Value of coronary computed tomography angiography-derived plaque multiparameter analysis for guiding the management of intermediate coronary stenosis

Introduction

Intermediate coronary stenosis (ICS) refers to coronary artery stenosis of 40–70% based on coronary angiography (CAG) and is a prevalent manifestation of coronary artery disease (CAD) (1). The PROMISE trial reported intermediate lesions in 60–70% of patients with acute coronary syndrome revealed by CAG (2). These lesions may lead to adverse cardiac events if not treated promptly.

Percutaneous coronary intervention (PCI) has demonstrated significant survival benefits in patients with obstructive coronary heart disease (2). However, the decision to pursue revascularization or medical therapy for patients with ICS is controversial because only one-third of ischemia patients require revascularization (2,3). Guidelines for the management of CAD support the use of functional assessment to guide revascularization in patients with ICS (3). Fractional flow reserve (FFR) is a well-validated index for determining the functional severity of ICS (3,4). FFR-guided functional assessment of ICS has been reported to be superior to visual assessment alone for guiding therapeutic decision-making (3-5). Plaque characterization can provide clinically valuable insights for patient-specific risk stratification and management. Intravascular ultrasonography (IVUS) provides histopathological insights into plaque morphology and composition and supplementary information for therapeutic decision-making for patients with ICS (3,6). Functional and anatomical assessments of coronary stenosis should be considered complementary. Current evidence supports the combined use of FFR and IVUS to guide clinical decision-making in ICS. However, their invasiveness and limited reproducibility prevent their widespread use.

Coronary computed tomography angiography (CCTA) is a routine method for examining cardiovascular diseases that provides a detailed evaluation of the anatomical structure of the coronary artery wall and accurately assesses plaque vulnerability and composition. This approach is highly useful for guiding disease treatment (3,5). Studies confirm that CCTA-based assessments of the coronary artery lumen, plaque characterization, and CT-derived FFR (CT-FFR) values are comparable to invasive methods such as FFR and IVUS (4-6). This facilitates comprehensive assessment of coronary plaque and may enhance our understanding of coronary atherosclerosis and cardiovascular risk (3). However, research on the use of CCTA-derived plaque multiparameter analysis to guide the management of ICS, especially using FFR and IVUS as the gold standard, is limited. This study aimed to evaluate the clinical value of multiparameter plaque analysis based on CCTA for optimizing treatment strategies in patients with ICS. The objectives were to improve the accuracy of clinical decision-making and reduce the use of unnecessary invasive procedures. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1-2587/rc).

Methods

Study population and inclusion criteria

This retrospective study analyzed consecutive patients with ICS in non-left main coronary arteries admitted to the Cardiology Department of Shaoxing People’s Hospital between February 1, 2023, and December 30, 2024. ICS was defined as 40–70% stenosis on CAG. All enrolled patients underwent CCTA, followed by CAG, FFR measurement, and IVUS within one month. In accordance with the 2021 American College of Cardiology (ACC)/American Heart Association (AHA)/Society for Cardiovascular Angiography and Interventions (SCAI) Guideline for Coronary Artery Revascularization (3), treatment strategies for eligible patients with ICS were guided by combined FFR and IVUS assessment. Based on this diagnostic evaluation, patients were stratified into two management groups: PCI (n=50) and non-PCI (n=56).

Inclusion criteria: (I) admission for ICS (40–70% stenosis on CAG) in non-left main coronary arteries; (II) completion of CCTA, followed by CAG, FFR measurement, and IVUS within one month.

Exclusion criteria: (I) poor-quality CCTA images precluding CT-FFR analysis; (II) allergy to contrast agents or inability to comply with breath-holding instructions; (III) bypass graft lesions; (IV) prior PCI; (V) recent myocardial infarction (<3 months); (VI) incomplete clinical data.

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by Academic Ethics Committee of Shaoxing People’s Hospital (acceptance No. 2023-012-01) and individual consent for this retrospective analysis was waived.

CCTA acquisition

Imaging was performed using a 320-detector row scanner (Canon Aquilion ONE, Toshiba Medical Systems, Tokyo, Japan) with a detector width of 0.5 mm. The scan range extended from the tracheal prominence to the diaphragmatic level of the heart. Scanning parameters included retrospective electrocardiogram-gated axial acquisition, a gantry rotation speed of 0.625 s/rotation, a tube voltage of 120 kV, and a tube current of 280 mA. Sublingual nitroglycerin (1.0 mg) was administered 1–2 minutes prior to scanning. All patients received strict breath-holding training and were monitored by electrocardiography during the scan. For patients with a heart rate >75 beats per minute, beta-blockers were administered before the examination. Iohexol (370 mg I/mL; Omnipaque, GE Healthcare, Shanghai) was used as the intravenous contrast agent. A volume of 60–70 mL was injected via an indwelling needle in the median cubital vein at a rate of 5 mL/s, followed by a 30 mL saline chaser. Image acquisition was automatically triggered upon reaching an attenuation threshold of 100 Hounsfield units (HU) in the aortic arch.

