Myocardial Blood Flow Reserve, Microvascular Coronary Health, and Myocardial Remodeling in Patients With Aortic Stenosis.

BACKGROUND: Coronary microvascular function and hemodynamics may play a role in coronary circulation and myocardial remodeling in patients with aortic stenosis (AS). We aimed to evaluate the relationship between myocardial blood flow and myocardial function in patients with AS, no AS, and aortic valve sclerosis. METHODS AND RESULTS: We included consecutive patients who had resting transthoracic echocardiography and clinically indicated positron emission tomography myocardial perfusion imaging to capture their left ventricular ejection fraction, global longitudinal strain (GLS), and myocardial flow reserve (MFR). The primary outcome was major adverse cardiovascular event (all-cause mortality, myocardial infarction, or late revascularization). There were 2778 patients (208 with aortic sclerosis, 39 with prosthetic aortic valve, 2406 with no AS, and 54, 49, and 22 with mild, moderate, and severe AS, respectively). Increasing AS severity was associated with impaired MFR (P<0.001) and GLS (P<0.001), even when perfusion was normal. Statistically significant associations were noted between MFR and GLS, MFR and left ventricular ejection fraction, and MFR and left ventricular ejection fraction reserve. After a median follow-up of 349 (interquartile range, 116-662) days, 4 (7.4%), 5 (10.2%), and 6 (27.3%) patients experienced a major adverse cardiovascular event in the mild, moderate, and severe AS groups, respectively. In a matched-control analysis, patients with mild-to-moderate AS had higher rates of impaired MFR (52.9% versus 39.9%; P=0.048) and major adverse cardiovascular event (11.8% versus 3.0%; P=0.002). CONCLUSIONS: Despite lack of ischemia, as severity of AS increased, MFR decreased and GLS worsened, reflecting worse coronary microvascular health and myocardial remodeling. Positron emission tomography-derived MFR showed a significant independent correlation with left ventricular ejection fraction and GLS. Patients with prosthetic aortic valve showed a high prevalence of impaired MFR.

Ejection fraction and ventricular volumes on rubidium positron emission tomography: Validation against cardiovascular magnetic resonance.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is the non-invasive gold standard for non-invasively determining left ventricular volumes (LVVs) and ejection fraction (EF). We aimed to assess the accuracy of LVV and left ventricular ejection fraction measured by positron emission tomography (PET) as compared to CMR. METHODS: Patients who underwent both PET and CMR within 1 year were identified from prospective institutional registries. Analysis was performed to evaluate the agreement between the raw and body-surface-area-normalized left ventricular volume (LVV) and EF derived from PET vs. those derived from CMR. RESULTS: The study population consisted of 669 patients (mean age 62 ± 13 years, 65% male). The median (interquartile range [IQR]) duration between CMR and PET imaging was 36 (7-118) days. The median (IQR) EF values were 52% (38-63%) on CMR and 53% (37-65%) on PET (mean difference: 0.53% ± 9.1, P = 0.129) with a strong correlation (Spearman rho = 0.84, P < 0.001; Intraclass Correlation Coefficient 0.84, 95% confidence interval [CI]: 0.82-0.86, P < 0.001; Lin's concordance correlation coefficient was 0.844, 95% CI: 0.822 to 0.865). Results were similar with LVV, normalized LVV/EF, and in subgroups of patients with reduced EF, coronary artery disease scar, and LV hypertrophy as well as in patients with defibrillators. However, PET tended to underestimate LVV compared to CMR. CONCLUSION: Our analysis showed a strong correlation of EF and LVV by PET against a reference standard of CMR, whereas PET significantly underestimated LVV, but not EF, compared to CMR.

Patient-level explainable machine learning to predict major adverse cardiovascular events from SPECT MPI and CCTA imaging.

