Quantification of plaque characteristics detected by dual source computed tomography angiography to predict myocardial ischemia as assessed by single photon emission computed tomography myocardial perfusion imaging

Diagnostic performance of coronary computed tomography angiography stenosis score for coronary stenosis

BACKGROUND

Coronary computed tomography angiography stenosis score (CCTA-SS) is a proposed diagnosis score that considers the plaque characteristics, myocardial function, and the diameter reduction rate of the lesions. This study aimed to evaluate the diagnostic performance of the CCTA-SS in seeking coronary artery disease (CAD).

METHODS

The 228 patients with suspected CAD who underwent CCTA and invasive coronary angiography (ICA) procedures were under examination. The diagnostic performance was evaluated with the receiver operating curve (ROC) for CCTA-SS in detecting CAD (defined as a diameter reduction of ≥ 50%) and severe CAD (defined as a diameter reduction of ≥ 70%).

RESULTS

The area under ROC (AUC) of CCTA-SS was 0.909 (95% CI: 0.864-0.943), which was significantly higher than that of CCTA (AUC: 0.826; 95% CI: 0.771-0.873; P = 0.0352) in diagnosing of CAD with a threshold of 50%. The optimal cutoff point of CCTA-SS was 51% with a sensitivity of 90.66%, specificity of 95.65%, positive predictive value of 98.80%, negative predictive value of 72.13%, and accuracy of 91.67%, whereas the optimal cutoff point of CCTA was 55%, and the corresponding values were 87.36%, 93.48%, 98.15%, 65.15%, and 88.60%, respectively. With a threshold of 70%, the performance of CCTA-SS with an AUC of 0.927 (95% CI: 0.885-0.957) was significantly higher than that of CCTA with an AUC of 0.521 (95% CI: 0.454-0.587) (P < 0.0001).

CONCLUSIONS

CCTA-SS significantly improved the diagnostic accuracy of coronary stenosis, including CAD and severe CAD, compared with CCTA.

The value of quantitative plaque analysis based on coronary computed tomography angiography in predicting the percutaneous coronary intervention outcome of chronic total occlusion lesions

Background

Due to the uncertainty of the success of percutaneous coronary intervention (PCI) and the complexity of selecting suitable treatment cases, the interventional outcome of coronary chronic total occlusion (CTO) remains challenging. The purpose of this study was to evaluate the role of quantitative plaque analysis based on coronary computed tomography angiography (CCTA) in predicting the CTO-PCI outcome.

Methods

We retrospectively included 78 patients with CTO (80 lesions) confirmed by invasive coronary angiography from July 2016 to December 2018. All patients underwent PCI treatment according to standard practice. A total of 47 lesions in 47 patients were successfully treated with PCI. PCI failed in the remaining 33 lesions in 31 patients. The following conventional CCTA morphologic parameters were evaluated and compared between the PCI-success and PCI-failure groups: stump morphology; occlusion length, tortuous course; CTO lesion calcium; bridging collateral vessel; retrograde collateral vessel; the appearance of the occluded distal segment; and quantitative CTO plaque characteristics, including total plaque volume, calcified plaque (CP) volume, noncalcified plaque (NCP) volume, low-density noncalcified plaque (LDNCP) volume, and plaque length. Univariate and multivariate logistic regression analyses were performed to determine independent parameters predictive of CTO-PCI outcomes. The predictive performances were assessed using receiver operating characteristic curve analysis.

Results

The blunt stump was the only independent CCTA morphologic parameter to predict the outcome of CTO-PCI [odds ratio (OR): 10.807; P<0.001]. NCP volume (OR: 1.018; P<0.001), CP volume (OR: 1.026; P=0.049), and plaque length (OR: 1.058; P=0.037) were independent quantitative CTO plaque characteristics predictive of CTO-PCI outcomes. The plaque-based model combining NCP volume with CP volume and plaque length had a higher area under the curve (AUC =0.96) than did the morphology-based model that included blunt stump (AUC 0.68) in predicting the outcomes of CTO-PCI (P<0.001).

Conclusions

The CCTA-based plaque characteristics, including NCP volume, CP volume, and plaque length, outperformed morphologic parameters in predicting the CTO-PCI outcomes.

Association between coronary plaque volume and myocardial ischemia detected by dynamic perfusion CT imaging

Introduction

We aimed to evaluate the relationship between quantitative plaque metrics derived from coronary CT angiography (CTA) and segmental myocardial ischemia using dynamic perfusion CT (DPCT).

