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Plaque assessment on coronary CT Angiography: Is there clinical value ?
Damini Dey, PhD, FSCCT
Associate Professor and Research Scientist Director, Quantitative Image Analysis Lab
Biomedical Imaging Research Institute Cedars-Sinai Medical Center
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Normal coronary CTA
43-y/o woman, family history of CAD
Normal CCTA. HR 65 bpm
100 kVp, Prospective
Radiation Dose 1.5 mSv
Warranty period for normal CTA: at least 8 years
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Coronary CTA – with Atherosclerosis
Noncalcified, low-density non-calcified plaque Calcified plaque
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Dangerous plaques: healing the heart National Geographic 2007
Coronary plaque
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Plaque assessment from coronary CTA
• High-risk plaque features - Low-attenuation < 30 HU - Positive remodeling - Napkin-ring sign • Quantitative plaque Characterization - Low-attenuation NCP - Plaque composition, burden - Positive remodeling - Stenosis & luminal features
Motoyama et al JACC 2009 Otsuka et al JACC imaging 2013
Hell et al EHJ-CI 2017, Doris et al JCCT 2017
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Quantitative plaque characterization from coronary CTA
• Standardized semi-automated software - Total plaque - Non-calcified plaque (NCP) - Calcified plaque - Low-attenuation NCP - Plaque composition - Positive outward remodeling - Stenosis
Hell et al EHJ-Cardiovascular Imaging 2017 Per-lesion, per-vessel and per-patient
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Total coronary plaque volume: IVUS
Matsumoto, …,Dey et al European Radiology 2019
118 plaques in 77 patients with IVUS
R = 0.943, p<0.001
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Lumen intima border
External elastic membrane
Coronary CTA
IVUS
NCP volume – blinded comparison to IVUS
Dey et al Radiology 2010
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NCP volume measurement
Dey et al Radiology 2010
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NCP volume measurement
116.6100.8105.9
0
50
100
150
200
IVUS Manual CCTA
APQ
NCP Volume
P=NS P=NS
Volu
me
(mm
3 )
Dey et al Radiology 2010
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Comparison with IVUS: Qangio CT
Park et al Eur Radiol 2015
142 patients
with IVUS
Stenosis, MLA,
plaque volume
and burden
R = 0.91 expert R=0.84 automated
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Plaque and Lesion-specific ischemia
from prospective, multicenter studies
Park et al JACC Cardiovascular Imaging 2015 Diaz Zamudio et al Radiology 2015
Gaur et al European Heart Journal 2016
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Plaque composition and Lesion-specific ischemia: prospective, multicenter NXT trial
254 patients
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Does plaque composition add to stenosis to predict FFR ?
Gaur et al European Heart Journal 2016
• Multicenter NXT trial • 254 patients (64% male) • 484 vessels with FFR
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• NXT trial N=254 (484 vessels) analyzed for stenosis, plaque and scan findings • Highest predictive value for contrast density difference and low attenuation plaque
Machine learning for integrating plaque features to predict ischemia Machine learning for decision-making
Dey et al European Radiology 2018
*
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Machine learning ischemia risk score from CTA Invasive FFR LAD = 0.73
Dey et al Artificial intelligence in Cardiovascular Imaging JACC 2019
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• 2748 patients, no prior CAD • Followup of 5 ± 2 years • 32 patients with cardiac death compared to controls matched by age, gender, risk factors and symptoms • Plaque analysis by Autoplaque
Quantitative plaque: prediction of future cardiac death
Hell et al EHJ Cardiovascular Imaging 2017
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Quantitative plaque: prediction of future cardiac death
Michaela Hell et al EHJ Cardiovascular Imaging 2017
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Quantitative plaque: prediction of future cardiac death
Among quantitative global plaque characteristics, low-density NCP, NCP and total plaque volume as well
as CDD predict future cardiac death Michaela Hell et al EHJ Cardiovascular Imaging 2017
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• ICONIC: nested case control study within CONFIRM registry (13 sites)
• Followup: 3.4 ± 2.1 years • 234 patients with ACS matched
to 234 controls – risk factors and CTA stenosis
• Plaque analysis by core lab with QAngio CT software
Quantitative plaque composition: as precursor of ACS
Chang et al JACC 2018; 71(22):2511-22
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• NCP components - Necrotic core NC (-30, 30) HU - Fibrofatty FF (31-130) HU - Fibrous (131-350) HU
• High-risk noncalcified plaque – precursor of ACS
Quantitative plaque composition: as precursor of ACS
Chang et al JACC 2018; 71(22):2511-22
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Quantitative plaque burden: beneficial changes with therapy ?
