TY - GEN
T1 - Minimally-Invasive Estimation of Patient-Specific End-Systolic Elastance Using a Biomechanical Heart Model
AU - Le Gall, Arthur
AU - Vallée, Fabrice
AU - Chapelle, Dominique
AU - Chabiniok, Radomír
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - The end-systolic elastance (Ees ) – the slope of the end-systolic pressure-volume relationship (ESPVR) at the end of ejection phase – has become a reliable indicator of myocardial functional state. The estimation of Ees by the original multiple-beat method is invasive, which limits its routine usage. By contrast, non-invasive single-beat estimation methods, based on the assumption of the linearity of ESPVR and the uniqueness of the normalised time-varying elastance curve EN(t) across subjects and physiology states, have been applied in a number of clinical studies. It is however known that these two assumptions have a limited validity, as ESPVR can be approximated by a linear function only locally, and EN(t) obtained from a multi-subject experiment includes a confidence interval around the mean function. Using datasets of 3 patients undergoing general anaesthesia (each containing aortic flow and pressure measurements at baseline and after introducing a vasopressor noradrenaline), we first study the sensitivity of two single-beat methods—by Sensaki et al. and by Chen et al.—to the uncertainty of EN(t). Then, we propose a minimally-invasive method based on a patient-specific biophysical modelling to estimate the whole time-varying elastance curve Emodel(t). We compare Eesmodel with the two single-beat estimation methods, and the normalised varying elastance curve EN, model(t) with EN(t) from published physiological experiments.
AB - The end-systolic elastance (Ees ) – the slope of the end-systolic pressure-volume relationship (ESPVR) at the end of ejection phase – has become a reliable indicator of myocardial functional state. The estimation of Ees by the original multiple-beat method is invasive, which limits its routine usage. By contrast, non-invasive single-beat estimation methods, based on the assumption of the linearity of ESPVR and the uniqueness of the normalised time-varying elastance curve EN(t) across subjects and physiology states, have been applied in a number of clinical studies. It is however known that these two assumptions have a limited validity, as ESPVR can be approximated by a linear function only locally, and EN(t) obtained from a multi-subject experiment includes a confidence interval around the mean function. Using datasets of 3 patients undergoing general anaesthesia (each containing aortic flow and pressure measurements at baseline and after introducing a vasopressor noradrenaline), we first study the sensitivity of two single-beat methods—by Sensaki et al. and by Chen et al.—to the uncertainty of EN(t). Then, we propose a minimally-invasive method based on a patient-specific biophysical modelling to estimate the whole time-varying elastance curve Emodel(t). We compare Eesmodel with the two single-beat estimation methods, and the normalised varying elastance curve EN, model(t) with EN(t) from published physiological experiments.
KW - End-systolic elastance estimation
KW - Patient-specific biophysical modelling
KW - Time-varying elastance
UR - http://www.scopus.com/inward/record.url?scp=85067177155&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067177155&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-21949-9_29
DO - 10.1007/978-3-030-21949-9_29
M3 - Conference contribution
AN - SCOPUS:85067177155
SN - 9783030219482
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 266
EP - 275
BT - Functional Imaging and Modeling of the Heart - 10th International Conference, FIMH 2019, Proceedings
A2 - Coudière, Yves
A2 - Ozenne, Valéry
A2 - Vigmond, Edward
A2 - Zemzemi, Nejib
PB - Springer Verlag
T2 - 10th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2019
Y2 - 6 June 2019 through 8 June 2019
ER -