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. 2022 Dec 21;95:1–6. doi: 10.1016/j.clinimag.2022.12.004

Subclinical cardiac involvement in student athletes after COVID-19 infection - Evaluation using feature tracking cardiac MRI strain analysis

Sarv Priya a,⁎, Sabarish Narayanasamy a, Abigail Walling b, Ravi C Ashwath c
PMCID: PMC9769024  PMID: 36565609

Abstract

Objectives

To evaluate subclinical cardiac dysfunction in student athletes after COVID-19 infection using feature tracking cardiac MRI strain analysis.

Methods

Student athletes with history of COVID-19 infection underwent cardiac MRI as part of screening before return to competitive play. Subjects were enrolled if they had no or mild symptoms, normal cardiac MRI findings with no imaging evidence of myocarditis. Feature tracking strain analysis was performed using short and long axis cine MRI images of athletes and a separate cohort of healthy controls. Differences between the cardiac strain parameters were statistically analyzed by Mann-Whitney U test.

Results

The study cohort included 122 athletes (49 females, mean age 20 years ± 1.5 standard deviations) who had a history of COVID-19, and 35 healthy controls (24 females, mean age 34 years ± 18 standard deviations). COVID-19 positive athletes had normal physiologic cardiac adaptations, including significantly higher left and right ventricle end-diastolic volumes (p = 0.00001) when compared to healthy controls. There was no significant difference between biventricular ejection fraction between athletes and control subjects (p > 0.05). Cardiac MRI parameters, including left ventricle global longitudinal strain (LV-GLS), global circumferential strain (LV-GCS), and global radial strain (LV-GRS) values were normal but slightly lower in athletes compared to controls. LV-GCS and LV-GRS were significantly lower in athletes compared to controls (p = 0.007 and p = 0.005 respectively), but there was no significant difference for LV-GLS (p = 0.088).

Conclusion

In this study of 122 athletes, there was no evidence of subclinical myocardial alterations following recovery from COVID-19 found on cardiac MRI strain analysis. When compared to healthy controls, the competitive athletes had higher end-diastolic volume indices and reduced, albeit normal, strain values of LV-GLS, LV-GCS, and LV-GRS.

Keywords: Cardiac MRI strain analysis, COVID-19, Subclinical myocardial dysfunction, Athletes

1. Introduction

SARS-CoV-2 (COVID-19) has been primarily known as a disease of the pulmonary system. However, there is building evidence of the acute and chronic effects that this virus has on many other organs, especially the heart. Hypothesized etiologies for the COVID-19 induced cardiac injury include myocarditis, systemic cytokine-mediated injury, microvascular injury, and stress-related cardiomyopathy.1 Up to 80% of individuals recovering from COVID-19 show cardiac MRI abnormalities of myocardial inflammation, regional myocardial scarring, and pericardial enhancement.1., 2. These cardiac structural changes may lead to an increased risk of dysrhythmias, ischemic heart disease, pericarditis, myocarditis, heart failure, and thromboembolic disease.3

During the initial stages of COVID-19 pandemic, concerns were raised about myopericarditis in athletes recovering from COVID-19 infection. Rajpal et al.4 reported a 15% incidence of myocarditis in college athletes with COVID-19 while Brito et al.5 reported a 40% incidence of pericarditis in athletes. This raised significant concern for sudden cardiac death in both collegiate and professional athletes leading to the performance of screening cardiac MRI to rule out myopericarditis before returning to competitive play. However, subsequent single center studies showed a far lower incidence of myocarditis ranging between 0 and 3%.6., 7., 8. In addition, the data from large COVID registries also showed minimal incidence of myopericarditis (0.1–3%) in the athletic population.9., 10. Moreover, the Big Ten COVID cardiac registry that mandated universal screening of 1597 athletes with CMR found myocarditis in only 2.3% population.11

Due to the concern of long COVID where symptoms may persist or develop later, it may be helpful to detect any myocardial alterations before the development of clinical myocardial damage (reduced ejection fraction or myocardial fibrosis) that may be caused secondary to SARS-COVID-19 virus.12 At present, the data is scarce for evidence of subclinical myocardial dysfunction in athletes with positive COVID-19 infection but with no or minimal cardiac symptoms, normal ventricular function and no imaging evidence of myocarditis. Myocardial strain imaging is a special technique that can identify subclinical myocardial dysfunction before an obvious reduction in heart function and is more sensitive than left ventricular ejection fraction as it is unrelated to stroke volume or left ventricular size.13 As such, this study aims to fill the knowledge gap about identifying subclinical cardiac dysfunction in athletes after COVID-19 infection using feature tracking cardiac MRI strain analysis.

