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Published on: April 11, 2025
Advanced Cardiac Imaging for Risk Prediction of Pacing-Induced Cardiomyopathy: A Narrative Literature Review
Karla Asturias1, Sarah Li1, Shivani Reddy2
1Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR 97239, USA.
Insights
Noninvasive cardiac imaging can identify patients at risk for pacing-induced cardiomyopathy (PICM) before symptoms arise. Echocardiography and cardiac MRI help predict heart failure and guide pacing strategies to mitigate PICM risk.
Area of Science:
- Cardiology
- Medical Imaging
- Biomedical Engineering
Background:
- Pacing-induced cardiomyopathy (PICM) is a frequent complication of right ventricular (RV) pacing, linked to dyssynchrony.
- Existing risk factors for PICM have limited predictive accuracy.
- PICM encompasses various forms, including heart failure with preserved ejection fraction and RV failure.
Purpose of the Study:
- To review current evidence on noninvasive imaging for identifying patients at high risk of PICM.
- To explore the role of cardiac imaging in predicting and managing PICM.
- To summarize imaging techniques for early PICM detection.
Main Methods:
- Comprehensive literature search of PubMed, Scopus, Google Scholar, and Cochrane databases (2000-2025).
- Inclusion of randomized controlled trials, observational studies, guidelines, and systematic reviews.
- Keywords included RV pacing, PICM, echocardiography, CT, and cardiac MRI.
Main Results:
- Cardiac imaging is crucial for diagnosing PICM and detecting at-risk patients pre-symptomatically.
- 2D/3D echocardiography with global longitudinal strain can detect early PICM development.
- Cardiac MRI accurately assesses volumes, synchrony, and quantifies myocardial fibrosis, a PICM predictor.
Conclusions:
- Pre-implantation cardiac imaging can predict heart failure risk and guide pacing modality selection.
- An imaging-guided approach can advance PICM management.
- Noninvasive imaging offers sensitive parameters for PICM risk stratification.
Abstract:
Background/Objective: Pacing-induced cardiomyopathy (PICM) is a common complication of right ventricular (RV) pacing, affecting 6-25% of patients with frequent RV pacing, due to electrical and mechanical dyssynchrony. Certain clinical and electrocardiographic risk factors have been identified, including high RV-pacing burden and longer paced QRS, but their ability to predict the development PICM remains limited. Additionally, other forms of PICM have been described, including heart failure with preserved ejection fraction and RV failure. The goal of this narrative review is to summarize the current evidence utilizing noninvasive imaging to identify patients predisposed to a high risk of PICM. Methods: Using a literature search in the PubMed, Scopus, Google Scholar, and the Cochrane databases from 2000 to 2025, which included but was not limited to the keywords right ventricular pacing, pacemaker-related cardiomyopathy, pacemaker-induced cardiomyopathy, biventricular pacing, conduction system pacing, His bundle pacing, left bundle pacing, echocardiography, computed tomography imaging, and cardiac magnetic resonance imaging, we reviewed randomized control trials, observational retrospective and prospective cohort studies, societal guidelines, and systematic review articles. Conclusions: Essential in the diagnosis of PICM, cardiac imaging can identify patients at risk, even before left ventricular (LV) dysfunction or symptoms develop. Pre- and early post-implantation 2- and 3-dimensional echocardiography with global longitudinal strain provides sensitive parameters for the potential development of PICM. Relative indices of contractile asymmetry have been described. Cardiac magnetic resonance imaging offers an accurate assessment of cardiac volumes and LV synchrony and can also quantify myocardial fibrosis, a significant predictor of PICM. Performing pre-device implantation imaging may help predict subsequent heart failure development and potentially can guide pacing modality selection that can mitigate this risk. Thus, an imaging-guided framework will advance the management of PICM.
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