CAG, FFR, and IVUS imaging

All patients underwent standard CAG using a digital angiography system (Siemens AXIOM Artis). Non-ionic iodinated contrast (iohexol, 370 mg I/mL; GE Healthcare, Shanghai) was administered at a rate of 4.0–5.5 mL/s via the right radial or femoral artery for selective CAG. CAG analysis included assessment of lesion length (LL), location, and stenosis severity.

Following CAG, FFR was measured using a pressure-sensing guidewire (Volcano, Philips) during maximal hyperemia induced by intravenous adenosine infusion (140 µg/kg/min). FFR was calculated as the ratio of mean distal coronary pressure to mean aortic pressure, with a value ≤0.80 considered indicative of hemodynamically significant ischemia.

IVUS imaging was performed using the BEIXIN TrueVision system with a 60 MHz center frequency. The automated pullback covered 150 mm at a maximum speed of 10 mm/s. All analyses were conducted in a core laboratory. Vulnerable plaques were defined as attenuated or echo-lucent plaques with an arc of the attenuated area exceeding 30°, typically corresponding to lipid-rich necrotic cores.

CCTA plaque characteristics and CT-FFR analysis

Images were analyzed using Vitrea 4.0 (Canon Medical Informatics, Minnetonka, MN, USA), a semi-automated postprocessing software. Axial images, cross-sectional view, curved planar reformation multi-planar reformation, area rendering and maximum intensity projection images were available for qualitative and quantitative plaque analysis. The qualitative parameters included plaque location, type, and high-risk characteristics. The quantitative parameters included plaque length, total plaque area, calcified area, lipid area, fibrous area, degree of stenosis, minimum lumen areas (MLAs), and plaque burden (PB).

The radiologist identified the inner and outer walls of the blood vessels and the plaque margin by adjusting the window and level settings and determined plaque location, type on axial, maximum intensity projection and curved planar reformation images. If the artery wall was not visible or its measured diameter was <1.0 mm, the artery was scored as plaque-free.

Quantitative parameters were measured as follows. Total LL was measured on curved planar reformation images and defined as the length from the proximal to the distal shoulder of the lesion, where no plaque could be detected. Combining the source axial and sagittal images, the maximum plaque thickness was approximated perpendicular to the long axis of the vessel in the narrowest portion of the coronary artery. The most stenotic section was identified using a digital caliper, and the MLA was determined after manual correction. PB was calculated as follows:

PB=vCSA−MLAvCSA[1]

where vCSA is the vessel cross-sectional area.

The high-risk plaque features were as follows (7): (I) positive remodeling (remodeling index >1.1, where the remodeling index is the ratio of the vessel diameter at the plaque site to the mean reference diameters proximal and distal to the lesion); (II) low attenuation (CT attenuation <30 HU); (III) spotty calcification (calcified nodule with a diameter of <3 mm); and (IV) napkin-ring sign (characterized by a central low-attenuation necrotic core surrounded by ring-like fibrous tissue with higher attenuation and peripheral contrast enhancement). Plaques with ≥2 of these features were classified as high risk.

After drawing the region of interest of the coronary artery plaque, different plaque compositions were automatically detected by the software based on fixed HU cutoff values (8): lipid components were expressed in red, with CT values ranging from −30 to 49 HU; fibrous components were expressed in blue, with CT values ranging from 50 to 149 HU and calcific components were expressed in yellow, with CT values >150 HU. The lumen of the carotid arteries was expressed in green. In addition, the software automatically calculated the area of different plaque compositions at each slice, expressed in square millimeters (mm²).

CT-FFR was computed using an automatic software the “Coronary Doc” software for CT-FFR (Shukun Technology, Shanghai, China). This software is based on machine-learning algorithm and can be used on-site to calculate CT-FFR value. For the on-site processing, after CCTA data were successfully loaded, the centerline and luminal contours for whole coronary tree were automatically generated. Users then manually identified all stenotic lesions to extract their geometrical features required for CT-FFR algorithm. Finally, those data were input into the pre-learned model and CT-FFR was computed automatically at all locations in the coronary arterial tree, and the resulting values were visualized by color-coded three-dimensional (3D) coronary maps. The lesion specific CT-FFR values were measured within 2 cm distal to the stenosis (5,6).

