Bone Mineral Density Derived from Cardiac CT Scans: Using Contrast Enhanced Scans for Opportunistic Screening.

PURPOSE: Osteoporosis is under-diagnosed and often co-exists with other diseases. Very low bone mineral density (BMD) indicates risk of osteoporosis and opportunistic screening for low BMD in CT-scans has been suggested. In a non-contrast enhanced thoracic CT scan, the scan-field-of-view includes vertebrae enabling BMD estimation. However, many CT scans are obtained by administration of contrast material. If the impact of contrast enhancement on BMD measurements could be quantified, considerably more patients are eligible for screening. METHODS: This study investigated the impact of intravenous contrast on thoracic BMD measurements in cardiac CT scans pre- and post-contrast, including different contrast trigger levels of 130 and 180 Hounsfield units (HU). BMD was measured using quantitative CT with asynchronous calibration. RESULTS: In 195 participants undergoing cardiac CT (mean age 57±9 years, 37 % females) contrast increased mean thoracic BMD from 116±33 mg/cm3 (non-enhanced CT) to 130±38 mg/cm3 (contrast-enhanced CT) (p<0.001). Using clinical cut-off values for very low (<80 mg/cm3) and low BMD (<120 mg/cm3) showed that 24 % (47/195 participants) were misclassified when BMD was measured on contrast-enhanced CT-scans. Of the misclassified patients, 6 % (12/195 participants) were categorized as having low BMD despite having very low BMD on the non-enhanced images. Contrast-CT using a higher contrast trigger level showed a significant increase in BMD compared to the lower trigger level (119±32 vs. 135±40 mg/cm3, p<0.01). CONCLUSION: For patients undergoing cardiac CT, using contrast-enhanced images to assess BMD entails substantial overestimation. Contrast protocol trigger levels also affect BMD measurements. Adjusting for these factors is needed before contrast-enhanced images can be used clinically. MINI ABSTRACT: Osteoporosis is under-diagnosed. Contrast-enhanced CT made to examine other diseases might be utilized simultaneously for bone mineral density (BMD) screening. These scans, however, likely entails overestimation of BMD due to the effect of contrast. Adjusting for this effect is needed before contrast-enhanced images can be implemented clinically for BMD screening.

Sex Differences in the Association Between Bone Mineral Density and Coronary Artery Disease in Patients Referred for Cardiac Computed Tomography.

Atherosclerosis and osteoporosis are both common and preventable diseases. Evidence supports a link between coronary artery disease (CAD) and low bone mineral density (BMD). This study aimed to assess the association between thoracic spine BMD and CAD in men and women with symptoms suggestive of CAD. This cross-sectional study included 1487 (mean age 57 years (range 40-80), 47% men) patients referred for cardiac computed tomography (CT). Agatston coronary artery calcium score (CACS), CAD severity (no, mild, moderate, and severe), vessel involvement (no, 1-, 2-, and 3/left main disease), and invasive measurements were evaluated. BMD of three thoracic vertebrae was measured using quantitative CT. We used the American college of radiology cut-off values for lumbar spine BMD to categorize patients into very low (<80 mg/cm3), low (80-120 mg/cm3), or normal BMD (>120 mg/cm3). BMD as a continuous variable was included in the linear regression analyses to assess associations between CACS (CACS=0, CACS 1- 399, and CACS ≥ 400) and BMD, and CAD severity and BMD. Significant lower BMD was present with increasing CACS and stenosis degree unadjusted. Multivariate linear regression analyses in women revealed a significant correlation between BMD and CACS groups (ß = -4.06, p<0.05), but no correlation between BMD and CAD severity (ß = -1.59, p = 0.14). No association was found between BMD and CACS (ß = -1.50, p = 0.36) and CAD severity (ß = 0.07, p = 0.94) in men. BMD is significantly correlated to CACS after adjusting for confounders in women, but not in men, suggesting a possible sex difference in pathophysiology.

Thoracic Bone Mineral Density Derived from Cardiac CT Is Associated with Greater Fracture Rate.

