Summary of biomarkers, outcomes, and effect measures.
| Author | Year | Biomarker(s) assessed | Outcomes evaluated | Included in systematic review | Effective measures reported |
|---|---|---|---|---|---|
| Nakahara et al. [1] | 2017 | Coronary artery calcification (CAC) | Cardiovascular events, risk stratification | Yes | CAC (Agatston score): independent predictor of future cardiac events; reclassified risk beyond Framingham; significant utility in asymptomatic intermediate-risk individuals. |
| Budoff et al. [2] | 2016 | CT plaque metrics | Hemodynamic lesion significance | Yes | Sensitivity 79–88%, specificity 55–63%AUC 0.75–0.77 for CTA vs. invasive FFR |
| Faulder et al. [3] | 2024 | CT-derived fractional flow reserve (FFR-CT) | Agreement with invasive FFR | Yes | Spearman r = 0.67; diagnostic accuracy 82.2% (sensitivity 80.9%, specificity 83.1%); accuracy ≥ 90% when FFR-CT > 0.90 or < 0.49, but drops to 54–87% in the intermediate range (0.74–0.82). |
| Channon et al. [4] | 2022 | Perivascular fat attenuation, plaque features | CAD risk stratification | No | Narrative review: no quantitative effect size reported; describes qualitative associations between perivascular fat attenuation, plaque characteristics, and CAD risk stratification. |
| Cundari et al. [5] | 2024 | EAT, FAI, LAP, FFR-CT | MACE, ischemia, mortality | Yes | OR 1.5–2.3; AUC 0.76–0.88 |
| Schuijf et al. [6] | 2020 | CT perfusion, plaque features | INOCA diagnosis | Yes | Prevalence: 8% (31/381) had CT-defined INOCA; compared to those without ischemia, INOCA patients had higher total atheroma volume (118 mm³ vs. 60 mm³, P = 0.008), more positive remodeling (13% vs. 1%, P = 0.006), and increased LAP volume (20 mm³ vs. 10 mm³, P = 0.007). |
| Lima and Schuijf [7] | 2020 | CT perfusion, scar imaging | CAD risk phenotyping | No | Expert narrative: no quantitative effect size reported; highlights potential prognostic value of combining CT perfusion and scar imaging for CAD risk assessment. |
| Williams et al. [8] | 2020 | LAP | MI | Yes | Adjusted HR 1.60 (1.10–2.34) per doubling of LAP burden; > 4% burden → HR 4.65 (2.06–10.50); strongest predictor of MI. |
| Klüner et al. [9] | 2021 | FAI | CV risk stratification | Yes | Reported HRs for elevated FAI vs. low FAI/no HRP (e.g., HR ~6.26 for adjusted cardiac risk in FAI-high/HRP group vs. FAI-low/HRP-negative); also described improvements in risk discrimination (e.g., AUC gains) when adding FAI beyond standard risk markers. |
| Rajiah et al. [10] | 2022 | FFR-CT | Clinical integration/interpretation | Yes | Reports diagnostic thresholds (FFR-CT > 0.80 normal; 0.76–0.80 borderline; ≤ 0.75 abnormal), discusses increased specificity of CTA when FFR-CT is used, and clinical decision-making implications (ICA vs. medical management). |
| Nørgaard et al. [11] | 2019 | FFR-CT | Diagnostic workflow | Yes | Consensus-based diagnostic algorithms and reporting standards for FFR-CT interpretation. |
| Manubolu et al. [12] | 2024 | EAT | Plaque burden | Yes | Mean density: 77.2 ± 4.6 HU & volume 118.5 ± 41.2 cm³; each +1 HU in EAT density → +7% fibrous-fatty plaque (P < 0.03); no association with EAT volume. |
| Gallone et al. [13] | 2023 | HRP features | MACE | Yes | OR 1.6–2.5; AUC up to 0.83 |
| Nørgaard et al. [14] | 2022 | FFR-CT | MACE prognosis | Yes | Meta-analysis of 5 studies (5,460 patients): FFR-CT ≤ 0.80 vs. > 0.80 RR = 2.31 (95% CI 1.29–4.13, P = 0.005); every −0.10-unit FFR-CT → RR = 1.67 (95% CI 1.47–1.87, P < 0.001). |
| Mathew et al. [15] | 2018 | FFR-CT | Guidance in angiography | Yes | Reports increased specificity of FFR-CT vs. CTA for detecting hemodynamically significant lesions; FFR-CT considered cost-effective as a gatekeeper to invasive angiography. |
| Schuijf et al. [16] | 2018 | FFR-CT, perfusion | Clinical utility of cardiac FFR-CT | Yes | Diagnostic accuracy of FFR-CT and CTP imaging (sensitivity, specificity) compared to invasive FFR; describes thresholds for functional ischemia; discusses incremental benefit beyond CTA. |
| Kimura et al. [17] | 2015 | FFR-CT cost metrics | Cost analysis | No | Cost per patient; no OR/HR. Economical Model on cost effectiveness. |
| Yu et al. [18] | 2025 | FAI | MACE in young patients | Yes | HR 2.37 (95% CI 1.38–4.07) |
| van der Bijl et al. [19] | 2022 | PAT attenuation | Diagnostic/prognostic roles | No | Describes how PCAT attenuation has shown associations with CAD risk and outcomes and emphasizes its potential prognostic implications. |
