Reduced left ventricular function on cardiac MRI of SLE patients correlates with measures of disease activity and inflammation

Background

Women with SLE have an elevated risk of cardiovascular disease. Many women with SLE frequently report chest pain in the absence of obstructive coronary artery disease (CAD) due to coronary microvascular dysfunction (CMD), a form of ischemia with no obstructive CAD. Echocardiographic studies have shown that SLE patients have reduced left ventricular (LV) function, which may also correlate with higher SLE disease activity scores. As such, we used cardiac magnetic resonance imaging (cMRI) to investigate the relationship between SLE, related inflammatory biomarkers, and cardiac function in female SLE patients.

Methods

We performed stress cMRI in women with SLE and chest pain with no obstructive CAD (n=13, all met ACR 1997 criteria,) and reference controls (n=22) using our published protocol. We evaluated LV function, tissue characterization (T1 mapping, ECV), and delayed enhancement, using CV142 software (Circle Cardiovascular Imaging Inc, Calgary, AB, Canada). Myocardial perfusion reserve index (MPRI) was calculated using our published protocol. SLEDAI and SLICC Damage Index (DI) were calculated per validated criteria. Serum samples were analyzed for inflammatory markers and autoantibodies. Wilcoxon rank-sum test was performed on clinical values with CMD and no CMD SLE subjects, and on cMRI values with all SLE subjects and controls. Correlation analysis was done on clinical values, and cMRI values on all SLE subjects.

Results

Overall, 40% of SLE subjects had MPRI values < 1.84, consistent with CMD. Compared to controls, SLE subjects had significantly lower LVEF, and higher LVESVi and LVMi. Corresponding to this, radial, longitudinal, and circumferential strain were significantly lower in the SLE subjects. In correlation analysis of serum inflammatory biomarkers to cMRI values in the SLE subjects, SLICC DI was related to worse cardiac function (lower radial, circumferential and longitudinal strain) and higher T1 time. Additionally, fasting insulin and ESR were negatively correlated with LVMi. Fasting insulin also negatively correlated with ECV. CRP had a positive association with LVESV index and CI and a negative association with longitudinal strain.

Conclusions

Among women with SLE with chest pain and no obstructive CAD, 40% have CMD. While evaluations of known inflammatory markers (such as CRP and ESR) predictably correlated with decreased cardiac function, our study found that decreased fasting insulin levels as a novel marker of diminished LV function. In addition, low insulin levels were observed to correlate with increased LVMi and ECV, suggesting a cardioprotective effect of insulin in SLE patients. We also noted that SLICC DI, an assessment of SLE damage, correlates with cardiac dysfunction in SLE. Our findings underline the potential of non-invasive cMRI as a tool for monitoring cardiovascular function in SLE, particularly in patients with high SLICC DI, ESR and CRP and low fasting insulin levels.

Sex and age-specific interactions of coronary atherosclerotic plaque onset and prognosis from coronary computed tomography

AIMS

The totality of atherosclerotic plaque derived from coronary computed tomography angiography (CCTA) emerges as a comprehensive measure to assess the intensity of medical treatment that patients need. This study examines the differences in age onset and prognostic significance of atherosclerotic plaque burden between sexes.

METHODS AND RESULTS

From a large multi-center CCTA registry the Leiden CCTA score was calculated in 24 950 individuals. A total of 11 678 women (58.5 ± 12.4 years) and 13 272 men (55.6 ± 12.5 years) were followed for 3.7 years for major adverse cardiovascular events (MACE) (death or myocardial infarction). The age where the median risk score was above zero was 12 years higher in women vs. men (64-68 years vs. 52-56 years, respectively, P < 0.001). The Leiden CCTA risk score was independently associated with MACE: score 6-20: HR 2.29 (1.69-3.10); score > 20: HR 6.71 (4.36-10.32) in women, and score 6-20: HR 1.64 (1.29-2.08); score > 20: HR 2.38 (1.73-3.29) in men. The risk was significantly higher for women within the highest score group (adjusted P-interaction = 0.003). In pre-menopausal women, the risk score was equally predictive and comparable with men. In post-menopausal women, the prognostic value was higher for women [score 6-20: HR 2.21 (1.57-3.11); score > 20: HR 6.11 (3.84-9.70) in women; score 6-20: HR 1.57 (1.19-2.09); score > 20: HR 2.25 (1.58-3.22) in men], with a significant interaction for the highest risk group (adjusted P-interaction = 0.004).