2. Material and methods

2.1. Study participants

This single center retrospective study was approved by the local institutional review board (IRB) (IRB ID # 202109397) and performed in accordance with the Declaration of Helsinki following relevant guidelines and regulations. The informed consent requirement was waived by the IRB. Patients were identified using a radiology information system and electronic medical records (EMR). The study identified all athletes between the period Jan 1, 2020, and Oct 1, 2021, who had a history of COVID-19 infection (confirmed by polymerase chain reaction (PCR) testing) and were referred for cardiac MRI for evaluation of myocarditis before returning to competitive sports. The athletic participants were included both before and after Big Ten Conference mandate14 of required CMRI testing before returning to competitive play. Part of the data was previously published as part of the Big Ten COVID cardiac registry which showed a low incidence of myocarditis after COVID-19 infection.11 Subjects were included if they met the following criteria: i) complete cardiac MRI examination including T1 mapping (pre-contrast and post contrast) and late gadolinium enhanced (LGE) images; ii) motion and artifact free balanced stead-state free precision cine images in short-axis, 4 chamber and 3 chamber planes; iii) hematocrit testing within 24 h of cardiac MRI; iv) cardiac MRI exam findings of normal left ventricular function (ejection fraction >55% and right ventricular function (ejection fraction >50%)15., 16., 17., 18. and no imaging evidence of myocarditis; and v) laboratory evidence of normal high sensitivity troponin and creatine kinase -MB. Exclusion criteria were as follows: i) prior cardiac history or history of cardiac surgery; ii) presence of moderate or severe cardiopulmonary symptoms necessitating treatment or hospital admission; iii) non-diagnostic cardiac MRI images; Iv) CMR findings positive for any diagnosis other than myocarditis (for example shunt, non-compaction, aortopathy) and vi) non availability of COVID-19 PCR testing.

A separate cohort of healthy subjects was identified from the EMR data base who had undergone cardiac MRI examination as part a of work up for family history of cardiovascular disease. These control subjects were included in the study if they had a normal cardiac MRI exam, no personal history of cardiac disease, and no personal history of cardiac interventions.

2.2. Cardiac MRI

Cardiac MRI was performed on a Siemens 1.5 T MRI (Siemens, Erlangen, Germany) scanner. The study protocol included: multiplane balanced stead state free precision cine images, late gadolinium enhanced images obtained between 10 and 15 min after administration of 0.15 mmol/kg body weight of Gadavist contrast, native and post contrast T1 mapping and precontrast T2 mapping at basal, mid and apical short-axis slices. Post contrast T1 mapping was done at 15–20 min after contrast administration. Cardiac cine imaging was performed with the following parameters: repetition time msec/echo time msec, 35.75/1.15; field of view, 330–380 mm; matrix size, 256 × 160 mm; voxel size, 1.5 × 1.5 × 8.0 mm; bandwidth, 930 Hz/pixel; flip angle, 63°; slice thickness, 8 mm; and gap, 2 mm.

2.3. Cardiac MRI image analysis

Cardiac MRI images were analyzed using commercially available post-processing software (Medis) for both functional analysis and T1 mapping. Extracellular volume fraction was derived using native and post contrast T1 mapping values for blood and myocardium and using hematocrit level. T2 mapping analysis was performed at the scanner using inline Siemens's mapping analysis. Late gadolinium enhanced images were visually assessed for location and pattern (subendocardial, mid wall, subepicardial) of myocardial enhancement. T1 and T2 mapping analysis was only performed for COVID-19 positive athletes as these were not available for control subjects.

Images were anonymized and transferred to an independent workstation (CVI42, version 5.1; Circle Cardiovascular Imaging) for strain analysis. Semiautomated left ventricle contouring was done in short-axis and two long axis cine images and feature tracking strain analysis was performed as described before.19 2-dimensional strain analysis was done, and the following values were recorded: Left ventricle (LV) global circumferential strain (GCS); global longitudinal strain (GLS); and global radial strain (GRS).

2.4. Statistical analysis

All statistical analyses were performed using R version 4.1.3. Categorical variables were expressed as counts and percentages, and continuous variable were expressed as mean ± standard deviation or median and interquartile range. Normality of distribution was tested by using the Shapiro-Wilk test. Comparisons between two groups were performed with the unpaired Student t-test (for normal distribution) or Mann-Whitney U test (for nonnormal distribution) with continuous variables; and Chi-Squared test or Fisher's Exact test with categorical variables. A two-tailed significance level of α = 0.05 was considered to indicate a significant difference.

