Multimodal Cardiac CT-Derived High-Risk Coronary and Myocardial Features for Predicting Adverse Outcomes After PCI in Patients With Acute Myocardial Infarction: A Multicenter Prospective Cohort Study
Conditions: Acute Myocardial Infarction (AMI)
Sponsor: Nanjing First Hospital, Nanjing Medical University

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Official title: 
Multimodal Cardiac CT–Derived High-Risk Coronary and 
Myocardial Features for Predicting Adverse Outcomes After 
PCI in Patients with Acute Myocardial Infarction: A Multicenter 
Prospective Cohort Study 
 
NCT number: 
 
Document date: April 11, 2026 
 

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1. Study Background 
Acute myocardial infarction (AMI) remains one of the leading causes 
of mortality in China. Even after successful percutaneous coronary 
intervention (PCI) and guideline-directed medical therapy, patients 
with coronary artery disease continue to face a substantial annual 
risk of adverse cardiovascular events, including heart failure, 
recurrent ischemic events, and malignant arrhythmias. Effective risk 
stratification is therefore essential for tailoring treatment strategies 
and optimizing patient outcomes. However, currently available tools 
for predicting adverse outcomes after PCI in patients with AMI are 
limited by suboptimal predictive accuracy or restricted accessibility. 
Cardiac imaging plays a central role in post-AMI risk assessment, 
with echocardiography serving as the standard imaging modality. 
Current clinical guidelines recommend routine echocardiographic 
evaluation after PCI to assess left ventricular function, right 
ventricular function, and valvular abnormalities, as well as to 
exclude early post-infarction mechanical complications and left 
ventricular thrombus formation. However, its ability to predict 
subsequent left ventricular remodeling remains uncertain. 
Cardiac magnetic resonance imaging (CMR) has emerged as the 
most powerful imaging modality for predicting adverse left 

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ventricular remodeling after AMI. Key prognostic indicators, 
including 
infarct 
size, 
microvascular 
obstruction, 
and 
intramyocardial hemorrhage, can be comprehensively evaluated 
using CMR and have been shown to be independent predictors of 
clinical outcomes in patients with AMI. Nevertheless, the routine 
implementation of CMR following AMI remains challenging due to 
limited availability, high cost, and logistical constraints. Moreover, 
although 
CMR 
provides 
comprehensive 
myocardial 
tissue 
characterization, it does not assess coronary artery anatomy, 
thereby limiting its ability to provide a comprehensive risk 
assessment that incorporates atherothrombotic components. 
In recent years, cardiac computed tomography (CT) has evolved 
into a first-line imaging modality for the evaluation of patients with 
chest pain. In addition to assessing coronary artery stenosis and 
high-risk plaque characteristics, cardiac CT can also evaluate 
cardiac morphology, function, and myocardial tissue characteristics. 
A recent meta-analysis demonstrated that CT-based delayed iodine 
enhancement imaging shows excellent diagnostic accuracy 
compared with late gadolinium enhancement on CMR. Furthermore, 
CT-derived extracellular volume fraction (ECV) enables quantitative 
assessment of myocardial fibrosis. Therefore, multimodal cardiac 

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CT provides an unprecedented opportunity for comprehensive risk 
stratification in patients with AMI following PCI. 
In this study, we plan to prospectively collect clinical and imaging 
data from 1,000 patients with AMI who have undergone PCI. The 
objectives are to evaluate the diagnostic performance of multimodal 
cardiac CT in assessing cardiac structure and function after PCI, 
identify key imaging biomarkers associated with adverse outcomes 
after AMI, and develop a machine learning–based predictive model 
for early risk stratification of adverse clinical outcomes in patients 
with AMI. The implementation of this study is expected to establish 
a novel risk assessment strategy for patients with AMI after PCI, 
thereby facilitating personalized management of coronary artery 
disease and reducing the incidence of future adverse cardiovascular 
events. 
2. Study Objectives 
Primary Objective: To investigate the association between high-risk 
coronary and myocardial features derived from multimodal cardiac 
CT and adverse clinical outcomes in patients with acute myocardial 
infarction (AMI) after PCI. 
Secondary Objective: To evaluate the diagnostic performance of 
multimodal cardiac CT in assessing cardiac morphology and 

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function in patients with AMI after PCI. 
 
