Characterization of non‐response to cardiac resynchronization therapy by post‐procedural computed tomography

Pezel, Théo; Mika, Delphine; Logeart, Damien; Cohen‐Solal, Alain; Beauvais, Florence; Henry, Patrick; Laissy, Jean Pierre; Moubarak, Ghassan

doi:10.1111/pace.14134

Cited by 8 publications

(12 citation statements)

References 28 publications

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“…The location of scar in the posterolateral region of the LV, which is empirically thought to be a target site for LV lead implantation, was associated with lower response rates following CRT (Chalil et al, 2007). In study by Pezel et al (2021), no difference was found in presence and extent of scar between CRT responders and non-responders. However, in non-responders, the LV lead was more often over an akinetic/dyskinetic area suggesting the presence of tissue lesions, a fibrotic area, or an area with myocardial thickness < 6 mm.…”

Section: Feature Selection For Classification Models From Hybrid Datamentioning

confidence: 88%

Machine Learning Prediction of Cardiac Resynchronisation Therapy Response From Combination of Clinical and Model-Driven Data

et al. 2021

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Background: Up to 30–50% of chronic heart failure patients who underwent cardiac resynchronization therapy (CRT) do not respond to the treatment. Therefore, patient stratification for CRT and optimization of CRT device settings remain a challenge.Objective: The main goal of our study is to develop a predictive model of CRT outcome using a combination of clinical data recorded in patients before CRT and simulations of the response to biventricular (BiV) pacing in personalized computational models of the cardiac electrophysiology.Materials and Methods: Retrospective data from 57 patients who underwent CRT device implantation was utilized. Positive response to CRT was defined by a 10% increase in the left ventricular ejection fraction in a year after implantation. For each patient, an anatomical model of the heart and torso was reconstructed from MRI and CT images and tailored to ECG recorded in the participant. The models were used to compute ventricular activation time, ECG duration and electrical dyssynchrony indices during intrinsic rhythm and BiV pacing from the sites of implanted leads. For building a predictive model of CRT response, we used clinical data recorded before CRT device implantation together with model-derived biomarkers of ventricular excitation in the left bundle branch block mode of activation and under BiV stimulation. Several Machine Learning (ML) classifiers and feature selection algorithms were tested on the hybrid dataset, and the quality of predictors was assessed using the area under receiver operating curve (ROC AUC). The classifiers on the hybrid data were compared with ML models built on clinical data only.Results: The best ML classifier utilizing a hybrid set of clinical and model-driven data demonstrated ROC AUC of 0.82, an accuracy of 0.82, sensitivity of 0.85, and specificity of 0.78, improving quality over that of ML predictors built on clinical data from much larger datasets by more than 0.1. Distance from the LV pacing site to the post-infarction zone and ventricular activation characteristics under BiV pacing were shown as the most relevant model-driven features for CRT response classification.Conclusion: Our results suggest that combination of clinical and model-driven data increases the accuracy of classification models for CRT outcomes.

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Section: Feature Selection For Classification Models From Hybrid Datamentioning

confidence: 88%

Machine Learning Prediction of Cardiac Resynchronisation Therapy Response From Combination of Clinical and Model-Driven Data

et al. 2021

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“…However, there continues to exist a group of patients for whom the indication for CRT is controversial (i.e., RBBB), and approximately one third of patients with an indication for CRT have a suboptimal clinical response (i.e., "non-responders") [76]. Causes of non-response include mechanical dyssynchrony, presence and extent of myocardial scar, and suboptimal LV lead position [77][78][79]. Other factors that have been shown to influence response to CRT include QRS width and morphology pattern, device optimization, and post-implant programming [80,81].…”

Section: Discussionmentioning

confidence: 99%

Contemporary management of heart failure patients with reduced ejection fraction: the role of implantable devices and catheter ablation

Ahsan

Briasoulis

Androulakis

et al. 2021

Rev. Cardiovasc. Med.