Background Osteoporosis is a prevalent, under-diagnosed, and treatable disease associated with increased fracture risk. Bone mineral density (BMD) derived from cardiac CT may be used to determine fracture rate. Purpose To assess the association between fracture rate and thoracic BMD derived from cardiac CT. Materials and Methods This prospective cohort study included consecutive participants referred for cardiac CT for evaluation of ischemic heart disease between September 2014 and March 2016. End of follow-up was June 30, 2018. In all participants, volumetric BMD of three thoracic vertebrae was measured by using quantitative CT software. The primary and secondary outcomes were any incident fracture and any incident osteoporosis-related fracture registered in the National Patient Registry, respectively. Hazard ratios were assessed by using BMD categorized as very low (<80 mg/cm3), low (80-120 mg/cm3), or normal (>120 mg/cm3). The study is registered at ClinicalTrials.gov (identifier: NCT02264717). Results In total, 1487 participants (mean age, 57 years ± 9; age range, 40-80 years; 52.5% women) were included, of whom 179 (12.0%) had very low BMD. During follow-up (median follow-up, 3.1 years; interquartile range, 2.7-3.4 years; range, 0.2-3.8 years), 80 of 1487 (5.3%) participants were diagnosed with an incident fracture and in 31 of 80 participants, the fracture was osteoporosis related. In unadjusted Cox regressions analyses, very low BMD was association with a greater rate of any fracture (hazard ratio, 2.6; 95% confidence interval [CI]: 1.4, 4.7; P = .002) and any osteoporosis-related fracture (hazard ratio, 8.1; 95% CI: 2.4, 26.7; P = .001) compared with normal BMD. After adjusting for age and sex, very low BMD remained associated with any fracture (hazard ratio, 2.1; 95% CI: 1.1, 4.2) and any osteoporosis-related fracture (hazard ratio, 4.0; 95% CI: 1.1, 14.6). Conclusion Routine cardiac CT can be used to help measure thoracic bone mineral density (BMD) to identify individuals who have low BMD and a greater fracture rate. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Bredella in this issue.

Feasibility of Opportunistic Screening for Low Thoracic Bone Mineral Density in Patients Referred for Routine Cardiac CT.

Despite being a frequent and treatable disease, osteoporosis remains under-diagnosed worldwide. Our study aim was to characterize the bone mineral density (BMD) status in a group of patients with symptoms suggestive of coronary artery disease (CAD) with low/intermediate risk profile undergoing routine cardiac computed tomography (CT) to rule out CAD. This cross-sectional study used prospectively acquired data from a large consecutively included cohort. Participants were referred for cardiac CT based on symptoms of CAD. Quantitative CT (QCT) dedicated software was used to obtain BMD measurements in 3 vertebrae starting from the level of the left main coronary artery. We used the American College of Radiology cut-off values for lumbar spine QCT to categorize patients into very low (<80 mg/cm3), low (80-120 mg/cm3), or normal BMD (>120 mg/cm3). Analyses included 1487 patients. Mean age was 57 years (range 40-80), and 52% were women. The number of patients with very low BMD was 105 women (14%, 105/773) and 74 men (10%, 74/714). The majority of patients with very low BMD was not previously diagnosed with osteoporosis (87%) and received no anti-osteoporotic treatment (90%). Opportunistic screening in patients referred for cardiac CT revealed a substantial number of patients with very low BMD. The majority of these patients was not previously diagnosed with osteoporosis and received no anti-osteoporotic treatment. Identification of these patients could facilitate initiation of anti-osteoporotic treatment and reduce the occurrence of osteoporosis-related complications.

Contact with general practice in patients with suspected chronic coronary syndrome before and after CT angiography compared with the general population.

BACKGROUND: Most patients undergoing coronary computed tomography angiography (CCTA) to diagnose coronary artery disease (CAD) are referred from general practitioners (GP). The burden in contacts to GP in relation to investigation on suspected CAD is unknown. METHODS: All patients undergoing CCTA in Western Denmark from 2014-2022 were included. CCTA stenosis was defined as diameter stenosis of ≥ 50%. Patients with and without stenosis were matched, in each group, 1:5 to a reference population based on birth-year, gender and municipality using data from national registries. All GP visits were registered in up to five years preceding and one year after the CTA and stratified by gender and age. Charlson comorbidity index (CCI) were calculated in all groups. RESULTS: Of the 62 512 patients included, 12 886 had a stenosis while 49 626 did not. Patients in both groups had a substantially higher GP visit frequency compared to reference populations. In the year of coronary CTA median GP contacts in patients with stenosis was 11 [6-17] vs. 6 [2-11] in the reference population (P < 0.001), in patients without stenosis 10 [6-17] vs. 5 [2-11] (P < 0.001). These findings were consistent across age and gender. CCI was higher among both patients with and without stenosis compared to reference groups. CONCLUSION: In patients undergoing CCTA to diagnose CAD, a substantially increased frequency of contacts to GP was observed in the five-year period prior to examination compared to the reference populations regardless of the CCTA findings. Obtaining the CCTA result did not seem to substantially affect the GP visit frequency.

Biomarkers for identification of high-risk coronary artery plaques in patients with suspected coronary artery disease.

