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Coronary artery calcium (CAC) scans contain valuable information beyond the Agatston Score which is currently reported for predicting coronary heart disease (CHD) only. We examined whether new artificial intelligence (AI) applied to CAC scans can predict non-CHD events, including heart failure, atrial fibrillation, and stroke. We applied AI-enabled automated cardiac chambers volumetry and calcified plaque characterization to CAC scans (AI-CAC) of 5830 asymptomatic individuals (52.2% women, age 61.7 ± 10.2 years) in the multi-ethnic study of atherosclerosis during 15 years of follow-up, 1773 CVD events accrued. The AUC at 1-, 5-, 10-, and 15-year follow-up for AI-CAC vs. Agatston score was (0.784 vs. 0.701), (0.771 vs. 0.709), (0.789 vs. 0.712) and (0.816 vs. 0.729) (p < 0.0001 for all), respectively. AI-CAC plaque characteristics, including number, location, density, plus number of vessels, significantly improved CHD prediction in the CAC 1-100 cohort vs. Agatston Score. AI-CAC significantly improved the Agatston score for predicting all CVD events., (© 2024. The Author(s).)

Regulating innate immunity is an emerging approach to improve cancer immunotherapy. Such regulation requires engaging myeloid cells by delivering immunomodulatory compounds to hematopoietic organs, including the spleen. Here we present a polymersome-based nanocarrier with splenic avidity and propensity for red pulp myeloid cell uptake. We characterized the in vivo behaviour of four chemically identical yet topologically different polymersomes by in vivo positron emission tomography imaging and innovative flow and mass cytometry techniques. Upon intravenous administration, relatively large and spherical polymersomes accumulated rapidly in the spleen and efficiently targeted myeloid cells in the splenic red pulp. When loaded with β-glucan, intravenously administered polymersomes significantly reduced tumour growth in a mouse melanoma model. We initiated our nanotherapeutic's clinical translation with a biodistribution study in non-human primates, which revealed that the platform's splenic avidity is preserved across species., Competing Interests: Competing interests W.J.M.M., L.A.B.J., M.G.N. and Z.A.F. are scientific founders of Trained Therapeutix Discovery. The remaining authors declare no competing interests., (© 2024. The Author(s).)

The innate immune system plays an essential role in regulating the immune responses to kidney transplantation, but the mechanisms through which innate immune cells influence long-term graft survival are unclear. The current study highlights the vital role of trained immunity in kidney allograft survival. Trained immunity describes the epigenetic and metabolic changes that innate immune cells undergo following an initial stimulus, allowing them have a stronger inflammatory response to subsequent stimuli. We stimulated healthy peripheral blood mononuclear cells with pretransplant and posttransplant serum of kidney transplant patients and immunosuppressive drugs in an in vitro trained immunity assay and measured tumor necrosis factor and interleukin 6 cytokine levels in the supernatant as a readout for trained immunity. We show that the serum of kidney transplant recipients collected 1 week after transplantation can suppress trained immunity. Importantly, we found that kidney transplant recipients whose serum most strongly suppressed trained immunity rarely experienced graft loss. This suppressive effect of posttransplant serum is likely mediated by previously unreported effects of immunosuppressive drugs. Our findings provide mechanistic insights into the role of innate immunity in kidney allograft survival, uncovering trained immunity as a potential therapeutic target for improving graft survival., Competing Interests: Declaration of competing interest The authors of this manuscript have conflicts of interest to disclose as described by the American Journal of Transplantation. L. A. B. Joosten is scientific founder of TTxD, LembaTX, and SalvinaTX. M. G. Netea is scientific founder of TTxD and Biotrip. W. J. M. Mulder is scientific founder of TTxD and Biotrip. Other authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: 18 F-Fluorodeoxyglucose ( 18 F-FDG) positron emission tomography (PET)/magnetic resonance (MR) can identify inflammation and fibrosis, which are high-risk features in cardiac sarcoidosis., Objective: The purpose of this study was to evaluate whether the involvement of certain myocardial segments is associated with higher risk compared to others., Methods: One hundred twenty-four patients with suspected clinical sarcoidosis underwent 18 F-FDG-PET/MR. Late gadolinium enhancement (LGE) and focal 18 F-FDG uptake were evaluated globally and in the 16 myocardial segments. Presence of LGE was defined when the percentage of LGE exceeded 5.7% globally (relative to myocardial volume) and in each myocardial segment. Patients were followed up for 5.5 years. Events were defined as ventricular arrhythmia (VA) (including sustained ventricular tachycardia, ventricular fibrillation, and appropriate implantable cardioverter-defibrillator discharge), heart failure hospitalization, or all-cause death., Results: Mean age was 57.1 ± 8.9 years, and 39.5% were female. Twenty-two patients (17.6%) had an event during follow-up, and 9 (7.2%) presented with VA. LGE and 18 F-FDG uptake were more