BACKGROUND: Machine learning (ML) has shown promise in improving the risk prediction in non-invasive cardiovascular imaging, including SPECT MPI and coronary CT angiography. However, most algorithms used remain black boxes to clinicians in how they compute their predictions. Furthermore, objective consideration of the multitude of available clinical data, along with the visual and quantitative assessments from CCTA and SPECT, are critical for optimal patient risk stratification. We aim to provide an explainable ML approach to predict MACE using clinical, CCTA, and SPECT data. METHODS: Consecutive patients who underwent clinically indicated CCTA and SPECT myocardial imaging for suspected CAD were included and followed up for MACEs. A MACE was defined as a composite outcome that included all-cause mortality, myocardial infarction, or late revascularization. We employed an Automated Machine Learning (AutoML) approach to predict MACE using clinical, CCTA, and SPECT data. Various mainstream models with different sets of hyperparameters have been explored, and critical predictors of risk are obtained using explainable techniques on the global and patient levels. Ten-fold cross-validation was used in training and evaluating the AutoML model. RESULTS: A total of 956 patients were included (mean age 61.1 ±14.2 years, 54% men, 89% hypertension, 81% diabetes, 84% dyslipidemia). Obstructive CAD on CCTA and ischemia on SPECT were observed in 14% of patients, and 11% experienced MACE. ML prediction's sensitivity, specificity, and accuracy in predicting a MACE were 69.61%, 99.77%, and 96.54%, respectively. The top 10 global predictive features included 8 CCTA attributes (segment involvement score, number of vessels with severe plaque ≥70, ≥50% stenosis in the left marginal coronary artery, calcified plaque, ≥50% stenosis in the left circumflex coronary artery, plaque type in the left marginal coronary artery, stenosis degree in the second obtuse marginal of the left circumflex artery, and stenosis category in the marginals of the left circumflex artery) and 2 clinical features (past medical history of MI or left bundle branch block, being an ever smoker). CONCLUSION: ML can accurately predict risk of developing a MACE in patients suspected of CAD undergoing SPECT MPI and CCTA. ML feature-ranking can also show, at a sample- as well as at a patient-level, which features are key in making such a prediction.

Prognostic value of positron emission tomography derived myocardial flow reserve: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Positron Emission Tomography (PET)-derived myocardial flow reserve (MFR) has been shown to have a role in the diagnosis and prognosis of patients with coronary artery disease (CAD). We performed a systematic review and meta-analysis to summarize the body of literature and synthesize the evidence on the prognostic role of PET-derived MFR in patients with known or suspected CAD. METHODS: A comprehensive literature search of the Medline database from its inception to August 2023, in humans, in any language, was conducted for clinical studies examining the prognostic value of PET imaging in patients of any age, sex, and CAD status. Systematic screening and data extraction of the identified studies were followed by quantitative meta-analysis of PET-MFR's role in predicting adverse clinical events using random effect model. Studies were appraised using the modified Newcastle-Ottawa tool. RESULTS: A total of 21 studies assessing the prognostic role of PET derived MFR in 46,815 patients with known and/or suspected CAD were included (mean (SD) age 66 (4) years, 48% women). The mean follow-up duration was 36 months (range 10-96). Cardiovascular risk factors were prevalent (73% hypertension, 35% diabetes and 67% dyslipidemia). The definition of the composite outcome varied between studies, with various combinations of mortality, non-fatal myocardial infarction, hospitalization, and coronary revascularization. Pooled impaired MFR was significantly associated with an increased risk of adverse outcomes (RR = 2.94, 95% CI 2.42-3.56, p < 0.001). Results were similar in a subgroup of patients with suspected CAD. CONCLUSIONS: The available body of evidence shows that impaired PET-derived MFR measured using different tracers and PET systems is strongly associated with an increased risk of adverse cardiovascular events. Limitations of this review include observational nature of studies, marked heterogeneity in patient populations, inconsistency in thresholds to define abnormal MFR, and differing components for the composite outcome.

Coronary microvascular health in symptomatic patients with prior COVID-19 infection: an updated analysis.