3. Results

3.1. Patient characteristics

The final analysis cohort consisted of 122 athletes (mean age 20 years ± 1.5 standard deviation; 49 females) and 35 control subjects (mean age 34 years ± 18 standard deviation; 24 females) (Fig. 1 ). Clinical characteristics can be found in Table 1 . The time interval from COVID-19 test positivity to CMRI testing ranged between 10 and 169 days (median [interquartile range], 21.514 days). Out of 122 athletes, 111 athletes were scanned after the Big Ten Conference mandate. Healthy control subjects were significantly older than athletes with positive COVID-19 test results (p = 0.004). Males and females were fairly equally represented in the total patient cohort; however, female patients encompassed 40% of the COVID-19 positive athletes as opposed to the 66% females in healthy controls (p = 0.014). On average, athletes had significantly lower body mass index (p = 0.036) and a higher body surface area (p = 0.001) compared to the controls.

Fig. 1.

Fig. 1

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Consort diagram shows selection criteria for athletes with COVID-19 infection.

Table 1.

Clinical characteristics of study participants.

Characteristic Healthy control subjects
(n = 35)		 Athletes with COVID-19
(n = 122)		 P value
Median age (y) 30 ± 18 20 ± 1.5 0.005
Average age (y) 34 ± 18 20.4 ± 1.5 0.004
No. of females (%) 24 (66) 49 (40) 0.002
BMI (kg/m2) 28.2 ± 6.8 25.4 ± 4.5 0.018
BSA (m2) 1.81 ± 0.40 2 ± 0.2 0.001
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Note.—Unless otherwise specified, data are means ± standard deviation. P < 0.05 is considered to indicate a significant difference. P values between participants (all COVID-19 participants and healthy control subjects) calculated with Mann-Whitney U test or Pearson's Chi-squared test.

3.2. Cardiac MRI parameters

Cardiac MRI parameters among COVID-19 positive athletes and controls are provided in Table 2 . COVID-19 positive athletes had significantly higher left ventricle end-diastolic volume (p = 0.00001) and right ventricle end-diastolic volume (p = 0.00001) compared to controls. There was no significant difference between biventricular ejection fraction among athletes and control subjects (p value >0.05).

Table 2.

Cardiac MRI parameters of participants.

Cardiac MRI parameters Healthy control subjects
(n = 35)		 Athletes with COVID-19
(n = 122)		 P value
LV ejection fraction (%) 61.5 ± 5.3 60.5 ± 3.6 0.111
Indexed LV EDV (mL/m2) 78.5 ± 14.7 99 ± 14 <0.00001
Indexed LV SV (mL/m2) 47.9 ± 8.7 59.7 ± 9.3 <0.00001
Indexed LV mass (g/m2) 47.6 ± 12.6 53.2 ± 14 <0.073
RV ejection fraction (%) 55.4 ± 5.5 56 ± 4.2 0.645
Indexed RV EDV (mL/m2) 73.4 ± 17.1 99.2 ± 18 <0.00001
Indexed RV SV (mL/m2) 40.6 ± 9.7 55.5 ± 10.4 <0.00001
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Note. —Unless otherwise specified, data are means ± standard deviation. P values between participants (all COVID-19 participants and healthy control subjects) calculated with Mann-Whitney U test (continuous variables).

3.3. Strain parameters

Table 3 shows the differences in average strains for athletes and controls. Left ventricle global longitudinal strain (LV-GLS), global circumferential strain (LV-GCS) and global radial strain (LV-GRS) values were normal but slightly lower in athletes compared to controls. A statistically significant difference was seen for LV-GRS (p = 0.007) and LV-GCS (p = 0.005) among athletes and controls but not for LV-GLS values (p = 0.088). Fig. 2, Fig. 3, Figs. 4 show boxplots depicting the strain distribution in controls and athletes for LV-GRS, LV-GCS and LV-GLS respectively. Fig. 5 depicts representative image of global peak circumferential strain for an athlete and a control subject.

Table 3.

Mean strain parameters for healthy controls & COVID-19 + athletes.

Strain Healthy control subjects
(n = 35)		 Athletes with COVID-19
(n = 122)		 P-value
2DLV rad 32 (30.9 to 35.9) 29.7 (26.8 to 16.9) <0.011
2DLV circ −19 (−20.3 to − 18.2) −18 (−19.4 to − 16.9) <0.007
2DLV long −18 (− 20.4 to − 16.3 −17 (−18.5 to − 15.6) 0.123
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Note — Unless otherwise specified, data are median (Interquartile range). P-values constructed from Mann-Whitney U test.

Fig. 2.

Fig. 2

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Boxplots depicting the strain distribution in controls and athletes for LV-GRS (global radial strain).

Fig. 3.

Fig. 3

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Boxplots depicting the strain distribution in controls and athletes for LV-GCS (global circumferential strain).

Figs. 4.

Figs. 4

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Boxplots depicting the strain distribution in controls and athletes for LV-GLS (global longitudinal strain).

Fig. 5.

Fig. 5

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Polar maps showing representative example of peak circumferential strain in athlete (A) and control subject (B).