frequent in patients with than without events (36.4% vs 7.8%, P = .001). Presence of LGE and 18 F-FDG in the basal anterior segment were independent predictors for events after adjustment for left ventricular ejection fraction and relative enhanced volume (LGE: odds ratio [1.2-92.4], P = .034; 18 F-FDG: odds ratio 5.5 [1.1-27.5], P = .038). LGE presence in basal to mid-anterior, mid-anteroseptal, and basal to mid-inferoseptal segments was an independent predictor of VA. Presence of 18 F-FDG in basal to mid-anterior, mid-inferoseptal and mid-inferior segments was an independent predictor of VA., Conclusion: Involvement of specific myocardial segments, particularly basal to mid-anterior and mid-septal segments, is associated with higher rates of events in patients with suspected cardiac sarcoidosis., Competing Interests: Disclosures The authors have no conflicts to disclose., (Copyright © 2024 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Assessing atherosclerosis severity is essential for precise patient stratification. Specifically, there is a need to identify patients with residual inflammation because these patients remain at high risk of cardiovascular events despite optimal management of cardiovascular risk factors. Molecular imaging techniques, such as PET, can have an essential role in this context. PET imaging can indicate tissue-based disease status, detect early molecular changes and provide whole-body information. Advances in molecular biology and bioinformatics continue to help to decipher the complex pathogenesis of atherosclerosis and inform the development of imaging tracers. Concomitant advances in tracer synthesis methods and PET imaging technology provide future possibilities for atherosclerosis imaging. In this Review, we summarize the latest developments in PET imaging techniques and technologies for assessment of atherosclerotic cardiovascular disease and discuss the relationship between imaging readouts and transcriptomics-based plaque phenotyping., (© 2024. Springer Nature Limited.)

Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with applications in disease diagnostics, intervention, and treatment planning. Accurate MRI segmentation is critical for diagnosing abnormalities, monitoring diseases, and deciding on a course of treatment. With the advent of advanced deep learning frameworks, fully automated and accurate MRI segmentation is advancing. Traditional supervised deep learning techniques have advanced tremendously, reaching clinical-level accuracy in the field of segmentation. However, these algorithms still require a large amount of annotated data, which is oftentimes unavailable or impractical. One way to circumvent this issue is to utilize algorithms that exploit a limited amount of labeled data. This paper aims to review such state-of-the-art algorithms that use a limited number of annotated samples. We explain the fundamental principles of self-supervised learning, generative models, few-shot learning, and semi-supervised learning and summarize their applications in cardiac, abdomen, and brain MRI segmentation. Throughout this review, we highlight algorithms that can be employed based on the quantity of annotated data available. We also present a comprehensive list of notable publicly available MRI segmentation datasets. To conclude, we discuss possible future directions of the field-including emerging algorithms, such as contrastive language-image pretraining, and potential combinations across the methods discussed-that can further increase the efficacy of image segmentation with limited labels., (© 2024 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Background: Coronary artery calcium (CAC) scans contain valuable information beyond the Agatston Score which is currently reported for predicting coronary heart disease (CHD) only. We examined whether new artificial intelligence (AI) algorithms applied to CAC scans may provide significant improvement in prediction of all cardiovascular disease (CVD) events in addition to CHD, including heart failure, atrial fibrillation, stroke, resuscitated cardiac arrest, and all CVD-related deaths., Methods: We applied AI-enabled automated cardiac chambers volumetry and automated calcified plaque characterization to CAC scans (AI-CAC) of 5830 individuals (52.2% women, age 61.7±10.2 years) without known CVD that were previously obtained for CAC scoring at the baseline examination of the Multi-Ethnic Study of Atherosclerosis (MESA). We used 15-year outcomes data and assessed discrimination using the time-dependent area under the curve (AUC) for AI-CAC versus the Agatston Score., Results: During 15 years of follow-up, 1773 CVD events accrued. The AUC at 1-, 5-, 10-, and 15-year follow up for AI-CAC vs Agatston Score was (0.784 vs 0.701), (0.771 vs. 0.709), (0.789 vs.0.712) and (0.816 vs. 0.729) (p<0.0001 for all), respectively. The category-free Net Reclassification Index of AI-CAC vs. Agatston Score at 1-, 5-, 10-, and 15-year follow up was 0.31, 0.24, 0.29 and 0.29 (p<.0001 for all), respectively. AI-CAC plaque characteristics including number, location, and density of plaque plus number of vessels significantly improved NRI for CAC 1-100 cohort vs. Agatston Score (0.342)., Conclusion: In this multi-ethnic longitudinal population study, AI-CAC significantly and consistently improved the prediction of all CVD events over 15 years compared with the Agatston score.