3. Study Design, Methods, and Procedures 
3.1 Study Design 
This study is designed as a prospective, multicenter study. 
3.2 Sample Size Calculation 
Sample size was estimated according to the rule-of-thumb principle, 
which requires at least 10 events per predictor variable in predictive 
modeling. Based on previous studies, the estimated 2-year 
incidence of thrombotic events after PCI in patients with AMI is 
approximately 8%. The covariates included in the model consist of 
clinical variables such as age, sex, clinical presentation, 
hypertension, diabetes mellitus, and statin therapy. Considering a 5% 
dropout rate, at least 921 participants are required. The estimated 
2-year incidence of heart failure and severe arrhythmic events after 
PCI in patients with AMI is approximately 20%, with the same set of 
clinical covariates included in the model. After accounting for a 5% 
dropout rate, at least 368 participants are required. To ensure 
adequate statistical power for both major endpoints, a total of 1,000 
participants will be enrolled in the study. 

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3.3 Study Procedures 
(1) Screening Phase 
A total of 1,000 patients with AMI undergoing PCI will be screened. 
All participants will undergo multimodal cardiac CT within 7 days 
after PCI, either following the index procedure or staged PCI. In 
addition, 50 participants will undergo cardiac magnetic resonance 
imaging (CMR) within 2 days after cardiac CT for comparative 
imaging analysis. 
(2) Clinical Data Collection 
Clinical information will be collected, including: Demographic 
characteristics: age, sex, body weight, height, clinical symptoms, 
cardiovascular risk factors (hypertension, diabetes mellitus, 
smoking history, and chronic kidney disease), medication history, 
laboratory 
biomarkers 
(hematocrit, 
low-density 
lipoprotein 
cholesterol, lipoprotein a, blood glucose, high-sensitivity C-reactive 
protein, interleukin-6, and other biochemical markers), PCI-related 
procedural data 
(3) Cardiac CT Follow-up 
Participants who remain free of thrombotic events, heart failure, or 
severe arrhythmias within one year after the baseline cardiac CT 

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examination will be recommended to undergo repeat cardiac CT 
imaging. Blood biochemical parameters, including triglycerides, LDL 
cholesterol, blood glucose, hs-CRP, and IL-6, will also be analyzed 
during this follow-up period. 
(4) Echocardiographic Follow-up 
Participants will be recommended to undergo transthoracic 
echocardiography at the following time points: 
6 months 
12 months 
2 years 
3 years 
4 years 
5 years 
(5) Clinical Follow-up 
All participants will undergo clinical follow-up at 1 month, 3 months, 
6 months, 12 months, 2 years, 3 years, and 4 years after PCI, and 
annually thereafter until the last enrolled participant completes 5 
years of follow-up. Follow-up will be conducted through telephone 
interviews or outpatient clinic visits. 

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4. Coronary Angiography and PCI Procedures 
Coronary angiography was performed according to standard clinical 
practice. All culprit lesions underwent successful PCI, which could 
be performed either during the index procedure or as a staged 
procedure within two months. These included lesions responsible 
for acute coronary syndrome (ACS) as well as other lesions with 
hemodynamically significant stenosis requiring revascularization. 
The decision to assess the hemodynamic significance of coronary 
lesions using fractional flow reserve (FFR), instantaneous wave-free 
ratio (iFR), or quantitative flow ratio (QFR) was made at the 
discretion of the interventional cardiologist. Eligible patients were 
required to undergo successful PCI of the culprit lesion without 
major procedural complications. Successful PCI was defined as 
residual diameter stenosis <50% at the target lesion with restoration 
of TIMI grade 3 coronary flow. 
 