Two cardiovascular radiologists with 5 years of experience in cardiac imaging who were blinded to clinical histories, CCTA plaque characteristics and CT-FFR results independently analyzed the data. To evaluate inter-observer variability, all patient results were confirmed by a second radiologist using the same technique and in the same manner as the first reader. Any disagreement between the two observers was resolved by consensus. The mean values of various parameters measured by two observers were used for analysis.

Statistical analysis

All analyses were performed using SPSS 27.0 (IBM Corp, Armonk, NY, USA). Continuous variables were tested for normality using Shapiro-Wilk tests. Normally distributed variables are presented as mean ± standard deviation and compared using Student’s t-test; non-normally distributed variables are reported as median and interquartile ranges (IQR), analyzed with Mann-Whitney U tests. Categorical variables are expressed as counts and compared using χ² or Fisher’s exact tests, as appropriate. Pearson correlation coefficient (r) was utilized to evaluate the correlation between CT-FFR values and FFR. Missing data were addressed using complete-case analysis; only subjects with complete data for all variables included in a given analysis were included. Variables demonstrating significant associations (P<0.05) in univariate analyses were entered into multivariate logistic regression models. The strength and precision of these independent associations are reported as adjusted odds ratios (ORs) with 95% confidence intervals (CIs). We constructed receiver operating characteristic (ROC) curves to evaluate both individual predictors and combined models, selecting the optimal predictive model based on area under the curve (AUC) comparisons. All tests were two-tailed, with statistical significance set at P<0.05.

Results

After stepwise screening, 106 patients were ultimately included in the analysis. The screening process and specific exclusion reasons are detailed in Figure 1.

Figure 1 Study flowchart. CAG, coronary angiography; CCTA, coronary computed tomography angiography; CT, computed tomography; FFR, fractional flow reserve; IVUS, intravascular ultrasonography; PCI, percutaneous coronary intervention.

The eligible patients were stratified into PCI (n=50) and non-PCI (n=56) groups. The mean age of the cohort was 64.4±1.0 years, including 60 male and 46 female patients. No statistically significant differences were observed in the baseline characteristics and medical histories between the two groups (P>0.05, Table 1).

CCTA characteristics of ICS lesions

In eligible patients, 170 ICS lesions were found, 78 (45.9%) were in the PCI group and 92 (54.1%) were in the non-PCI group. Of these, 91 plaques (53.5%) were located in the left anterior descending (LAD) artery, 32 plaques (18.8%) in the left circumflex artery, and 47 plaques (27.7%) in the right coronary artery. The PCI group had smaller MLA and lower CT-FFR values than the non-PCI group (2.96±1.09 vs. 4.54±1.18 mm², P<0.001; 0.78±0.05 vs. 0.81±0.06 mm², P=0.03). The PCI group had longer LL and greater total plaque area than the non-PCI group [21.9 (IQR, 14.3–31.6) mm vs. 11.4 (IQR, 5.3–20.5) mm, P=0.001; 83.3 (IQR, 69.1–104.0) mm² vs. 57.9 (IQR, 25.9–75.9) mm², P<0.001]. The PCI group had significantly higher lipid area and PB for the target lesions [10.9 (IQR, 3.0–20.3) mm² vs. 3.5 (IQR, 1.3–7.5) mm², P=0.001; 71.5%±7.0% vs. 66.0%±8.1%, P=0.002]. Low-attenuation plaques were more prevalent in the PCI than in the non-PCI group (33 vs. 23, P=0.01). No significant differences were observed in: lumen stenosis, plaque location, plaque type, other plaque components area (fibrous, calcified), other high-risk features (positive remodeling, napkin-ring sign, spotty calcification) and high-risk plaques (P>0.05) (Tables 2,3).

Analysis of risk factors and predictive efficacy of CCTA parameters for PCI

Logistic regression analyses identified MLA, LL, and plaque lipid area as independent predictors of PCI (Table 4). Their combined use significantly improved discrimination (AUC =0.91; 95% CI: 0.84–0.97) relative to their individual use (P<0.05 for all AUC comparisons) (Table 5, Figure 2).

Figure 2 ROC analysis of CCTA parameters for predicting PCI. CCTA, coronary computed tomography angiography; LIP, plaque lipid area; MLA, minimal lumen area; PCI, percutaneous coronary intervention; ROC, receiver operating characteristic.