CONCLUSION

Women developed coronary atherosclerosis approximately 12 years later than men. Post-menopausal women within the highest atherosclerotic burden group were at significantly higher risk for MACE than their male counterparts, which may have implications for the medical treatment intensity.

Interplay Between Zero CAC, Quantitative Plaque Analysis, and Adverse Events in a Diverse Patient Cohort

BACKGROUND

Coronary artery calcium scoring (CAC) has garnered attention in the diagnostic approach to chest pain patients. However, little is known about the interplay between zero CAC, sex, race, ethnicity, and quantitative coronary plaque analysis.

METHODS

We conducted a retrospective analysis from our computed tomography registry of patients with stable angina without prior myocardial infarction or revascularization undergoing coronary computed tomography angiography at Montefiore Healthcare System. Follow-up end points collected included invasive angiography, type-1 myocardial infarction, coronary revascularization, cardiovascular and all-cause death.

RESULTS

A total of 2249 patients were included (66% female). The median follow-up was 5.5 years. The median age of those without CAC was 52 years (interquartile range, 44-59) and 60 years (interquartile range, 53-68) in those with CAC. Most patients were Hispanic (58%), and the rest were non-Hispanic Black (28%), non-Hispanic White (10%), and non-Hispanic Asian (5%). The majority had CAC=0 (55%). The negative predictive value of CAC=0 was 92.8%, 99.9%, and 99.9% for any plaque, obstructive coronary artery stenosis, and the composite outcome of all-cause death, myocardial infarction, or coronary revascularization, respectively. Among patients without CAC (n=1237), 89 patients (7%) had evidence of plaque on their coronary computed tomography angiography with a median low-attenuation noncalcified plaque burden of 4% (2-7). There were no significant differences in the negative predictive value for CAC=0 by sex, race, or ethnicity. Patients with ≥2 risk factors had higher odds of having plaque with zero CAC.

CONCLUSIONS

In summary, no sex, race, or ethnicity differences were demonstrated in the negative predictive value of a zero CAC; however, patients with ≥2 risk factors had a higher prevalence of plaque. A small percentage (7%) of symptomatic patients undergoing coronary computed tomography angiography with zero CAC had noncalcified coronary plaque, with the implication that caution is needed for downscaling of preventive treatment in patients with zero CAC, chest pain, and multiple risk factors.

Usefulness of phase analysis on ECG gated single photon emission computed tomography myocardial perfusion imaging

Electrocardiogram (ECG)-gated single photon emission computed tomography myocardial perfusion imaging (GSPECT-MPI) is widely used for assessing coronary artery disease. Phase analysis on GSPECT-MPI can assess left ventricular mechanical dyssynchrony quantitatively on standard GSPECT-MPI alongside myocardial perfusion and function assessment. It has been shown that phase variables by GSPECT-MPI correlate well with tissue Doppler imaging by echocardiography. Main phase variables quantified by GSPECT-MPI are entropy, bandwidth, and phase standard deviation. Although those variables are automatically obtained from several software packages including Quantitative Gated SPECT and Emory Cardiac Toolbox, the methods for their measurement vary in each package. Several studies have shown that phase analysis has predictive value for response to cardiac resynchronization therapy and prognostic value for future adverse cardiac events beyond standard GSPECT-MPI variables. In this review, we summarize the basics of phase analysis on GSPECT-MPI and usefulness of phase analysis in clinical practice.

Relationship between impaired myocardial blood flow by positron emission tomography and low-attenuation plaque burden and pericoronary adipose tissue attenuation from coronary computed tomography: From the prospective PACIFIC trial

BACKGROUND

Positron emission tomography (PET) is the clinical gold standard for quantifying myocardial blood flow (MBF). Pericoronary adipose tissue (PCAT) attenuation may detect vascular inflammation indirectly. We examined the relationship between MBF by PET and plaque burden and PCAT on coronary CT angiography (CCTA).

METHODS

This post hoc analysis of the PACIFIC trial included 208 patients with suspected coronary artery disease (CAD) who underwent [15O]H2O PET and CCTA. Low-attenuation plaque (LAP, < 30HU), non-calcified plaque (NCP), and PCAT attenuation were measured by CCTA.