5. Multimodal Cardiac CT Acquisition and Analysis 
5.1 Multimodal Cardiac CT Acquisition 
All participants at the study center underwent multimodal cardiac CT 

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using a third-generation dual-source CT scanner (Siemens). Prior to 
scanning, 0.1 mg of sublingual nitroglycerin was administered 3–5 
minutes before image acquisition. A breath-hold scout scan was 
performed from the thoracic inlet to the cardiac diaphragm. The 
acquisition range for coronary CT angiography (CCTA) extended 
from 2 cm below the tracheal carina to the cardiac diaphragm, with 
an additional 10–20 mm margin beyond the cardiac borders 
bilaterally. A dual-head power injector (Urich) was used to administer 
60–80 mL of nonionic iodinated contrast agent (iopromide, 370 mg 
iodine/mL; Bayer, Germany) via a peripheral vein at an injection rate 
of 5.0 mL/s. Scan timing was determined using an artificial 
intelligence–assisted bolus tracking system, with the region of 
interest placed in the ascending aorta. Image acquisition was 
automatically triggered 7 seconds after the attenuation value 
reached 100 HU. Scanning parameters included: Tube voltag 80–
120 kVp and automatic tube current modulation. For cardiac 
multiphase image reconstruction, images were reconstructed 
throughout the entire cardiac cycle (0%–95%) at 5% intervals of the 
R–R interval, with a slice thickness of 0.75 mm, generating 20 
phases of cardiac cine images. After completion of CCTA acquisition, 
an additional 40 mL of contrast agent was injected, followed by a 5-
minute 
delay 
before 
performing 
dual-energy 
CT 
delayed 

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enhancement 
imaging. 
Scanning 
parameters 
for 
delayed 
enhancement imaging were as follows: 
Tube A: 90 kV, 165 mA 
Tube B: 150 kV, 127mA 
5.2 CCTA Image Analysis 
All CCTA images were interpreted by experienced radiologists. The 
presence of a coronary plaque on CCTA was considered a positive 
finding. Coronary artery segments were analyzed according to the 
18-segment model recommended by the American Heart 
Association (AHA). The number, location, and degree of stenosis of 
plaques were recorded, along with the total number of coronary 
segments involved by atherosclerotic lesions. 
Assessment of Coronary Artery Stenosis 
The degree of coronary artery stenosis was classified as follows: no 
stenosis; minimal stenosis (1–24%); mild stenosis (25–40%); 
moderate stenosis (50–69%); severe stenosis (70–99%); and 
total occlusion. Stenosis of ≥50% was defined as significant 
stenosis. 
Qualitative Plaque Analysis 
High-risk plaque (HRP) features included low-attenuation plaque, 

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napkin-ring sign, positive remodeling, and spotty calcification. 
a) Low-attenuation plaque was defined as a non-calcified plaque 
with an attenuation value of <30 Hounsfield units (HU) measured 
within the plaque. 
b) Napkin-ring sign was defined as a central low-attenuation plaque 
core adjacent to the coronary lumen surrounded by a higher-
attenuation rim. 
c) Spotty calcification was defined as calcified foci within plaques 
with a diameter <3 mm on any cross-sectional image and occupying 
less than one-quarter of the vessel circumference. 
d) Positive remodeling was defined as a ratio of the maximum vessel 
diameter at the lesion site (including plaque and lumen) to the mean 
diameter of the proximal and distal reference segments ≥1.1. 
The presence of two or more of these features was defined as a 
high-risk plaque. 
Quantitative Plaque Analysis 
Quantitative plaque analysis was performed using a semi-
automated plaque analysis software (Medis). The following 
parameters were measured: 
Degree of stenosis 

