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Automatic Quantitation of Regional Myocardial Wall Motion and Thickening From Gated Technetium-99m Sestamibi Myocardial Perfusion Single-Photon Emission Computed Tomography

Authors
Journal
Journal of the American College of Cardiology
0735-1097
Publisher
Elsevier
Publication Date
Volume
30
Issue
5
Identifiers
DOI: 10.1016/s0735-1097(97)00276-3
Keywords
  • New Methods
Disciplines
  • Computer Science
  • Mathematics
  • Medicine
  • Physics

Abstract

Abstract Objectives. We developed an automatic quantitative algorithm for the measurement of regional myocardial wall motion and wall thickening from three-dimensional gated technetium-99m sestamibi myocardial perfusion single-photon emission computed tomographic images. Background. The algorithm measures the motion of the three-dimensional endocardial surface using a modification of the centerline method, as well as wall thickening using both geometry (gaussian fit) and partial volume (counts). Methods. The algorithm was tested using a “variable thickness” heart phantom, and the quantitative results were compared with visual segmental assessment of myocardial motion and thickening in 79 clinical patients with a wide range of ejection fractions (6% to 87%). Results. Phantom measurements of simulated motion and thickening were accurate regardless of the camera used (dual or triple detector), the angular span of reconstructed data (180° or 360°), the amount of motion (3 or 6 mm) or the amount of thickening (33%, 50% or 100%). Quantitative measurements of segmental motion and thickening in the patients were correlated with visual scores (r = 0.668, exact agreement 72.6%, kappa 0.433 and r = 0.550, exact agreement 74.7%, kappa 0.408, respectively). Significant inverse linear relations exist between the global (summed) visual motion score and the average quantitative motion, and between the global (summed) visual thickening score and the average quantitative thickening. Automatic quantitative ejection fraction measurements correlated extremely well with average quantitative motion (r = 0.929) and thickening (r = 0.959). Conclusions. Our algorithm is accurate and may be the first automatic technique for the quantitative three-dimensional assessment of regional ventricular function in cardiology.

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