Pericardial fat volume is related to endothelial-mediated coronary blood flow in women with suspected coronary microvascular dysfunction. A report from the Women's Ischemia Syndrome Evaluation-Coronary Vascular Dysfunction (WISE-CVD) study.

Background: Coronary microvascular dysfunction is prevalent in women with signs and symptoms of ischemia but no obstructive coronary artery disease (CAD) and is associated with an adverse prognosis. Elevated pericardial fat volume predicts adverse cardiac events, but mechanistic pathways of the association are not well understood. Methods: 118 women enrolled in the NHLBI-sponsored Women's Ischemia Syndrome Evaluation-Coronary Vascular Dysfunction study with suspected coronary microvascular dysfunction but no obstructive CAD underwent adenosine stress 1.5 T cardiovascular magnetic resonance imaging (CMR) imaging and invasive coronary reactivity testing. Semi-quantitative myocardial perfusion reserve index (MPR) index was derived from perfusion images. Pericardial fat volume was measured by manually contouring the cardiac margins and adjacent adipose tissue on a single trans-axial HASTE slice at the level of the left main coronary artery origin and indexed to body surface-area. Simple standard deviation analysis obtained for continuous variables and frequency (percent) for categorical variables. The relationships between pericardial fat volume and coronary reactivity testing parameters were examined by correlation and multivariable regression analyses. Results: Women with suspected coronary microvascular dysfunction had a mean age of 55 ± 10 years, body mass index (BMI) of 28 ± 7 kg/m2, 44 % had a history of smoking, 63 % hypertension, 8 % diabetes, and 20 % dyslipidemia. CMR imaging-derived pericardial fat volume and coronary blood flow response to intracoronary acetylcholine (Δ CBF) were negatively correlated (r = -0.32, p = 0.0013). After adjustment for age, number of risk factors, high-density lipoprotein (HDL), and cold pressor diameter response, pericardial fat volume remained a significant predictor of Δ coronary blood flow (p = 0.04). There was no association with other coronary reactivity testing measures or CMRI derived MPR index. Conclusions: Among women with suspected coronary microvascular dysfunction but no obstructive CAD, pericardial fat volume appears to be related in a hypothesized adverse direction to coronary microvascular endothelial function. These results support further work confirming and extending these results to investigate pericardial fat volume as mechanistic pathway and potential treatment target for coronary microvascular dysfunction-related adverse events.Trial registration: clinicaltrials.govNCT00832702.

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.

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.

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 â€‹± â€‹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 â€‹< â€‹0.001). Women had a smaller burden of all plaque subtypes (all p â€‹< â€‹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 â€‹= â€‹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 â€‹= â€‹0.001; Women, OR: 1.96, 95%CI: 1.11-3.46, p â€‹= â€‹0.02). No significant interaction existed between sex and total plaque burden for predicting ischemia (interaction p â€‹= â€‹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.

Exercise-induced right ventricular cardiomyopathy in an endurance cyclist: a case report.

Background: The wide-ranging benefits of frequent and moderate exercise are well recorded in the literature. Chronic deleterious remodelling in response to exercise is less well described. We describe an amateur endurance cyclist who, in addition to developing a heart failure syndrome and electrocardiographic evidence of arrhythmia, also developed severe functional tricuspid regurgitation. Case summary: After developing palpitations during long distance cycle rides as part of his fitness regimen, a 69-year-old male presented to emergency services but was discharged. While continuing to enjoy long-distance cycling, he began to develop peripheral swelling and presented for a second time to hospital. Subsequent investigation found he had a dilated right heart, exercise-induced arrhythmia, and mid-wall myocardial fibrosis. A diagnosis of exercise-induced cardiomyopathy was made. He was managed with diuretics and immediate cessation of exercise. His symptoms improved and he remains symptom free. Discussion: The volume of blood passing through the right heart increases during exercise. In vulnerable individuals undertaking frequent endurance exercise, this can promote structural remodelling and fibrotic change. It is unclear if cessation of exercise can reverse the remodelled heart. There are some early advances in predictive biomarkers and imaging techniques in categorizing those in the population who would be at risk of developing this cardiomyopathy, and those who can undergo intense exercise regimens without concern. If those at risk of developing an exercise-induced cardiomyopathy can be accurately identified, the next dilemma is how can their risk of heart failure or sudden death be acceptably minimized.