BACKGROUND: Patients with atherosclerotic plaques containing high-risk features have an increased likelihood of events and a worse prognosis. Whether increased levels of Troponin I (TnI) and C-reactive protein (CRP) are associated with the presence of high-risk coronary atherosclerotic plaques (HRP) is not well described. We assessed the association between 1) TnI and 2) CRP with quantified coronary plaque burden, luminal diameter stenosis, and HRP in patients with low/intermediate pre-test probability of obstructive coronary artery disease (CAD) referred for coronary computed tomography angiography (CCTA). METHODS: The CCTA from 1615 patients were analyzed using a semiautomatic software for coronary artery plaque characterization. Patients with high TnI (>6 â€‹ng/L) and high CRP (>2 â€‹mg/L) were identified. Associations of TnI and CRP with plaque burden, stenosis (≥50% luminal diameter stenosis on CCTA), and HRP were investigated. RESULTS: TnI and CRP were both positively correlated with total plaque burden (TnI rs â€‹= â€‹0.14, p â€‹< â€‹0.001; CRP rs â€‹= â€‹0.08, p â€‹< â€‹0.001). In multivariate logistic regression analyses, high TnI was associated with stenosis (OR 1.43, 95% confidence interval (CI) 1.03-1.99, p â€‹= â€‹0.034), the presence of HRP (OR 1.79, 95% CI: 1.17-2.74, p â€‹= â€‹0.008), and the subtypes of HRP; low attenuation plaque (OR 1.93, 95% CI: 1.24-3.00, p â€‹= â€‹0.003), and positive remodeling (OR 1.51, 95% CI: 1.07-2.13, p â€‹= â€‹0.018). For CRP, only stenosis and napkin ring sign correlated significantly. CONCLUSION: In patients with suspected CAD, TnI and CRP are associated with HRP features. These findings may suggest that inflammatory and particularly ischemic biomarkers might improve early risk stratification and affect patient management. GOV IDENTIFIER: NCT02264717.

Predicting the presence of coronary plaques featuring high-risk characteristics using polygenic risk scores and targeted proteomics in patients with suspected coronary artery disease.

BACKGROUND: The presence of coronary plaques with high-risk characteristics is strongly associated with adverse cardiac events beyond the identification of coronary stenosis. Testing by coronary computed tomography angiography (CCTA) enables the identification of high-risk plaques (HRP). Referral for CCTA is presently based on pre-test probability estimates including clinical risk factors (CRFs); however, proteomics and/or genetic information could potentially improve patient selection for CCTA and, hence, identification of HRP. We aimed to (1) identify proteomic and genetic features associated with HRP presence and (2) investigate the effect of combining CRFs, proteomics, and genetics to predict HRP presence. METHODS: Consecutive chest pain patients (n = 1462) undergoing CCTA to diagnose obstructive coronary artery disease (CAD) were included. Coronary plaques were assessed using a semi-automatic plaque analysis tool. Measurements of 368 circulating proteins were obtained with targeted Olink panels, and DNA genotyping was performed in all patients. Imputed genetic variants were used to compute a multi-trait multi-ancestry genome-wide polygenic score (GPSMult). HRP presence was defined as plaques with two or more high-risk characteristics (low attenuation, spotty calcification, positive remodeling, and napkin ring sign). Prediction of HRP presence was performed using the glmnet algorithm with repeated fivefold cross-validation, using CRFs, proteomics, and GPSMult as input features. RESULTS: HRPs were detected in 165 (11%) patients, and 15 input features were associated with HRP presence. Prediction of HRP presence based on CRFs yielded a mean area under the receiver operating curve (AUC) ± standard error of 73.2 ± 0.1, versus 69.0 ± 0.1 for proteomics and 60.1 ± 0.1 for GPSMult. Combining CRFs with GPSMult increased prediction accuracy (AUC 74.8 ± 0.1 (P = 0.004)), while the inclusion of proteomics provided no significant improvement to either the CRF (AUC 73.2 ± 0.1, P = 1.00) or the CRF + GPSMult (AUC 74.6 ± 0.1, P = 1.00) models, respectively. CONCLUSIONS: In patients with suspected CAD, incorporating genetic data with either clinical or proteomic data improves the prediction of high-risk plaque presence. TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT02264717 (September 2014).

Clinical Likelihood Prediction of Hemodynamically Obstructive Coronary Artery Disease in Patients With Stable Chest Pain.

