Virtual pacing of a patient's digital twin to predict left ventricular reverse remodelling after cardiac resynchronization therapy.
Europace
; 26(1)2023 Dec 28.
Article
em En
| MEDLINE
| ID: mdl-38288616
ABSTRACT
AIMS:
Identifying heart failure (HF) patients who will benefit from cardiac resynchronization therapy (CRT) remains challenging. We evaluated whether virtual pacing in a digital twin (DT) of the patient's heart could be used to predict the degree of left ventricular (LV) reverse remodelling post-CRT. METHODS ANDRESULTS:
Forty-five HF patients with wide QRS complex (≥130â ms) and reduced LV ejection fraction (≤35%) receiving CRT were retrospectively enrolled. Echocardiography was performed before (baseline) and 6 months after CRT implantation to obtain LV volumes and 18-segment longitudinal strain. A previously developed algorithm was used to generate 45 DTs by personalizing the CircAdapt model to each patient's baseline measurements. From each DT, baseline septal-to-lateral myocardial work difference (MWLW-S,DT) and maximum rate of LV systolic pressure rise (dP/dtmax,DT) were derived. Biventricular pacing was then simulated using patient-specific atrioventricular delay and lead location. Virtual pacing-induced changes ΔMWLW-S,DT and ΔdP/dtmax,DT were correlated with real-world LV end-systolic volume change at 6-month follow-up (ΔLVESV). The DT's baseline MWLW-S,DT and virtual pacing-induced ΔMWLW-S,DT were both significantly associated with the real patient's reverse remodelling ΔLVESV (r = -0.60, P < 0.001 and r = 0.62, P < 0.001, respectively), while correlation between ΔdP/dtmax,DT and ΔLVESV was considerably weaker (r = -0.34, P = 0.02).CONCLUSION:
Our results suggest that the reduction of septal-to-lateral work imbalance by virtual pacing in the DT can predict real-world post-CRT LV reverse remodelling. This DT approach could prove to be an additional tool in selecting HF patients for CRT and has the potential to provide valuable insights in optimization of CRT delivery.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article