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Heart failure (HF) is a complex clinical syndrome characterised by significant morbidity and mortality worldwide. Evidence-based therapies for the management of HF include several well-established neurohormonal antagonists and antiarrhythmic drug therapy to mitigate the onset of cardiac arrhythmia. However, the degree of rate and rhythm control achieved is often suboptimal and mortality rates continue to remain high. Implantable cardioverter-defibrillators (ICDs), cardiac resynchronization (CRT), and combined (CRT-D) therapies have emerged as integral and rapidly expanding technologies in the management of select patients with heart failure with reduced ejection fraction (HFrEF). ICDs treat ventricular arrhythmia and are used as primary prophylaxis for sudden cardiac death, while CRT resynchronizes ventricular contraction to improve left ventricular systolic function. Left ventricular assist device therapy has also been shown to provide clinically meaningful survival benefits in patients with advanced HF, and His-bundle pacing has more recently emerged as a safe, viable, and promising pacing modality for patients with CRT indication. Catheter ablation is another important and wellestablished strategy for managing cardiac arrhythmia in HF, demonstrating superior efficacy when compared with antiarrhythmic drug therapy alone. In this article, we provide a comprehensive and indepth evaluation of the role of implantable devices and catheter ablation in patients with HFrEF, outlining current applications, recent advances, and future directions in practice.

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“…Greater segmental dyssynchrony between the anterior and inferior segments, between the inferoseptal and anterolateral segments, and between the anteroseptal and inferolateral segments was found between non-responders. In addition, in the non-responders, the LV lead location was less often concordant with the region of maximal wall thickness (9% vs. 72%, p = .001) [78].…”

Section: Cardiac Resynchronization Therapy Guided By Computed Tomographymentioning

confidence: 91%

“…Late iodine enhancement computed tomography (LIE-CT) was found to be an important elegant diagnostic modality in this regard. Théo Pezel et al investigated CT dyssynchrony measurements for which the LV short-axis images from the multiphase reformatted reconstructions were used [78]. CT dyssynchrony indices used in their investigation were: global and segmental time to maximal wall thickness, global and segmental time to maximal inward wall motion, and time to minimum systolic volume.…”

Section: Cardiac Resynchronization Therapy Guided By Computed Tomographymentioning

confidence: 99%

CRT Past, Present, and Future Directions: Toward Intelligent Responders Selection and Optimizing Pacing Modalities

Alabdulgader¹

2022

Cardiac Rhythm Management - Pacing, Ablation, Devices

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Congestive heart failure (CHF) is a serious health problem affecting all nations of world. Its impact is increasing with increasing individual age. Ventricular dyssynchrony is well known to contribute to pathophysiological deterioration in more than one-third of CHF subjects. The therapeutic choices of CHF witnessed long decades of stagnant periods and a relative paucity of effective treatment. The discovery of the electrical therapy that is capable of reversing ventricular dyssynchrony, in the form of cardiac resynchronization therapy (CRT), is a true revolution in the timeline of CHF management. Despite the early enthusiasm associated with CRT implantations started in 2001, we know from the last two decades’ experience that non-responders constitute to nearly 40% of all CRT patients. This chapter is devoted to reviewing the past, present and future of CRT with special attention on better intelligent detection of the electrical substrate responsive to CRT as well as optimizing the choice of CRT subjects using the latest knowledge in electrocardiographic and state-of-art imagining technologies. Novel future directions are discussed with new scientific philosophies capable of optimizing CRT. Promising new implants techniques such as endocardial pacing of the left ventricle, His bundle pacing as well as His-optimized cardiac resynchronization therapy are discussed.

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Characterization of non‐response to cardiac resynchronization therapy by post‐procedural computed tomography

Cited by 8 publications

References 28 publications

Machine Learning Prediction of Cardiac Resynchronisation Therapy Response From Combination of Clinical and Model-Driven Data

Machine Learning Prediction of Cardiac Resynchronisation Therapy Response From Combination of Clinical and Model-Driven Data

Contemporary management of heart failure patients with reduced ejection fraction: the role of implantable devices and catheter ablation

CRT Past, Present, and Future Directions: Toward Intelligent Responders Selection and Optimizing Pacing Modalities

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