RESULTS

In 582 vessels, 211 (36.3%) had impaired per-vessel hyperemic MBF (≤ 2.30 mL/min/g). In multivariable analysis, LAP burden was independently and consistently associated with impaired hyperemic MBF (P = 0.016); over NCP burden (P = 0.997). Addition of LAP burden improved predictive performance for impaired hyperemic MBF from a model with CAD severity and calcified plaque burden (P < 0.001). There was no correlation between PCAT attenuation and hyperemic MBF (r = - 0.11), and PCAT attenuation was not associated with impaired hyperemic MBF in univariable or multivariable analysis of all vessels (P > 0.1).

CONCLUSION

In patients with stable CAD, LAP burden was independently associated with impaired hyperemic MBF and a stronger predictor of impaired hyperemic MBF than NCP burden. There was no association between PCAT attenuation and hyperemic MBF.

Standardized Medical Terminology for Cardiac Computed Tomography 2023 Update: An Expert Consensus Document of the Society of Cardiovascular Computed Tomography (SCCT), American Association of Physicists in Medicine (AAPM), American College of Radiology (ACR), North American Society for Cardiovascular Imaging (NASCI), and Radiological Society of North America (RSNA) with endorsement by the Asian Society of Cardiovascular Imaging (ASCI), the European Association of Cardiovascular Imaging (EACI), and the European Society of Cardiovascular Radiology (ESCR)

Since the emergence of cardiac computed tomography (Cardiac CT) at the turn of the 21st century, there has been an exponential growth in research and clinical development of the technique, with contributions from investigators and clinicians from varied backgrounds: physics and engineering, informatics, cardiology, and radiology. However, terminology for the field is not unified. As a consequence, there are multiple abbreviations for some terms, multiple terms for some concepts, and some concepts that lack clear definitions and/or usage. In an effort to aid the work of all those who seek to contribute to the literature, clinical practice, and investigation of the field, the Society of Cardiovascular Computed Tomography updates a standard set of medical terms commonly used in clinical and research activities related to cardiac CT. Keywords: Cardiac, CT, Medical Terminology Supplemental material is available for this article. This article is published synchronously in Radiology: Cardiothoracic Imaging and Journal of Cardiovascular Computed Tomography. ©2023 Society of Cardiovascular Computed Tomography. Published by RSNA with permission.

Decline in typical angina among patients referred for cardiac stress testing

OBJECTIVE

To evaluate temporal trends in the prevalence of typical angina and its clinical correlates among patients referred for stress/rest SPECT myocardial perfusion imaging (MPI).

PATIENTS AND METHODS

We evaluated the prevalence of chest pain symptoms and their relationship to inducible myocardial ischemia among 61,717 patients undergoing stress/rest SPECT-MPI between January 2, 1991 and December 31, 2017. We also assessed the relationship between chest pain symptom and angiographic findings among 6,579 patients undergoing coronary CT angiography between 2011 and 2017.

RESULTS

The prevalence of typical angina among SPECT-MPI patients declined from 16.2% between 1991 and 1997 to 3.1% between 2011 and 2017, while the prevalence of dyspnea without any chest pain increased from 5.9 to 14.5% over the same period. The frequency of inducible myocardial ischemia declined over time within all symptom groups, but its frequency among current patients (2011-2017) with typical angina was approximately three-fold higher versus other symptom groups (28.4% versus 8.6%, p < 0.001). Overall, patients with typical angina had a higher prevalence of obstructive CAD on CCTA than those with other clinical symptoms, but 33.3% of typical angina patients had no coronary stenoses, 31.1% had 1-49% stenoses, and 35.4% had ≥ 50% stenoses.

CONCLUSIONS

The prevalence of typical angina has declined to a very low level among contemporary patients referred for noninvasive cardiac tests. The angiographic findings among current typical angina patients are now quite heterogeneous, with one-third of such patients having normal coronary angiograms. However, typical angina remains associated with a substantially higher frequency of inducible myocardial ischemia compared to patients with other cardiac symptoms.

