Dataset Information

Towards reference values of pericoronary adipose tissue attenuation: impact of coronary artery and tube voltage in coronary computed tomography angiography.

ABSTRACT:

Objectives

To determine normal pericoronary adipose tissue mean attenuation (PCAT_MA) values for left the anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) in patients without plaques on coronary CT angiography (cCTA), taking into account tube voltage influence.

Methods

This retrospective study included 192 patients (76 (39.6%) men; median age 49 years (range, 19-79)) who underwent cCTA with third-generation dual-source CT for the suspicion of CAD between 2015 and 2017. We selected patients without plaque on cCTA. PCAT_MA was measured semi-automatically on cCTA images in the proximal segment of the three main coronary arteries with 10 mm length. Paired t-testing was used to compare PCAT_MA between combinations of two coronary arteries within each patient, and one-way ANOVA testing was used to compare PCAT_MA in different kV groups.

Results

The overall mean ± standard deviation (SD) PCAT_MA was - 90.3 ± 11.1 HU. PCAT_MA in men was higher than that in women: - 88.5 ± 10.5 HU versus - 91.5 ± 11.3 HU (p = 0.001). PCAT_MA of LAD, LCX, and RCA was - 92.4 ± 11.6 HU, - 88.4 ± 9.9 HU, and - 90.2 ± 11.4 HU, respectively. Pairwise comparison of the arteries showed significant difference in PCAT_MA: LAD and LCX (p < 0.001), LAD and RCA (p = 0.009), LCX and RCA (p = 0.033). PCAT_MA of the 70 kV, 80 kV, 90 kV, 100 kV, and 120 kV groups was - 95.6 ± 9.6 HU, - 90.2 ± 11.5 HU, - 87.3 ± 9.9 HU, - 82.7 ± 6.2 HU, and - 79.3 ± 6.8 HU, respectively (p < 0.001).

Conclusions

In patients without plaque on cCTA, PCAT_MA varied by tube voltage, with minor differences in PCAT_MA between coronary arteries (LAD, LCX, RCA). PCAT_MA values need to be interpreted taking into account tube voltage setting.

Key points

• In patients without plaque on cCTA, PCAT_MA differs slightly by coronary artery (LAD, LCX, RCA). • Tube voltage of cCTA affects PCAT_MA measurement, with mean PCAT_MA increasing linearly with increasing kV. • For longitudinal cCTA analysis of PCAT_MA , the use of equal kV setting is strongly recommended.

SUBMITTER: Ma R

PROVIDER: S-EPMC7599179 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Towards reference values of pericoronary adipose tissue attenuation: impact of coronary artery and tube voltage in coronary computed tomography angiography.

Ma Runlei R Ties Daan D van Assen Marly M Pelgrim Gert Jan GJ Sidorenkov Grigory G van Ooijen Peter M A PMA van der Harst Pim P van Dijk Randy R Vliegenthart Rozemarijn R

European radiology 20200722 12

<h4>Objectives</h4>To determine normal pericoronary adipose tissue mean attenuation (PCAT<sub>MA</sub>) values for left the anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) in patients without plaques on coronary CT angiography (cCTA), taking into account tube voltage influence.<h4>Methods</h4>This retrospective study included 192 patients (76 (39.6%) men; median age 49 years (range, 19-79)) who underwent cCTA with third-generation dual-source CT for the suspicio ...[more]

PMID: 32700017

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Project description:Background Recent studies have reported the association between pericoronary inflammation assessed by pericoronary adipose tissue attenuation (PCATA) on computed tomography angiography and worse outcomes in patients with coronary artery disease. We investigated the determinants predicting increased PCATA in patients with known or suspected coronary artery disease. Methods and Results A total of 540 patients who underwent computed tomography angiography and invasive coronary angiography were studied. Mean computed tomography attenuation values of PCAT (-190 to -30 Hounsfield units) (PCATA) were assessed at the proximal 40-mm segments of all 3 major coronary arteries by crude analysis. Univariable and multivariable analyses were performed to determine the predictors of increased PCATA surrounding the proximal right coronary artery. Mean right coronary artery-PCATA was -72.22±8.47 Hounsfield units and the average of 3-vessel PCATA was -70.24±6.60 Hounsfield units. Multivariable linear regression analysis revealed that the independent determinants of right coronary artery-PCATA were male (β coefficient=4.965, P<0.001), left ventricular mass index (β coefficient=0.040, P=0.025), and angiographically significant stenosis (diameter stenosis >50%) (β coefficient=2.418, P=0.008). Sex-related determinants were NT-proBNP level (N-terminal pro-B-type natriuretic peptide; β coefficient <0.001, P=0.026), Agatston score (β coefficient=-0.002, P=0.010), left ventricular mass index (β coefficient=0.041, P=0.028), and significant stenosis (β coefficient=4.006, P<0.001) in male patients and left ventricular ejection fraction (β coefficient=-0.217, P=0.010) and significant stenosis (β coefficient=3.835, P=0.023) in female patients. Conclusions Right coronary artery-PCATA was associated with multiple clinical characteristics, established risk factors, and the presence of significant stenosis. Our results suggest that clinically significant factors such as sex, left ventricular hypertrophy, ejection fraction, calcification, and epicardial stenosis should be taken into account in the assessment of pericoronary inflammation using computed tomography angiography.

