Macrophages Facilitate Electrical Conduction in the Heart.

Organ-specific functions of tissue-resident macrophages in the steady-state heart are unknown. Here, we show that cardiac macrophages facilitate electrical conduction through the distal atrioventricular node, where conducting cells densely intersperse with elongated macrophages expressing connexin 43. When coupled to spontaneously beating cardiomyocytes via connexin-43-containing gap junctions, cardiac macrophages have a negative resting membrane potential and depolarize in synchrony with cardiomyocytes. Conversely, macrophages render the resting membrane potential of cardiomyocytes more positive and, according to computational modeling, accelerate their repolarization. Photostimulation of channelrhodopsin-2-expressing macrophages improves atrioventricular conduction, whereas conditional deletion of connexin 43 in macrophages and congenital lack of macrophages delay atrioventricular conduction. In the Cd11bDTR mouse, macrophage ablation induces progressive atrioventricular block. These observations implicate macrophages in normal and aberrant cardiac conduction.

Patient contrastive learning: A performant, expressive, and practical approach to electrocardiogram modeling.

Supervised machine learning applications in health care are often limited due to a scarcity of labeled training data. To mitigate the effect of small sample size, we introduce a pre-training approach, Patient Contrastive Learning of Representations (PCLR), which creates latent representations of electrocardiograms (ECGs) from a large number of unlabeled examples using contrastive learning. The resulting representations are expressive, performant, and practical across a wide spectrum of clinical tasks. We develop PCLR using a large health care system with over 3.2 million 12-lead ECGs and demonstrate that training linear models on PCLR representations achieves a 51% performance increase, on average, over six training set sizes and four tasks (sex classification, age regression, and the detection of left ventricular hypertrophy and atrial fibrillation), relative to training neural network models from scratch. We also compared PCLR to three other ECG pre-training approaches (supervised pre-training, unsupervised pre-training with an autoencoder, and pre-training using a contrastive multi ECG-segment approach), and show significant performance benefits in three out of four tasks. We found an average performance benefit of 47% over the other models and an average of a 9% performance benefit compared to best model for each task. We release PCLR to enable others to extract ECG representations at https://github.com/broadinstitute/ml4h/tree/master/model_zoo/PCLR.

Remote monitoring in the use of extracorporeal membrane oxygenation and acute mechanical circulatory support.

PURPOSE OF REVIEW: To provide an overview of the role of remote monitoring tools in management of critically-ill patients requiring acute mechanical circulatory support (MCS). RECENT FINDINGS: Tele-critical care systems have received new interest during the COVID-19 pandemic, which has stretched the capacity of health systems everywhere. At the same time, utilization of MCS and extracorporeal membrane oxygenation (ECMO) technologies has increased during the pandemic. The opportunity for remote monitoring and clinical decision support for ECMO and acute MCS devices has been recognized by industry partners, with several major platforms implementing technology infrastructure for it in available products. Healthcare systems face challenges interfacing multiple devices from multiple manufacturers with each other and with their designated electronic health records. Furthermore, the availability of data must be combined with algorithms for alerting on clinical events and with implementation systems to act upon these alerts. Studies are not yet published validating remote monitoring platforms for ECMO and MCS in clinical care. SUMMARY: Remote monitoring for MCS devices represents a major opportunity for further investigation to improve the utilization of these devices and better serve patients.

An activatable PET imaging radioprobe is a dynamic reporter of myeloperoxidase activity in vivo.