AIMS: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with endothelial dysfunction. We aimed to determine the effects of prior coronavirus disease 2019 (COVID-19) on the coronary microvasculature accounting for time from COVID-19, disease severity, SARS-CoV-2 variants, and in subgroups of patients with diabetes and those with no known coronary artery disease. METHODS AND RESULTS: Cases consisted of patients with previous COVID-19 who had clinically indicated positron emission tomography (PET) imaging and were matched 1:3 on clinical and cardiovascular risk factors to controls having no prior infection. Myocardial flow reserve (MFR) was calculated as the ratio of stress to rest myocardial blood flow (MBF) in mL/min/g of the left ventricle. Comparisons between cases and controls were made for the odds and prevalence of impaired MFR (MFR < 2). We included 271 cases matched to 815 controls (mean ± SD age 65 ± 12 years, 52% men). The median (inter-quartile range) number of days between COVID-19 infection and PET imaging was 174 (58-338) days. Patients with prior COVID-19 had a statistically significant higher odds of MFR <2 (adjusted odds ratio 3.1, 95% confidence interval 2.8-4.25 P < 0.001). Results were similar in clinically meaningful subgroups. The proportion of cases with MFR <2 peaked 6-9 months from imaging with a statistically non-significant downtrend afterwards and was comparable across SARS-CoV-2 variants but increased with increasing severity of infection. CONCLUSION: The prevalence of impaired MFR is similar by duration of time from infection up to 1 year and SARS-CoV-2 variants, but significantly differs by severity of infection.

Splenic switch-off in regadenoson 82Rb-PET myocardial perfusion imaging: assessment of clinical utility.

BACKGROUND: Splenic switch-off (SSO) is a phenomenon describing a decrease in splenic radiotracer uptake after vasodilatory stress. We aimed to assess the diagnostic utility of regadenoson-induced SSO. METHODS: We included consecutive patients who had clinically indicated Regadenoson Rb-82 PET-MPI for suspected CAD. This derivation cohort (no perfusion defects and myocardial flow reserves (MFR) ≥ 2) was used to calculate the splenic response ratio (SRR). The validation cohort was defined as patients who underwent both PET-MPI studies and invasive coronary angiography (ICA). RESULTS: The derivation cohort (n = 100, 57.4 ± 11.6 years, 77% female) showed a decrease in splenic uptake from rest to stress (79.9 ± 16.8 kBq⋅mL vs 69.1 ± 16.2 kBq⋅mL, P < .001). From the validation cohort (n = 315, 66.3 ± 10.4 years, 67% male), 28% (via SRR = 0.88) and 15% (visually) were classified as splenic non-responders. MFR was lower in non-responders (SRR; 1.55 ± 0.65 vs 1.76 ± 0.78, P = .02 and visually; 1.18 ± 0.33 vs 1.79 ± 0.77, P < .001). Based on ICA, non-responders were more likely to note obstructive epicardial disease with normal PET scans especially in patients with MFR < 1.5 (SRR; 61% vs 34% P = .05 and visually; 68% vs 33%, P = .01). CONCLUSION: Lack of splenic response based on visual or quantitative assessment of SSO may be used to identify an inadequate vasodilatory response.

Incremental prognostic value of positron emission tomography derived left ventricular mass.

BACKGROUND: Left ventricular hypertrophy has been shown to be an independent predictor of outcomes in patients with coronary artery disease (CAD). We aimed to determine the incremental prognostic value of positron emission tomography (PET) derived left ventricular mass (LVM) to clinical variables and myocardial flow reserve (MFR). METHODS: We included consecutive patients who had clinically indicated PET myocardial perfusion imaging for suspected or established CAD. Patients were followed from the date of PET imaging for major adverse cardiovascular events (MACE, inclusive of all-cause death, non-fatal myocardial infarction, and percutaneous coronary intervention/coronary artery bypass grafting 90 days after imaging). RESULTS: A total of 2357 patients underwent PET MPI during the study period (47% female, mean age 66 ± 12 years, 87% hypertensive, 47% diabetic, 79% dyslipidemia). After a mean follow-up of 11.6 ± 6.6 months, 141 patients (6.0%, 5.1 per 1000 person-year) experienced MACE (86 D/24 MI/39 PCI/9 CABG). In nested multivariable Cox models, LVM was not independently associated with outcomes (HR 1.00, P = .157) and had no incremental prognostic value (C index: 0.75, P = .571) over MFR and clinical variables. CONCLUSION: Our analysis shows that LVM provides no independent and incremental prognostic value over MFR and clinical variables.