Coronary Volume to Left Ventricular Mass Ratio in Patients With Hypertension

The coronary vascular volume to left ventricular mass (V/M) ratio assessed by coronary computed tomography angiography (CCTA) is a promising new parameter to investigate the relation of coronary vasculature to the myocardium supplied. It is hypothesized that hypertension decreases the ratio between coronary volume and myocardial mass by way of myocardial hypertrophy, which could explain the detected abnormal myocardial perfusion reserve reported in patients with hypertension. Individuals enrolled in the multicenter ADVANCE (Assessing Diagnostic Value of Noninvasive FFRCT in Coronary Care) registry who underwent clinically indicated CCTA for analysis of suspected coronary artery disease with known hypertension status were included in current analysis. The V/M ratio was calculated from CCTA by segmenting the coronary artery luminal volume and left ventricular myocardial mass. In total, 2,378 subjects were included in this study, of whom 1,346 (56%) had hypertension. Left ventricular myocardial mass and coronary volume were higher in subjects with hypertension than normotensive patients (122.7 ± 32.8 g vs 120.0 ± 30.5 g, p = 0.039, and 3,105.0 ± 992.0 mm3 vs 2,965.6 ± 943.7 mm3, p <0.001, respectively). Subsequently, the V/M ratio was higher in patients with hypertension than those without (26.0 ± 7.6 mm3/g vs 25.3 ± 7.3 mm3/g, p = 0.024). After correcting for potential confounding factors, the coronary volume and ventricular mass remained higher in patients with hypertension (least square) mean difference estimate: 196.3 (95% confidence intervals [CI] 119.9 to 272.7) mm3, p <0.001, and 5.60 (95% CI 3.42 to 7.78) g, p <0.001, respectively), but the V/M ratio was not significantly different (least square mean difference estimate: 0.48 (95% CI -0.12 to 1.08) mm3/g, p = 0.116). In conclusion, our findings do not support the hypothesis that the abnormal perfusion reserve would be caused by reduced V/M ratio in patients with hypertension.

Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging

PURPOSE

Patients with known coronary artery disease (CAD) comprise a heterogenous population with varied clinical and imaging characteristics. Unsupervised machine learning can identify new risk phenotypes in an unbiased fashion. We use cluster analysis to risk-stratify patients with known CAD undergoing single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI).

METHODS

From 37,298 patients in the REFINE SPECT registry, we identified 9221 patients with known coronary artery disease. Unsupervised machine learning was performed using clinical (23), acquisition (17), and image analysis (24) parameters from 4774 patients (internal cohort) and validated with 4447 patients (external cohort). Risk stratification for all-cause mortality was compared to stress total perfusion deficit (< 5%, 5-10%, ≥10%).

RESULTS

Three clusters were identified, with patients in Cluster 3 having a higher body mass index, more diabetes mellitus and hypertension, and less likely to be male, have dyslipidemia, or undergo exercise stress imaging (p < 0.001 for all). In the external cohort, during median follow-up of 2.6 [0.14, 3.3] years, all-cause mortality occurred in 312 patients (7%). Cluster analysis provided better risk stratification for all-cause mortality (Cluster 3: hazard ratio (HR) 5.9, 95% confidence interval (CI) 4.0, 8.6, p < 0.001; Cluster 2: HR 3.3, 95% CI 2.5, 4.5, p < 0.001; Cluster 1, reference) compared to stress total perfusion deficit (≥10%: HR 1.9, 95% CI 1.5, 2.5 p < 0.001; < 5%: reference).

CONCLUSIONS

Our unsupervised cluster analysis in patients with known CAD undergoing SPECT MPI identified three distinct phenotypic clusters and predicted all-cause mortality better than ischemia alone.

Latent Coronary Plaque Morphology From Computed Tomography Angiography, Molecular Disease Activity on Positron Emission Tomography, and Clinical Outcomes

BACKGROUND

Assessments of coronary disease activity with 18F-sodium fluoride positron emission tomography and radiomics-based precision coronary plaque phenotyping derived from coronary computed tomography angiography may enhance risk stratification in patients with coronary artery disease. We sought to investigate whether the prognostic information provided by these 2 approaches is complementary in the prediction of myocardial infarction.

METHODS

Patients with known coronary artery disease underwent coronary 18F-sodium fluoride positron emission tomography and coronary computed tomography angiography on a hybrid positron emission tomography/computed tomography scanner. Coronary 18F-NaF uptake was determined by the coronary microcalcification activity. We performed quantitative plaque analysis of coronary computed tomography angiography datasets and extracted 1103 radiomic features for each plaque. Using weighted correlation network analysis, we derived latent morphological features of coronary lesions which were aggregated to patient-level radiomics nomograms to predict myocardial infarction.