Project description:ObjectivesDifferent computed tomography (CT) scanners, variations in acquisition protocols, and technical parameters employed for image reconstruction may introduce bias in the analysis of pericoronary adipose tissue (PCAT) attenuation derived from coronary computed tomography angiography (CCTA). Therefore, the aim of this study was to establish the effect of tube voltage, measured as kilovoltage peak (kVp), and iterative reconstruction on PCAT mean attenuation (PCATMA).MethodsTwelve healthy ex vivo porcine hearts were injected with iodine-enriched agar-agar to allow for ex vivo CCTA imaging on a 256-slice CT and a dual-source CT system. Images were acquired at tube voltages of 80, 100, 120, and 140 kVp and reconstructed by using both filtered back projection and iterative reconstruction algorithms. PCATMA was measured semi-automatically on CCTA images in the proximal segment of coronary arteries.ResultsThe tube voltage showed a significant effect on PCATMA measurements on both the 256-slice CT scanner (p < 0.001) and the dual-source CT system (p = 0.013), resulting in higher attenuation values with increasing tube voltage. Similarly, the use of iterative reconstructions was associated with a significant increase of PCATMA (256-slice CT: p < 0.001 and dual-source CT: p = 0.014). Averaged conversion factors to correct PCATMA measurements for tube voltage other than 120 kVp were 1.267, 1.080 and 0.947 for 80, 100, and 140 kVp, respectively.ConclusionPCATMA values are significantly affected by acquisition and reconstruction parameters. The same tube voltage and reconstruction type are recommended when PCAT attenuation is used in multicenter and longitudinal studies.Key points• The tube voltage used for CCTA acquisition affects pericoronary adipose tissue attenuation, resulting in higher attenuation values of fat with increasing tube voltage. • Conversion factors for pericoronary adipose tissue attenuation values could be used to adjust for differences in attenuation between scans performed at different tube voltages. • In longitudinal CCTA studies employing pericoronary adipose tissue attenuation as imaging endpoint, it is recommended to maintain tube voltage and image reconstruction type constant across serial scans.

Project description:BackgroundPeriaortic fat is associated with coronary disease. Thus, it was hypothesized that the inflammation associated with acute aortic dissection (AAD) spreads to pericoronary adipose tissue (PCAT) via thoracic periaortic fat. Pericoronary adipose tissue attenuation (PCATa) serves as a marker for inflammation of perivascular adipose tissue (PVAT). This study sought to examine PCATa in individuals diagnosed with AAD.MethodsConsecutive patients with chest pain from May 2020 to September 2022 were prospectively enrolled in this study and underwent coronary computed tomography angiography (CCTA) and/or aorta computed tomography angiography (CTA). Based on the results of the CTA, the patients were divided into the following two groups: (I) the AAD group; and (II) the non-AAD group. PCATa of the right coronary angiography (RCA), left anterior descending (LAD), and left circumflex (LCx) was quantified for each patient using semi-automated software. The PCATa values were compared between the AAD and non-AAD patients according to the atherosclerosis of the coronary arteries. Similarly, the PCATa values of the AAD patients were compared between the preoperative and postoperative steady states.ResultsA total of 136 patients (42 female, 94 male; mean age: 63.3±11.9 years) were divided into the two groups according to the presence of aortic dissection on CTA. The RCAPCATa, LADPCATa, and LCxPCATa values were significantly higher in the AAD subjects than the non-AAD subjects, regardless of the presence or absence of atherosclerosis in the coronary arteries [-85.1±9.3 vs. -92.9±10.0 Hounsfield unit (HU); -83.2±7.4 vs. -89.9±9.1 HU; -77.5±8.4 vs. -85.6±7.9 HU, all P<0.001). The preoperative RCAPCATa, LADPCATa, and LCxPCATa values were higher in the AAD patients than the postoperative steady-state patients (-82.9±8.7 vs. -97.6±8.8 HU; -79.8±7.6 vs. -92.8±6.8 HU; -74.6±7.1 vs. -87.7±6.9 HU, all P<0.001). According to the multivariable logistic regression analysis, high RCAPCATa and LADPCATa values were associated with AAD regardless of the degree of stenosis [odds ratio (OR) =0.014; 95% confidence interval (CI): 0.001-0.177; P=0.001 and OR =0.010; 95% CI: 0.001-0.189; P=0.002].ConclusionsPCATa on computed tomography was increased in patients with AAD regardless of the presence or absence of coronary artery disease (CAD). This suggests that vascular inflammation is present in AAD independent of CAD. Further research should be conducted to investigate the potential of this imaging biomarker to predict AAD and monitor patients' responses to therapies for AAD.