The utility of beta-hydroxybutyrate in detecting myocardial glucose uptake suppression in patients undergoing inflammatory [18F]-FDG PET studies.

PURPOSE: We evaluated whether serum beta-hydroxybutyrate (BHB) can identify adequate suppression of the left ventricle (LV) among patients undergoing [18F]-fluorodeoxyglucose positron emission tomography ([18F]-FDG PET) for cardiac inflammatory/infectious studies. METHODS: Consecutive patients who underwent [18F]-FDG PET imaging were included. Serum BHB levels were measured in all patients on the day of imaging prior to injecting [18F]-FDG. Myocardial [18F]-FDG suppression was defined if [18F]-FDG uptake in the walls of myocardium, measured using standardized uptake values (SUV), was lower than the blood pool. The optimal threshold of BHB to identify myocardial suppression was based on receiver operating characteristics (ROC) in a random 30% sample of the study population (derivation cohort) and tested in the remaining 70% of sample (validation cohort). RESULTS: A total of 256 images from 220 patients were included. Patients with sufficient LV suppression had significantly higher BHB levels compared to those with non-suppressed myocardium (median (IQR) BHB 0.6 (0.3-0.8) vs. 0.2 (0.2-0.3) mmol/l, p < 0.001, respectively). BHB level ≥ 0.335 mmol/l had a sensitivity of 84.90% and a specificity of 92.60% to identify adequate LV suppression in the validation cohort. All patients (100%) with BHB ≥ 0.41 mmol/l had adequate myocardial suppression compared to 29.63% of patients with BHB ≤ 0.20 mmol/l. CONCLUSION: Serum BHB level can be used at the point of care to identify sufficient LV suppression in patients undergoing [18F]-FDG PET cardiac inflammatory/infectious studies. Central illustration (image to the right) shows representative cases of patient images and BHB and, in the image to the left, shows the sensitivity and specificity to identify left myocardial suppression using BHB in validation group.

Incremental prognostic value of digital positron emission tomography derived myocardial flow reserve: A prospective cohort study.

BACKGROUND: Positron Emission Tomography (PET) Myocardial Perfusion Imaging (MPI) is a robust diagnostic and prognostic test in patients with suspected or known coronary artery disease (CAD). We aimed to assess the incremental prognostic value of myocardial flow reserve (MFR) using the latest generation of digital PET scanners. METHODS: Consecutive patients with clinically indicated PET MPI for suspected or known CAD were included. Myocardial blood flow (MBF) in ml/min/g was obtained from dynamic images at rest and peak hyperemia, and the myocardial flow reserve (MFR) was calculated as the ratio of stress to rest MBF. Patients were followed from the date of PET imaging for the occurrence of the primary outcome (composite of all-cause death, myocardial infarction, and Percutaneous Coronary Intervention or Coronary Artery Bypass Graft occurring >90 days after imaging). Nested multivariable Cox regression models were used to assess the incremental prognostic role of MFR over traditional risk factors and PET relative perfusion parameters. RESULTS: The final cohort consisted of 3534 patients (mean age 67 ± 12 years, 48% female, 67% Caucasian, 53% obese, 55% hypertension, 32% diabetes, 42% dyslipidemia). During a median follow-up of 8.5 (3.0-15.4) months, 229 patients (6.5%, 6.4 per 1000 person-years) experienced the primary outcome. In nested multivariable Cox models, impaired MFR (MFR < 2) was significantly associated with the primary outcome (HR 2.9, 95% CI 2.0-4.1, p < 0.001) and significantly improved discrimination (Harrell's C 0.77, p = 0.002). CONCLUSION: MFR derived from digital PET scanners has an independent and incremental prognostic role in patients with suspected or known CAD.

Sex differences in machine learning computed tomography-derived fractional flow reserve.

