Computational Method for Identifying and Quantifying Shape Features of Human Left Ventricular Remodeling

Siamak Ardekani, Robert George Weiss, Albert C. Lardo, Richard T. George, Joao Lima, Katherine Chih-Ching Wu, Michael I. Miller, Raimond Winslow, Laurent Younes

Research output: Contribution to journalArticle

Abstract

Left ventricular remodeling during the development of heart failure is a strong predictor of cardiovascular mortality. However, methods to objectively quantify remodeling-associated shape changes are not routinely available but may be possible with new computational anatomy tools. In this study, we analyzed and compared multi-detector computed tomographic (MDCT) images of ventricular shape at end-systole (ES) and end-diastole (ED) to determine whether regional structural characteristics could be identified and, as a proof of principle, whether differences in hearts of patients with anterior myocardial infarction (MI) and ischemic cardiomyopathy (ICM) could be distinguished from those with global nonischemic cardiomyopathy (NICM). MDCT images of hearts from 11 patients (5 with ICM) with ejection fractions (EF) <35% were analyzed. An average ventricular shape model (template) was constructed for each cardiac phase by bringing heart shapes into correspondence using linear and nonlinear image matching algorithms. Next, transformation fields were computed between the template image and individual heart images in the population. Principal component analysis (PCA) method was used to quantify ventricular shape differences described by the transformation vector fields. Statistical analysis of PCA coefficients revealed significant ventricular shape differences at ED (p = 0.03) and ES (p = 0.03). For validation, a second set of 14 EF-matched patients (8 with ICM) were evaluated. The discrimination rule learned from the training data set was able to differentiate ICM from NICM patients (p = 0.008). Application of a novel shape analysis method to in vivo human cardiac images acquired on a clinical scanner is feasible and can quantify regional shape differences at end-systole in remodeled myopathic human myocardium. This approach may be useful in identifying differences in the remodeling process between ICM and NICM populations and possibly in differentiating the populations.

Original languageEnglish (US)
Pages (from-to)1043-1054
Number of pages12
JournalAnnals of Biomedical Engineering
Volume37
Issue number6
DOIs
StatePublished - Jun 2009

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Computational methods
Principal component analysis
Detectors
Image matching
Statistical methods

Keywords

  • Cardiomyopathy
  • Imaging
  • Remodeling

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Computational Method for Identifying and Quantifying Shape Features of Human Left Ventricular Remodeling. / Ardekani, Siamak; Weiss, Robert George; Lardo, Albert C.; George, Richard T.; Lima, Joao; Wu, Katherine Chih-Ching; Miller, Michael I.; Winslow, Raimond; Younes, Laurent.

In: Annals of Biomedical Engineering, Vol. 37, No. 6, 06.2009, p. 1043-1054.

Research output: Contribution to journalArticle

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