Myeloperoxidase (MPO) is a critical proinflammatory enzyme implicated in cardiovascular, neurological, and rheumatological diseases. Emerging therapies targeting inflammation have raised interest in tracking MPO activity in patients. We describe 18F-MAPP, an activatable MPO activity radioprobe for positron emission tomography (PET) imaging. The activated radioprobe binds to proteins and accumulates at sites of MPO activity. The radioprobe 18F-MAPP has a short blood half-life, remains stable in plasma, does not demonstrate cytotoxicity, and crosses the intact blood-brain barrier. The 18F-MAPP imaging detected sites of elevated MPO activity in living mice embedded with human MPO and in mice induced with chemical inflammation or myocardial infarction. The 18F-MAPP PET imaging noninvasively differentiated varying amounts of MPO activity, competitive inhibition, and MPO deficiency in living animals, confirming specificity and showing that the radioprobe can quantify changes in in vivo MPO activity. The radiosynthesis has been optimized and automated, an important step in translation. These data indicate that 18F-MAPP is a promising translational candidate to noninvasively monitor MPO activity and inflammation in patients.

Late onset atrial fibrillation in patients undergoing surgical aortic valve replacement.

OBJECTIVE: Aortic valve disease is a risk factor for atrial fibrillation (AF), and AF is associated with increased late mortality and morbidity after cardiac surgery. The evolution of alternative approaches to AF prophylaxis, including less invasive technologies and medical therapies, has altered the balance between risk and potential benefit for prophylactic intervention at the time of surgical aortic valve replacement (SAVR). Such interventions impose incremental risk, however, making an understanding of predictors of new onset AF that persists beyond the perioperative episode relevant. METHODS: We conducted a retrospective single-institution cohort analysis of patients undergoing SAVR with no history of preoperative AF (n = 1014). These patients were cross-referenced against an institutional electrocardiogram (ECG) database to identify those with ECGs 3-12 months after surgery. Logistic regression was used to identify predictors of late AF. RESULTS: Among the 401 patients (40%), who had ECGs in our institution 3-12 months after surgery, 16 (4%) had late AF. Patients with late AF were older than patients without late AF (73 vs. 65, p = .025), and underwent procedures that were more urgent/emergent (38% vs. 15%, p = .015), with higher predicted risk of mortality (2.2% vs. 1.3%, p = .012). Predictors associated with the development of late AF were advanced age, higher preoperative creatinine level and urgent/emergent surgery. CONCLUSIONS: The incidence of late AF 3-12 months after SAVR, is low. Prophylactic AF interventions at the time of SAVR may not be warranted.

A Miniaturized, Programmable Pacemaker for Long-Term Studies in the Mouse.

RATIONALE: Cardiac pacing is a critical technology for the treatment of arrhythmia and heart failure. The impact of specific pacing strategies on myocardial function is an area of intense research and high clinical significance. Mouse models have proven extremely useful for probing mechanisms of heart disease, but there is currently no reliable technology for long-term pacing in the mouse. OBJECTIVE: We sought to develop a device for long-term pacing studies in mice. We evaluated the device for (1) treating third-degree atrioventricular block after macrophage depletion, (2) ventricular pacing-induced cardiomyopathy, and (3) high-rate atrial pacing. METHODS AND RESULTS: We developed a mouse pacemaker by refashioning a 26 mm×6.7 mm clinical device powered by a miniaturized, highly efficient battery. The electrode was fitted with a single flexible lead, and custom software extended the pacing rate to up to 1200 bpm. The wirelessly programmable device was implanted in the dorsal subcutaneous space of 39 mice. The tunneled lead was passed through a left thoracotomy incision and attached to the epicardial surface of the apex (for ventricular pacing) or the left atrium (for atrial pacing). Mice tolerated the implantation and both long-term atrial and ventricular pacing over weeks. We then validated the pacemaker's suitability for the treatment of atrioventricular block after macrophage depletion in Cd11b DTR mice. Ventricular pacing increased the heart rate from 313±59 to 550 bpm ( P<0.05). In addition, we characterized tachypacing-induced cardiomyopathy in mice. Four weeks of ventricular pacing resulted in reduced left ventricular function, fibrosis, and an increased number of cardiac leukocytes and endothelial activation. Finally, we demonstrated the feasibility of chronic atrial pacing at 1200 bpm. CONCLUSIONS: Long-term pacing with a fully implantable, programmable, and battery-powered device enables previously impossible investigations of arrhythmia and heart failure in the mouse.

