| Title |
Sensitivity analysis of ventricular activation and electrocardiogram in tailored models of heart-failure patients
|
|---|---|
| Published in |
Medical & Biological Engineering & Computing, August 2017
|
| DOI | 10.1007/s11517-017-1696-9 |
| Pubmed ID | |
| Authors |
C. Sánchez, G. D’Ambrosio, F. Maffessanti, E. G. Caiani, F. W. Prinzen, R. Krause, A. Auricchio, M. Potse |
| Abstract |
Cardiac resynchronization therapy is not effective in a variable proportion of heart failure patients. An accurate knowledge of each patient's electroanatomical features could be helpful to determine the most appropriate treatment. The goal of this study was to analyze and quantify the sensitivity of left ventricular (LV) activation and the electrocardiogram (ECG) to changes in 39 parameters used to tune realistic anatomical-electrophysiological models of the heart. Electrical activity in the ventricles was simulated using a reaction-diffusion equation. To simulate cellular electrophysiology, the Ten Tusscher-Panfilov 2006 model was used. Intracardiac electrograms and 12-lead ECGs were computed by solving the bidomain equation. Parameters showing the highest sensitivity values were similar in the six patients studied. QRS complex and LV activation times were modulated by the sodium current, the cell surface-to-volume ratio in the LV, and tissue conductivities. The T-wave was modulated by the calcium and rectifier-potassium currents, and the cell surface-to-volume ratio in both ventricles. We conclude that homogeneous changes in ionic currents entail similar effects in all ECG leads, whereas the effects of changes in tissue properties show larger inter-lead variability. The effects of parameter variations are highly consistent between patients and most of the model tuning could be performed with only ~10 parameters. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 39 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 31% |
| Researcher | 10 | 26% |
| Student > Doctoral Student | 4 | 10% |
| Professor | 2 | 5% |
| Student > Bachelor | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 7 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 10 | 26% |
| Computer Science | 4 | 10% |
| Medicine and Dentistry | 3 | 8% |
| Mathematics | 2 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Other | 4 | 10% |
| Unknown | 15 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 October 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from Medical & Biological Engineering & Computing
#1,899
of 2,053 outputs
Outputs of similar age
#287,266
of 327,377 outputs
Outputs of similar age from Medical & Biological Engineering & Computing
#12
of 15 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,053 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 327,377 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.