BACKGROUND: Selection for invasive angiography is recommended to be based on pretest probabilities (PTPs), and physiological measures of hemodynamical impairment by, for example, fractional flow reserve (FFR) should guide revascularization. The risk factor-weighted clinical likelihood (RF-CL) and coronary artery calcium score-weighted clinical likelihood (CACS-CL) models show superior discrimination of patients with suspected obstructive coronary artery disease (CAD), but validation against hemodynamic impairment is warranted. OBJECTIVES: The aim of this study was to validate the RF-CL and CACS-CL models against hemodynamically obstructive CAD. METHODS: Stable de novo chest pain patients (N = 4,371) underwent coronary computed tomography angiography and subsequently invasive coronary angiography with FFR measurements. Hemodynamically obstructive CAD was defined as invasive FFR ≤0.80 or high-grade stenosis by visual assessment (>90% diameter stenosis). For comparison, a guideline-endorsed basic PTP model was calculated based on age, sex, and symptom typicality. The RF-CL model additionally included the number of risk factors, and the CACS-CL model incorporated the coronary artery calcium score into the RF-CL. RESULTS: In total, 447 of 4,371 (10.9%) patients had hemodynamically obstructive CAD. Both the RF-CL and CACS-CL models classified more patients with a very low clinical likelihood (≤5%) of obstructive CAD compared to the basic PTP model (33.0% and 53.7% vs 12.0%; P < 0.001) with a preserved low prevalence of hemodynamically obstructive CAD (<5% for all models). Against hemodynamically obstructive CAD, calibration and discrimination of the RF-CL and CACS-CL models were superior to the basic PTP model. CONCLUSIONS: The RF-CL and CACS-CL models are well calibrated and superior to a currently recommended basic PTP model to predict hemodynamically obstructive CAD. (Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease [Dan-NICAD]; NCT02264717; Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease 2 [Dan-NICAD 2]; NCT03481712, Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease 3 [Dan-NICAD 3]; NCT04707859).

Association between socioeconomic position and coronary artery calcium score in patients with symptoms suggestive of obstructive coronary artery disease.

AIM: Low socioeconomic-position (SEP) is associated with increased prevalence of cardiovascular disease. Whether this is caused by earlier development of atherosclerotic calcifications is not well understood. This study aimed to investigate the association between SEP and coronary artery calcium score (CACS) in a population presenting with symptoms suggestive of obstructive coronary artery disease. METHODS: We included 50,561 patients (mean age 57 â€‹± â€‹11, 53% women) from a national registry undergoing coronary computed tomography angiography (CTA) from 2008 to 2019. CACS was used as outcome in categories; 1-399 and â€‹≥ â€‹400 in regression analyses. SEP was obtained from central registries and defined as mean personal income and length of education. RESULTS: The number of risk factors were negatively associated with income and education among both men and women. The adjusted OR of having a CACS≥400 was 1.67(1.50-1.86) among women with <10 years of education compared to >13 years. For men the corresponding OR was 1.03(0.91-1.16). For women with low income the adjusted OR of CACS ≥400 was 2.29(1.96-2.69) using high income as a reference. For men the corresponding OR was 1.13(0.99-1.29). CONCLUSION: In patients referred for coronary CTA we found an increased level of risk factors among men and women with short education and low income. Among women with longer education and a higher income we demonstrated a lower CACS compared to other women and men. Socioeconomic differences seem to affect the development of CACS beyond what can be explained by traditional risk factors. Part of the observed result may be due to referral bias. GOV IDENTIFIER: None.

Radiomics analysis enhances the diagnostic performance of CMR stress perfusion: a proof-of-concept study using the Dan-NICAD dataset.

Objectives: To assess the feasibility of extracting radiomics signal intensity based features from the myocardium using cardiovascular magnetic resonance (CMR) imaging stress perfusion sequences. Furthermore, to compare the diagnostic performance of radiomics models against standard-of-care qualitative visual assessment of stress perfusion images, with the ground truth stenosis label being defined by invasive Fractional Flow Reserve (FFR) and quantitative coronary angiography. Methods: We used the Dan-NICAD 1 dataset, a multi-centre study with coronary computed tomography angiography, 1,5 T CMR stress perfusion, and invasive FFR available for a subset of 148 patients with suspected coronary artery disease. Image segmentation was performed by two independent readers. We used the Pyradiomics platform to extract radiomics first-order (n = 14) and texture (n = 75) features from the LV myocardium (basal, mid, apical) in rest and stress perfusion images. Results: Overall, 92 patients (mean age 62 years, 56 men) were included in the study, 39 with positive FFR. We double-cross validated the model and, in each inner fold, we trained and validated a per territory model. The conventional analysis results reported sensitivity of 41% and specificity of 84%. Our final radiomics model demonstrated an improvement on these results with an average sensitivity of 53% and specificity of 86%. Conclusion: In this proof-of-concept study from the Dan-NICAD dataset, we demonstrate the feasibility of radiomics analysis applied to CMR perfusion images with a suggestion of superior diagnostic performance of radiomics models over conventional visual analysis of perfusion images in picking up perfusion defects defined by invasive coronary angiography.

