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Differences in LIMA Doppler characteristics for different LAD perfusion areas
J M Hartman1, J C Kelder, R G Ackerstaff
1Department of Cardiothoracic Surgery, University Hospital Rotterdam, Dr. Molewaterplein 40, 3015 GD Rotterdam, The Netherlands. jmhartman88@hotmail.com
Objectives:
To correlate supraclavicular left internal mammary artery (LIMA) to left anterior descending artery (LAD) area Doppler characteristics with angiographically perfused area.
Methods:
Sixty patients (50 male, mean age 62+/-7.3 years) with LIMA to LAD area grafting were prospectively entered in a follow up study. Supraclavicular echo Doppler of the LIMA was studied at the LIMA origin preoperatively, and at 4.8+/-3.8 months and 1.8+/-0.9 years postoperatively. The potential area to be revascularized judged from preoperative angiography was called the 'target' area. Control angiography (native and LIMA) was done at 1.5+/-0.9 years. The perfused area % was classified into group I < or =17.0% (n=16), group II >17.0% and <22.50% (n=17), and group III > or =22.50% (n=18) and related to LIMA Doppler characteristics. Multivariate linear regression analyses (MLRA) were performed to assess the relations between Doppler variables and the perfused area, target area and ratio of perfused/target area.
Results:
At MLRA perfused area was significantly related to the natural logarithm of diastolic peak velocity (DPV) (P=0.013) and diastolic mean velocity (P=0.048) and the ratio only to the degree of LAD stenosis (P=0.004). In hyperaemic response maximal DPV (DPV max) showed significant correlation to the perfused area (P=0.005) as well as to the ratio (P=0.017). When analyzing the additive power of both investigations, only DPV max (P=0.005) correlated significantly to the perfused area and for the ratio only the degree of stenosis of the LAD emerged as significant (P=0.004).
Conclusions:
At MLRA the diastolic flow pattern at rest and the maximal DPV in hyperaemic response correlated significantly with the LIMA run-off area whereas the last variable is the strongest predictor of the LIMA run-off area.