2022 Artificial intelligence primer for the nuclear cardiologist.

Driven by advances in computing power, the past decade has seen rapid developments in artificial intelligence (AI) which now offers potential enhancements to every aspect of nuclear cardiology workflow including acquisition, reconstruction, segmentation, direct image analysis, and interpretation; as well as facilitating clinical and imaging big-data integration for superior personalized risk stratification. To understand the relevance and potential of AI in their field, this review provides a primer for nuclear cardiologists in 2022. The aim is to explain terminology and provide a summary of key current implementations, challenges, and future aspirations of AI-based enhancements to nuclear cardiology.

Cardiac Involvement in Fabry Disease and the Role of Multimodality Imaging in Diagnosis and Disease Monitoring.

Fabry disease (FD) is a rare, progressive, X-linked inherited disorder of glycosphingolipid metabolism. It is a monogenic disease due to α-galactosidase A (α-GAL) enzyme deficiency, leading to the accumulation of globotriaosylceramide (GL3) within lysosomes beginning in utero. Multiple systems are involved, most notably the vascular, renal, cardiac, and nervous systems. Early clinical manifestations include neuropathic pain, angiokeratomas, anhidrosis, cornea verticillata, and gastrointestinal symptoms. In the later stages, FD manifests with transient ischemic attacks, strokes, hearing loss, and life-threatening complications involving the kidneys and heart. Cardiac involvement in Fabry disease is typically characterized by increased left ventricular wall thickness/mass, functional abnormalities, valvular heart disease, arrhythmias, and heart failure. The life expectancy of the patient with untreated Fabry disease falls significantly once cardiac or renal manifestations develop. This review will focus on the cardiac manifestations of FD and the role of multimodality imaging in diagnosis and follow-up.

Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood Flow.

BACKGROUND: A pathophysiological interplay exists between plaque morphology and coronary physiology. Machine learning (ML) is increasingly being applied to coronary computed tomography angiography (CCTA) for cardiovascular risk stratification. We sought to assess the performance of a ML score integrating CCTA-based quantitative plaque features for predicting vessel-specific ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by positron emission tomography (PET). METHODS: This post-hoc analysis of the PACIFIC trial (Prospective Comparison of Cardiac Positron Emission Tomography/Computed Tomography [CT]' Single Photon Emission Computed Tomography/CT Perfusion Imaging and CT Coronary Angiography with Invasive Coronary Angiography) included 208 patients with suspected coronary artery disease who prospectively underwent CCTA' [15O]H2O PET, and invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. An ML algorithm trained on the prospective NXT trial (484 vessels) was used to develop a ML score for the prediction of ischemia (FFR≤0.80), which was then evaluated in 581 vessels from the PACIFIC trial. Thereafter, the ML score was applied for predicting impaired hyperemic MBF (≤2.30 mL/min per g) from corresponding PET scans. The performance of the ML score was compared with CCTA reads and noninvasive FFR derived from CCTA (FFRCT). RESULTS: One hundred thirty-nine (23.9%) vessels had FFR-defined ischemia, and 195 (33.6%) vessels had impaired hyperemic MBF. For the prediction of FFR-defined ischemia, the ML score yielded an area under the receiver-operating characteristic curve of 0.92, which was significantly higher than that of visual stenosis grade (0.84; P<0.001) and comparable with that of FFRCT (0.93; P=0.34). Quantitative percent diameter stenosis and low-density noncalcified plaque volume had the greatest ML feature importance for predicting FFR-defined ischemia. When applied for impaired MBF prediction, the ML score exhibited an area under the receiver-operating characteristic curve of 0.80; significantly higher than visual stenosis grade (area under the receiver-operating characteristic curve 0.74; P=0.02) and comparable with FFRCT (area under the receiver-operating characteristic curve 0.77; P=0.16). CONCLUSIONS: An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and impaired MBF by PET, performing superiorly to standard CCTA stenosis evaluation and comparably to FFRCT.