Diagnostic performance of clinical likelihood models of obstructive coronary artery disease to predict myocardial perfusion defects.

AIMS: Clinical likelihood (CL) models are designed based on a reference of coronary stenosis in patients with suspected obstructive coronary artery disease. However, a reference standard for myocardial perfusion defects (MPDs) could be more appropriate. We aimed to investigate the ability of the 2019 European Society of Cardiology pre-test probability (ESC-PTP), the risk-factor-weighted (RF-CL) model, and coronary artery calcium score-weighted (CACS-CL) model to diagnose MPDs. METHODS AND RESULTS: Symptomatic stable de novo chest pain patients (n = 3374) underwent coronary computed tomography angiography and subsequent myocardial perfusion imaging by single-photon emission computed tomography, positron emission tomography, or cardiac magnetic resonance. For all modalities, MPD was defined as coronary computed tomography angiography with suspected stenosis and stress-perfusion abnormality in ≥2 segments. The ESC-PTP was calculated based on age, sex, and symptom typicality, and the RF-CL and CACS-CL additionally included a number of risk factors and CACS. In total, 219/3374 (6.5%) patients had an MPD. Both the RF-CL and the CACS-CL classified substantially more patients to low CL (<5%) of obstructive coronary artery disease compared with the ESC-PTP (32.5 and 54.1 vs. 12.0%, P < 0.001) with preserved low prevalences of MPD (<2% for all models). Compared with the ESC-PTP [area under the receiver-operating characteristic curve (AUC) 0.74 (0.71-0.78)], the discrimination of having an MPD was higher for the CACS-CL model [AUC 0.88 (0.86-0.91), P < 0.001], while it was similar for the RF-CL model [AUC 0.73 (0.70-0.76), P = 0.32]. CONCLUSION: Compared with basic CL models, the RF-CL and CACS-CL models improve down classification of patients to a very low-risk group with a low prevalence of MPD.

Combining Polygenic and Proteomic Risk Scores With Clinical Risk Factors to Improve Performance for Diagnosing Absence of Coronary Artery Disease in Patients With de novo Chest Pain.

BACKGROUND: Patients with de novo chest pain, referred for evaluation of possible coronary artery disease (CAD), frequently have an absence of CAD resulting in millions of tests not having any clinical impact. The objective of this study was to investigate whether polygenic risk scores and targeted proteomics improve the prediction of absence of CAD in patients with suspected CAD, when added to the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) minimal risk score (PMRS). METHODS: Genotyping and targeted plasma proteomics (N=368 proteins) were performed in 1440 patients with symptoms suspected to be caused by CAD undergoing coronary computed tomography angiography. Based on individual genotypes, a polygenic risk score for CAD (PRSCAD) was calculated. The prediction was performed using combinations of PRSCAD, proteins, and PMRS as features in models using stability selection and machine learning. RESULTS: Prediction of absence of CAD yielded an area under the curve of PRSCAD-model, 0.64±0.03; proteomic-model, 0.58±0.03; and PMRS model, 0.76±0.02. No significant correlation was found between the genetic and proteomic risk scores (Pearson correlation coefficient, -0.04; P=0.13). Optimal predictive ability was achieved by the full model (PRSCAD+protein+PMRS) yielding an area under the curve of 0.80±0.02 for absence of CAD, significantly better than the PMRS model alone (P<0.001). For reclassification purpose, the full model enabled down-classification of 49% (324 of 661) of the 5% to 15% pretest probability patients and 18% (113 of 611) of >15% pretest probability patients. CONCLUSIONS: For patients with chest pain and low-intermediate CAD risk, incorporating targeted proteomics and polygenic risk scores into the risk assessment substantially improved the ability to predict the absence of CAD. Genetics and proteomics seem to add complementary information to the clinical risk factors and improve risk stratification in this large patient group. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02264717.

Improved pre-test likelihood estimation of coronary artery disease using phonocardiography.