Coronary computed tomography angiography (CCTA) derived machine learning fractional flow reserve (ML-FFRCT) can assess the hemodynamic significance of coronary artery stenoses. We aimed to assess sex differences in the association of ML-FFRCT and incident cardiovascular outcomes. We studied a retrospective cohort of consecutive patients who underwent clinically indicated CCTA and single photon emission computed tomography (SPECT). Obstructive stenosis was defined as ≥ 70% stenosis severity in non-left main vessels or ≥ 50% in the left main coronary. ML-FFRCT was computed using a machine learning algorithm with significant stenosis defined as ML-FFRCT < 0.8. The primary outcome was a composite of death or non-fatal myocardial infarction (D/MI). Our study population consisted of 471 patients with mean (SD) age 65 (13) years, 53% men, and multiple comorbidities (78% hypertension, 66% diabetes, 81% dyslipidemia). Compared to men, women were less likely to have obstructive stenosis by CCTA (9% vs. 18%; p = 0.006), less multivessel CAD (4% vs. 6%; p = 0.25), lower prevalence of ML-FFRCT < 0.8 (39% vs. 44%; p = 0.23) and higher median (IQR) ML-FFRCT (0.76 (0.53-0.86) vs. 0.71 (0.47-0.84); p = 0.047). In multivariable adjusted models, there was no significant association between ML-FFRCT < 0.8 and D/MI [Hazard Ratio 0.82, 95% confidence interval (0.30, 2.20); p = 0.25 for interaction with sex.]. In a high-risk cohort of symptomatic patients who underwent CCTA and SPECT testing, ML-FFRCT was higher in women than men. There was no significant association between ML-FFRCT and incident mortality or MI and no evidence that the prognostic value of ML-FFRCT differs by sex.

Prognostic Interplay Between Coronary Artery Calcium Scoring and Cardiorespiratory FItness: The CAC-FIT Study.

OBJECTIVE: To assess the incremental prognostic role of coronary artery calcium score (CACS) and exercise capacity (EC), two independent prognostic tests in the assessment of patients with coronary artery disease. METHODS: The cohort consisted of patients who had clinically indicated exercise stress testing and CACS assessment from January 1, 2015, to September 30, 2021, with a median of 27 days between each other. Exercise capacity was defined by peak metabolic equivalents of task (METs) achieved during exercise stress test. The CACS was determined by the Agatston method. Patients were observed from the latest test date to incident major adverse cardiac events (inclusive of all-cause death, nonfatal myocardial infarction, late revascularization, and admission for heart failure). RESULTS: There were a` total of 1932 patients in the study population (mean age, 56±12 years; 42% female, 48% hypertension, 21% diabetes, 48% dyslipidemia). Peak METs below 6 was achieved in 8% of patients, and the median (interquartile range) CACS was 9 (0-203). In multivariable Cox regression models, both CACS (1 unit increase in log CACS: hazard ratio, 1.19; 95% CI, 1.06 to 1.34; P=.003;) and EC (1 unit increase in peak METs: hazard ratio, 0.89; 95% CI, 0.81 to 0.97; P=.01) were independently associated with outcomes. Using CACS+EC added incremental prognostic value over clinical and fitness models (C index increase from 0.68 to 0.75; P=.015). Incident event rates increased across categories of CACS and EC. CONCLUSION: Our analysis found that CACS and EC have complementary risk-stratifying roles in coronary artery disease.

Incremental prognostic value of spect over CCTA.

BACKGROUND: Coronary computed tomographic angiography (CCTA) and Single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) provide comprehensive anatomic and functional assessment of the coronary arteries useful in the diagnosis and prognosis of patients with coronary artery disease (CAD). We aimed to assess the incremental prognostic role of SPECT physiologic assessment to CCTA in patients with suspected CAD. METHODS: Consecutive patients with suspected CAD undergoing clinically indicated CCTA within 180 days of undergoing SPECT were included. Patients were followed for major adverse cardiovascular events (MACE, inclusive of all-cause death, non-fatal myocardial infarction, and percutaneous coronary intervention or coronary artery bypass grafting 90-days after imaging test.) RESULTS: The cohort consisted of 956 patients (mean age 61.1 ± 14.2 years, 54% men, 89% hypertension, 81% diabetes, 84% dyslipidemia). Obstructive stenosis was found in 14% of patients, while scar (fixed perfusion defect), ischemia and left ventricular ejection fraction <40% were found in 17, 14 and 9% of patients, respectively. In nested multivariable cox regression models, perfusion and left ventricular function when added to a model with CCTA obstructive stenosis significantly improved model risk prediction (Harrell's C = 0.73, p = 0.037) and risk reclassification on a continuous scale (P < 0.001). CONCLUSION: We have shown that a combined assessment of perfusion burden and left ventricular function added incremental value over and above a CCTA based anatomic assessment in patients with suspected CAD.

