AimsWe tested the hypothesis that shortening of time-to-peak left ventricular pressure rise (Td) reflect resynchronization in an animal model and that Td measured in patients will be helpful to identify long-term volumetric responders [end-systolic volume (ESV) decrease >15%] in cardiac resynchronization therapy (CRT). Methods Td was analysed in an animal study (n = 12) of left bundle-branch block (LBBB) with extensive instrumentation to detect left ventricular myocardial deformation, electrical activation, and pressures during pacing. The sum of electrical delays from the onset of pacing to four intracardiac electrodes formed a synchronicity index (SI). Pacing was performed at baseline, with LBBB, right and left ventricular pacing and finally with biventricular pacing (BIVP). We then studied Td at baseline and with BIVP in a clinical observational study in 45 patients during the implantation of CRT and followed up for up to 88 months. ResultsWe found a strong relationship between Td and SI in the animals (R = 0.84, P < 0.01). Td and SI increased from narrow QRS at baseline (Td = 95 ± 2 ms, SI = 141 ± 8 ms) to LBBB (Td = 125 ± 2 ms, SI = 247 ± 9 ms, P < 0.01), and shortened with biventricular pacing (BIVP) (Td = 113 ± 2 ms and SI = 192 ± 7 ms, P < 0.01). Prolongation of Td was associated with more wasted deformation during the preejection period (R = 0.77, P < 0.01). Six patients increased ESV by 2.5 ± 18%, while 37 responders (85%) had a mean ESV decrease of 40 ± 15% after more than 6 months of follow-up. Responders presented with a higher Td at baseline than non-responders (163 ± 26 ms vs. 121 ± 19 ms, P < 0.01). Td decreased to 156 ± 16 ms (P = 0.02) with CRT in responders, while in non-responders, Td increased to 148 ± 21 ms (P < 0.01). A decrease in Td with BIVP to values similar or below what was found at baseline accurately identified responders to therapy (AUC 0.98, P < 0.01). Td at baseline and change in Td from baseline was linear related to the decrease in ESV at follow-up. All-cause mortality was high among six non-responders (n = 4), while no patients died in the responder group during follow-up. Conclusions Prolongation of Td is associated with cardiac dyssynchrony and more wasted deformation during the preejection period. Shortening of a prolonged Td with CRT in patients accurately identifies volumetric responders to CRT with incremental value on top of current guidelines and practices. Thus, Td carries the potential to become a biomarker to predict long-term volumetric response in CRT candidates.
Measurements of the left ventricular (LV) pressure trace are rarely performed despite high clinical interest. We estimated the LV pressure trace for an individual heart by scaling the isovolumic, ejection and filling phases of a normalized, averaged LV pressure trace to the time-points of opening and closing of the aortic and mitral valves detected in the individual heart. We developed a signal processing algorithm that automatically detected the time-points of these valve events from the motion signal of a miniaturized accelerometer attached to the heart surface. Furthermore, the pressure trace was used in combination with measured displacement from the accelerometer to calculate the pressure–displacement loop area. The method was tested on data from 34 animals during different interventions. The accuracy of the accelerometer-detected valve events was very good with a median difference of 2 ms compared to valve events defined from hemodynamic reference recordings acquired simultaneously with the accelerometer. The average correlation coefficient between the estimated and measured LV pressure traces was r = 0.98. Finally, the LV pressure–displacement loop areas calculated using the estimated and measured pressure traces showed very good correlation (r = 0.98). Hence, the pressure–displacement loop area can be assessed solely from accelerometer recordings with very good accuracy.
Background: Miniaturized accelerometers incorporated in pacing leads attached to the myocardium, are used to monitor cardiac function. For this purpose functional indices must be extracted from the acceleration signal. A method that automatically detects the time of aortic valve opening (AVO) and aortic valve closure (AVC) will be helpful for such extraction. We tested if deep learning can be used to detect these valve events from epicardially attached accelerometers, using high fidelity pressure measurements to establish ground truth for these valve events. Method: A deep neural network consisting of a CNN, an RNN, and a multi-head attention module was trained and tested on 130 recordings from 19 canines and 159 recordings from 27 porcines covering different interventions. Due to limited data, nested cross-validation was used to assess the accuracy of the method. Result: The correct detection rates were 98.9% and 97.1% for AVO and AVC in canines and 98.2% and 96.7% in porcines when defining a correct detection as a prediction closer than 40 ms to the ground truth. The incorrect detection rates were 0.7% and 2.3% for Manuscript
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.