A Supramolecular Nanocarrier for Delivery of Amiodarone Anti-Arrhythmic Therapy to the Heart.

Amiodarone is an effective antiarrhythmic drug used to treat and prevent different types of cardiac arrhythmias. However, amiodarone can have considerable side effects resulting from accumulation in off-target tissues. Cardiac macrophages are highly prevalent tissue-resident immune cells with importance in homeostatic functions, including immune response and modulation of cardiac conduction. We hypothesized that amiodarone could be more efficiently delivered to the heart via cardiac macrophages, an important step toward reducing overall dose and off-target tissue accumulation. Toward this goal, we synthesized a nanoparticle drug carrier composed of l-lysine cross-linked succinyl-ß-cyclodextrin that demonstrates amiodarone binding through supramolecular host-guest interaction as well as a high macrophage affinity. Biodistribution analyses at the organ and single-cell level demonstrate accumulation of nanoparticles in the heart resulting from rapid uptake by cardiac macrophages. Nanoparticle assisted delivery of amiodarone resulted in a 250% enhancement in the selective delivery of the drug to cardiac tissue in part due to a concomitant decrease of pulmonary accumulation, the main source of off-target toxicity.

Prevalence and Predictors of Multiple Coronary Plaque Ruptures: In Vivo 3-Vessel Optical Coherence Tomography Imaging Study.

OBJECTIVE: Plaque rupture may be the local expression of a widespread coronary instability. This study aimed to investigate: (1) the prevalence and characteristics of nonculprit plaque rupture; (2) the pancoronary atherosclerotic phenotype in patients with and without nonculprit plaque rupture; and (3) the prevalence and predictors of multiple plaque ruptures. APPROACH AND RESULTS: Six hundred and seventy-five nonculprit plaques from 261 patients (34 acute myocardial infarction, 73 unstable angina pectoris, and 154 stable angina pectoris) were analyzed by 3-vessel optical coherence tomography. Nonculprit plaque ruptures were identified in 51 patients (20%). Patients with nonculprit plaque ruptures had higher prevalence of thin-cap fibroatheroma (51% versus 13%; P<0.001) in the 3 major epicardial coronary vessels. Multiple plaque ruptures were observed in 20% of patients (38% acute myocardial infarction versus 10% unstable angina pectoris versus 19% stable angina pectoris; P=0.042). Thin-cap fibroatheroma, intimal vasculature, and macrophages were independent morphological predictors of multiple plaque ruptures, whereas acute myocardial infarction and chronic kidney disease were independent clinical predictors. Patients with nonculprit plaque ruptures showed higher 1-year rates of nontarget lesion revascularization (11.8% versus 4.4%; P=0.039). CONCLUSIONS: Nonculprit plaque ruptures were observed in 20% of patients with coronary artery disease and were associated with pancoronary vulnerability and higher 1-year revascularization rate.

Intravital imaging of cardiac function at the single-cell level.

Knowledge of cardiomyocyte biology is limited by the lack of methods to interrogate single-cell physiology in vivo. Here we show that contracting myocytes can indeed be imaged with optical microscopy at high temporal and spatial resolution in the beating murine heart, allowing visualization of individual sarcomeres and measurement of the single cardiomyocyte contractile cycle. Collectively, this has been enabled by efficient tissue stabilization, a prospective real-time cardiac gating approach, an image processing algorithm for motion-artifact-free imaging throughout the cardiac cycle, and a fluorescent membrane staining protocol. Quantification of cardiomyocyte contractile function in vivo opens many possibilities for investigating myocardial disease and therapeutic intervention at the cellular level.

Pancoronary plaque vulnerability in patients with acute coronary syndrome and ruptured culprit plaque: a 3-vessel optical coherence tomography study.