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Plaque length 
Total plaque volume 
Calcified plaque volume 
Non-calcified plaque volume 
Minimum lumen area (MLA) 
Remodeling index (RI) 
Plaque burden (PB) 
Total plaque volume (TPV) 
Percent atheroma volume (PAV) 
Plaque volume was calculated as: Plaque volume = vessel volume 
− lumen volume. At the patient level, plaque volume was defined as 
the sum of all plaque volumes. The minimum lumen area (MLA) was 
defined as the lumen area at the site of maximal stenosis. The 
remodeling index (RI) was calculated as: RI = lumen area at the 
most stenotic site / mean lumen area of the proximal and distal 
reference segments. Positive remodeling was defined as RI > 1.1. 
Local plaque burden (PB) was defined as: PB = plaque area / vessel 
area at the site of the minimum lumen area. Percent atheroma 
volume (PAV) was calculated as: PAV = 100% × (plaque volume / 

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vessel volume). Plaque components were classified based on CT 
attenuation values:  
Lipid plaque: <30 HU 
Fibrofatty plaque: 30–130 HU 
Fibrous plaque: 130–350 HU 
Calcified plaque: >350 HU 
Non-calcified plaque volume was defined as the sum of: fibrous 
plaque volume + fibrofatty plaque volume + lipid plaque volume. 
CT-Derived Fractional Flow Reserve (CT-FFR) Analysis 
CT-FFR analysis was performed using a fully automated CT-FFR 
analysis software (Shukun Technology). The software automatically 
measured CT-FFR values throughout the entire coronary tree 
without manual adjustment. The following parameters were 
recorded:  
CT-FFR value 2 cm distal to the lesion 
Terminal CT-FFR value of the vessel 
Translesional ΔCT-FFR 
Pericoronary Adipose Tissue Inflammation Analysis 
Pericoronary adipose tissue inflammation analysis was conducted 

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using a fully automated analysis software (Shukun Technology), 
which automatically quantified pericoronary fat inflammation along 
the coronary artery tree. The following parameters were recorded: 
Patient-level FAI measured in the proximal 1–5 cm segment of the 
right coronary artery (RCA) 
Lesion-specific FAI surrounding the culprit lesion 
Cardiac Function and Strain Analysis 
Multiphasic cardiac CT images were transferred to the CVI42 post-
processing workstation for analysis. The software automatically 
delineated the endocardial and epicardial borders, with manual 
adjustment performed when necessary. After segmentation, the 
software automatically calculated cardiac structural parameters. 
Dual-Energy Delayed Enhancement Analysis and Extracellular 
Volume (ECV) 
Dual-energy delayed enhancement images were transferred to the 
Siemens post-processing workstation (syngo.via VB60) for analysis. 
In the MM Reading module, delayed iodine enhancement of the left 
ventricular myocardium was evaluated by comparing with coronary 
CT angiography images. The delayed enhancement data were then 
imported into the Heart-PBV module, where the software 

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automatically 
generated 
iodine 
maps 
based 
on 
material 
decomposition algorithms, displaying iodine distribution throughout 
the myocardium. Delayed iodine density values were obtained from 
left ventricular myocardium and blood pool. Regions of interest 
(ROIs) were manually drawn within the left ventricular myocardium, 
avoiding artifacts such as beam hardening. On the same slice, a 
ROI with a minimum size of 200 mm² was placed in the left 
ventricular blood pool. Finally, the extracellular volume fraction (ECV) 
was calculated using the following formula: 
ECV = (HUm / HUb) × (1 − HCT) × 100% 
HUm = delayed iodine density of the myocardium 
HUb = delayed iodine density of the blood pool 
HCT = hematocrit 
6. Follow-up 
The follow-up assessment included composite clinical outcomes at 
both the vessel level and the patient level, comprising: 
Thrombotic events, including cardiac death, recurrent myocardial 
infarction, and urgent or clinically driven revascularization. 
Heart failure and arrhythmic events, including new-onset congestive 
heart failure, sustained ventricular arrhythmia, implantable 

