Plaque progression assessed by a novel semi-automated quantitative plaque software on coronary computed tomography angiography between diabetes and non-diabetes patients: A propensity-score matching study.
We aimed at investigating whether diabetes is associated with progression in coronary plaque components.



We identified 142 study subjects undergoing serial coronary computed tomography angiography. The resulting propensity score was applied 1:1 to match diabetic patients to non-diabetic patients for clinical risk factors, prior coronary stenting, coronary artery calcium (CAC) score and the serial scan interval, resulting in the 71 diabetes and 71 non-diabetes patients. Coronary plaque (total, calcified, non-calcified including fibrous, fibrous-fatty and low attenuation plaque [LAP]) volume normalized by total coronary artery length was measured using semi-automated plaque software and its change overtime between diabetic and non-diabetic patients was evaluated.



The matching was successful without significant differences between the two groups in all matched variables. The baseline volumes in each plaque also did not differ. During a mean scan interval of 3.4 ± 1.8 years, diabetic patients showed a 2-fold greater progression in normalized total plaque volume (TPV) than non-diabetes patients (52.8 mm3vs. 118.3 mm3, p = 0.005). Multivariable linear regression model revealed that diabetes was associated with normalized TPV progression (β 72.3, 95%CI 24.3-120.3). A similar trend was observed for the non-calcified components, but not calcified plaque (β 3.8, 95%CI -27.0-34.7). Higher baseline CAC score was found to be associated with total, non-calcified and calcified plaque progression. However, baseline non-calcified volume but not CAC score was associated with LAP progression.



The current study among matched patients indicates diabetes is associated with a greater plaque progression. Our results show the need for strict adherence of diabetic patients to the current preventive guidelines.
Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA. Electronic address: rnakanishi@labiomed.org.
Rine
R
Nakanishi
Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
Indre
I
Ceponiene
Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
Kazuhiro
K
Osawa
Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
Yanting
Y
Luo
Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
Mitsuru
M
Kanisawa
Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
Nichelle
N
Megowan
Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
Negin
N
Nezarat
Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
Sina
S
Rahmani
Leiden University Medical Center, Leiden, 2333 ZA, The Netherlands.
Alexander
A
Broersen
Leiden University Medical Center, Leiden, 2333 ZA, The Netherlands; Medis Medical Systems bv, Leiden, 2316 XG, The Netherlands.
Pieter H
PH
Kitslaar
Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
Christopher
C
Dailing
Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
Matthew J
MJ
Budoff
D000368:Aged; D001331:Automation; D002140:California; D000072226:Computed Tomography Angiography / Q000379:methods*; D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging* / Q000378:metabolism / Q000473:pathology; D003331:Coronary Vessels / Q000737:chemistry / Q000000981:diagnostic imaging* / Q000473:pathology; D003920:Diabetes Mellitus / Q000175:diagnosis; D018450:Disease Progression; D005260:Female; D005355:Fibrosis; D006801:Humans; D016014:Linear Models; D008055:Lipids / Q000032:analysis; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D061330:Multidetector Computed Tomography / Q000379:methods*; D015999:Multivariate Analysis; D058226:Plaque, Atherosclerotic; D011237:Predictive Value of Tests; D057216:Propensity Score; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012189:Retrospective Studies; D012307:Risk Factors; D012984:Software; D013997:Time Factors; D061205:Vascular Calcification / Q000000981:diagnostic imaging
D008055:Lipids
Coronary computed tomography angiography; Diabetes; Plaque progression