Impaired aortic distensibility measured by computed tomography is associated with the severity of coronary artery

Naser Ahmadi1, Vahid Nabavi, Fereshteh Hajsadeghi

  • 1Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, 1124 W. Carson Street, RB2, Torrance, CA 90502, USA. nahmadi@labiomed.org

Insights

Impaired aortic distensibility (ADI) measured by computed tomographic angiography strongly correlates with coronary atherosclerosis severity. Adding ADI to coronary artery calcium (CAC) and risk factors improves prediction of cardiovascular disease risk.

Area of Science:

  • Cardiovascular Imaging
  • Atherosclerosis Research
  • Biomedical Engineering

Background:

  • Impaired aortic distensibility index (ADI) is linked to cardiovascular risk factors.
  • Assessing ADI's relationship with coronary atherosclerosis severity is crucial for risk stratification.

Purpose of the Study:

  • To evaluate the association between ADI measured by computed tomographic angiography (CTA) and the severity of coronary atherosclerosis.
  • To compare CTA-derived ADI with echocardiography-derived ADI.
  • To determine the incremental predictive value of ADI in individuals with suspected coronary artery disease (CAD).

Main Methods:

  • Two hundred twenty-nine subjects with suspected CAD underwent CTA and coronary artery calcium (CAC) scanning.
  • ADI was calculated using CTA-derived aortic cross-sectional area changes and systemic pulse pressure.
  • Correlation between CTA- and TTE-derived ADI was assessed. ADI, CAC, and Framingham Risk Score (FRS) were analyzed against CAD severity.

Main Results:

  • CTA-derived ADI showed excellent correlation with TTE-derived ADI (r²=0.94, P=0.0001).
  • ADI decreased significantly with increasing CAC scores and FRS categories (P<0.05).
  • Lower ADI was independently associated with higher CAC scores and CAD severity, demonstrating incremental predictive value over FRS and CAC alone.

Conclusions:

  • Impaired aortic distensibility, measured by CTA, is a strong indicator of coronary atherosclerosis severity.
  • Incorporating ADI into risk assessment models alongside CAC and traditional risk factors enhances the prediction of individuals at risk for CAD.

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