Relationship between CT-FFR and FFR

CT-FFR was positively correlated with FFR, r=0.75, P<0.001 (Figure 3).

Figure 3 Relationship between CT-FFR and FFR. CT-FFR, computed tomography-derived fractional flow reserve; FFR, fractional flow reserve.

Figure 4 shows a representative case of ICS lesion managed medically; Figure 5 shows a representative case of ICS lesion treated with stent implantation.

Figure 4 A 57-year-old woman presented with one week of chest tightness. (A) CCTA: demonstrates a mixed plaque in the proximal to mid segment of the LAD artery, causing approximately 60% luminal stenosis (arrow). (B) Plaque analysis: quantitative plaque assessment of the proximal LAD lesion reveals a plaque burden of 57.5%. The MLAs is 11.0 mm², with a total plaque area of 8.6 mm² composed of lipid (3.4 mm²), fibrous (4.1 mm²), and calcified (1.1 mm²) components. (C) Invasive correlation: CAG confirms 50–60% stenosis in the proximal to mid LAD (arrow). IVUS assessment of the same lesion corroborates the findings, showing a plaque burden of 55% and an MLAs of 10.29 mm². CAG, coronary angiography; CCTA, coronary computed tomography angiography; IVUS, intravascular ultrasonography; LAD, left anterior descending; MLA, minimal lumen area.

Figure 5 A 62-year-old man was admitted due to chest pain for three days. (A) CCTA: reveals a mixed plaque in the proximal to mid segment of the LAD, resulting in approximately 65% luminal stenosis (arrow). (B) Plaque analysis: quantitative assessment shows a plaque burden of 69.2%. The MLAs is 6.2 mm², with a total plaque area of 24.7 mm² distributed as lipid (4.1 mm²), fibrous (10.4 mm²), and calcified (10.2 mm²) component. (C) Invasive correlation: CAG demonstrates a 70% stenosis in the proximal to mid LAD (arrow). IVUS confirms a plaque burden of 70% and an MLAs of 5.8 mm². A Medtronic drug-eluting stent (3.5 mm × 18 mm) was subsequently implanted in the LAD lesion. CAG, coronary angiography; CCTA, coronary computed tomography angiography; IVUS, intravascular ultrasonography; LAD, left anterior descending; MLA, minimal lumen area.

Discussion

The following key findings were obtained. (I) Patients with ICS who underwent PCI revascularization had significantly smaller MLAs and lower CT-FFR values than those who did not undergo PCI. The PCI group had significantly greater plaque area, longer LL, higher PB, more low-attenuation plaques, and greater plaque lipid area. (II) Multivariate regression analysis identified plaque lipid area, LL, and MLA as independent predictors of revascularization for ICS. MLA had the best predictive performance. (III) The combination of these parameters significantly enhanced the accuracy of predicting the need for PCI revascularization.

The guidelines for CAD management recommend functional assessment to support revascularization in patients with ICS (3). Our study confirmed the high agreement between CT-FFR and invasive FFR. This is consistent with previous reports (3,5,9) and supports the use of CT-FFR as a reliable noninvasive tool for the hemodynamic classification of stenoses and guidance of treatment strategy. The CT-FFR and invasive FFR values were significantly lower for the PCI group than for the non-PCI group. The trial revealed a significant interaction between CT-FFR and treatment strategy, with the patients with ICS having better clinical outcomes when managed using CT-FFR-guided therapy (10). However, only one-third of patients with ICS had ischemia requiring revascularization. The optimal management approach for ICS without demonstrated ischemia remains uncertain (2,3). Emerging evidence demonstrates a bidirectional relationship between plaque morphology and local hemodynamics that improves the prediction of PCI revascularization requirements (3,4,11).

We conducted the first systematic evaluation of the differences in plaque morphology associated with the treatment of patients with ICS. The PCI group had significantly longer lesions, greater plaque areas, and smaller MLAs than the non-PCI group. However, the plaque locations and types did not differ significantly. These findings suggest that plaque morphological assessments should be used as complementary approaches for making revascularization decisions in patients with ICS. This is supported by the findings of Li et al. (12). They reported improved diagnostic accuracy of invasive FFR for the evaluation of moderate non-left main lesions following the incorporation of plaque length. Deseive et al. (13) reported findings consistent with ours. They demonstrated the superiority of comprehensive plaque area assessment incorporating quantitative and morphological parameters over conventional metrics for evaluating the severity of coronary lesions. Kishi et al. (14) reported the utility of PB of >70% as an adjunctive criterion for guiding revascularization decisions in ICS. Studies have reported a close correlation between PB and plaque morphology, which is associated with hemodynamic changes (14,15). MLA is inversely correlated with plaque length and size, which is associated with exacerbated luminal obstruction and increased PB. These changes affect endothelial function stability and cause plaque rupture (14). Further assessment revealed that the PCI group had a significantly higher PB than the non-PCI group.

