King's College London

Research portal

The estimation of patient-specific cardiac diastolic functions from clinical measurements

Research output: Contribution to journalArticle

Jiahe Xi, Pablo Lamata de la Orden, Steven Niederer, Sander Land, Wenzhe Shi, Xiahai Zhuang, Sebastien Ourselin, Simon G. Duckett, Anoop K. Shetty, C. Aldo Rinaldi, Daniel Rueckert, Reza Razavi, Nicolas Smith

Original languageEnglish
Article numberN/A
Pages (from-to)133-146
Number of pages14
JournalMEDICAL IMAGE ANALYSIS
Volume17
Issue number2
Early online date15 Oct 2012
DOIs
StatePublished - Feb 2013

Documents

King's Authors

Abstract

An unresolved issue in patients with diastolic dysfunction is that the estimation of myocardial stiffness cannot be decoupled from diastolic residual active tension (AT) because of the impaired ventricular relaxation during diastole. To address this problem, this paper presents a method for estimating diastolic mechanical parameters of the left ventricle (LV) from cine and tagged MRI measurements and LV cavity pressure recordings, separating the passive myocardial constitutive properties and diastolic residual AT. Dynamic C(1)-continuous meshes are automatically built from the anatomy and deformation captured from dynamic MRI sequences. Diastolic deformation is simulated using a mechanical model that combines passive and active material properties. The problem of non-uniqueness of constitutive parameter estimation using the well known Guccione law is characterized by reformulation of this law. Using this reformulated form, and by constraining the constitutive parameters to be constant across time points during diastole, we separate the effects of passive constitutive properties and the residual AT during diastolic relaxation. Finally, the method is applied to two clinical cases and one control, demonstrating that increased residual AT during diastole provides a potential novel index for delineating healthy and pathological cases.

Download statistics

No data available

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454