BACKGROUND: Recent studies described different clinical and underlying plaque characteristics between patients with and without plaque rupture presenting with acute coronary syndrome (ACS). In light of the systemic nature of atherosclerosis, we hypothesized that nonculprit plaques might also express different morphological features in these 2 groups of patients. METHODS: Thirty-eight patients with ACS who underwent 3-vessel optical coherence tomography imaging were identified from the Massachusetts General Hospital Optical Coherence Tomography Registry. Based on culprit plaque morphology, the study population was divided into 2 groups: patients with plaque rupture at the culprit lesion (group 1) and patients with nonruptured plaque at the culprit lesion (group 2). Prevalence and features of nonculprit plaques were compared between the 2 groups. RESULTS: A total of 118 nonculprit plaques were analyzed. Patients in group 1 (n = 17) had nonculprit plaques with higher prevalence of thin-cap fibroatheroma (52.9% vs 19.0%, P = .029) and disruption (35.3% vs 4.8%, P = .016) compared with patients in group 2 (n = 21). Nonculprit plaques in group 1 showed wider maximum lipid arc (198.9° ± 41.7° vs 170.2° ± 41.9°, P = .003), greater lipid length (7.8 ± 4.4 mm vs 5.1 ± 2.4 mm, P = .003), higher lipid index (1196.9 ± 700.5 vs 747.7 ± 377.3, P = .001), and thinner fibrous cap (107.0 ± 56.5 µm vs 137.3 ± 69.8 µm, P = .035) compared with those in group 2. CONCLUSIONS: The present study showed distinctive features of nonculprit plaques between patients with ACS caused by plaque rupture and patients with ACS caused by nonruptured plaques. Patients with plaque rupture had increased pancoronary vulnerability in nonculprit plaques, suggesting that a more aggressive treatment paradigm aiming at the stabilization of vulnerable plaques may offer additional benefit to these patients.

QTNet: Deep Learning for Estimating QT Intervals Using a Single Lead ECG.

QT prolongation often leads to fatal arrhythmia and sudden cardiac death. Antiarrhythmic drugs can increase the risk of QT prolongation and therefore require strict post-administration monitoring and dosage control. Measurement of the QT interval from the 12-lead electrocardiogram (ECG) by a trained expert, in a clinical setting, is the accepted method for tracking QT prolongation. Recent advances in wearable ECG technology, however, raise the possibility of automated out-of-hospital QT tracking. Applications of Deep Learning (DL) - a subfield within Machine Learning - in ECG analysis holds the promise of automation for a variety of classification and regression tasks. In this work, we propose a residual neural network, QTNet, for the regression of QT intervals from a single lead (Lead-I) ECG. QTNet is trained in a supervised manner on a large ECG dataset from a U.S. hospital. We demonstrate the robustness and generalizability of QTNet on four test-sets; one from the same hospital, one from another U.S. hospital, and two public datasets. Over all four datasets, the mean absolute error (MAE) in the estimated QT interval ranges between 9ms and 15.8ms. Pearson correlation coefficients vary between 0.899 and 0.914. By contrast, QT interval estimation on these datasets with a standard method for automated ECG analysis (NeuroKit2) yields MAEs between 22.29ms and 90.79ms, and Pearson correlation coefficients 0.345 and 0.620. These results demonstrate the utility of QTNet across distinct datasets and patient populations, thereby highlighting the potential utility of DL models for ubiquitous QT tracking.Clinical Relevance- QTNet can be applied to inpatient or ambulatory Lead-I ECG signals to track QT intervals. The method facilitates ambulatory monitoring of patients at risk of QT prolongation.

Timing of diuretic administration effects on urine volume in hospitalized patients.

