Coronary CT angiography derived plaque markers correlated with invasive instantaneous flow reserve for detecting hemodynamically significant coronary stenoses

Coronary CT Angiography-based Morphologic Index for Predicting Hemodynamically Significant Coronary Stenosis

Purpose To develop a new coronary CT angiography (CCTA)-based index, α×LL/MLD4, that considers lesion entrance angle (α) in addition to lesion length (LL) and minimal lumen diameter (MLD) and to evaluate its efficacy in predicting hemodynamically significant coronary stenosis compared with invasive coronary angiography (ICA)-derived fractional flow reserve (FFR). Materials and Methods This prospective study enrolled participants (September 2016-March 2020) from two centers who underwent CCTA followed by ICA (ClinicalTrials.gov identifier: NCT03054324). CCTA images were processed semiautomatically to measure LL, MLD, and α for calculating α×LL/MLD4. Diagnostic performance and accuracy of α×LL/MLD4 and LL/MLD4 in detecting hemodynamically significant coronary stenosis were compared against the reference standard (invasive FFR ≤ 0.80). Results In total, 133 participants (mean age, 63 years ± 9 [SD]; 99 [74%] men) with 210 stenosed coronary arteries were analyzed. Median α×LL/MLD4 was 54.0 degree/mm3 (IQR, 25.3-128.7) in participants with invasive FFR of 0.80 or less and 6.7 degree/mm3 (IQR, 3.3-12.8) in participants with invasive FFR of more than 0.80 (P < .001). The per-vessel accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for discriminating ischemic lesions were 86.2%, 83.1%, 88.4%, 84.1%, and 87.7% for α×LL/MLD4 and 80.5%, 66.3%, 90.9%, 84.3%, and 78.6% for LL/MLD4, respectively. Area under the receiver operating characteristic curve for discriminating hemodynamically significant stenosis was 0.93 for α×LL/MLD4, which was significantly greater than the values of 0.84 for LL/MLD4 and 0.63 for diameter stenosis (both P < .001). Conclusion The new morphologic index, α×LL/MLD4, incorporating lesion entrance angle achieved higher diagnostic performance in detecting hemodynamically significant lesions compared with diameter stenosis and LL/MLD4. Keywords: CT Angiography, Cardiac, Coronary Arteries, Ischemia, Infarction, Technology Assessment Clinical trial registration no. NCT03054324 Supplemental material is available for this article. © RSNA, 2023 See also the commentary by Fairbairn and Nørgaard in this issue.

[Morphological and functional diagnostics of coronary artery disease by computed tomography]

Computed tomography coronary angiography (cCTA) is a safe option for the noninvasive exclusion of significant coronary stenoses in patients with a low or moderate pretest probability for coronary artery disease (CAD). Furthermore, it also allows functional and morphological assessment of coronary stenoses. The European Society of Cardiology (ESC) guidelines on the diagnosis and management of chronic coronary syndrome published in 2019 have strengthened the importance of cCTA in this context and for this reason it has experienced a considerable upgrade. The determination of the Agatston score is a clinically established method for quantifying coronary calcification and influences the initiation of drug treatment. With technologies, such as the introduction of electrocardiography (ECG)-controlled dose modulation and iterative image reconstruction, cCTA can be performed with high image quality and low radiation exposure. Anatomic imaging of coronary stenoses alone is currently being augmented by innovative techniques, such as myocardial CT perfusion imaging or CT-fractional flow reserve (FFR) but the clinical value of these methods merits further investigation. The cCTA could therefore develop into a gatekeeper with respect to the indications for invasive coronary diagnostics and interventions.

Serial Changes in Coronary Plaque Formation Using CT Angiography in Patients Undergoing PCSK9-Inhibitor Therapy With 1-year Follow-up

PURPOSE

Previous studies have shown positive effects of intensive low-density lipoprotein (LDL)-lowering therapy on atheroma volume using invasive intravascular ultrasound. This study describes the changes in coronary plaque composition on coronary computed tomography angiography in patients treated with proprotein convertase subtilisin kexin type 9 (PCSK9) inhibitors.

MATERIALS AND METHODS

In this prospective study, coronary plaques were analyzed using third-generation dual-source computed tomography before and after 1 year of PCSK9-inhibitor treatment. Plaque markers included total plaque volume (TPV), calcified plaque volume (CPV), noncalcified plaque volume (NCPV), lumen volume and vessel volume (VV), minimal luminal area (MLA), minimal lumen diameter (MLD), corrected coronary opacification, eccentricity, remodeling index, and functional plaque parameters. Primary endpoint was defined as change in TPV; the secondary endpoint was TPV or CPV regression or nominal change in plaque parameters.

