% of the patients. In fact, the distribution of patients ultimately diagnosed by CMR and their underlying pathogeneses vary considerably. In a previous study, the median time from admission to CMR was 10 (4–54) days, with CMR confirming a diagnosis in 71% of patients and the most frequent diagnoses being myocarditis (39%) and MI (15%). 31 Additionally, another study revealed that 63.8% of patients had an ischemic pathogenesis, 20.7% had a nonischemic pathogenesis, and 15.5% showed no significant abnormalities. 32 These different results may be related to the following 2 factors: First, variations in the populations studied could lead to varying distributions of pathogeneses. For instance, Reynolds et al 32 included female patients with a clinical diagnosis of MI who underwent coronary angiography, resulting in a lower proportion of myocarditis cases (15%) compared with the CMR meta‐analysis of patients with MINOCA, which reported a 33% incidence of myocarditis. 33 Conversely, Vágó et al 34 reported a myocarditis diagnosis in 54% of patients referred specifically for this condition. Additionally, the timing of CMR significantly affects its diagnostic utility in suspected MINOCA cases, as features such as edema and areas at risk may diminish over time. 35 , 36 , 37 Previous studies indicate that performing CMR within 2 weeks can nearly double the incidence of LGE abnormalities, resulting in a diagnostic rate of 90%. 31 , 38 , 39 , 40 Williams et al 37 reported that early implementation of CMR could increase the diagnostic rate from 72% to 94%. Consequently, early refinement of CMR screening is widely endorsed. 41
Data on the long‐term prognosis of true MINOCA are still relatively scarce and not well defined. A prior study with a median follow‐up of 34.8 months indicated that more than one‐third (35.8%) of patients experienced MACEs. 42 In our study, with a median follow‐up of 26.5 months, the incidence of MACEs was 32.8%. These differences may be attributed to variations in racial demographics, the definition of MACE, and the follow‐up time. Consequently, further research is necessary to clarify the prognosis of patients with true MINOCA. While strain has been well established as a prognostic indicator in patients with acute coronary syndrome, 15 , 16 , 19 , 20 the strain characteristics of patients with MINOCA with various pathogeneses identified by CMR, and the relationship between strain and prognosis in true MINOCA cases remain inadequately explored. In this study, we observed a notable variation in myocardial strain across different pathogeneses of MINOCA. Specifically, strain values were lowest in patients with cardiomyopathy and highest in those with normal CMR performance. Considering that strains are indicators of myocardial function, such a result seems to be acceptable. This also underscores the critical role of accurate pathogenetic diagnosis in suspected MINOCA cases. We innovatively realized that reduced LA reservoir strain and GLS were independent risk factors for MACE in patients with true MINOCA. In previous studies, GLS was shown to be an independent predictor of prognosis in patients with MI, even after adjusting for traditional cardiac risk factors such as LVEF and infarct size. 15 , 16 Additionally, LA reservoir strain has been identified as an independent risk factor for MACEs in other MI cohorts. 19 , 20 Our study corroborates these findings, showing that GLS, LA reservoir strain, and LGE are independently associated with MACEs. Strain, as a tool for quantifying myocardial deformation, can sensitively and reliably assess the presence and severity of myocardial remodeling. 43 What is known is that myocardial remodeling is an important mechanism for MACEs in cardiovascular disease. However, it is worth noting that LVEF was not independently associated with MACEs after adjusting for strain‐related variables. This may be due to the fact that while LVEF is an important prognostic and functional indicator in patients with MI, 44 it has limitations in detecting subtle changes in cardiac function and does not reliably predict long‐term recovery when measured early after reperfusion. 45 , 46 These studies may partially explain our findings. Furthermore, the cutoff values of LA reservoir strain and GLS in our study were 21.25% and 16.4%, respectively, which were higher than those reported in studies of other MI types. 15 , 47 This discrepancy may be due to the generally higher strains observed in patients with true MINOCA. Specifically, higher strains may be associated with less myocardial damage, higher proportion of female sex, and younger age. In our study, we found that patients with LA reservoir strain ≤21.25% or GLS ≤16.4% had a significantly higher long‐term risk of MACE. LGE, a well‐established risk factor for true MINOCA, 48 was also found to be independently associated with MACEs in our study of patients with true MINOCA. Additionally, the calculation of NRI and IDI revealed that incorporating GLS or LA reservoir strain significantly enhances the model's predictive capability for MACEs. We found significantly different strains in patients with MINOCA of various pathogeneses, and these data demonstrate the importance of early CMR in ensuring a rapid and accurate diagnosis, which is essential for providing adequate treatment and follow‐up to improve the overall prognosis of such patients.
Overall, our findings highlight the significant role of GLS and LA reservoir strain in prognostic assessment for patients with true MINOCA. These parameters offer valuable prognostic insights beyond traditional cardiac risk factors like LVEF and could enhance risk stratification following MI. Lower GLS and LA reservoir strain are particularly strong indicators of poor prognosis and may represent new targets for therapeutic intervention.
Limitations
Several limitations should be noted in this study. First, this was a retrospective observational single‐center study with a limited sample size, and there may be some unavoidable bias. Second, we lacked data on invasive optical coherence tomography of the coronary arteries, which could have provided additional insights into MINOCA cases with normal CMR findings, as some studies suggest. Third, the cohort in our study has limited racial diversity. Therefore, some results may need to be validated repeatedly in patients of different races with MINOCA. Fourth, not all patients with clinically suspected MINOCA had a perfected CMR examination, which may have led to missed pathogenetic diagnoses. Despite these limitations, the study primarily focused on the association between myocardial strains and the prognosis of patients diagnosed with true MINOCA via CMR.
CONCLUSIONS
LA and LV strains differ significantly among patients with MINOCA with different pathogeneses. GLS and LA reservoir strain are associated with the risk of MACEs in patients with true MINOCA. Even after adjusting for LGE and LVEF, GLS and LA reservoir strains remain independently associated with MACEs. Integration of LA reservoir strain or/and GLS can significantly improve the prediction of MACE. CMR assessment of GLS and LA reservoir strain may provide important prognostic information for predicting MACEs in patients with true MINOCA.
Sources of Funding
This work was partly supported by the Jiangsu Commission of Health (Grant No. M2021046) and the Science and Technology Commission of Shanghai Municipality (Grant No. 20dz1207200).
Disclosures
None.
Supporting information
Tables S1–S2
This manuscript was sent to Timothy C. Wong, MD, MS, Associate Editor, for review by expert referees, editorial decision, and final disposition.
Supplemental Material is available at https://www.ahajournals.org/doi/suppl/10.1161/JAHA.124.039395
For Sources of Funding and Disclosures, see page 13.
Contributor Information
Wenliang Che, Email: chewenliang@tongji.edu.cn.
Yuan Lu, Email: xyfyluyuan@163.com.
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Supplementary Materials
Tables S1–S2