Remotely Monitored Cardiac Implantable Electronic Device Data Predict All-Cause and Cardiovascular Unplanned Hospitalization.

Background Unplanned hospitalizations are common in patients with cardiovascular disease. The "Triage Heart Failure Risk Status" (Triage-HFRS) algorithm in patients with cardiac implantable electronic devices uses data from up to 9 device-derived physiological parameters to stratify patients as low/medium/high risk of 30-day heart failure (HF) hospitalization, but its use to predict all-cause hospitalization has not been explored. We examined the association between Triage-HFRS and risk of all-cause, cardiovascular, or HF hospitalization. Methods and Results A prospective observational study of 435 adults (including patients with and without HF) with a Medtronic Triage-HFRS-enabled cardiac implantable electronic device (cardiac resynchronization therapy device, implantable cardioverter-defibrillator, or pacemaker). Cox proportional hazards models explored association between Triage-HFRS and time to hospitalization; a frailty term at the patient level accounted for repeated measures. A total of 274 of 435 patients (63.0%) transmitted ≥1 high HFRS transmission before or during the study period. The remaining 161 patients never transmitted a high HFRS. A total of 153 (32.9%) patients had ≥1 unplanned hospitalization during the study period, totaling 356 nonelective hospitalizations. A high HFRS conferred a 37.3% sensitivity and an 86.2% specificity for 30-day all-cause hospitalization; and for HF hospitalizations, these numbers were 62.5% and 85.6%, respectively. Compared with a low Triage-HFRS, a high HFRS conferred a 4.2 relative risk of 30-day all-cause hospitalization (8.5% versus 2.0%), a 5.0 relative risk of 30-day cardiovascular hospitalization (3.6% versus 0.7%), and a 7.7 relative risk of 30-day HF hospitalization (2.0% versus 0.3%). Conclusions In patients with cardiac implantable electronic devices, remotely monitored Triage-HFRS data discriminated between patients at high and low risk of all-cause hospitalization (cardiovascular or noncardiovascular) in real time.

Chest Pain Post-Transcatheter Aortic Valve Implantation: Don't Forget the Uncommon Complication.

Transesophageal echocardiography guides a range of structural heart disease interventions, especially in older adult and frail patients who are deemed not suitable to undergo surgical repair. Although rare, transesophageal echocardiography can be associated with esophageal trauma, including perforation. Treating physicians should be cognizant of such a complication. (Level of Difficulty: Intermediate.).

Remote monitoring data from cardiac implantable electronic devices predicts all-cause mortality.

AIMS: To determine if remotely monitored physiological data from cardiac implantable electronic devices (CIEDs) can be used to identify patients at high risk of mortality. METHODS AND RESULTS: This study evaluated whether a risk score based on CIED physiological data (Triage-Heart Failure Risk Status, 'Triage-HFRS', previously validated to predict heart failure (HF) events) can identify patients at high risk of death. Four hundred and thirty-nine adults with CIEDs were prospectively enrolled. Primary observed outcome was all-cause mortality (median follow-up: 702 days). Several physiological parameters [including heart rate profile, atrial fibrillation/tachycardia (AF/AT) burden, ventricular rate during AT/AF, physical activity, thoracic impedance, therapies for ventricular tachycardia/fibrillation] were continuously monitored by CIEDs and dynamically combined to produce a Triage-HFRS every 24 h. According to transmissions patients were categorized into 'high-risk' or 'never high-risk' groups. During follow-up, 285 patients (65%) had a high-risk episode and 60 patients (14%) died (50 in high-risk group; 10 in never high-risk group). Significantly more cardiovascular deaths were observed in the high-risk group, with mortality rates across groups of high vs. never-high 10.3% vs. <4.0%; P = 0.03. Experiencing any high-risk episode was associated with a substantially increased risk of death [odds ratio (OR): 3.07, 95% confidence interval (CI): 1.57-6.58, P = 0.002]. Furthermore, each high-risk episode ≥14 consecutive days was associated with increased odds of death (OR: 1.26, 95% CI: 1.06-1.48; P = 0.006). CONCLUSION: Remote monitoring data from CIEDs can be used to identify patients at higher risk of all-cause mortality as well as HF events. Distinct from other prognostic scores, this approach is automated and continuously updated.

