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Quantitative analysis of coronary arteriograms by microprocessor cinevideodensitometry.

K H Silver1, J A Buczek, P D Esser

  • 1College of Physicians and Surgeons, Columbia University, New York, New York.

Catheterization and Cardiovascular Diagnosis
|September 1, 1987
PubMed
Summary

A new microprocessor method accurately measures coronary artery stenosis using cinevideodensitometry. This technique offers a rapid, inexpensive, and reproducible way to assess coronary artery dimensions and disease severity.

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Area of Science:

  • Cardiovascular imaging
  • Medical device technology
  • Quantitative coronary angiography

Background:

  • Assessing coronary atherosclerotic lesions requires accurate measurement of stenosis.
  • Existing methods for measuring coronary artery dimensions can be time-consuming or expensive.

Purpose of the Study:

  • To develop and validate a rapid microprocessor technique for measuring coronary artery dimensions and stenosis.
  • To evaluate the accuracy, reproducibility, and cost-effectiveness of the developed method.

Main Methods:

  • Developed a cinevideodensitometric analysis technique using a microprocessor system.
  • Analyzed video images from coronary arteriographic cine frames.
  • Validated measurements using radiographic phantoms and postmortem coronary artery casts.

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Main Results:

  • Cinevideodensitometric measurements showed high linear correlation with known stenosis percentage, diameter, and cross-sectional area in phantom studies.
  • Measurements correlated well with acrylic resin casts of coronary arteries in postmortem studies.
  • Demonstrated low intraobserver and interobserver variability and superior reproducibility compared to caliper measurements.

Conclusions:

  • The developed microprocessor system provides rapid and accurate measurements of coronary arterial dimensions and stenosis.
  • This inexpensive technique offers a reproducible alternative to existing methods for quantitative coronary angiography.
  • The system eliminates the need for manual tracing and expensive mainframe computers.