Aims: Current early risk stratification of coronary artery disease (CAD) consists of pre-test probability scoring such as the 2019 ESC guidelines on chronic coronary syndromes (ESC2019), which has low specificity and thus rule-out capacity. A newer clinical risk factor model (risk factor-weighted clinical likelihood, RF-CL) showed significantly improved rule-out capacity over the ESC2019 model. The aim of the current study was to investigate if the addition of acoustic features to the RF-CL model could improve the rule-out potential of the best performing clinical risk factor models. Methods and results: Four studies with heart sound recordings from 2222 patients were pooled and distributed into two data sets: training and test. From a feature bank of 40 acoustic features, a forward-selection technique was used to select three features that were added to the RF-CL model. Using a cutoff of 5% predicted risk of CAD, the developed acoustic-weighted clinical likelihood (A-CL) model showed significantly (P < 0.05) higher specificity of 48.6% than the RF-CL model (specificity of 41.5%) and ESC 2019 model (specificity of 6.9%) while having the same sensitivity of 84.9% as the RF-CL model. Area under the curve of the receiver operating characteristic for the three models was 72.5% for ESC2019, 76.7% for RF-CL, and 79.5% for A-CL. Conclusion: The proposed A-CL model offers significantly improved rule-out capacity over the ESC2019 model and showed better overall performance than the RF-CL model. The addition of acoustic features to the RF-CL model was shown to significantly improve early risk stratification of symptomatic patients suspected of having stable CAD.

The PROMISE Minimal Risk Score Improves Risk Classification of Symptomatic Patients With Suspected CAD.

BACKGROUND: Guidelines for evaluating patients with suspected coronary artery disease (CAD) recommend pretest probability (PTP) estimation but provide no clear recommendations regarding diagnostic testing in patients with >5% to 15% risk of obstructive CAD. The diagnostic and prognostic value of PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) minimal risk score (PMRS) calculation in this patient group is unknown. OBJECTIVES: This work aims to improve the evaluation of stable patients with suspected CAD by using the PMRS, which identifies patients at minimal risk of CAD and events in patients with >5% to 15% PTP of obstructive CAD. METHODS: Greater than 5% to 15% PTP patients from 2 large clinical trials were used for subcohort derivation: PROMISE (N = 10,003) and Dan-NICAD (Danish study of Non-Invasive Testing in Coronary Artery Disease) (N = 3,252). First, the PMRS cutoff associated with a prevalence of obstructive CAD ≤5% was determined in the >5% to 15% PTP PROMISE core lab computed tomographic angiography patients (discovery cohort: n = 2,191). This cutoff was validated for obstructive CAD in >5% to 15% PTP Dan-NICAD patients (CAD validation cohort: n = 1,386) and for prognostic impact on death and myocardial infarction in >5% to 15% PTP PROMISE non-core lab computed tomographic angiography patients (prognosis validation cohort: n = 2,753). RESULTS: In the discovery cohort, a CAD prevalence of ≤5% was found at a PMRS of ≥34%. In the CAD validation cohort, this cutoff down-classified 442 (31.9%) of >5% to 15% PTP patients into the low PTP group (CAD ≤5%); the prevalence of obstructive CAD in down-classified patients was 3.2% compared to 7.1% in non-down-classified patients. A PMRS ≥34% was nonsignificantly associated with a lower risk of myocardial infarction and death in the prognosis validation cohort (HR: 0.58 [95% CI: 0.29-1.18]; P = 0.13). CONCLUSIONS: For evaluating patients with suspected CAD, a combined use of traditional PTP and the PMRS correctly down-classified one-third of >5% to 15% PTP patients into a group with very low prevalence of obstructive CAD and adverse events. The proposed strategy may improve risk stratification and help reduce unneeded diagnostic testing.

Spectral analysis of heart sounds associated with coronary artery disease.

Objective. The aim of this study was to find spectral differences of diagnostic interest in heart sound recordings of patients with coronary artery disease (CAD) and healthy subjects.Approach. Heart sound recordings from three studies were pooled, and patients with clear diagnostic outcomes (positive: CAD and negative: Non-CAD) were selected for further analysis. Recordings from 1146 patients (191 CAD and 955 Non-CAD) were analyzed for spectral differences between the two groups using Welch's spectral density estimate. Frequency spectra were estimated for systole and diastole segments, and time-frequency spectra were estimated for first (S1) and second (S2) heart sound segments. An ANCOVA model with terms for diagnosis, age, gender, and body mass index was used to evaluate statistical significance of the diagnosis term for each time-frequency component.Main results. Diastole and systole segments of CAD patients showed increased energy at frequencies 20-120 Hz; furthermore, this difference was statistically significant for the diastole. CAD patients showed decreased energy for the mid-S1 and mid-S2 segments and conversely increased energy before and after the valve sounds. Both S1 and S2 segments showed regions of statistically significant difference in the time-frequency spectra.Significance. Results from analysis of the diastole support findings of increased low-frequency energy from previous studies. Time-frequency components of S1 and S2 sounds showed that these two segments likely contain heretofore untapped information for risk assessment of CAD using phonocardiography; this should be considered in future works. Further development of features that build on these findings could lead to improved acoustic detection of CAD.