Project description:Pericoronary adipose tissue (PCAT) features on Computed Tomography (CT) have been shown to reflect local inflammation and increased cardiovascular risk. Our goal was to determine whether PCAT radiomics extracted from coronary CT angiography (CCTA) images are associated with intravascular optical coherence tomography (IVOCT)-identified vulnerable-plaque characteristics (e.g., microchannels (MC) and thin-cap fibroatheroma (TCFA)). The CCTA and IVOCT images of 30 lesions from 25 patients were registered. The vessels with vulnerable plaques were identified from the registered IVOCT images. The PCAT-radiomics features were extracted from the CCTA images for the lesion region of interest (PCAT-LOI) and the entire vessel (PCAT-Vessel). We extracted 1356 radiomic features, including intensity (first-order), shape, and texture features. The features were reduced using standard approaches (e.g., high feature correlation). Using stratified three-fold cross-validation with 1000 repeats, we determined the ability of PCAT-radiomics features from CCTA to predict IVOCT vulnerable-plaque characteristics. In the identification of TCFA lesions, the PCAT-LOI and PCAT-Vessel radiomics models performed comparably (Area Under the Curve (AUC) ± standard deviation 0.78 ± 0.13, 0.77 ± 0.14). For the identification of MC lesions, the PCAT-Vessel radiomics model (0.89 ± 0.09) was moderately better associated than the PCAT-LOI model (0.83 ± 0.12). In addition, both the PCAT-LOI and the PCAT-Vessel radiomics model identified coronary vessels thought to be highly vulnerable to a similar standard (i.e., both TCFA and MC; 0.88 ± 0.10, 0.91 ± 0.09). The most favorable radiomic features tended to be those describing the texture and size of the PCAT. The application of PCAT radiomics can identify coronary vessels with TCFA or MC, consistent with IVOCT. Furthermore, the use of CCTA radiomics may improve risk stratification by noninvasively detecting vulnerable-plaque characteristics that are only visible with IVOCT.

Project description:PurposeTo determine the impact of low tube voltage coronary CT angiography on detection of subclinical atherosclerosis.Materials and methodsRetrospective sampling of an emergency department coronary CT angiography registry was performed. All patients in the registry underwent a noncontrast coronary artery calcium (CAC) scoring scan at 120 kV before coronary CT angiography. The study sample (n = 264) constituted patients with subclinical atherosclerosis (Coronary Artery Disease Reporting and Data System™ [CAD-RADS] 1 or 2) randomly mixed one-to-one with patients without atherosclerosis (CAD-RADS 0). The patients with coronary CT angiography performed at 70-90 kV were considered the low tube voltage group (n = 159) and patients with coronary CT angiography performed at 100-120 kV were considered the standard tube voltage group (n = 105). The number of coronary plaques and overall CAD-RADS classification (per patient) were evaluated twice: initially, by reading coronary CT angiography alone, and then, by coronary CT angiography in combination with a CAC scan. Considering the combined reading (CT angiography plus CAC scan) as the reference standard, the performance of coronary CT angiography alone was assessed for plaque detection and appropriate CAD-RADS (per patient) classification. The comparisons were made between the low tube voltage and standard tube voltage groups by using a Fisher exact test and χ2 test for proportions and a Mann-Whitney test and Kruskal-Wallis test for means.ResultsIn total, 455 plaques were identified in 118 patients (70 of 159 patients in the low tube voltage group; 48 of 105 in the standard tube voltage group). When reading coronary CT angiographic images alone, 97 of 455 (21%) plaques were missed that led to an incorrect CAD-RADS classification in 16 of 264 (6%) studies (interpreted as CAD-RADS 0 instead of CAD-RADS 1 or 2). Missed plaques were significantly more frequent in the low tube voltage group versus the standard tube voltage group (41% [85 of 206] vs 5% [12 of 249], respectively; P < .001). Incorrect CAD-RADS classification was also seen more commonly in the low tube voltage group (8.8% [14 of 159] vs 2% [two of 105]; P = .01), typically at low plaque burden (median CAC score, 1; range, 1-4). Calcified plaques that appeared isodense to luminal contrast material attenuation were seen more frequently in the low tube voltage group compared with the standard tube voltage group (20% [32 of 159] vs 7.6% [eight of 105], respectively; P = .005).ConclusionCoronary artery plaques may be missed at low tube voltage coronary CT angiographic examination performed without a concomitant CAC scan.© RSNA, 2019Supplemental material is available for this article.See also the commentary by Truong in this issue.