It Takes a Village: Multimodality Imaging of Cardiac Amyloidosis.

Cardiac amyloidosis (CA) is the buildup and infiltration of amyloid plaque in cardiac muscle. An underdiagnosed form of restrictive cardiomyopathy, CA can rapidly progress into heart failure. CA is evaluated using a multimodality approach that includes echocardiography, cardiac magnetic imaging, and nuclear imaging. Echocardiography remains an essential first-line modality that raises suspicion for CA and establishes functional baselines. Cardiac magnetic imaging provides additional incremental value via high-resolution imaging, robust functional assessment, and superior tissue characterization, all of which enable a more comprehensive investigation of CA. Cardiac scintigraphy has eliminated the need for invasive diagnostic approaches and helps differentiate CA subtypes. Positron emission tomography is the first modality introducing targeted amyloid binding tracers that allow for precise burden quantification, early detection, and disease monitoring. In this review, we highlight the role of several cardiac imaging techniques in the evaluation of CA.

Change in positron emission tomography perfusion imaging quality with a data-driven motion correction algorithm.

INTRODUCTION: Cardiac motion frequently reduces the interpretability of PET images. This study utilized a prototype data-driven motion correction (DDMC) algorithm to generate corrected images and compare DDMC images with non-corrected images (NMC) to evaluate image quality and change of perfusion defect size and severity. METHODS: Rest and stress images with NMC and DDMC from 40 consecutive patients with motion were rated by 2 blinded investigators on a 4-point visual ordinal scale (0: minimal motion; 1: mild motion; 2: moderate motion; 3: severe motion/uninterpretable). Motion was also quantified using Dwell Fraction, which is the fraction of time the motion vector shows the heart to be within 6 mm of the corrected position and was derived from listmode data of NMC images. RESULTS: Minimal motion was seen in 15% of patients, while 40%, 30%, and 15% of patients had mild moderate and severe motion, respectively. All corrected images showed an improvement in quality and were interpretable after processing. This was confirmed by a significant correlation (Spearman's correlation coefficient 0.626, P < .001) between machine measurement of motion quantification and physician interpretation. CONCLUSION: The novel DDMC algorithm improved quality of cardiac PET images with motion. Correlation between machine measurement of motion quantification and physician interpretation was significant.

Cardiovascular magnetic resonance for suspected cardiac amyloidosis: where are we now?

Cardiac amyloidosis (CA) is an underdiagnosed form of restrictive cardiomyopathy leading to a rapid progression into heart failure. Evaluation of CA requires a multimodality approach making use of echocardiography, cardiac magnetic imaging (CMR), and nuclear imaging. With superior tissue characterization, high-resolution imaging, and precise cardiac assessment, CMR has emerged as a versatile tool in the workup of cardiac amyloidosis with a wide array of parameters both visual and quantitative. This includes late gadolinium enhancement patterns, T1/T2 mapping, and extracellular volume (ECV) measurement providing robust diagnostic accuracies, patient stratification, and prognostication. Recent advancements have introduced new measures able to identify early disease, track disease progression, and response to therapy positioning CMR as an instrumental imaging modality in the era of rising interest in CA screening and emerging effective therapies.

Interoperator reliability of an on-site machine learning-based prototype to estimate CT angiography-derived fractional flow reserve.