Sortilin as a Biomarker for Cardiovascular Disease Revisited.

Genetic variants in the genomic region containing SORT1 (encoding the protein sortilin) are strongly associated with cholesterol levels and the risk of coronary artery disease (CAD). Circulating sortilin has therefore been proposed as a potential biomarker for cardiovascular disease. Multiple studies have reported association between plasma sortilin levels and cardiovascular outcomes. However, the findings are not consistent across studies, and most studies have small sample sizes. The aim of this study was to evaluate sortilin as a biomarker for CAD in a well-characterized cohort with symptoms suggestive of CAD. In total, we enrolled 1,173 patients with suspected stable CAD referred to coronary computed tomography angiography. Sortilin was measured in plasma using two different technologies for quantifying circulating sortilin: a custom-made enzyme-linked immunosorbent assay (ELISA) and OLINK Cardiovascular Panel II. We found a relative poor correlation between the two methods (correlation coefficient = 0.21). In addition, genotyping and whole-genome sequencing were performed on all patients. By whole-genome regression analysis of sortilin levels measured with ELISA and OLINK, two independent cis protein quantitative trait loci (pQTL) on chromosome 1p13.3 were identified, with one of them being a well-established risk locus for CAD. Incorporating rare genetic variants from whole-genome sequence data did not identify any additional pQTLs for plasma sortilin. None of the traditional CAD risk factors, such as sex, age, smoking, and statin use, were associated with plasma sortilin levels. Furthermore, there was no association between circulating sortilin levels and coronary artery calcium score (CACS) or disease severity. Sortilin did not improve discrimination of obstructive CAD, when added to a clinical pretest probability (PTP) model for CAD. Overall, our results indicate that studies using different methodologies for measuring circulating sortilin should be compared with caution. In conclusion, the well-known SORT1 risk locus for CAD is linked to lower sortilin levels in circulation, measured with ELISA; however, the effect sizes are too small for sortilin to be a useful biomarker for CAD in a clinical setting of low- to intermediate-risk chest-pain patients.

Validation and update of the minimal risk tool in patients suspected of chronic coronary syndrome.

Risk stratification in patients with suspected coronary artery disease (CAD) is important. Recently, the minimal-risk-tool (MRT) was developed to identify individuals with low CAD risk despite symptoms in order to avoid unnecessary testing. We aimed to validate and update the MRT-model in a contemporary cohort. The Dan-NICAD trial cohort, consisting of 1675 consecutive patients referred for coronary computed tomography angiography (CTA), was used to calculate the MRT-score based on the published fitted variable coefficients from the PROMISE and SCOT-HEART trials. Minimal risk was defined as zero calcium score, no coronary atherosclerosis at coronary CTA, and no cardiovascular events in the follow-up period. We tested an updated MRT-model by pooling the fitted variable coefficients from all three trials. A total of 1544 patients fulfilling the inclusion criteria were followed for 3.1 [2.7-3.4] years. In 710 (46%) patients, the criteria for minimal risk were fulfilled. Despite substantial coefficient variation, the MRTs based on the PROMISE, the SCOT-HEART and the updated MRT variables showed similar moderate to high discriminative performance for minimal risk estimation. Although all three models tended to underestimate minimal risk, the updated MRT had the best performance. Using a 75% minimal risk cut-off, the updated MRT showed a sensitivity of 11.6% (95% CI 9.3-14.2%) and specificity of 99.3% (95% CI 98.6-99.8%). An updated MRT model based on three large studies increased calibration compared to the existing MRT models, whereas discrimination was similar despite substantial coefficient variation. The updated MRT might supplement currently recommended pre-test probability models.

Advanced heart sound analysis as a new prognostic marker in stable coronary artery disease.

Aims: Recent technological advances enable diagnosing of obstructive coronary artery disease (CAD) from heart sound analysis with a high negative predictive value. However, the prognostic impact of this approach remains unknown. To investigate the prognostic value of heart sound analysis as two scores, the Acoustic-score and the CAD-score, in patients with suspected CAD which is treated according to standard of care. Methods and results: Consecutive patients with angina symptoms referred for coronary computed tomography angiography (CTA) were enrolled. The Acoustic-score was developed from eight acoustic CAD-related features. This score was combined with risk factors to generate the CAD-score. A cut-off score >20 was pre-specified for both scores to indicate disease. If coronary CTA raised suspicion of obstructive CAD, patients were referred to invasive angiography and revascularized when indicated. Of 1675 enrolled patients, 1464 (87.4%) were included in this substudy. The combined primary endpoint was all-cause mortality and myocardial infarction (n = 26). Follow-up was 3.1 (2.7-3.4) years. Of patients with primary endpoints, the Acoustic-score was >20 in 25 (96%); the CAD-score was >20 in 22 (85%). In an unadjusted Cox analysis of the primary endpoints, the hazard ratio for scores >20 under current standard clinical care was 12.6 (1.7-93.2) for the Acoustic-score and 5.4 (1.9-15.7) for the CAD-score. The CAD-score contained prognostic information even after adjusting for lipid-lowering therapy initiation, stenosis at CTA, and early revascularization. Conclusion: Heart sound analysis seems to carry prognostic information and may improve initial risk stratification of patients with suspected CAD. Clinicaltrialsorg ID: NCT02264717.