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Plaque changes with statins
• PARADIGM cohort (13-center)
• 1255 patients serial CTA ≥ 2 years apart
• Plaque measurement by core lab QAngio CT
Lee et al JACC Cardiovascular Imaging 2018
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Plaque changes with statins
Lee et al JACC Cardiovascular Imaging 2018
• PARADIGM cohort (13-center)
• 1255 patients serial CTA ≥ 2 years apart
• Plaque volume: 21% reduction
• HRP: 35% reduction
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Plaque changes with statins
Lee et al JACC Cardiovascular Imaging 2018 Lee et al Circ Cardiovascular Imaging 2018
• Statins were associated with slower progression of total plaque volume, with increased plaque calcification and reduction of high-risk plaque features.
• Statins did not affect the progression of percent stenosis but induced changes in plaque composition.
• Both baseline plaque burden and its change improved prediction of MACE
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Baseline Follow-up
LDL-C (mg/dl) 164 80
Plaque volume(mm3) Total plaque 581.6 408.0
Calcified plaque 67.8 63.6
Non-calcified plaque 513.9 344.3
Low-density non-calcified plaque 42.2 12.0
Baseline Follow-up
CTA plaque changes with LDL decrease ≥ 10% over 1 year 52 y.o. male with family history of CAD on statin
LAD
CP
NCP
Tamarappoo, Otaki,…, Dey, Berman et al, JCCT 2018
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Otaki, Tamarappoo,…, Dey, Berman Otaki et al Atherosclerosis 2019
-60
-40
-20
0
20
40
60
80
100
h t tih ti tih ff ti h f ti h d ti
Annu
al c
hang
e in
pla
que
volu
me
(mm
3 ) p<0.0001
p=0.0001* p=0.0001* p=0.0005* p=0.60
Plaque volume change with LDL decrease and increase All plaque components
Medium attenuation
Total plaque
Calcified plaque
Low attenuation
Medium-low attenuation
Patients with LDL decrease Patients with no LDL decrease
154 patients with serial CTA time interval 4±2 years
Non-calcified plaque
Reduction in LDL (≥10%) related to beneficial changes in plaque composition ( all components of NCP)
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• CTA allows plaque characterization over the coronary tree
• Quantitative CTA measures improves prediction of lesion-specific ischemia beyond stenosis
– Low-density noncalcified plaque
– Noncalcified plaque
– Positive remodeling
– Contrast density difference
Summary: quantitative CTA
Adverse cardiac events
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• More automation and standardization necessary - for faster accurate analysis
• Adverse plaque thresholds needed
• Noninvasive quantitative plaque characterization
• Improves identification of patients at risk of ischemia and cardiac events
• Improves prognostication
• Allows assessment of serial therapy: emphasis on prevention
Summary
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Thank you very much
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Quantitative plaque burden predict ischemia in intermediate coronary lesions ?
Diaz-Zamudio et al Radiology 2015
CTA
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Automated quantification in a 65-y-o male patient. FFR (at arrow)= 0.78
DS= 34%
TP= 43%
CP= 13%
NCP= 30%
LDNCP= 2%
Quantitative plaque burden predict ischemia in intermediate coronary lesions ?
Diaz-Zamudio et al Radiology 2015
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Quantitative plaque burden predict ischemia in intermediate coronary lesions ?
Diaz-Zamudio et al Radiology 2015