4. Discussion

Our study findings showed no evidence of subclinical left ventricle dysfunction in athletes recovering from COVID-19 infection with normal myocardial peak global LV-GRS, LV-GCS and LV-GLS values.

Post viral myocarditis can lead to sudden cardiac death in athletes. When initial cases of COVID-19 myocarditis were first reported in athletes, there was extreme uncertainty regarding the involvement of athletes in competitive play due to the risk of sudden cardiac death. Experts recommended a two-week period of no competitive sports after recovering from infection with resumption of activities based on clinical history, an electrocardiogram and an echocardiogram.20 Subsequent studies stressed upon including cardiac MRI for risk stratification assessment in athletes recovering from COVID-19 infection.4 This also led to screening with cardiac MRI as part of “return to competitive sports” for athletes who contracted COVID-19 infection. However, as the understanding and literature about COVID-19 evolved, multiple subsequent studies showed an extremely low risk of myopericarditis in COVID-19 positive athletes, especially when asymptomatic.6., 7., 21. This questioned the utility of cardiac MRI as a screening tool for myocarditis in student athletic population. Current expert consensus by American College of Cardiology do not recommend screening cardiac MRI in athletes after recovering from COVID-19 infection and diagnostic testing is only recommended for those with moderate to severe cardiopulmonary symptoms.22

Our findings are in sync with prior reports of normal myocardial adaption in athletes with an elevated left ventricle and right ventricle end-diastolic volume indices compared to non-athletes.17 We also found slightly lower but normal global strain values in athletes compared to controls similar a to study by Szabo et al.23 The data on feature tracking strain for athletes is limited. In addition, comparison for normal MRI strain values in athletes may also be challenging as strain values can vary significantly based upon myocardial tracings (endocardium versus epicardium versus mid wall) and software used to process feature tracking strain.13 However, values below −14% are generally considered abnormal for global circumferential and longitudinal strain.18 Data on global radial strain is lacking, however more positive values are considered normal and our radial strain values are in sync with prior reported normal ranges.24

Detection of presence of subclinical myocardial damage by CMR may be helpful in athletic population due to high risk of sudden cardiac death in this population and early detection of subclinical myocardial damage may lead to appropriate evaluation before return to competitive sports. However, the utility of CMR in asymptomatic athletes is limited as shown in the study. Our study fills the gap regarding data on subclinical myocardial alterations that may be caused by COVID-19 infection and found no evidence of cardiac damage. Our findings reemphasize that screening with cardiac MRI is not required in athletes recovering from COVID-19 infection with mild or no symptoms. This is due to the low prevalence of persistent cardiac and pulmonary symptoms and lack of evidence of myocardial abnormalities at cardiac MRI in those athletes without symptoms. As such cardiac MRI should be reserved for diagnostic indications in patients with moderate to severe symptoms at presentation, with or without abnormal exercise testing/ECG to look for post infection myocardial scarring or those presenting with exertional chest pain on return to sports.25

4.1. Limitations

Besides retrospective design, the main limitation of this study is that all subjects were recruited from only a single center. Additionally, majority of athletes were asymptomatic and thus our findings may be applicable to this group only. The goal of this study was to evaluate for subclinical myocardial damage since once myocardial edema or fibrosis and/or reduced ejection fraction manifests, strain parameters may not provide any incremental information. As such, the current inclusion criteria were able to answer the major question. The other limitation is the small sample size for control subjects and the lack of age and gender matched athletic control population. In addition, our study findings can primarily be attributed to myocardial alterations that may be present early in the course of disease following COVID-19 infection. This is since the athletic participants were part of the Big Ten Conference that mandated advanced testing including CMRI for all athletes following COVID-19 infection prior to the return to competitive play. Since our athletic study population only included those with no or minimal symptoms, no follow up CMR was performed following a normal initial CMR study. As such, the study is limited to assess long-term (>6 months) myocardial changes after COVID-19 infection. Future studies should include matched athletic control population and may also include assessment of long-term subclinical myocardial alterations on CMR strain imaging in athletes following COVID-19 infection with no or minimal symptoms. Lastly, we did not study parametric mapping to evaluate subclinical myocardial dysfunction. T1 and T2 mapping values may provide evidence of subclinical myocardial alteration caused by viral infection and should be investigated in future studies.

5. Conclusion

In this study evaluating 122 athletes recovering from COVID-19 infection we found no evidence of subclinical myocardial alterations with normal myocardial strain parameters. We found myocardial adaptations in competitive athletes with higher end-diastolic volume indices and slightly reduced but normal strain values compared to controls. Our study concluded that in athletes with no or minimal symptoms, the risk of underlying subclinical myocardial dysfunction is negligible.

Declaration of competing interest

None.

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