One-step anatomic and function testing by cardiac CT versus second-line functional testing in symptomatic patients with coronary artery stenosis: head-to-head comparison of CT-derived fractional flow reserve and myocardial perfusion imaging.

BACKGROUND: CT-QFR is a novel coronary computed tomography angiography (CTA)-based method for on-site evaluation of patients with suspected obstructive coronary artery disease (CAD). AIMS: We aimed to compare the diagnostic performance of CT-QFR with myocardial perfusion scintigraphy (MPS) and cardiovascular magnetic resonance (CMR) as second-line tests in patients with suspected obstructive CAD after coronary CTA. METHODS: A paired analysis of CT-QFR and MPS or CMR, with an invasive FFR-based classification as reference standard was carried out. Symptomatic patients with >50% diameter stenosis on coronary CTA were randomised to MPS or CMR and referred for invasive coronary angiography. RESULTS: The rate of coronary CTA not feasible for CT-QFR analysis was 17%. Paired patient-level data were available for 118 patients in the MPS group and 113 in the CMR group. Patient-level diagnostic accuracy was better for CT-QFR than for both MPS (82.2% [95% CI: 75.2-89.2] vs 70.3% [95% CI: 62.0-78.7], p=0.029) and CMR (77.0% [95% CI: 69.1-84.9] vs 65.5% [95% CI: 56.6-74.4], p=0.047). Following a positive coronary CTA and with the intention to diagnose, CT-QFR, CMR and MPS were equally suitable as rule-in and rule-out modalities. CONCLUSIONS: The diagnostic performance of CT-QFR as a second-line test was at least similar to MPS and CMR for the evaluation of obstructive CAD in symptomatic patients presenting with ≥50% diameter stenosis on coronary CTA.

Polygenic Risk Score-Enhanced Risk Stratification of Coronary Artery Disease in Patients With Stable Chest Pain.

BACKGROUND: Polygenic risk scores (PRSs) are associated with coronary artery disease (CAD), but the clinical potential of using PRSs at the single-patient level for risk stratification has yet to be established. We investigated whether adding a PRS to clinical risk factors (CRFs) improves risk stratification in patients referred to coronary computed tomography angiography on a suspicion of obstructive CAD. METHODS: In this prespecified diagnostic substudy of the Dan-NICAD trial (Danish study of Non-Invasive testing in Coronary Artery Disease), we included 1617 consecutive patients with stable chest symptoms and no history of CAD referred for coronary computed tomography angiography. CRFs used for risk stratification were age, sex, symptoms, prior or active smoking, antihypertensive treatment, lipid-lowering treatment, and diabetes. In addition, patients were genotyped, and their PRSs were calculated. All patients underwent coronary computed tomography angiography. Patients with a suspected ≥50% stenosis also underwent invasive coronary angiography with fractional flow reserve. A combined end point of obstructive CAD was defined as a visual invasive coronary angiography stenosis >90%, fractional flow reserve <0.80, or a quantitative coronary analysis stenosis >50% if fractional flow reserve measurements were not feasible. RESULTS: The PRS was associated with obstructive CAD independent of CRFs (adjusted odds ratio, 1.8 [95% CI, 1.5-2.2] per SD). The PRS had an area under the curve of 0.63 (0.59-0.68), which was similar to that for age and sex. Combining the PRS with CRFs led to a CRF+PRS model with area under the curve of 0.75 (0.71-0.79), which was 0.04 more than the CRF model (P=0.0029). By using pretest probability (pretest probability) cutoffs at 5% and 15%, a net reclassification improvement of 15.8% (P=3.1×10-4) was obtained, with a down-classification of risk in 24% of patients (211 of 862) in whom the pretest probability was 5% to 15% based on CRFs alone. CONCLUSIONS: Adding a PRS improved risk stratification of obstructive CAD beyond CRFs, suggesting a modest clinical potential of using PRSs to guide diagnostic testing in the contemporary clinical setting. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02264717.