Back

A New Mathematical Model for LVAD-Supported Ventricles: Direct Parameterization from Ramp-Test Clinical Data and Verification via Hybrid Modeling

Umo, A.; Welch, B.; Kilic, A.; Kung, E.

2026-03-23 bioengineering
10.64898/2026.03.20.712251 bioRxiv
Show abstract

BackgroundConventional left ventricular assist device ramp metrics are load dependent, obscuring intrinsic myocardial recovery. A mechanistic, patient-specific representation of ventricular mechanics, identifiable from routine clinical data, could provide quantitative indices of intrinsic left ventricular (LV) function for longitudinal recovery surveillance. ObjectiveTo develop and verify a ramp-integrated, patient-specific model of HeartMate 3-assisted LV function that can yield indices of intrinsic myocardial contractility and remodeling. MethodsWe represented LV pressure-volume (PV) behavior with a PV envelope composed of a monotonic passive PV relation (pPVR) and a unimodal active PV relation (aPVR). We developed a parameterization procedure to infer the patient-specific shape of this envelope directly from routine ramp-test data. We then embedded the parameterized envelope within the PSCOPE framework, a hybrid platform that couples a lumped-parameter network to a physical HeartMate 3 flow loop, to reproduce clinical ramp hemodynamics. Percent residuals between simulated outputs and the corresponding clinical measurements verified the implementation of the PV envelope within PSCOPE. ResultsIn three HeartMate 3 recipients, the PSCOPE models reproduced ramp hemodynamics with residuals generally [≤] 20% across pump speeds and measured variables. Cardiac index residuals ranged from 0-18.5%, systemic and pulmonary arterial pressure residuals remained [≤] 18.4%, and pulmonary arterial wedge pressure residuals remained [≤] 20%. The PSCOPE models matched central venous pressure within [≤] 3 mmHg in all cases, although one setting yielded a 33.3% residual due to a low reference pressure. For one patient, the model reproduced ramp hemodynamics at a speed deliberately withheld from PV-envelope parameterization with residuals [≤] 10%, supporting cross-speed generalizability. Patient-specific PV envelopes also revealed clinically meaningful heterogeneity in LV diastolic stiffness, volume threshold for declining systolic function, operating PV points for peak systolic function, and contractile reserve. ConclusionsRamp-integrated parameterization of the monotonic pPVR and unimodal aPVR yields a compact, mechanistic PV envelope that is identifiable from routine clinical data and verifiable within PSCOPE. The resulting indices characterize intrinsic LV function and may enhance longitudinal recovery surveillance and inform LVAD management. Prospective multicenter validation is warranted to confirm the generalizability and clinical utility of this approach.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Annals of Biomedical Engineering
34 papers in training set
Top 0.1%
23.0%
2
PLOS Computational Biology
1633 papers in training set
Top 2%
13.0%
3
PLOS ONE
4510 papers in training set
Top 18%
10.3%
4
Scientific Reports
3102 papers in training set
Top 13%
7.0%
50% of probability mass above
5
Computers in Biology and Medicine
120 papers in training set
Top 0.3%
6.5%
6
npj Digital Medicine
97 papers in training set
Top 1%
4.0%
7
Frontiers in Physiology
93 papers in training set
Top 1%
3.1%
8
Nature Communications
4913 papers in training set
Top 46%
2.1%
9
Circulation
66 papers in training set
Top 1%
2.1%
10
Computer Methods and Programs in Biomedicine
27 papers in training set
Top 0.3%
1.7%
11
International Journal for Numerical Methods in Biomedical Engineering
12 papers in training set
Top 0.2%
1.4%
12
Biomechanics and Modeling in Mechanobiology
25 papers in training set
Top 0.5%
1.4%
13
European Heart Journal - Digital Health
15 papers in training set
Top 0.5%
1.0%
14
Advanced Science
249 papers in training set
Top 15%
1.0%
15
Communications Biology
886 papers in training set
Top 18%
0.9%
16
Frontiers in Bioengineering and Biotechnology
88 papers in training set
Top 2%
0.9%
17
Computational and Structural Biotechnology Journal
216 papers in training set
Top 8%
0.8%
18
iScience
1063 papers in training set
Top 28%
0.8%
19
Journal of The Royal Society Interface
189 papers in training set
Top 4%
0.8%
20
American Journal of Physiology-Heart and Circulatory Physiology
32 papers in training set
Top 1%
0.7%
21
Journal of Neural Engineering
197 papers in training set
Top 2%
0.7%
22
BMC Cardiovascular Disorders
14 papers in training set
Top 2%
0.7%
23
IEEE Transactions on Biomedical Engineering
38 papers in training set
Top 1%
0.7%
24
Journal of Biomechanical Engineering
17 papers in training set
Top 0.5%
0.5%
25
JCI Insight
241 papers in training set
Top 9%
0.5%
26
JACC: Basic to Translational Science
15 papers in training set
Top 0.6%
0.5%
27
AIDS
31 papers in training set
Top 0.6%
0.5%