RESULTS

Among 260 patients with established coronary artery disease (age, 65±9 years; 83% men), 179 (69%) participants showed increased coronary 18F-NaF activity (coronary microcalcification activity>0). Over 53 (40-59) months of follow-up, 18 patients had a myocardial infarction. Using weighted correlation network analysis, we derived 15 distinct eigen radiomic features representing latent morphological coronary plaque patterns in an unsupervised fashion. Following adjustments for calcified, noncalcified, and low-density noncalcified plaque volumes and 18F-NaF coronary microcalcification activity, 4 radiomic features remained independent predictors of myocardial infarction (hazard ratio, 1.46 [95% CI, 1.03-2.08]; P=0.03; hazard ratio, 1.62 [95% CI, 1.04-2.54]; P=0.02; hazard ratio, 1.49 [95% CI, 1.07-2.06]; P=0.01; and hazard ratio, 1.50 (95% CI, 1.05-2.13); P=0.02).

CONCLUSIONS

In patients with established coronary artery disease, latent coronary plaque morphological features, quantitative plaque volumes, and disease activity on 18F-sodium fluoride positron emission tomography are additive predictors of myocardial infarction.

Autoimmune rheumatic diseases in women with coronary microvascular dysfunction: a report from the Women's Ischemia Syndrome Evaluation-Coronary Vascular Dysfunction (WISE-CVD) project

Background

While autoimmune rheumatic diseases (ARDs) have been linked with coronary microvascular dysfunction (CMD), the relationship between ARD and CMD in women with signs and symptoms of ischemia and no obstructive arteries (INOCA) are not well described. We hypothesized that among women with CMD, those with ARD history have greater angina, functional limitations, and myocardial perfusion compromise compared to those without ARD history.

Methods

Women with INOCA and confirmed CMD by invasive coronary function testing were included from the Women's Ischemia Syndrome Evaluation-Coronary Vascular Dysfunction (WISE-CVD) project (NCT00832702). Seattle Angina Questionnaire (SAQ), Duke Activity Status Index (DASI), and cardiac magnetic resonance myocardial perfusion reserve index (MPRI) were collected at baseline. Chart review was performed to confirm self-reported ARD diagnosis.

Results

Of the 207 women with CMD, 19 (9%) had a confirmed history of ARD. Compared to those without ARD, women with ARD were younger (p = 0.04). In addition, they had lower DASI-estimated metabolic equivalents (p = 0.03) and lower MPRI (p = 0.008) but similar SAQ scores. There was a trend towards increased nocturnal angina and stress-induced angina in those with ARD (p = 0.05 for both). Invasive coronary function variables were not significantly different between groups.

Conclusions

Among women with CMD, women with a history of ARD had lower functional status and worse myocardial perfusion reserve compared to women without ARD. Angina-related health status and invasive coronary function were not significantly different between groups. Further studies are warranted to understand mechanisms contributing to CMD among women with ARDs with INOCA.

Influence of Obesity on Coronary Artery Disease and Clinical Outcomes in the ADVANCE Registry

BACKGROUND

The relationship between body size and cardiovascular events is complex. This study utilized the ADVANCE (Assessing Diagnostic Value of Noninvasive FFR_CT in Coronary Care) Registry to investigate the association between body mass index (BMI), coronary artery disease (CAD), and clinical outcomes.

METHODS

The ADVANCE registry enrolled patients undergoing evaluation for clinically suspected CAD who had >30% stenosis on cardiac computed tomography angiography. Patients were stratified by BMI: normal <25 kg/m², overweight 25-29.9 kg/m², and obese ≥30 kg/m². Baseline characteristics, cardiac computed tomography angiography and computed tomography fractional flow reserve (FFR_CT), were compared across BMI groups. Adjusted Cox proportional hazards models assessed the association between BMI and outcomes.

RESULTS

Among 5014 patients, 2166 (43.2%) had a normal BMI, 1883 (37.6%) were overweight, and 965 (19.2%) were obese. Patients with obesity were younger and more likely to have comorbidities, including diabetes and hypertension (all P<0.001), but were less likely to have obstructive coronary stenosis (65.2% obese, 72.2% overweight, and 73.2% normal BMI; P<0.001). However, the rate of hemodynamic significance, as indicated by a positive FFR_CT, was similar across BMI categories (63.4% obese, 66.1% overweight, and 67.8% normal BMI; P=0.07). Additionally, patients with obesity had a lower coronary volume-to-myocardial mass ratio compared with patients who were overweight or had normal BMI (obese BMI, 23.7; overweight BMI, 24.8; and normal BMI, 26.3; P<0.001). After adjustment, the risk of major adverse cardiovascular events was similar regardless of BMI (all P>0.05).

