Discrimination Between Healthy and Diseased Hearts by Spectral Decomposition of Their Left Ventricular Three-Dimensional Geometry

Haim Azhari, Isak Gath, Raphael Beyar, Melvin L. Marcus, Samuel Sideman

Research output: Contribution to journalArticlepeer-review

Abstract

As the heart, and particularly the left ventricle (LV), tends to remodel its shape under varying pathological conditions, it is hypothesized that the quantitative assessment of its three-dimensional (3-D) geometry may help in the objective discrimination between different pathological conditions. The 3-D LV geometries of 27 human subjects were studied using ultrafast tomography (Cine-CT) cross-sectional multislice imaging. Ten of the studied hearts were normal (NR); nine had LV aneurysms (AN), five had myocardial infarctions (MI), and three had hypertension/hypertrophic hearts (HT). After tracing the endocardial boundaries, the end systolic (ES) shape of each LV was represented by its corresponding “geometrical cardiogram’’ (GCG), a recently introduced shape descriptor used to characterize the LV’s 3-D instantaneous geometry by an anatomically aligned normalized helical vector. Applying a Fourier-sine series expansion to the GCG yielded a geometrical spectrum, which decomposed the LV shape into a family of sinusoidal geometries. It was found that the different pathological states of the LV were associated with characteristic changes in the geometrical spectrum domain. Representing each heart by a feature vector in the spectral domain and applying unsupervised fuzzy clustering to the obtained 27 feature vectors, an overall success of 85% in classification was obtained. These results indicate that an operator-independent shape-based diagnosis is potentially feasible for the four different pathological categories studied here.

Original languageEnglish (US)
Pages (from-to)207-215
Number of pages9
JournalIEEE Transactions on Medical Imaging
Volume10
Issue number2
DOIs
StatePublished - 1991
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Electrical and Electronic Engineering
  • Radiological and Ultrasound Technology
  • Computational Theory and Mathematics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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