Advances in the Application of Non-invasive Myocardial Work Assessment in Evaluating the Risk and Prognosis of Stroke-Heart Syndrome in Patients with Acute Ischemic Stroke

Liting Wu; Chengcai Chen; Shenghao Fu; Huihui Wen; Ji Wang

doi:10.54097/956cvn55

Authors

Liting Wu
Chengcai Chen
Shenghao Fu
Huihui Wen
Ji Wang

DOI:

https://doi.org/10.54097/956cvn55

Keywords:

Non-invasive Myocardial Work, Acute Ischemic Stroke, Stroke-heart Syndrome

Abstract

Timely assessment of the risk of stroke-heart syndrome (SHS) in patients with acute ischemic stroke (AIS), accurate prediction of clinical prognosis and optimization of clinical treatment strategies are crucial for improving the overall clinical outcomes of such patients. Traditional assessment methods including conventional echocardiography and single serological tests have inherent limitations, such as insufficient sensitivity and low specificity for detecting early myocardial dysfunction, which make it difficult to fully reflect the pathophysiological changes of SHS. The non-invasive myocardial work (MW) technique integrates speckle-tracking echocardiography with left ventricular pressure-strain loop analysis to dynamically quantify the mechanical properties and energy metabolism efficiency of the myocardium, thus providing a novel non-invasive approach for the evaluation of SHS in AIS patients. By reviewing the recent relevant literature, this article elaborates on the fundamental principles of the MW technique and its clinical applications in SHS risk screening, prognostic assessment and guidance of clinical treatment decisions in AIS patients. It also discusses the current limitations and future development directions of this technique, aiming to clarify the clinical value of the MW technique in the diagnosis and management of AIS patients complicated with SHS.

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References

[1] GBD S C. Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019[J]. The Lancet. Neurology, 2021,20(10):795-820.

[2] Buckley B J R, Harrison S L, Lane D A, et al. Stroke-heart syndrome: mechanisms, risk factors, and adverse cardiovascular events[J]. European journal of preventive cardiology, 2024,31(5): e23-e26.

[3] Sposato L A, Hilz M J, Aspberg S, et al. Post-Stroke Cardiovascular Complications and Neurogenic Cardiac Injury: JACC State-of-the-Art Review[J]. Journal of the American College of Cardiology, 2020,76(23):2768-2785.

[4] Scheitz J F, Sposato L A, Schulz-Menger J, et al. Stroke-Heart Syndrome: Recent Advances and Challenges[J]. Journal of the American Heart Association, 2022,11(17): e26528.

[5] Nagueh S F, Smiseth O A, Appleton C P, et al. Recommendations for the Evaluation of Left Ventricular Diastolic Function by Echocardiography: An Update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging[J]. European heart journal. Cardiovascular Imaging, 2016,17(12):1321-1360.

[6] Moya A, Buytaert D, Penicka M, et al. State-of-the-Art: Noninvasive Assessment of Left Ventricular Function Through Myocardial Work[J]. Journal of the American Society of Echocardiography: official publication of the American Society of Echocardiography, 2023,36(10):1027-1042.

[7] Guo W, Li H, Li H, et al. Sympathetic overactivation and catecholamine toxicity: mechanisms and therapeutic strategies for neurogenic heart injury following acute ischemic stroke[J]. Frontiers in cardiovascular medicine, 2025,12:1632704.

[8] Scheitz J F, Nolte C H, Doehner W, et al. Stroke-heart syndrome: clinical presentation and underlying mechanisms[J]. The Lancet. Neurology, 2018,17(12):1109-1120.

[9] Buckley B J R, Harrison S L, Hill A, et al. Stroke-Heart Syndrome: Incidence and Clinical Outcomes of Cardiac Complications Following Stroke[J]. Stroke, 2022,53(5):1759-1763.

[10] Russell K, Eriksen M, Aaberge L, et al. A novel clinical method for quantification of regional left ventricular pressure-strain loop area: a non-invasive index of myocardial work[J]. European heart journal, 2012,33(6):724-733.

[11] Boe E, Skulstad H, Smiseth O A. Myocardial work by echocardiography: a novel method ready for clinical testing[J]. European Heart Journal - Cardiovascular Imaging, 2019,20(1): 18-20.

[12] Boe E, Russell K, Eek C, et al. Non-invasive myocardial work index identifies acute coronary occlusion in patients with non-ST-segment elevation-acute coronary syndrome[J]. European heart journal. Cardiovascular Imaging, 2015,16(11):1247-1255.

[13] Marzlin N, Hays A G, Peters M, et al. Myocardial Work in Echocardiography[J]. Circulation. Cardiovascular imaging, 2023,16(2):e14419.

[14] Li Y, Zheng Q, Cui C, et al. Application value of myocardial work technology by non-invasive echocardiography in evaluating left ventricular function in patients with chronic heart failure[J]. Quantitative imaging in medicine and surgery, 2022,12(1):244-256.

[15] Zhang J, Wu X, Zheng X. A Novel Approach to Assessing the Severity of Acute Stroke and Neurological Deficits in Patients with Acute Ischemic Stroke Using Myocardial Work Echocardiography[J]. Anatolian journal of cardiology, 2022, 26(12):893-901.

[16] Zheng L, Lin X, Xue Y. Effect of Cerebral Ischemic Strokes in Different Cerebral Artery Regions on Left Ventricular Function[J]. Frontiers in cardiovascular medicine, 2022,9: 782173.

[17] Zhao M, Guan L, Collet J, et al. Relationship between ischemic stroke locations, etiology subtypes, neurological outcomes, and autonomic cardiac function[J]. Neurological research, 2020,42(8):630-639.

[18] Huang H, Ruan Q, You Z, et al. Segmental and global myocardial work in hypertensive patients with different left ventricular ejection fraction: what's the role of the apex played? [J]. The international journal of cardiovascular imaging, 2023, 39 (8):1505-1514.

[19] Trimarchi G, Carerj S, Di Bella G, et al. Clinical Applications of Myocardial Work in Echocardiography: A Comprehensive Review[J]. Journal of cardiovascular echography, 2024,34 (3): 99-113.

[20] Shu L, Aziz Y N, de Havenon A, et al. Perioperative Stroke: Mechanisms, Risk Stratification, and Management[J]. Stroke, 2025,56(9):2798-2809.

[21] Zhang T, Hao Z, Jiang Q, et al. Machine learning-based prediction model for post-stroke cerebral-cardiac syndrome: a risk stratification study[J]. Scientific reports, 2025,15(1):30657.

[22] Gao Y, Wang H, Liu M, et al. Early detection of myocardial fibrosis in cardiomyopathy in the absence of late enhancement: role of T1 mapping and extracellular volume analysis[J]. European radiology, 2023,33(3):1982-1991.

[23] Hamza I, Odigie-Okon E, Xie T, et al. Apical Hypertrophic Cardiomyopathy: A Clinical & Multimodality Imaging Assessment[J]. Echocardiography (Mount Kisco, N.Y.), 2025,42(7):e70235.

[24] Xiong P, Lee S M, Chan G. Deep Learning for Detecting and Locating Myocardial Infarction by Electrocardiogram: A Literature Review[J]. Frontiers in cardiovascular medicine, 2022,9:860032.

[25] Dell'Angela L, Nicolosi G L. From ejection fraction, to myocardial strain, and myocardial work in echocardiography: Clinical impact and controversies[J]. Echocardiography (Mount Kisco, N.Y.), 2024,41(1): e15758.