RESULTS

We analyzed 74 coronary plaques in 23 patients (60±9 y, 65% male). After 1 year of PCSK9-inhibitor treatment, LDL was reduced from 148 to 66 mg/dL ( P <0.0001). Significant changes were found for VV (196 to 215 mm 3 , P =0.0340), MLA (3.1 to 2.6 mm 2 , P =0.0413), and MLD (1.7 to 1.4 mm, P =0.0048). TPV, CPV, NCPV, lumen volume, and functional plaque parameters did not change significantly ( P >0.05).

CONCLUSIONS

Coronary artery plaque analysis by coronary computed tomography angiography highlights that LDL lowering therapy affects plaque composition. The primary endpoint of TPV change was not reached; however, VV, MLA, and MLD changed significantly.

Additive value of epicardial adipose tissue quantification to coronary CT angiography-derived plaque characterization and CT fractional flow reserve for the prediction of lesion-specific ischemia

OBJECTIVES

Epicardial adipose tissue (EAT) from coronary CT angiography (CCTA) is strongly associated with coronary artery disease (CAD). We investigated the additive value of EAT volume to coronary plaque quantification and CT-derived fractional flow reserve (CT-FFR) to predict lesion-specific ischemia.

METHODS

Patients (n = 128, 60.6 ± 10.5 years, 61% male) with suspected CAD who had undergone invasive coronary angiography (ICA) and CCTA were retrospectively analyzed. EAT volume and plaque measures were derived from CCTA using a semi-automatic software approach, while CT-FFR was calculated using a machine learning algorithm. The predictive value and discriminatory power of EAT volume, plaque measures, and CT-FFR to identify ischemic CAD were assessed using invasive FFR as the reference standard.

RESULTS

Fifty-five of 152 lesions showed ischemic CAD by invasive FFR. EAT volume, CCTA ≥ 50% stenosis, and CT-FFR were significantly different in lesions with and without hemodynamic significance (all p < 0.05). Multivariate analysis revealed predictive value for lesion-specific ischemia of these parameters: EAT volume (OR 2.93, p = 0.021), CCTA ≥ 50% (OR 4.56, p = 0.002), and CT-FFR (OR 6.74, p < 0.001). ROC analysis demonstrated incremental discriminatory value with the addition of EAT volume to plaque measures alone (AUC 0.84 vs. 0.62, p < 0.05). CT-FFR (AUC 0.89) showed slightly superior performance over EAT volume with plaque measures (AUC 0.84), however without significant difference (p > 0.05).

CONCLUSIONS

EAT volume is significantly associated with ischemic CAD. The combination of EAT volume with plaque quantification demonstrates a predictive value for lesion-specific ischemia similar to that of CT-FFR. Thus, EAT may aid in the identification of hemodynamically significant coronary stenosis.

KEY POINTS

• CT-derived EAT volume quantification demonstrates high discriminatory power to identify lesion-specific ischemia. • EAT volume shows incremental diagnostic performance over CCTA-derived plaque measures in detecting lesion-specific ischemia. • A combination of plaque measures with EAT volume provides a similar discriminatory value for detecting lesion-specific ischemia compared to CT-FFR.

Interactions Between Morphological Plaque Characteristics and Coronary Physiology: From Pathophysiological Basis to Clinical Implications

High-risk coronary plaque refers to a distinct set of plaque characteristics prone to future coronary events. Coronary physiology represents a group of indexes reflective of the local physiological environment and hemodynamic changes in the macrovascular and microvascular system. Although a large body of evidence has supported the clinical relevance of these 2 factors, currently, identifying plaque morphology cannot reliably capture the lesion subset that causes hard events. Also, the guideline-directed approach based on physiological indexes cannot fully predict and prevent clinical events. In parallel, there is accumulating evidence that these 2 aspects of coronary artery disease influence each other with significant clinical implications, despite traditionally being considered to have separate effects on significances, treatments, and outcomes. In this state-of-the-art review, we explore the clinical evidence of pathophysiological interplay of physiological indexes related to local hemodynamics, epicardial stenosis, and microvascular dysfunction with plaque morphological characteristics that provide a better understanding of the nature of coronary events. Furthermore, we examine the emerging data on the complementary role between plaque morphology and coronary physiology in prognostication and how to apply this concept to overcome the limitations of individual assessment alone. Finally, we propose the potential benefit of integrative assessment of coronary anatomy, plaque quantity and quality, and physiological aspects of a target lesion and vessels for personalized risk profiling and optimized treatment strategy.

Radiomic features of plaques derived from coronary CT angiography to identify hemodynamically significant coronary stenosis, using invasive FFR as the reference standard

OBJECTIVE

This study aimed to investigate the diagnostic performance of radiomics features derived from coronary computed tomography angiography (CCTA) in the identification of ischemic coronary stenosis plaque using invasive fractional flow reserve (FFR) as the reference standard.