Importance: Some medications have effects that depend on the time of day they are given. Current knowledge of the time-of-day effects of specific medications in hospitalized patients with cardiovascular disease is very limited. In hospitalized patients, increased medication efficiency might reduce dose (and associated side effects) and/or the length of time in the Intensive Care Unit (ICU) or hospital-potentially improving patient outcomes and patient and family quality of life and reducing financial costs. We studied whether the time of day or night patients in Cardiac or Intensive Care Units receive a diuretic affects urine volume. Methods: In this observational study, data were collected from 7,685 patients (63% male, 18 to 98 years old) admitted to one hospital's Acute Care Cardiac units, Cardiac ICUs, Cardiac Surgery ICUs, and/or Non-cardiac ICUs who received intravenous furosemide (a diuretic), had measurements of urine volume, were hospitalized for ≥3 days between January 2016 to July 2021 and were older than 18 years. The outcomes of interest were urine volume normalized by the most recent (not older than 24 h) weight or body mass index (BMI), (i) in the hour after the time of diuretic administration, and (ii) when no diuretics were administered for the previous 3 h. Results: We identified diuretic medication administration time 23:00-04:59 as a predictor of higher urine volume response. For patients without recent diuretic medication, higher urine volume was predicted 11:00-16:59 and 17:00-22:59. Other factors that affected urine volume response to the diuretic were sex, age, medication dose, creatinine concentration, diagnoses, and hospital unit. Discussion: Time-of-day of medication administration may be a factor associated with increased medication efficiency. Randomized controlled trials should be conducted to quantify the relative effect of modifiable factors, such as time of medication administration, that may affect short- and longer-term outcomes.

Deep Learning to Predict Mortality After Cardiothoracic Surgery Using Preoperative Chest Radiographs.

BACKGROUND: The Society of Thoracic Surgeons Predicted Risk of Mortality (STS-PROM) estimates mortality risk only for certain common procedures (eg, coronary artery bypass or valve surgery) and is cumbersome, requiring greater than 60 inputs. We hypothesized that deep learning can estimate postoperative mortality risk based on a preoperative chest radiograph for cardiac surgeries in which STS-PROM scores were available (STS index procedures) or unavailable (non-STS index procedures). METHODS: We developed a deep learning model (CXR-CTSurgery) to predict postoperative mortality based on preoperative chest radiographs in 9283 patients at Massachusetts General Hospital (MGH) having cardiac surgery before April 8, 2014. CXR-CTSurgery was tested on 3615 different MGH patients and externally tested on 2840 patients from Brigham and Women's Hospital (BWH) having surgery after April 8, 2014. Discrimination for mortality was compared with the STS-PROM using the C-statistic. Calibration was assessed using the observed-to-expected ratio (O/E ratio). RESULTS: For STS index procedures, CXR-CTSurgery had a C-statistic similar to STS-PROM at MGH (CXR-CTSurgery: 0.83 vs STS-PROM: 0.88; P = .20) and BWH (0.74 vs 0.80; P = .14) testing cohorts. The CXR-CTSurgery C-statistic for non-STS index procedures was similar to STS index procedures in the MGH (0.87 vs 0.83) and BWH (0.73 vs 0.74) testing cohorts. For STS index procedures, CXR-CTSurgery had better calibration than the STS-PROM in the MGH (O/E ratio: 0.74 vs 0.52) and BWH (O/E ratio: 0.91 vs 0.73) testing cohorts. CONCLUSIONS: CXR-CTSurgery predicts postoperative mortality based on a preoperative CXR with similar discrimination and better calibration than the STS-PROM. This may be useful when the STS-PROM cannot be calculated or for non-STS index procedures.

Tissue perfusion pressure enables continuous hemodynamic evaluation and risk prediction in the intensive care unit.

Treatment of circulatory shock in critically ill patients requires management of blood pressure using invasive monitoring, but uncertainty remains as to optimal individual blood pressure targets. Critical closing pressure, which refers to the arterial pressure when blood flow stops, can provide a fundamental measure of vascular tone in response to disease and therapy, but it has not previously been possible to measure this parameter routinely in clinical care. Here we describe a method to continuously measure critical closing pressure in the systemic circulation using readily available blood pressure monitors and then show that tissue perfusion pressure (TPP), defined as the difference between mean arterial pressure and critical closing pressure, provides unique information compared to other hemodynamic parameters. Using analyses of 5,988 admissions to a modern cardiac intensive care unit, and externally validated with 864 admissions to another institution, we show that TPP can predict the risk of mortality, length of hospital stay and peak blood lactate levels. These results indicate that TPP may provide an additional target for blood pressure optimization in patients with circulatory shock.