The decision to extubate patients on invasive mechanical ventilation is critical; however, clinician performance in identifying patients to liberate from the ventilator is poor. Machine Learning-based predictors using tabular data have been developed; however, these fail to capture the wide spectrum of data available. Here, we develop and validate a deep learning-based model using routinely collected chest X-rays to predict the outcome of attempted extubation. We included 2288 serial patients admitted to the Medical ICU at an urban academic medical center, who underwent invasive mechanical ventilation, with at least one intubated CXR, and a documented extubation attempt. The last CXR before extubation for each patient was taken and split 79/21 for training/testing sets, then transfer learning with k-fold cross-validation was used on a pre-trained ResNet50 deep learning architecture. The top three models were ensembled to form a final classifier. The Grad-CAM technique was used to visualize image regions driving predictions. The model achieved an AUC of 0.66, AUPRC of 0.94, sensitivity of 0.62, and specificity of 0.60. The model performance was improved compared to the Rapid Shallow Breathing Index (AUC 0.61) and the only identified previous study in this domain (AUC 0.55), but significant room for improvement and experimentation remains.

Background and Aims: Chronic stress associates with cardiovascular disease, but mechanisms remain incompletely defined. Advanced imaging was used to identify stress-related neural imaging phenotypes associated with atherosclerosis., Methods: Twenty-seven individuals with post-traumatic stress disorder (PTSD), 45 trauma-exposed controls without PTSD, and 22 healthy controls underwent 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI). Atherosclerotic inflammation and burden were assessed using 18F-FDG PET (as maximal target-to-background ratio, TBR max) and MRI, respectively. Inflammation was assessed using high-sensitivity C-reactive protein (hsCRP) and leucopoietic imaging (18F-FDG PET uptake in spleen and bone marrow). Stress-associated neural network activity (SNA) was assessed on 18F-FDG PET as amygdala relative to ventromedial prefrontal cortex (vmPFC) activity. MRI diffusion tensor imaging assessed the axonal integrity (AI) of the uncinate fasciculus (major white matter tract connecting vmPFC and amygdala)., Results: Median age was 37 years old and 54% of participants were female. There were no significant differences in atherosclerotic inflammation between participants with PTSD and controls; adjusted mean difference in TBR max (95% confidence interval) of the aorta 0.020 (-0.098, 0.138), and of the carotids 0.014 (-0.091, 0.119). Participants with PTSD had higher hsCRP, spleen activity, and aorta atherosclerotic burden (normalized wall index). Participants with PTSD also had higher SNA and lower AI. Across the cohort, carotid atherosclerotic burden (standard deviation of wall thickness) associated positively with SNA and negatively with AI independent of Framingham risk score., Conclusions: In this study of limited size, participants with PTSD did not have higher atherosclerotic inflammation than controls. Notably, impaired cortico-limbic interactions (higher amygdala relative to vmPFC activity or disruption of their intercommunication) associated with carotid atherosclerotic burden. Larger studies are needed to refine these findings., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: Heart rate variability (HRV) biofeedback is often performed with structured education, laboratory-based assessments, and practice sessions. It has been shown to improve psychological and physiological function across populations. However, a means to remotely use and monitor this approach would allow for wider use of this technique. Advancements in wearable and digital technology present an opportunity for the widespread application of this approach., Objective: The primary aim of the study was to determine the feasibility of fully remote, self-administered short sessions of HRV-directed biofeedback in a diverse population of health care workers (HCWs). The secondary aim was to determine whether a fully remote, HRV-directed biofeedback intervention significantly alters longitudinal HRV over the intervention period, as monitored by wearable devices. The tertiary aim was to estimate the impact of this intervention on metrics of psychological well-being., Methods: To determine whether remotely implemented short sessions of HRV biofeedback can improve autonomic metrics and psychological well-being, we enrolled HCWs across 7 hospitals in New York City in the United States. They downloaded our study app, watched brief educational videos about HRV biofeedback, and used a well-studied HRV biofeedback program remotely through their smartphone. HRV biofeedback sessions were used for 5 minutes per day for 5 weeks. HCWs were then followed for 12 weeks after the intervention period. Psychological measures were obtained over the study period, and they wore an Apple Watch for at least 7 weeks to monitor the circadian features of HRV., Results: In total, 127 HCWs were enrolled in the study. Overall, only 21 (16.5%) were at least 50% compliant with the HRV biofeedback intervention, representing a small portion of the total sample. This demonstrates that this study design does not feasibly result in adequate rates of compliance with the intervention. Numerical improvement in psychological metrics was observed over the 17-week study period, although it did not reach statistical significance (all P>.05). Using a mixed effect cosinor model, the mean midline-estimating statistic of rhythm (MESOR) of the circadian pattern of the SD of the interbeat interval of normal sinus beats (SDNN), an HRV metric, was observed to increase over the first 4 weeks of the biofeedback intervention in HCWs who were at least 50% compliant., Conclusions: In conclusion, we found that using brief remote HRV biofeedback sessions and monitoring its physiological effect using wearable devices, in the manner that the study was conducted, was not feasible. This is considering the low compliance rates with the study intervention. We found that remote short sessions of HRV biofeedback demonstrate potential promise in improving autonomic nervous function and warrant further study. Wearable devices can monitor the physiological effects of psychological interventions., (©Robert P Hirten, Matteo Danieletto, Kyle Landell, Micol Zweig, Eddye Golden, Renata Pyzik, Sparshdeep Kaur, Helena Chang, Drew Helmus, Bruce E Sands, Dennis Charney, Girish Nadkarni, Emilia Bagiella, Laurie Keefer, Zahi A Fayad. Originally published in JMIR Mental Health (https://mental.jmir.org), 25.04.2024.)

