TY - JOUR
T1 - Personalized aortic pressure waveform estimation from brachial pressure waveform using an adaptive transfer function
AU - Du, Shuo
AU - Yao, Yang
AU - Sun, Guozhe
AU - Wang, Lu
AU - Alastruey, Jordi
AU - Avolio, Alberto P.
AU - Xu, Lisheng
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China (No. 62273082 , and No. 61773110 ), the Natural Science Foundation of Liaoning Province (No. 20170540312 and No. 2021-YGJC-14 ), the Basic Scientific Research Project (Key Project) of Liaoning Provincial Department of Education ( LJKZ00042021 ), and Fundamental Research Funds for the Central Universities (No. N2119008 ), the Shenyang Science and Technology Plan Fund (No. 21-104-1-24 , No. 20-201-4-10 , and No. 201375 ), the Member Program of Neusoft Research of Intelligent Healthcare Technology, Co. Ltd. (No. MCMP062002 ), the British Heart Foundation ( PG/15/104/31913 ), the Wellcome/Engineering Physical Sciences Research Council (EPSRC) Centre for Medical Engineering at King's College London ( WT 203148/Z/16/Z ), and the Department of Health and Social Care (DHSC) through the National Institute for Health and Care Research (NIHR) MedTech Co-Operative award for Cardiovascular Diseases to Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London ( MIC-2016-019 ).
Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/3
Y1 - 2023/3
N2 - Background and objective: The aortic pressure waveform (APW) provides reliable information for the diagnosis of cardiovascular disease. APW is often measured using a generalized transfer function (GTF) applied to the peripheral pressure waveform acquired noninvasively, to avoid the significant risks of invasive APW acquisition. However, the GTF ignores various physiological conditions, which affects the accuracy of the estimated APW. To solve this problem, this study utilized an adaptive transfer function (ATF) combined with a tube-load model to achieve personalized and accurate estimation of APW from the brachial pressure waveform (BPW). Methods: The proposed method was validated using APWs and BPWs from 34 patients. The ATF was defined using a tube-load model in which pulse transit time and reflection coefficients were determined from, respectively, the diastolic-exponential-pressure-decay of the APW and a piece-wise constant approximation. The root-mean-square-error of overall morphology, mean absolute errors of common hemodynamic indices (systolic blood pressure, diastolic blood pressure and pulse pressure) were used to evaluate the ATF. Results: The proposed ATF performed better in estimating diastolic blood pressure and pulse pressure (1.63 versus 1.94 mmHg, and 2.37 versus 3.10 mmHg, respectively, both P < 0.10), and produced similar errors in overall morphology and systolic blood pressure (3.91 versus 4.24 mmHg, and 2.83 versus 2.91 mmHg, respectively, both P > 0.10) compared to GTF. Conclusion: Unlike the GTF which uses fixed parameters trained on existing clinical datasets, the proposed method can achieve personalized estimation of APW. Hence, it provides accurate pulsatile hemodynamic measures for the evaluation of cardiovascular function.
AB - Background and objective: The aortic pressure waveform (APW) provides reliable information for the diagnosis of cardiovascular disease. APW is often measured using a generalized transfer function (GTF) applied to the peripheral pressure waveform acquired noninvasively, to avoid the significant risks of invasive APW acquisition. However, the GTF ignores various physiological conditions, which affects the accuracy of the estimated APW. To solve this problem, this study utilized an adaptive transfer function (ATF) combined with a tube-load model to achieve personalized and accurate estimation of APW from the brachial pressure waveform (BPW). Methods: The proposed method was validated using APWs and BPWs from 34 patients. The ATF was defined using a tube-load model in which pulse transit time and reflection coefficients were determined from, respectively, the diastolic-exponential-pressure-decay of the APW and a piece-wise constant approximation. The root-mean-square-error of overall morphology, mean absolute errors of common hemodynamic indices (systolic blood pressure, diastolic blood pressure and pulse pressure) were used to evaluate the ATF. Results: The proposed ATF performed better in estimating diastolic blood pressure and pulse pressure (1.63 versus 1.94 mmHg, and 2.37 versus 3.10 mmHg, respectively, both P < 0.10), and produced similar errors in overall morphology and systolic blood pressure (3.91 versus 4.24 mmHg, and 2.83 versus 2.91 mmHg, respectively, both P > 0.10) compared to GTF. Conclusion: Unlike the GTF which uses fixed parameters trained on existing clinical datasets, the proposed method can achieve personalized estimation of APW. Hence, it provides accurate pulsatile hemodynamic measures for the evaluation of cardiovascular function.
KW - Adaptive transfer function
KW - Aortic pressure waveform
KW - Brachial pressure waveform
KW - Diastolic exponential decay phenomenon
KW - Tube-load model
UR - http://www.scopus.com/inward/record.url?scp=85147989464&partnerID=8YFLogxK
U2 - 10.1016/j.compbiomed.2023.106654
DO - 10.1016/j.compbiomed.2023.106654
M3 - Article
C2 - 36791548
AN - SCOPUS:85147989464
SN - 0010-4825
VL - 155
JO - Computers in Biology and Medicine
JF - Computers in Biology and Medicine
M1 - 106654
ER -