Prediction of operative mortality for patients undergoing cardiac surgical procedures without established risk scores.

OBJECTIVE: Current cardiac surgery risk models do not address a substantial fraction of procedures. We sought to create models to predict the risk of operative mortality for an expanded set of cases. METHODS: Four supervised machine learning models were trained using preoperative variables present in the Society of Thoracic Surgeons (STS) data set of the Massachusetts General Hospital to predict and classify operative mortality in procedures without STS risk scores. A total of 424 (5.5%) mortality events occurred out of 7745 cases. Models included logistic regression with elastic net regularization (LogReg), support vector machine, random forest (RF), and extreme gradient boosted trees (XGBoost). Model discrimination was assessed via area under the receiver operating characteristic curve (AUC), and calibration was assessed via calibration slope and expected-to-observed event ratio. External validation was performed using STS data sets from Brigham and Women's Hospital (BWH) and the Johns Hopkins Hospital (JHH). RESULTS: Models performed comparably with the highest mean AUC of 0.83 (RF) and expected-to-observed event ratio of 1.00. On external validation, the AUC was 0.81 in BWH (RF) and 0.79 in JHH (LogReg/RF). Models trained and applied on the same institution's data achieved AUCs of 0.81 (BWH: LogReg/RF/XGBoost) and 0.82 (JHH: LogReg/RF/XGBoost). CONCLUSIONS: Machine learning models trained on preoperative patient data can predict operative mortality at a high level of accuracy for cardiac surgical procedures without established risk scores. Such procedures comprise 23% of all cardiac surgical procedures nationwide. This work also highlights the value of using local institutional data to train new prediction models that account for institution-specific practices.

Integrated optical coherence tomography and optical coherence microscopy imaging of ex vivo human renal tissues.

PURPOSE: We evaluated the feasibility of using optical coherence tomography and optical coherence microscopy technology to assess human kidney morphology. MATERIALS AND METHODS: A total of 35 renal specimens from 19 patients, consisting of 12 normal tissues and 23 tumors (16 clear cell renal cell carcinomas, 5 papillary renal cell carcinomas and 2 oncocytomas) were imaged ex vivo after surgical resection. Optical coherence tomography and optical coherence microscopy images were compared to corresponding hematoxylin and eosin histology to identify characteristic features of normal and pathological renal tissues. Three pathologists blinded to histology evaluated the sensitivity and specificity of optical coherence microscopy images to differentiate normal from neoplastic renal tissues. RESULTS: Optical coherence tomography and optical coherence microscopy images of normal kidney revealed architectural features, including glomeruli, convoluted tubules, collecting tubules and loops of Henle. Each method of imaging renal tumors clearly demonstrated morphological changes and decreased imaging depth. Optical coherence tomography and microscopy features matched well with the corresponding histology. Three observers achieved 88%, 100% and 100% sensitivity, and 100%, 88% and 100% specificity, respectively, when evaluating normal vs neoplastic specimens using optical coherence microscopy images with substantial interobserver agreement (κ = 0.82, p <0.01). CONCLUSIONS: Integrated optical coherence tomography and optical coherence microscopy imaging provides coregistered, multiscale images of renal pathology in real time without exogenous contrast medium or histological processing. High sensitivity and specificity were achieved using optical coherence microscopy to differentiate normal from neoplastic renal tissues, suggesting possible applications for guiding renal mass biopsy or evaluating surgical margins.

Human acute inflammatory recovery is defined by co-regulatory dynamics of white blood cell and platelet populations.