Methods

In a prospective single-center study, patients with > 30% stenosis on rest CTA underwent regadenoson stress DPCT. 480 myocardium segments of 30 patients were analyzed. Quantitative plaque assessment included total plaque volume (PV), area stenosis, and remodeling index (RI). High-risk plaque (HRP) was defined as low-attenuation plaque burden > 4% or RI > 1.1. Absolute myocardial blood flow (MBF) and relative MBF (MBFi: MBF/75th percentile of all MBF values) were quantified. Linear and logistic mixed models correcting for intra-patient clustering and clinical factors were used to evaluate the association between total PV, area stenosis, HRP and MBF or myocardial ischemia (MBF < 101 ml/100 g/min).

Results

Median MBF and MBFi were 111 ml/100 g/min and 0.94, respectively. The number of ischemic segments were 164/480 (34.2%). Total PV of all feeding vessels of a given myocardial territory differed significantly between ischemic and non-ischemic myocardial segments (p = 0.001). Area stenosis and HRP features were not linked to MBF or MBFi (all p > 0.05). Increase in PV led to reduced MBF and MBFi after adjusting for risk factors including hypertension, diabetes, and statin use (per 10 mm³; β = −0.035, p < 0.01 for MBF; β = −0.0002, p < 0.01 for MBFi). Similarly, using multivariate logistic regression total PV was associated with ischemia (OR = 1.01, p = 0.033; per 10 mm³) after adjustments for clinical risk factors, area stenosis and HRP.

Conclusion

Total PV was independently associated with myocardial ischemia based on MBF, while area stenosis and HRP were not.

Identification of Flow-Limiting Coronary Stenosis With PCS: A New Cost-Effective Index Derived From the Product of Corrected TIMI Frame Count and Percent Diameter Stenosis

Background: Identifying functional coronary stenosis with simple and cost-effective methods during invasive coronary angiography is still challenging. Corrected TIMI frame count (CTFC) is considered to be the frame count velocity of coronary blood flow. We aimed to propose a simple and cost-effective index based on CTFC and percent diameter stenosis (DS) to identify flow-limiting coronary stenosis. For this, a new index was put forward as the product of CTFC and DS (PCS). PCS can be regarded as the loss of coronary blood flow due to diameter stenosis.

Methods: DS, CTFC, PCS, and Fractional flow reserve (FFR) of 111 vessels in 84 patients with suspected coronary heart disease were measured. FFR ≤0.80 was defined as flow-limiting. Models involving CTFC, DS, and PCS were developed. Logistic regression was performed to evaluate the values on diagnosing flow-limiting stenosis.

Results: Vessels with flow-limiting coronary stenosis exhibited higher CTFC values than those without (28.56 vs. 21.64). The performance including the AUC (0.887), sensitivity (87.8%), and Youden index (0.678) for detecting flow-limiting stenosis was improved by adding the CTFC to the DS, while PCS had the largest positive predictive value (PPV) and diagnostic accuracy (DA) being 72.0 and 82.9%, respectively. For vessels with ≥50% lesions, PCS still had the best DA (80.9%), specificity (85.9%), and PPV (72.9%). At the same stenosis severity level, the AUC, Youden index and, DA of PCS were higher than those of CTFC.

Conclusions: PCS is simple and accurate to identify flow-limiting coronary stenosis, especially at vessels with moderate to severe stenosis.

Optimization of image quality and accuracy of low iodine concentration quantification as function of dose level and reconstruction algorithm for abdominal imaging using dual-source CT: A phantom study

PURPOSE

The purpose of this study was to assess the impact of advanced modeled iterative reconstruction (ADMIRE) algorithm and dose levels on the accuracy of Hounsfield unit (HU) measurement, image noise and contrast-to-noise ratio (CNR) in virtual monochromatic images (VMIs) with low iodine concentrations, and the accuracy of iodine quantification.

MATERIALS AND METHODS

A CT phantom was scanned with dual-source CT using abdomen-pelvis examination parameters at four dose levels: 5, 8, 11 and 20 mGy. Images were reconstructed using filtered-back projection (FBP) and ADMIRE levels 3 and 5 (A3-A5). HU accuracy was assessed calculating the root-mean-square deviation (RMSD_HU). Image noise and CNR were computed on VMIs at 40/50/60/70 keV for 4 iodine inserts with 0.5, 1, 2 and 5 mg/mL concentrations. Accuracy of iodine quantification was assessed by the RMSD_iodine and iodine bias (IB).

RESULTS

The RMSD_HU decreased significantly as the dose levels increased compared to 5 mGy, except for 8 mGy with A3 (P = 0.380) and with A5 level (P = 0.945). Noise increased by 63.0 ± 3.0 (standard deviation [SD])% from 20 mGy to 5 mGy. Noise decreased significantly by -53.8 ± 0.9 (SD) % with A5 compared to FBP. The CNR decreased by -43.1 ± 6.5 (SD)% from 20 mGy to 5 mGy. It increased using ADMIRE, and as the ADMIRE levels increased. The RMSD_iodine and IB decreased as the dose level increased, and this was similar for all reconstruction types.