The heterogeneous composition of arterial plaques contributes to the divergent clinical trajectories of CAD. However, the benefits of using CCTA image-based coronary plaque analysis to guide management have not been fully established. We used CCTA to comprehensively analyze the composition of the critical lesions and evaluate their association with revascularization requirements. Our analysis revealed significantly higher lipid areas for the PCI group than for the non-PCI group, suggesting a strong correlation between plaque lipid burden and ICS revascularization. The underlying pathophysiology likely involves inflammatory cascades and oxidative stress responses triggered by necrotic core components. These cascades and responses promote plaque hypoxia, necrosis, and destabilization. Gardner et al. (16) reported that 33.6% of the patients with lipid-rich plaques had major adverse cardiovascular events (MACE) during follow-up. These insights suggest that the greater lipid areas have a dose-dependent relationship with future MACE risk (16). Quantitative assessment of plaque lipid areas using CCTA may facilitate early identification of high-risk patients who could benefit from intensive medical therapy or closer surveillance and improve their clinical outcomes. A lipid-rich necrotic core appears as low-attenuation plaque on CCTA. Our analysis revealed a higher prevalence of low-density plaques for the PCI group than for the non-PCI group. Histopathological validation studies have established a strong association between low-attenuation plaques detected using CCTA and lipid-rich necrotic cores (17). A recent study reported the benefits of visually identifying low-attenuation plaques for predicting the future risk of MACE infarction. However, our study found no statistically significant difference in the prevalence of high-risk plaques between the groups, which contrasts with previous reports (18). This discrepancy may be due to variations in the study populations and baseline atherosclerotic burden.

Multivariate logistic regression identified MLA, LL, and lipid content as independent predictors of revascularization. The predictive performance of MLA was superior to those of LL and lipid area. MLA is associated with PB and lipids promote coronary inflammation. Both contribute to plaque vulnerability and subsequent MACE (14-17). The composite model incorporating all three parameters demonstrated excellent predictive accuracy.

In clinical practice, it is recommended to integrate quantitative multiparameter CCTA indicators into routine ICS reporting. Using these objective metrics, patients with high-risk lesions can proceed directly to invasive CAG accompanied by coronary imaging. For those with low-risk lesions, guideline-directed medical therapy can be initiated first, followed by noninvasive surveillance. This imaging guided “anatomy-function-risk” integrated assessment provides practical evidence to support heart team decision making and subsequent management, as well as enhances patient adherence to therapy.

There are several limitations in this study. First, the findings may have been affected by selection bias because this was a single-center retrospective analysis with a limited sample size. Future studies should incorporate larger, multi-center cohorts with external validation to enhance generalizability. Second, the lack of follow-up data on MACE represents a notable gap. Subsequent research should include longitudinal assessments of MACE to better evaluate the clinical implications of the findings. This study focused on specific plaque parameters. However, additional quantitative measures, such as coronary perivascular fat attenuation indices and radiomics parameters, may provide further insights into cardiovascular risk stratification.

Conclusions

Plaque analysis based on CCTA significantly enhances the identification of critical lesions that indicate ICS intervention. The diagnostic accuracy of the integrated assessment of MLA, LL, and lipid-rich plaque area is superior to that of individual parameters alone. The multi-parametric plaque analysis approach may help optimize the treatment strategies for ICS.

Acknowledgments

We have benefited from the presence of our teachers and colleagues in writing this paper. They generously helped us collect the needed materials and made many invaluable suggestions. At this moment, we extend my thanks to them for their kind help, without which the paper would not have been what it is.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1-2587/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1-2587/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1-2587/prf

Funding: This study was approved by Zhejiang Medicine and Health Science and Technology Project (Nos. 2024KY475 and 2023KY431); Shaoxing Medicine and Health Science and Technology Project (Nos. 2022KY026 and 2024SKY016).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1-2587/coif). The authors have no conflicts of interest to declare.

Ethical Statement:The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The studies involving human participants were reviewed and approved by Academic Ethics Committee of Shaoxing People’s Hospital (acceptance No. 2023-012-01). The patients/participants provided their written informed consent to participate in this study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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