Glyph-based SPECT visualization for the diagnosis of coronary artery disease.

Meyer-Spradow J, Stegger L, Döring C, Ropinski T, Hinrichs K

Research article (journal) | Peer reviewed

Abstract

Myocardial perfusion imaging with single photon emission computed tomography (SPECT) is an established method for the detection and evaluation of coronary artery disease (CAD). State-of-the-art SPECT scanners yield a large number of regional parameters of the left-ventricular myocardium (e.g., blood supply at rest and during stress, wall thickness, and wall thickening during heart contraction) that all need to be assessed by the physician. Today, the individual parameters of this multivariate data set are displayed as stacks of 2D slices, bull's eye plots, or, more recently, surfaces in 3D, which depict the left-ventricular wall. In all these visualizations, the data sets are displayed side-by-side rather than in an integrated manner, such that the multivariate data have to be examined sequentially and need to be fused mentally. This is time consuming and error-prone. In this paper we present an interactive 3D glyph visualization, which enables an effective integrated visualization of the multivariate data. Results from semiotic theory are used to optimize the mapping of different variables to glyph properties. This facilitates an improved perception of important information and thus an accelerated diagnosis. The 3D glyphs are linked to the established 2D views, which permit a more detailed inspection, and to relevant meta-information such as known stenoses of coronary vessels supplying the myocardial region. Our method has demonstrated its potential for clinical routine use in real application scenarios assessed by nuclear physicians.

Details about the publication

JournalIEEE Transactions on Visualization and Computer Graphics (TVCG)
Volume14
Issue6
Page range1499-1506
StatusPublished
Release year2008
Language in which the publication is writtenEnglish
DOI10.1109/TVCG.2008.136
KeywordsImage Enhancement; Sensitivity and Specificity; Computer Graphics; Image Interpretation Computer-Assisted; Pattern Recognition Automated; Tomography Emission-Computed Single-Photon; Artificial Intelligence; Ventricular Dysfunction Left; Imaging Three-Dimensional; Algorithms; Coronary Artery Disease; User-Computer Interface; Reproducibility of Results; Humans; Image Enhancement; Sensitivity and Specificity; Computer Graphics; Image Interpretation Computer-Assisted; Pattern Recognition Automated; Tomography Emission-Computed Single-Photon; Artificial Intelligence; Ventricular Dysfunction Left; Imaging Three-Dimensional; Algorithms; Coronary Artery Disease; User-Computer Interface; Reproducibility of Results; Humans

Authors from the University of Münster

Döring, Christian
European Institute of Molecular Imaging (EIMI)
Hinrichs, Klaus
Professorship for applied computer science
Ropinski, Timo
Institute of Computer Science
Stegger, Lars
Clinic for Nuclear Medicine