Impact of lesion length on functional significance in intermediate coronary lesions

Clin Cardiol. 2013 Mar;36(3):172-7. doi: 10.1002/clc.22076. Epub 2012 Nov 6.


Background: Myocardial fractional flow reserve (FFR) is useful in the evaluation of coronary lesion ischemia. However, the impact of lesion length on FFR has not been adequately assessed.

Hypothesis: We hypothesized that lesion length would influence functional significance in intermediate coronary lesions.

Methods: FFR measurements were assessed in 136 patients (163 lesions) with stable angina who had >40% stenotic coronary lesion by quantitative coronary angiography (QCA). One hundred sixty-three lesions were classified as intermediate (40%-70% stenosis; n=107; group I) or significant (≥70%; n=56; group S) by QCA. We assessed the relationships between lesion length, coronary stenosis, and FFR in these 163 lesions.

Results: Regression analysis revealed an inverse correlation between the percentage of diameter stenosis (%DS) and FFR in group S (r = -0.83, P < 0.0001). In group I, no significant correlation was found between %DS and FFR (r = -0.06, P = 0.55), whereas lesion length was significantly inversely correlated with FFR (r = -0.79, P < 0.0001). Receiver operating characteristic curve analysis demonstrated that the best cutoff value for predicting an FFR value <0.80 was a lesion length >16.1 mm in group I (sensitivity, 86%; specificity, 94%).

Conclusions: These study findings suggest that lesion length has a physiologically significant impact on intermediate-grade coronary lesions.

Publication types

  • Comparative Study

MeSH terms

  • Aged
  • Angina, Stable / diagnosis
  • Angina, Stable / physiopathology
  • Cardiac Catheterization*
  • Chi-Square Distribution
  • Coronary Angiography*
  • Coronary Stenosis / diagnosis*
  • Coronary Stenosis / diagnostic imaging
  • Coronary Stenosis / physiopathology
  • Female
  • Fractional Flow Reserve, Myocardial*
  • Humans
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • ROC Curve
  • Regression Analysis
  • Severity of Illness Index