CONCLUSION

ADMIRE strongly improves image quality in VMIs and slightly improves HU accuracy but does not affect the accuracy of iodine quantification.

Research on the distribution spectrum of atherosclerotic plaques in patients with suspected coronary artery disease and the noninvasive screening model for coronary atherosclerosis burden

BACKGROUND

This study aimed to establish a non-invasive and simple screening model of coronary atherosclerosis burden based on the associations between multiple blood parameters and total plaque score (TPS), segment-stenosis score (SSS), coronary artery disease severity (CADS) in coronary artery disease (CAD) and thus reduce unnecessary coronary angiography (CAG).

METHODS

A total of 1,366 patients with suspected CAD who underwent CAG were included in this study. The clinical risk factors [age, gender, systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), high-density lipoprotein (HDL), triglyceride (TG), low-density lipoprotein (LDL), fasting plasma glucose (FPG), and glycated hemoglobin (GHB)] were collected. The presence of plaques and lumen stenosis was assessed based on CAG imaging. The TPS, SSS, and CADS were calculated, and the distribution spectrum of atherosclerotic plaques was described. Kruskal-Wallis test for multiple comparison tests was performed to analyze the differences in groups of different risk factors. The selected independent predictors were put into a multivariate logistic model, and the variables were further screened by stepwise regression to establish a screening model. Finally, the receiver operating characteristic (ROC) curve was used to evaluate the selected model's discriminant effect.

RESULTS

The distributions of TPS and SSS scores were both right-skewed. Among males, both TPS and SSS scores were higher than in females (χ2=46.7659, P<0.0001, χ2=51.6603, P<0.0001). Both TPS and SSS scores increased with age (χ2=123.4456, P<0.0001, χ2=123.4456, P<0.0001). For TPS, the most common position was proximal left anterior descending artery (P-LAD, 51.39%). In SSS, the P-LAD plaque was highest: 0: 48.61%, 1: 10.32%, 2: 9.15%, and 3: 31.92%. The TPS score >5, SSS score >5, and CAD >0 were valuable indicators for SBP, FPG, TG, HDL, and GHB. In the model, TPS score >5, SSS score >5, and CADS >0, the area under ROC curve (AUC) was 0.753 [95% confidence interval (CI): 0.713 to 0.789], 0.728 (95% CI: 0.687 to 0.766), and 0.756 (95% CI: 0.717 to 0.793), respectively.

CONCLUSIONS

The most common site of lesions was P-LAD. These models can be used as non-invasive and simple initial screening tools without CAG.

Effect of different reconstruction algorithms on coronary artery calcium scores using the reduced radiation dose protocol: a clinical and phantom study

Background

This study aimed to evaluate the effects of different iterative reconstruction (IR) algorithms on coronary artery calcium (CAC) score quantification using the reduced radiation dose (RRD) protocol in an anthropomorphic phantom and in patients.

Methods

A thorax phantom, containing 9 calcification inserts with varying hydroxyapatite (HA) densities, was scanned with the reference protocol [120 kv, 80 mAs, filtered back projection (FBP)] and RRD protocol (120 kV, 20-80 mAs, 5 mAs interval) using a 256-slice computed tomography (CT) scanner. Raw data were reconstructed with different reconstruction algorithms [iDose⁴ levels 1-7 and iterative model reconstruction (IMR) levels 1-3]. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and Agatston score (AS) were calculated for each image series. The correction factor was derived from linear regression analysis between the reference image series and other image series with different parameters. Additionally, 40 patients were scanned with the RRD protocol (50 mAs) and reconstructed with FBP, iDose⁴ level 4, and IMR level 2. AS was calculated for the 3-group image series, and was corrected by applying a correction factor for the IMR group. The agreement of risk stratification with different reconstruction algorithms was also analyzed.

Results

For the phantom study, the iDose⁴ and IMR groups had significantly higher SNR and CNR than the FBP group (all P<0.05). There were no significant differences in the total AS after comparing image series reconstructed with iDose⁴ (level 1-7) and FBP (all P>0.05), while AS from the IMR (level 1-3) image series were lower than the FBP group (all P<0.05). The tube current of 50 mAs was determined for the clinical study, and the correction factor was 1.14. For the clinical study, the median AS from the iDose⁴ and IMR groups were both significantly lower compared to the FBP image series [(112.89 (63.01, 314.09), 113.22 (64.78, 364.95) vs. 118.59 (65.05, 374.48), both P<0.05]. After applying the correction factor, the adjusted AS from the IMR group was not significantly different from that of the FBP group [126.48 (69.62, 355.85) vs. 118.59 (65.05, 374.48), P=0.145]. Moreover, the agreement in risk stratification between FBP and IMR improved from 0.81 to 0.85.

Conclusions

The RRD CAC scoring scan using the IMR reconstruction algorithm is clinically feasible, and a correction factor can help reduce the AS underestimation effect.