| Deseive et al. [20] | 2018 | LAP volume | Cardiac events | Yes | HR 2.3 (95% CI 1.4–3.7) |
| Yamaura et al. [21] | 2022 | LAP burden | Predictors in asymptomatic patients | Yes | Percent LAP independently predicted cardiac events: HR 3.05 (95% CI 1.09–8.54, P = 0.033); AUC improved from 0.637 (CACS) to 0.728 with CACS + EAT (P = 0.013). |
| Antoniades and Shirodaria [22] | 2019 | Perivascular fat maps | Coronary inflammation | No | Diagnostic performance (sensitivity, specificity) of FAI in detecting coronary inflammation. |
| Abdulkareem et al. [23] | 2022 | EAT via AI | Imaging quantification | Yes | Reports high accuracy for CT slice classification (~98%) and segmentation (Dice ~0.84), with strong correlation (r ≈ 0.97) between automated and manual measures for both EAT volume and attenuation. |
| Oikonomou et al. [24] | 2019 | CT inflammation markers | Plaque prognosis | No | Describes diagnostic accuracy metrics for plaque morphology; prognostic associations (mortality) for FAI in cited cohorts; improved model discrimination when CT biomarkers are added. |
| Vecsey-Nagy et al. [25] | 2024 | LAP burden | CAD risk evaluation | Yes | OR 1.62 per doubling of LAP burden for hscTnI ≥ 5 ng/L (95% CI 1.17–2.32, P = 0.005); adjusted OR 1.57 (1.07–2.37, P = 0.026). Mediation analysis linking LAP to troponin elevation via plaque rupture processes. |
| Alyami et al. [26] | 2023 | Non-calcified plaque (NCP) | Prevalence in asymptomatic adults | Yes | Systematic review (14 studies, n = 37,808): overall NCP prevalence 10% (95% CI 6–13%); obstructive NCP 1.1% (0.7–1.5%). |
| Alfakih et al. [27] | 2018 | CTA biomarkers | CAD evaluation | Yes | Summarizes diagnostic accuracy (sensitivity, specificity, overall performance) of FFR-CT compared with invasive FFR from cited trials and highlights associated health-economic benefits and reductions in unnecessary invasive angiography. |
| Coerkamp et al. [28] | 2025 | FAI | CV risk reclassification | Yes | Retrospective cohort of high-risk patients, FAI led to 62% reclassification in ASCVD risk categories, 22% up-classified, 40% down-classified; no HR/OR reported. |
| Cai et al. [29] | 2023 | FFR-CT | Ischemia detection | Yes | Correlation r = 0.80–0.82 (95% CI 0.70–0.88); AUC = 0.768–0.857 for ischemia detection by FFR-CT, highest at 2 cm distal to stenosis (AUC 0.857). |
| Yu et al. [31] | 2020 | FAI | Predict ischemia severity | Yes | OR = 1.028 per 1 HU (%), P = 0.01; combined model (DS + PVAT + plaque): AUC = 0.821; integrated DS + FAI + FFR-CT model: AUC = 0.917. |
| Pontone et al. [32] | 2021 | CT perfusion | Diagnostic value | No | Summarize diagnostic performance improvements of dynamic perfusion CT over anatomical CTA; mentions the ability to detect ischemia more reliably and reduce overestimation of disease severity. |
| Imai et al. [33] | 2019 | FFR-CT, plaque features | Non-obstructive CAD ischemia | Yes | Area remodeling index: AUC = 0.921; percent plaque area: AUC = 0.681; myocardial mass: AUC = 0.641. |
| Min et al. [34] | 2022 | Plaque volume vs. FFR | Diagnostic accuracy | Yes | ischemic (PAV 15.2 ± 9.5%, TPV 694.6 ± 485.1 mm3); non-ischemic (PAV 9.2 ± 7.3%, TPV 422.9 ± 387.9 mm3). No AUC or correlation values reported. |
| Simantiris et al. [35] | 2024 | Perivascular fat (FAI) | CAD risk | Yes | Reports higher PCAT attenuation in plaque vs. healthy segments (~–34 HU vs. –56 HU); elevated FAI linked to impaired coronary flow reserve; in type 2 diabetes, LAD PCAT attenuation independently predicted CV events, and adding it to adverse CCTA features improved discrimination (ΔAUC ≈ 0.05). |
| Oikonomou et al. [36] | 2018 | FAI | Cardiac mortality | Yes | HR 2.06–2.15 per 1SD increase in FAI; ΔAUC +0.049 (cardiac), +0.075 (all-cause) over models including RCA calcium, HRP, and clinical risk factors. |
| Khan et al. [37] | 2023 | EAT volume | Plaque vulnerability and ischemia | Yes | High EAT (> 125 mL) independently associated with positive remodeling (P = 0.038); no difference in ischemia (P ≥ 0.34). |
AUC: area under the curve; CAD: coronary artery disease; CCTA: coronary CT angiography; CT: computed tomography; CTP: CT myocardial perfusion; EAT: epicardial adipose tissue; HR: hazard ratio; HU: Hounsfield unit; MACE: major adverse cardiac events; MI: myocardial infarction; OR: odds ratio; PVAT: perivascular adipose tissue; TPV: total plaque volume; HRP: high-risk plaque; DS: diameter stenosis; INOCA: Ischemia with No Obstructive Coronary Artery Disease; FAI: fat attenuation index; LAP: low-attenuation plaque.