CONCLUSIONS

Patients with obesity in the ADVANCE registry were less likely to have anatomically obstructive CAD by cardiac computed tomography angiography but had a similar degree of physiologically significant CAD by FFR_CT and similar rates of adverse events. An exclusively anatomic assessment of CAD in patients with obesity may underestimate the burden of physiologically significant disease that is potentially due to a significantly lower volume-to-myocardial mass ratio.

Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging

Standard clinical interpretation of myocardial perfusion imaging (MPI) has proven prognostic value for predicting major adverse cardiovascular events (MACE). However, personalizing predictions to a specific event type and time interval is more challenging. We demonstrate an explainable deep learning model that predicts the time-specific risk separately for all-cause death, acute coronary syndrome (ACS), and revascularization directly from MPI and 15 clinical features. We train and test the model internally using 10-fold hold-out cross-validation (n = 20,418) and externally validate it in three separate sites (n = 13,988) with MACE follow-ups for a median of 3.1 years (interquartile range [IQR]: 1.6, 3.6). We evaluate the model using the cumulative dynamic area under receiver operating curve (cAUC). The best model performance in the external cohort is observed for short-term prediction - in the first six months after the scan, mean cAUC for ACS and all-cause death reaches 0.76 (95% confidence interval [CI]: 0.75, 0.77) and 0.78 (95% CI: 0.78, 0.79), respectively. The model outperforms conventional perfusion abnormality measures at all time points for the prediction of death in both internal and external validations, with improvement increasing gradually over time. Individualized patient explanations are visualized using waterfall plots, which highlight the contribution degree and direction for each feature. This approach allows the derivation of individual event probability as a function of time as well as patient- and event-specific risk explanations that may help draw attention to modifiable risk factors. Such a method could help present post-scan risk assessments to the patient and foster shared decision-making.

Left ventricular morphologic progression in apical hypertrophic cardiomyopathy

BACKGROUND

Left ventricular (LV) morphologic progression in apical hypertrophic cardiomyopathy (AHC) has not been well studied. We evaluated serial echocardiographic changes in LV morphology.

METHODS

Serial echocardiograms in AHC patients were assessed. LV morphology was categorized according to the presence of an apical pouch or aneurysm, and LV hypertrophic severity and extent; relative, pure, and apical-mid type defined as mild (<15 mm thickness) apical hypertrophy, significant (≥15 mm) apical hypertrophy, and both apical and midventricular hypertrophy, respectively. Adverse clinical events and late gadolinium enhancement (LGE) extent on cardiac magnetic resonance were evaluated for each morphologic type.

RESULTS

In 41 patients, 165 echocardiograms (maximal interval: 4.2 [IQR, 2.3-11.8] years) were evaluated. Morphologic changes were observed in 19 (46%) patients. Eleven (27%) patients displayed the progression of LV hypertrophy toward pure or apical-mid type. Five (12%) and 6 (15%) patients developed new pouches and aneurysms. Patients with progression tended to be younger (50 ± 15.6 vs 59 ± 14.4 years, P = 0.058) and had a longer period of follow-up (12 [5-14] vs 3 [2-4] years, P < 0.001). During a follow-up of 7.6 (IQR 3.0-12.1) years, 21 (51%) experienced clinical events. The relative, pure, and apical-mid types showed different LGE extents (2%, 6%, and 19%, P = 0.004). Patients with severe hypertrophic and apical involvement showed higher clinical event rates.

CONCLUSIONS

About half of AHC patients had a progression of LV morphology to more hypertrophic involvement and/or an apical pouch or aneurysm formation. Advanced AHC morphologic types were associated with higher event rates and scar burdens.

