title: Important parameters in the detection of left main trunk disease using stress myocardial perfusion imaging.
abstract: OBJECTIVE
  We sought noninvasively to diagnose left main trunk (LMT) disease using myocardial perfusion imaging (MPI).
  
  
  METHODS
  Five hundred and eight patients with suspected coronary artery disease (CAD) underwent both stress MPI and coronary angiography. The extent and severity of perfusion abnormalities were assessed using a 20-segment model. In addition, perfusion defects in both left anterior descending and left circumflex arterial territories were defined as a left main (LM) pattern defect, and those in 3-coronary arterial territories as a 3-vessel pattern defect.
  
  
  RESULTS
  In 42 patients with LMT disease, a summed stress score (19.4 ± 10.0 vs. 13.5 ± 10.0; p < 0.0001) and a summed rest score (12.1 ± 9.7 vs. 7.0 ± 7.8; p = 0.002) were greater than in 466 patients without LMT disease, while a summed difference score was similar (7.3 ± 7.7 vs. 6.5 ± 6.1; p = NS). The prevalence of an LM-pattern defect was low in both groups (12% vs. 8%; p = NS). However, a 3-vessel pattern defect (33% vs. 7%; p < 0.0001), lung uptake of radiotracers (38% vs. 11%; p < 0.0001), and transient ischemic dilation (31% vs. 13%; p = 0.003) were more frequently observed in patients with LMT disease than in those without. Logistic regression analysis showed that a 3-vessel pattern defect (OR=3.5, 95% CI = 1.4-8.8; p = 0.007), lung uptake of radiotracers (OR = 2.5, 95% CI = 1.1-5.7; p = 0.03), and previous myocardial infarction (MI) (OR = 2.4, 95% CI = 1.0-5.7; p = 0.05) were the most important parameters to detect LMT disease. After excluding 163 patients with previous MI, a repeat analysis revealed that lung uptake of radiotracers (OR = 8.2, 95% CI = 2.3-29.2; p = 0.001) and an LM-pattern defect (OR = 6.3, 95% CI = 1.4-27.2; p < 0.02) were independent predictors for LMT disease.
  
  
  CONCLUSIONS
  In the identification of LMT disease, lung uptake of radiotracers was a single best parameter, which was independent of the presence or absence of previous MI.
authors.affiliation: Department of Cardiology, Tokyo Medical University, Shinjuku-ku, Tokyo, Japan.
authors.forename: Chie
authors.initials: C
authors.lastname: Shiba
authors.forename: Taishiro
authors.initials: T
authors.lastname: Chikamori
authors.forename: Satoshi
authors.initials: S
authors.lastname: Hida
authors.forename: Yuko
authors.initials: Y
authors.lastname: Igarashi
authors.forename: Hirokazu
authors.initials: H
authors.lastname: Tanaka
authors.forename: Ken-Ichi
authors.initials: K
authors.lastname: Hirose
authors.forename: Yuka
authors.initials: Y
authors.lastname: Ohtaki
authors.forename: Yasuhiro
authors.initials: Y
authors.lastname: Usui
authors.forename: Manabu
authors.initials: M
authors.lastname: Miyagi
authors.forename: Tsuguhisa
authors.initials: T
authors.lastname: Hatano
authors.forename: Akira
authors.initials: A
authors.lastname: Yamashina
mesh_terms: D000368:Aged; D017023:Coronary Angiography; D003327:Coronary Disease / Q000000981:diagnostic imaging*; D005080:Exercise Test / Q000379:methods*; D005260:Female; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging; D008297:Male; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D012189:Retrospective Studies; D015899:Tomography, Emission-Computed, Single-Photon