MATERIALS AND METHODS

174 plaques of 149 patients (age: 62.21 ± 8.47 years, 96 males) with at least one lesion stenosis degree between 30 % and 90 % were retrospectively included. Stenosis degree and plaque characteristics were recorded, and a conventional multivariate logistic model was established. Over 1000 radiomics features of the plaque were derived from CCTA images. The plaques were randomly divided into training set (n = 139) and validation set (n = 35). A random forest model was built. The area under the curve (AUC) of the models was compared.

RESULTS

Fifty-eight radiomics features were correlated with functionally significant stenosis (p <  0.05), wherein 56 features had an AUC of >0.6. NCP volume, NRS, remodeling index, and spotty calcification were included in the conventional model. Ultimately, 14 features were integrated to build the radiomics model. The AUC showed an improvement: 0.71 vs 0.82 for the training set and 0.70 vs 0.77 for the validation set (conventional model and radiomics model, respectively); however, it was not statistically significant (p =  0.58).

CONCLUSION

The radiomics analysis of plaques showed improvement compared with conventional plaques assessment in identifying hemodynamically significant coronary stenosis. The statistical advancement of machine learning for plaques to predict hemodynamic stenosis with a noninvasive approach still needs further studies on a large-scale dataset.

CT-FFR vs a model of combined plaque characteristics for identifying ischemia: Results from CT-FFR CHINA trial

OBJECTIVES

To evaluate the diagnostic performance of fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA; CT-FFR) and combined plaque characteristics for ischemia in different CCTA stenosis levels.

METHODS

This clinical trial analyzed 317 patients with 30 %-90 % coronary stenosis in 366 vessels from 5 centers undergoing CCTA and invasive FFR. 366 vessels were assigned into < 50 % (nonobstructive) and ≥ 50 % (obstructive) stenosis groups. Lesion length (LL), plaque burden (PB), diameter stenosis (DS), volume ratio of plaque subcomponents < 30 HU (VR < 30HU), and high-risk features were analyzed. Logistic regression models were used to identify plaque characteristic predictors for lesion-specific ischemia in different stenosis grades. The area under receiver operating characteristics curve (AUC) of integrated plaque characteristics and CT-FFR were calculated and compared.

RESULTS

In < 50 % stenosis lesions, PB (OR: 1.296, p = 0.002), LL (OR:1.075, p = 0.020), and DS (OR:1.085, p = 0.031) were independent predictors of ischemia. In ≥ 50 % stenosis lesions, VR < 30HU (OR:1.031, p = 0.005) and DS (OR: 1.020, p =  0.044) were independent predictors for ischemia. AUC of plaque characteristic (VR < 30HU plus DS) for ischemia was 0.67 (95 % CI: 0.61-0.72) in ≥ 50 % stenosis level, which was significantly lower than CT-FFR (AUC=0.90; 95 % CI: 0.86-0.93) (p <  0.001). For lesions causing < 50 % stenosis, AUC of combined plaque model (VR < 30HU plus DS) was 0.88 (95 % CI: 0.80-0.95), equivalent to AUC of CT-FFR (AUC = 0.88; 95 % CI: 0.80-0.96; p =  0.957).

CONCLUSION

CT-FFR is a powerful functional assessment tool for both obstructive and nonobstructive diseases. However, for nonobstructive CAD confirmed by CCTA, a model of a combination of plaque characteristics could be a valuable alternative to CT-FFR.

Comparison of Machine Learning Computed Tomography-Based Fractional Flow Reserve and Coronary CT Angiography-Derived Plaque Characteristics with Invasive Resting Full-Cycle Ratio

BACKGROUND

The aim is to compare the machine learning-based coronary-computed tomography fractional flow reserve (CT-FFRML) and coronary-computed tomographic morphological plaque characteristics with the resting full-cycle ratio (RFRTM) as a novel invasive resting pressure-wire index for detecting hemodynamically significant coronary artery stenosis.

METHODS

In our single center study, patients with coronary artery disease (CAD) who had a clinically indicated coronary computed tomography angiography (cCTA) and subsequent invasive coronary angiography (ICA) with pressure wire-measurement were included. On-site prototype CT-FFRML software and on-site CT-plaque software were used to calculate the hemodynamic relevance of coronary stenosis.

RESULTS

We enrolled 33 patients (70% male, mean age 68 ± 12 years). On a per-lesion basis, the area under the receiver operating characteristic curve (AUC) of CT-FFRML (0.90) was higher than the AUCs of the morphological plaque characteristics length/minimal luminal diameter4 (LL/MLD4; 0.80), minimal luminal diameter (MLD; 0.77), remodeling index (RI; 0.76), degree of luminal diameter stenosis (0.75), and minimal luminal area (MLA; 0.75).

CONCLUSION

CT-FFRML and morphological plaque characteristics show a significant correlation to detected hemodynamically significant coronary stenosis. Whole CT-FFRML had the best discriminatory power, using RFRTM as the reference standard.