Deep Learning Coronary Artery Calcium Scores from SPECT/CT Attenuation Maps Improve Prediction of Major Adverse Cardiac Events

Low-dose ungated CT attenuation correction (CTAC) scans are commonly obtained with SPECT/CT myocardial perfusion imaging. Despite the characteristically low image quality of CTAC, deep learning (DL) can potentially quantify coronary artery calcium (CAC) from these scans in an automatic manner. We evaluated CAC quantification derived with a DL model, including correlation with expert annotations and associations with major adverse cardiovascular events (MACE). Methods: We trained a convolutional long short-term memory DL model to automatically quantify CAC on CTAC scans using 6,608 studies (2 centers) and evaluated the model in an external cohort of patients without known coronary artery disease (n = 2,271) obtained in a separate center. We assessed agreement between DL and expert annotated CAC scores. We also assessed associations between MACE (death, revascularization, myocardial infarction, or unstable angina) and CAC categories (0, 1-100, 101-400, or >400) for scores manually derived by experienced readers and scores obtained fully automatically by DL using multivariable Cox models (adjusted for age, sex, past medical history, perfusion, and ejection fraction) and net reclassification index. Results: In the external testing population, DL CAC was 0 in 908 patients (40.0%), 1-100 in 596 (26.2%), 100-400 in 354 (15.6%), and >400 in 413 (18.2%). Agreement in CAC category by DL CAC and expert annotation was excellent (linear weighted κ, 0.80), but DL CAC was obtained automatically in less than 2 s compared with about 2.5 min for expert CAC. DL CAC category was an independent risk factor for MACE with hazard ratios in comparison to a CAC of zero: CAC of 1-100 (2.20; 95% CI, 1.54-3.14; P < 0.001), CAC of 101-400 (4.58; 95% CI, 3.23-6.48; P < 0.001), and CAC of more than 400 (5.92; 95% CI, 4.27-8.22; P < 0.001). Overall, the net reclassification index was 0.494 for DL CAC, which was similar to expert annotated CAC (0.503). Conclusion: DL CAC from SPECT/CT attenuation maps agrees well with expert CAC annotations and provides a similar risk stratification but can be obtained automatically. DL CAC scores improved classification of a significant proportion of patients as compared with SPECT myocardial perfusion alone.

Does Coronary Plaque Morphology Matter Beyond Plaque Burden?

PURPOSE OF REVIEW

Imaging of adverse coronary plaque features by coronary computed tomography angiography (CCTA) has advanced greatly and at a fast pace. We aim to describe the evolution, present and future in plaque analysis, and its value in comparison to plaque burden.

RECENT FINDINGS

Recently, it has been demonstrated that in addition to plaque burden, quantitative and qualitative assessment of coronary plaque by CCTA can improve the prediction of future major adverse cardiovascular events in diverse coronary artery disease scenarios. The detection of high-risk non-obstructive coronary plaque can lead to higher use of preventive medical therapies such as statins and aspirin, help identify culprit plaque, and differentiate between myocardial infarction types. Even more, over traditional plaque burden, plaque analysis including pericoronary inflammation can potentially be useful tools for tracking disease progression and response to medical therapy. The identification of the higher risk phenotypes with plaque burden, plaque characteristics, or ideally both can allow the allocation of targeted therapies and potentially monitor response. Further observational data are now required to investigate these key issues in diverse populations, followed by rigorous randomized controlled trials.

Coronary Artery Calcium Dispersion and Cause-Specific Mortality

Coronary artery calcium (CAC) measures subclinical atherosclerosis and improves risk stratification. CAC characteristics-including vessel(s) involved, number of vessels, volume, and density-have been shown to differentially impact risk. We assessed how dispersion-either the number of calcified vessels or CAC phenotype (diffuse, normal, and concentrated)-impacted cause-specific mortality. The CAC Consortium is a retrospective cohort of 66,636 participants without coronary heart disease (CHD) who underwent CAC scoring. This study included patients with CAC >0 (n = 28,147). CAC area, CAC density, and CAC phenotypes (derived from the index of diffusion = 1 - [CAC in most concentrated vessel/total Agatston score]) were calculated. The associations between CAC characteristics and cause-specific mortality were assessed. The participant details included (n = 28,147): mean age 58.3 years, 25% female, 89.6% White, and 66% had 2+ calcified vessels. Diabetes, hypertension, and hyperlipidemia were predictors of multivessel involvement (p <0.001). After controlling for the overall CAC score, those with 4-vessel CAC involvement had more CAC area and less dense calcifications than those with 1-vessel. There was a graded increase in all-cause and cardiovascular disease (CVD)- and CHD-specific mortality as the number of calcified vessels increased. Among those with ≥2 vessels involved (n = 18,516), a diffuse phenotype was associated with a higher CVD-specific mortality and had a trend toward higher all-cause and CHD-specific mortality than a concentrated CAC phenotype. Diffuse CAC involvement was characterized by less dense calcification, more CAC area, multiple coronary vessel involvement, and presence of certain traditional risk factors. There is a graded increase in all-cause and CVD- and CHD-specific mortality with increasing CAC dispersion.