Inflammation is the physiologic reaction to cellular and tissue damage caused by trauma, ischemia, infection, and other pathologic conditions. Elevation of white blood cell count (WBC) and altered levels of other acute phase reactants are cardinal signs of inflammation, but the dynamics of these changes and their resolution are not well established. Here we studied inflammatory recovery from trauma, ischemia, and infection by tracking longitudinal dynamics of clinical laboratory measurements in hospitalized patients. We identified a universal recovery trajectory defined by exponential WBC decay and delayed linear growth of platelet count (PLT). Co-regulation of WBC-PLT dynamics is a fundamental mechanism of acute inflammatory recovery and provides a generic approach for identifying high-risk patients: 32x relative risk (RR) of adverse outcomes for cardiac surgery, 9x RR of death from COVID-19, 9x RR of death from sepsis, and 5x RR of death from myocardial infarction.

Intravital Microscopy in Atherosclerosis Research.

Atherosclerosis is a lipid-driven inflammatory disorder that narrows the arterial lumen and can induce life-threatening complications from coronary artery disease, cerebrovascular disease, and peripheral artery disease. On a mechanistic level, the development of novel cellular-resolution intravital microscopy imaging approaches has recently enabled in vivo studies of underlying biological processes governing disease onset and progress. In particular, multiphoton microscopy has emerged as a promising intravital imaging tool utilizing two-photon-excited fluorescence and second-harmonic generation that provides subcellular resolution and increased imaging depths beyond confocal and epifluorescence microscopy. In this chapter, we describe the state-of-the-art multiphoton microscopy applied to the study of murine atherosclerosis.

Neutrophils incite and macrophages avert electrical storm after myocardial infarction.

Sudden cardiac death, arising from abnormal electrical conduction, occurs frequently in patients with coronary heart disease. Myocardial ischemia simultaneously induces arrhythmia and massive myocardial leukocyte changes. In this study, we optimized a mouse model in which hypokalemia combined with myocardial infarction triggered spontaneous ventricular tachycardia in ambulatory mice, and we showed that major leukocyte subsets have opposing effects on cardiac conduction. Neutrophils increased ventricular tachycardia via lipocalin-2 in mice, whereas neutrophilia associated with ventricular tachycardia in patients. In contrast, macrophages protected against arrhythmia. Depleting recruited macrophages in Ccr2 -/- mice or all macrophage subsets with Csf1 receptor inhibition increased both ventricular tachycardia and fibrillation. Higher arrhythmia burden and mortality in Cd36 -/- and Mertk -/- mice, viewed together with reduced mitochondrial integrity and accelerated cardiomyocyte death in the absence of macrophages, indicated that receptor-mediated phagocytosis protects against lethal electrical storm. Thus, modulation of leukocyte function provides a potential therapeutic pathway for reducing the risk of sudden cardiac death.

Optical coherence tomography in coronary atherosclerosis assessment and intervention.

Since optical coherence tomography (OCT) was first performed in humans two decades ago, this imaging modality has been widely adopted in research on coronary atherosclerosis and adopted clinically for the optimization of percutaneous coronary intervention. In the past 10 years, substantial advances have been made in the understanding of in vivo vascular biology using OCT. Identification by OCT of culprit plaque pathology could potentially lead to a major shift in the management of patients with acute coronary syndromes. Detection by OCT of healed coronary plaque has been important in our understanding of the mechanisms involved in plaque destabilization and healing with the rapid progression of atherosclerosis. Accurate detection by OCT of sequelae from percutaneous coronary interventions that might be missed by angiography could improve clinical outcomes. In addition, OCT has become an essential diagnostic modality for myocardial infarction with non-obstructive coronary arteries. Insight into neoatherosclerosis from OCT could improve our understanding of the mechanisms of very late stent thrombosis. The appropriate use of OCT depends on accurate interpretation and understanding of the clinical significance of OCT findings. In this Review, we summarize the state of the art in cardiac OCT and facilitate the uniform use of this modality in coronary atherosclerosis. Contributions have been made by clinicians and investigators worldwide with extensive experience in OCT, with the aim that this document will serve as a standard reference for future research and clinical application.