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14 Assessment of mathematic models for the prediction of branching coronary anatomy using CT coronary angiography
  1. S Sultana1,
  2. Holloway2,
  3. I Das1,
  4. P Nightingale3,
  5. Peter Ludman1
  1. 1Queen Elizabeth Hospital Birmingham, UK
  2. 2Glenfield Hospital Leicester, UK
  3. 3University of Birmingham, UK

Abstract

Introduction Several mathematic models exist that purport to predict the relationship between branching vessels. In the context of diffuse atheroma, it can be difficult to appreciate if the left main stem is abnormally diffusely narrow relative to the other vessels. Accurately determining the normal size relationship is useful to define if disease is present. The purpose of this study is to assess the reliability of different mathematical models at predicting the size relationship between left main stem, left anterior descending (LAD) and circumflex arteries using CT coronary angiography.

Methods 60 consecutive CTCA examinations showing no atheroma performed as a part of a clinical service formed the study cohort. Retrospective analysis was undertaken to independently assess the diameter of the left main stem, LAD and circumflex vessels using two experienced observers. Three mathematic models were assessed to determine the accuracy of predicting left main diameter using the LAD and CX dimensions; Murray, Huo-Kassab (HK) and Finet.

Results Based on intraclass correlation values the interobserver agreement for diameter measurement is good (0.9). Murray’s formula generated a result that was the closest to the actual diameter of the three estimates in 86.0% of cases (49 of 57). Murray was the best predictor, being significantly better than both HK (p<0.001) and Finet (p<0.001). HK was significantly better than Finet (p=0.011). The disparity in size of the two daughter vessels does not affect the ability of each equation to predict LMS size.

Conclusion Our results indicate that Murray’s law is the best predictor of left main stem diameter based on the size of the LAD and circumflex coronary arteries.

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