Model-Assisted Time-Synchronization of Cardiac MR Image and Catheter Pressure Data

Maria Gusseva, Joshua S. Greer, Daniel A. Castellanos, Mohamed Abdelghafar Hussein, Gerald Greil, Surendranath R. Veeram Reddy, Tarique Hussain, Dominique Chapelle, Radomír Chabiniok

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

When combining cardiovascular magnetic resonance imaging (CMR) with pressure catheter measurements, the acquired image and pressure data need to be synchronized in time. The time offset between the image and pressure data depends on a number of factors, such as the type and settings of the MR sequence, duration and shape of QRS complex or the type of catheter, and cannot be typically estimated beforehand. In the present work we propose using a biophysical heart model to synchronize the left ventricular (LV) pressure and volume (P-V) data. Ten patients, who underwent CMR and LV catheterization, were included. A biophysical model of reduced geometrical complexity with physiologically substantiated timing of each phase of the cardiac cycle was first adjusted to individual patients using basic morphological and functional indicators. The pressure and volume waveforms simulated by the patient-specific models were then used as templates to detect the time offset between the acquired ventricular pressure and volume waveforms. Time-varying ventricular elastance was derived from clinical data both as originally acquired as well as when time-synchronized, and normalized with respect to end-systolic time and maximum elastance value (EorigN(t), Et-synN(t), respectively). Et-synN(t) was significantly closer to the experimentally obtained EexpN(t) published in the literature (p < 0.05, L2 norm). The work concludes that the model-driven time-synchronization of P-V data obtained by catheter measurement and CMR allows to generate high quality P-V loops, which can then be used for clinical interpretation.

Original languageEnglish (US)
Title of host publicationFunctional Imaging and Modeling of the Heart - 11th International Conference, FIMH 2021, Proceedings
EditorsDaniel B. Ennis, Luigi E. Perotti, Vicky Y. Wang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages362-372
Number of pages11
ISBN (Print)9783030787097
DOIs
StatePublished - 2021
Externally publishedYes
Event11th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2021 - Virtual, Online
Duration: Jun 21 2021Jun 25 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12738 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2021
CityVirtual, Online
Period6/21/216/25/21

Keywords

  • Cardiovascular modeling
  • Interventional cardiovascular magnetic resonance imaging
  • Personalized medicine
  • Pressure-volume loops
  • Time-synchronization of clinical data
  • Translational research

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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