BACKGROUND: Advances in CT and machine learning have enabled on-site non-invasive assessment of fractional flow reserve (FFRCT). PURPOSE: To assess the interoperator and intraoperator variability of coronary CT angiography-derived FFRCT using a machine learning-based postprocessing prototype. MATERIALS AND METHODS: We included 60 symptomatic patients who underwent coronary CT angiography. FFRCT was calculated by two independent operators after training using a machine learning-based on-site prototype. FFRCT was measured 1 cm distal to the coronary plaque or in the middle of the segments if no coronary lesions were present. Intraclass correlation coefficient (ICC) and Bland-Altman analysis were used to evaluate interoperator variability effect in FFRCT estimates. Sensitivity analysis was done by cardiac risk factors, degree of stenosis and image quality. RESULTS: A total of 535 coronary segments in 60 patients were assessed. The overall ICC was 0.986 per patient (95% CI 0.977 to 0.992) and 0.972 per segment (95% CI 0.967 to 0.977). The absolute mean difference in FFRCT estimates was 0.012 per patient (95% CI for limits of agreement: -0.035 to 0.039) and 0.02 per segment (95% CI for limits of agreement: -0.077 to 0.080). Tight limits of agreement were seen on Bland-Altman analysis. Distal segments had greater variability compared with proximal/mid segments (absolute mean difference 0.011 vs 0.025, p<0.001). Results were similar on sensitivity analysis. CONCLUSION: A high degree of interoperator and intraoperator reproducibility can be achieved by on-site machine learning-based FFRCT assessment. Future research is required to evaluate the physiological relevance and prognostic value of FFRCT.

Association of Twitter Metrics and Cardiology and Heart Surgery National Hospital Rankings.

Since 1990, the U.S. News and World Report (USNWR) has been publishing rankings of US adult and children's hospitals. The aim of this study was to analyze the association between hospital Twitter metrics and the 2020 USNWR hospital cardiology and heart surgery ranking. We collected data on the cardiology and heart surgery overall ranking score and expert opinion. Twitter metrics were obtained on October 20, 2020, and included time on Twitter, number of followers, accounts being followed, total tweets, reach score (difference between followers and followed), and annual tweet rate (total tweets divided by time on Twitter). The final cohort consisted of 463 hospitals (48 of which were top-ranking hospitals). A significant positive relation was observed with Twitter metrics and hospital ranking. On multivariable regression after adjusting for time on Twitter, the overall score was independently associated with annual tweet rate and reach score (ß=12.45% and ß=0.34% for each 1,000 tweets per year and 10,000 reach score accounts; P<.001). Similarly, expert opinion was independently associated with annual tweet rate and reach score (ß=0.025% and ß=0.002% for each 1000 tweets per year and 10,000 reach score accounts; P<.001). Our results emphasize how hospital leaders may leverage social media platforms as an important medium to disseminate accomplishments and increase their visibility and reputation, potentially translating to higher USNWR ranking.

Added Prognostic Value of Plaque Burden to Computed Tomography Angiography and Myocardial Perfusion Imaging in Patients with Diabetes.

BACKGROUND: We aimed to compare the added prognostic value of plaque burden to cardiac computed tomographic angiography (CCTA) anatomic assessment and single-photon emission computed tomography (SPECT) physiologic assessment in patients with diabetes undergoing both tests. METHODS: Consecutive patients with diabetes who underwent clinically indicated CCTA and SPECT myocardial imaging for suspected coronary artery disease were included. Stenosis severity and segment involvement score (SIS) were determined from CCTA, and presence of ischemia was determined from SPECT. Patients were followed from date of imaging for major adverse cardiovascular events (MACE). RESULTS: A total of 778 patients were included (mean age 60.6 ± 14.4 years, 55% males). After a median follow-up of 31 months, 87 (11%) patients experienced a MACE. In multivariable Cox regression models, SIS significantly predicted outcomes in models including obstructive stenosis and ischemia (hazard ratio 1.17, 95% confidence interval 1.10-1.24, P < .001; hazard ratio 1.16, 95% confidence interval 1.10-1.23, P < .001, respectively), and improved discrimination (Harrel's C 0.75, P = .006; 0.76, P = .006 in models with CCTA obstructive stenosis and SPECT ischemia, respectively). Results were consistent using subgroups of summed scores by composition of plaque (calcified vs noncalcified) and alternate definitions of obstructive stenosis. CONCLUSION: Our results suggest that in high-risk patients with diabetes and suspected coronary disease, SIS has incremental prognostic value over ischemia by SPECT or stenosis by CCTA in predicting incident cardiovascular outcomes.