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cardioverter-defibrillator (ICD) implantation, sudden cardiac death 
or resuscitated cardiac arrest. 
Identification of culprit lesions was determined based on 
electrocardiographic findings, repeat coronary CT angiography 
(CCTA), or invasive coronary angiography. Clinical follow-up was 
conducted through outpatient visits, telephone interviews, and 
review of electronic medical records. All primary endpoint events 
were independently reviewed and adjudicated by a blinded clinical 
event adjudication committee. 
7. Study Population 
The study population consisted of patients with acute myocardial 
infarction (AMI) who underwent percutaneous coronary intervention 
(PCI). Patients were enrolled if they met the following criteria: age 
≥18 years; AMI occurring within 4 weeks prior to enrollment, 
including ST-segment elevation myocardial infarction (STEMI) or 
non–ST-segment elevation myocardial infarction (NSTEMI); PCI 
performed for the culprit lesion of acute coronary syndrome (ACS) 
according to current clinical guidelines; hemodynamically stable 
condition; willingness to undergo multimodality cardiac CT 
examination within 7 days after PCI; and agreement to participate in 
telephone follow-up. 

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Patients were excluded if they met any of the following criteria: 
inability to undergo cardiac CT examination (such as estimated 
glomerular filtration rate [eGFR] <30 mL/min/1.73 m² or iodinated 
contrast allergy); prior coronary artery bypass grafting (CABG); 
previous diagnosis of congestive heart failure or prior myocardial 
infarction; severe arrhythmia or structural heart disease; poor-
quality multimodality cardiac CT images or missing imaging data; or 
an expected life expectancy of less than 6 months. 
8. Statistical Analysis 
All analyses were conducted using SPSS software (IBM SPSS, 
version 26.0; SPSS Inc., Chicago, IL, USA), MedCalc (version 
18.2.1, Ostend, Belgium), and R software (version 4.0.3, R 
Foundation for Statistical Computing). Categorical variables were 
presented as frequencies and percentages, while continuous 
variables were expressed as mean ± standard deviation (SD) for 
normally distributed data or as median with interquartile range 
(25th–75th percentiles) for non-normally distributed data. For 
comparisons between groups, categorical variables were analyzed 
using the Pearson χ² test, with continuity-corrected χ² test or 
Fisher’s exact test applied when appropriate. Normally distributed 
continuous variables were compared using the independent 

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samples t-test, whereas non-normally distributed variables were 
compared using the Mann–Whitney U test. High-risk plaque 
morphological characteristics were defined as follows: high local 
plaque burden was defined as minimum lumen area (MLA) <4 mm2 
and plaque burden (PB) ≥70%; high global plaque burden was 
defined as total plaque volume (TPV) or percent atheroma volume 
(PAV) ≥ the median value; high low-attenuation plaque burden 
was defined as >4%; and high-risk plaque was defined as the 
presence of two or more high-risk plaque features. Receiver 
operating characteristic (ROC) curves were constructed to evaluate 
the predictive value of CT-derived fractional flow reserve (CT-FFR) 
for major adverse cardiovascular events (MACE), and the optimal 
cutoff value was determined using the Youden index to define high-
risk 
hemodynamic 
characteristics. 
High-risk 
myocardial 
characteristics included the number of myocardial segments with 
delayed enhancement, extracellular volume fraction (ECV), 
myocardial ejection fraction, and myocardial strain parameters. 
Kaplan–Meier survival analysis with the log-rank test was used to 
estimate and compare cumulative event rates between groups with 
different high-risk coronary plaque and myocardial characteristics. 
Furthermore, Cox proportional hazards regression models were 
applied to evaluate the association between coronary plaque high-

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risk features, myocardial high-risk characteristics, and clinical 
outcomes, with results reported as hazard ratios (HRs) and 
corresponding 95% confidence intervals (CIs). 
9. Ethical Principles and Requirements for Clinical Research 
This clinical study will be conducted in accordance with the ethical 
principles outlined in the Declaration of Helsinki issued by the World 
Medical Association. 
10. Study Timeline 
From January 2026 to April 2026, ethical approval will be obtained 
from the Ethics Committee and the study protocol will be finalized.  
From April 2026 to December 2029, data collection, data analysis, 
and clinical follow-up will be conducted.  
From December 2029 to December 2030, manuscript preparation, 
submission for publication, and dissemination of study results will 
be completed. 
 

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