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Related Experiment Videos

Multi-detector row CT of left ventricular function with dedicated analysis software versus MR imaging: initial

Kai Uwe Juergens1, Matthias Grude, David Maintz

  • 1Department of Clinical Radiology, University of Muenster, Albert-Schweitzer-Strasse 33, D-48149 Muenster, Germany. kujuerg@uni-muenster.de

Radiology
|December 12, 2003
PubMed
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Semiautomated software accurately analyzes left ventricular (LV) function and volume using multi-detector row CT. Results closely correlate with magnetic resonance (MR) imaging, offering a reliable alternative for cardiac assessment.

Area of Science:

  • Cardiovascular imaging
  • Medical physics
  • Radiology

Background:

  • Accurate assessment of left ventricular (LV) volumetric and functional parameters is crucial for diagnosing and managing cardiovascular diseases.
  • Magnetic resonance (MR) imaging is considered a gold standard for cardiac assessment, but computed tomography (CT) offers wider availability and faster acquisition times.

Purpose of the Study:

  • To evaluate the accuracy of semiautomated analysis software in determining LV volumetric and functional parameters from retrospectively electrocardiographically gated multi-detector row CT (MDCT) data.
  • To compare these CT-derived parameters with those obtained from MR imaging in a cohort of patients.

Main Methods:

  • Thirty patients with known or suspected coronary artery disease underwent four-channel MDCT.
  • Semiautomated contour detection software was used to calculate end-diastolic and end-systolic LV volumes from CT images.

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  • Cine MR images were acquired within 48 hours and analyzed using dedicated software.
  • Bland-Altman analysis was performed to assess agreement and systematic errors between CT and MR imaging.

    • Main Results:

    • Mean LV end-diastolic and end-systolic volumes derived from CT showed excellent correlation with MR imaging measurements (r = 0.93 and r = 0.94, respectively).
    • LV ejection fraction and stroke volume also demonstrated strong correlations between CT and MR imaging (r = 0.89 and r = 0.88, respectively).
    • Bland-Altman analysis indicated acceptable limits of agreement for ejection fraction (+/-9.8%) without significant systematic errors.

    Conclusions:

    • Semiautomated analysis software provides accurate LV volumetric and functional assessment from MDCT datasets.
    • CT-derived parameters correlate well with MR imaging findings, suggesting its utility in selected patient populations.
    • This approach offers a potentially valuable tool for cardiac assessment, complementing existing imaging modalities.