Deep Learning-Based Attenuation Correction Improves Diagnostic Accuracy of Cardiac SPECT

To improve diagnostic accuracy, myocardial perfusion imaging (MPI) SPECT studies can use CT-based attenuation correction (AC). However, CT-based AC is not available for most SPECT systems in clinical use, increases radiation exposure, and is impacted by misregistration. We developed and externally validated a deep-learning model to generate simulated AC images directly from non-AC (NC) SPECT, without the need for CT. Methods: SPECT myocardial perfusion imaging was performed using 99mTc-sestamibi or 99mTc-tetrofosmin on contemporary scanners with solid-state detectors. We developed a conditional generative adversarial neural network that applies a deep learning model (DeepAC) to generate simulated AC SPECT images. The model was trained with short-axis NC and AC images performed at 1 site (n = 4,886) and was tested on patients from 2 separate external sites (n = 604). We assessed the diagnostic accuracy of the stress total perfusion deficit (TPD) obtained from NC, AC, and DeepAC images for obstructive coronary artery disease (CAD) with area under the receiver-operating-characteristic curve. We also quantified the direct count change among AC, NC, and DeepAC images on a per-voxel basis. Results: DeepAC could be obtained in less than 1 s from NC images; area under the receiver-operating-characteristic curve for obstructive CAD was higher for DeepAC TPD (0.79; 95% CI, 0.72-0.85) than for NC TPD (0.70; 95% CI, 0.63-0.78; P < 0.001) and similar to AC TPD (0.81; 95% CI, 0.75-0.87; P = 0.196). The normalcy rate in the low-likelihood-of-coronary-disease population was higher for DeepAC TPD (70.4%) and AC TPD (75.0%) than for NC TPD (54.6%, P < 0.001 for both). The positive count change (increase in counts) was significantly higher for AC versus NC (median, 9.4; interquartile range, 6.0-14.2; P < 0.001) than for AC versus DeepAC (median, 2.4; interquartile range, 1.3-4.2). Conclusion: In an independent external dataset, DeepAC provided improved diagnostic accuracy for obstructive CAD, as compared with NC images, and this accuracy was similar to that of actual AC. DeepAC simplifies the task of artifact identification for physicians, avoids misregistration artifacts, and can be performed rapidly without the need for CT hardware and additional acquisitions.

Sex differences in computed tomography angiography-derived coronary plaque burden in relation to invasive fractional flow reserve

BACKGROUND

Distinct sex-related differences exist in coronary artery plaque burden and distribution. We aimed to explore sex differences in quantitative plaque burden by coronary CT angiography (CCTA) in relation to ischemia by invasive fractional flow reserve (FFR).

METHODS

This post-hoc analysis of the PACIFIC trial included 581 vessels in 203 patients (mean age 58.1 ​± ​8.7 years, 63.5% male) who underwent CCTA and per-vessel invasive FFR. Quantitative assessment of total, calcified, non-calcified, and low-density non-calcified plaque burden were performed using semiautomated software. Significant ischemia was defined as invasive FFR ≤0.8.

RESULTS

The per-vessel frequency of ischemia was higher in men than women (33.5% vs. 7.5%, p ​< ​0.001). Women had a smaller burden of all plaque subtypes (all p ​< ​0.01). There was no sex difference on total, calcified, or non-calcified plaque burdens in vessels with ischemia; only low-density non-calcified plaque burden was significantly lower in women (beta: -0.183, p ​= ​0.035). The burdens of all plaque subtypes were independently associated with ischemia in both men and women (For total plaque burden (5% increase): Men, OR: 1.15, 95%CI: 1.06-1.24, p ​= ​0.001; Women, OR: 1.96, 95%CI: 1.11-3.46, p ​= ​0.02). No significant interaction existed between sex and total plaque burden for predicting ischemia (interaction p ​= ​0.108). The addition of quantitative plaque burdens to stenosis severity and adverse plaque characteristics improved the discrimination of ischemia in both men and women.

CONCLUSIONS

In symptomatic patients with suspected CAD, women have a lower CCTA-derived burden of all plaque subtypes compared to men. Quantitative plaque burden provides independent and incremental predictive value for ischemia, irrespective of sex.