Project description:ImportancePericoronary adipose tissue (PCAT) computed tomography (CT) attenuation measured from coronary CT angiography (CTA) may be a promising metric in identifying high-risk plaques.ObjectiveTo determine whether high-risk plaque characteristics from coronary CTA are associated with PCAT CT attenuation in patients with a first acute coronary syndrome (ACS) and matched controls with stable coronary artery disease (CAD).Design, setting, and participantsThis retrospective, single-center case-control study (data were acquired at the University of Erlangen from 2009-2010) analyzed the CTA data sets of 19 patients who presented with ACS and 16 controls with stable CAD who were matched based on sex, age, and risk factors. Study observers were blinded to patients' clinical data. Semiautomated software was used to quantify and characterize plaques. The CT attenuation (Hounsfield unit [HU]) of PCAT was automatically measured around all lesions.Main outcomes and measuresTo investigate the association between high-risk plaque characteristics from CTA and PCAT CT attenuation as a novel surrogate measure of coronary inflammation.ResultsA total of 35 patients (mean [SD] age, 59.5 [11.3] years; 30 men [86%] and 5 women [14%]) were included in the analysis. Low- and intermediate-attenuation noncalcified plaque (NCP) burden were increased in culprit lesions (n = 19) compared with both nonculprit lesions (n = 55) in patients with ACS (12.6% vs 3.6%; P < .001; 38.4% vs 19.4%; P < .001) and the control group's highest-grade stenosis lesions (n = 16) (12.6% vs 5.6%; P = .002; 38.4% vs 22.1%; P < .001). Pericoronary adipose tissue attenuation was increased around culprit lesions (n = 19) compared with nonculprit lesions (n = 55) in patients with ACS (-69.1 HU vs -74.8 HU; P = .01) and highest-grade stenosis lesions in control patients (n = 16) (-69.1 HU vs -76.4 HU; P = .01). Pericoronary adipose tissue CT attenuation of all lesions in patients with ACS (n = 74) correlated more strongly with intermediate-attenuation (r = 0.393; P = .001) over low-attenuation (r = 0.221; P = .06) and high-attenuation NCP burden (r = -0.103; P = .38). In a multivariable analysis, low- and intermediate-attenuation NCP burden and PCAT CT attenuation were independently associated with the presence of culprit lesions (P < .05).Conclusions and relevancePericoronary CT attenuation was increased around culprit lesions compared with nonculprit lesions of patients with ACS and the lesions of matched controls. Combined quantitative high-risk plaque features and PCAT CT attenuation may allow for a more reliable identification of vulnerable plaques.

Project description:ObjectivesTo evaluate whether radiomics signature of pericoronary adipose tissue (PCAT) based on coronary computed tomography angiography (CCTA) could improve the prediction of future acute coronary syndrome (ACS) within 3 years.MethodsWe designed a retrospective case-control study that patients with ACS (n = 90) were well matched to patients with no cardiac events (n = 1496) during 3 years follow-up, then which were randomly divided into training and test datasets with a ratio of 3:1. A total of 107 radiomics features were extracted from PCAT surrounding lesions and 14 conventional plaque characteristics were analyzed. Radiomics score, plaque score, and integrated score were respectively calculated via a linear combination of the selected features, and their performance was evaluated with discrimination, calibration, and clinical application.ResultsRadiomics score achieved superior performance in identifying patients with future ACS within 3 years in both training and test datasets (AUC = 0.826, 0.811) compared with plaque score (AUC = 0.699, 0.640), with a significant difference of AUC between two scores in the training dataset (p = 0.009); while the improvement of integrated score discriminating capability (AUC = 0.838, 0.826) was non-significant. The calibration curves of three predictive models demonstrated a good fitness respectively (all p > 0.05). Decision curve analysis suggested that integrated score added more clinical benefit than plaque score. Stratified analysis revealed that the performance of three predictive models was not affected by tube voltage, CT version, different sites of hospital.ConclusionCCTA-based radiomics signature of PCAT could have the potential to predict the occurrence of subsequent ACS. Radiomics-based integrated score significantly outperformed plaque score in identifying future ACS within 3 years.Key points• Plaque score based on conventional plaque characteristics had certain limitations in the prediction of ACS. • Radiomics signature of PCAT surrounding plaques could have the potential to improve the predictive ability of subsequent ACS. • Radiomics-based integrated score significantly outperformed plaque score in the identification of future ACS within 3 years.

Dataset Information

Towards reference values of pericoronary adipose tissue attenuation: impact of coronary artery and tube voltage in coronary computed tomography angiography.

Objectives

Methods

Results

Conclusions

Key points

Publications

Towards reference values of pericoronary adipose tissue attenuation: impact of coronary artery and tube voltage in coronary computed tomography angiography.

Similar Datasets

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