Impact of COVID-19 pandemic on bariatric surgery in India: An obesity and metabolic surgery society of India survey of 1307 patients.

BACKGROUND: Although safe practice guidelines were issued by the Obesity and Metabolic Surgery Society of India (OSSI) in the end of May 2020, surgeons have been in a dilemma about risk of subjecting patients to hospitalisation and bariatric surgery. This survey was conducted with the objective to evaluate the risk of coronavirus disease-19 (COVID-19) infection in peri- and post-operative period after bariatric and metabolic surgery (BMS). METHODS: A survey with OSSI members was conducted from 20 July 2020 to 31 August 2020 in accordance with EQUATOR guidelines. Google Form was circulated to all surgeon members through E-mail and WhatsAppTM. In the second phase, clinical details were captured from surgeons who reported positive cases. RESULTS: One thousand three hundred and seven BMS were reported from 1 January 2020 to 15 July 2020. Seventy-eight per cent were performed prior to 31 March 2020 and 276 were performed after 1 April 2020. Of these, 13 (0.99%) patients were reported positive for COVID-19 in the post-operative period. All suffered from a mild disease and there was no mortality. Eighty-seven positive cases were reported from patients who underwent BMS prior to 31 December 2019. Of these, 82.7% of patients had mild disease, 13.7% of patients had moderate symptoms and four patients succumbed to COVID-19. CONCLUSION: BMS may be considered as a safe treatment option for patients suffering from clinically severe obesity during the COVID-19 pandemic. Due care must be taken to protect patients and healthcare workers and all procedures must be conducted in line with the safe practice guidelines.

Ambulatory intravenous furosemide for decompensated heart failure: safe, feasible, and effective.

AIMS: This study aims to establish the feasibility, safety, and efficacy of outpatient intravenous (IV) diuretic treatment for the management of decompensated heart failure (HF) for patients enrolled in the HeartFailure@Home service. METHODS AND RESULTS: We retrospectively analysed the clinical episodes of decompensated HF for patients enrolled in the HeartFailure@Home service, managed by ambulatory IV diuretic treatment either at home or on a day-case unit. A control group consisting of HF patients admitted to hospital for IV diuretics (standard-of-care) was also evaluated. In total, 203 episodes of decompensated HF (n = 154 patients) were evaluated. One hundred and fourteen episodes in 79 patients were managed exclusively by the ambulatory IV diuretic service-78 (68.4%) on a day-case unit and 36 (31.6%) domiciliary; 84.1% of patient episodes under the HF@Home service were successfully managed entirely in an out-patient setting without hospitalization. Eleven patients required admission in order to administer higher doses of IV diuretics than could be provided in the ambulatory setting. During follow-up, there were 20 (17.5%) 30 day re-admissions with HF or death in the ambulatory IV group and 29 (32.6%) in the standard-of-care arm (P = 0.02). There was no difference in 30 day HF readmissions between the two groups (14.9% ambulatory vs. 13.5% inpatients, P = 0.8), but 30 day mortality was significantly lower in the ambulatory group (3.5% vs. 21.3% inpatients, P < 0.001). CONCLUSIONS: Outpatient ambulatory management of decompensated HF with IV diuretics given either on a day case unit or in a domiciliary setting is feasible, safe, and effective in selected patients with decompensated HF. This should be explored further as a model in delivering HF services in the outpatient setting during COVID-19.

Artificial intelligence in cardiovascular CT: Current status and future implications.

Artificial intelligence (AI) refers to the use of computational techniques to mimic human thought processes and learning capacity. The past decade has seen a rapid proliferation of AI developments for cardiovascular computed tomography (CT). These algorithms aim to increase efficiency, objectivity, and performance in clinical tasks such as image quality improvement, structure segmentation, quantitative measurements, and outcome prediction. By doing so, AI has the potential to streamline clinical workflow, increase interpretative speed and accuracy, and inform subsequent clinical pathways. This review covers state-of-the-art AI techniques in cardiovascular CT and the future role of AI as a clinical support tool.