Objectives: Rheumatoid arthritis (RA) and atherosclerosis share many common inflammatory pathways. We studied whether a multi-biomarker panel for RA disease activity (MBDA) would associate with changes in arterial inflammation in an interventional trial., Methods: In the TARGET Trial, RA patients with active disease despite methotrexate were randomly assigned to the addition of either a TNF inhibitor or sulfasalazine+hydroxychloroquine (triple therapy). Baseline and 24-week follow-up 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography scans were assessed for change in arterial inflammation measured as the maximal arterial target-to-blood background ratio of FDG uptake in the most diseased segment of the carotid arteries or aorta (MDS-TBRmax). The MBDA test, measured at baseline and weeks 6, 18, and 24, was assessed for its association with the change in MDS-TBRmax., Results: Interpretable scans were available at baseline and week 24 for n = 112 patients. The MBDA score at week 24 was significantly correlated with the change in MDR-TBRmax (Spearman's rho = 0.239; p= 0.011) and remained significantly associated after adjustment for relevant confounders. Those with low MBDA at week 24 had a statistically significant adjusted reduction in arterial inflammation of 0.35 units vs no significant reduction in those who did not achieve low MBDA. Neither DAS28-CRP nor CRP predicted change in arterial inflammation. The MBDA component with the strongest association with change in arterial inflammation was serum amyloid A (SAA)., Conclusions: Among treated RA patients, achieved MBDA predicts of changes in arterial inflammation. Achieving low MBDA at 24 weeks was associated with clinically meaningful reductions in arterial inflammation, regardless of treatment., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: The mechanisms underlying the psychological and cardiovascular disease (CVD) benefits of physical activity (PA) are not fully understood., Objectives: This study tested whether PA: 1) attenuates stress-related neural activity, which is known to potentiate CVD and for its role in anxiety/depression; 2) decreases CVD in part through this neural effect; and 3) has a greater impact on CVD risk among individuals with depression., Methods: Participants from the Mass General Brigham Biobank who completed a PA survey were studied. A subset underwent 18 F-fluorodeoxyglucose positron emission tomography/computed tomographic imaging. Stress-related neural activity was measured as the ratio of resting amygdalar-to-cortical activity (AmygA C ). CVD events were ascertained from electronic health records., Results: A total of 50,359 adults were included (median age 60 years [Q1-Q3: 45-70 years]; 40.1% male). Greater PA was associated with both lower AmygA C (standardized β: -0.245; 95% CI: -0.444 to -0.046; P = 0.016) and CVD events (HR: 0.802; 95% CI: 0.719-0.896; P < 0.001) in multivariable models. AmygA C reductions partially mediated PA's CVD benefit (OR: 0.96; 95% CI: 0.92-0.99; P < 0.05). Moreover, PA's benefit on incident CVD events was greater among those with (vs without) preexisting depression (HR: 0.860; 95% CI: 0.810-0.915; vs HR: 0.929; 95% CI: 0.910-0.949; P interaction = 0.011). Additionally, PA above guideline recommendations further reduced CVD events, but only among those with preexisting depression (P interaction = 0.023)., Conclusions: PA appears to reduce CVD risk in part by acting through the brain's stress-related activity; this may explain the novel observation that PA reduces CVD risk to a greater extent among individuals with depression., Competing Interests: Funding Support and Author Disclosures This study is in part funded by National Institutes of Health (NIH) grants R56AR077187-01 and P01HL131478-05. This study was in part supported by NIH grants 1R01AR077187 (Dr Tawakol), P01HL131478 (Drs Tawakol and Fayad), K23HL151909 (Dr Osborne). Dr Osborne has received consulting fees from WCG Intrinsic Imaging, LLC, for unrelated work. Dr Choi has received support in part by funding from the National Institute of Mental Health (K08MH127413) and a NARSAD Brain and Behavior Foundation Young Investigator Award. Dr Smoller has received support for work outside the submitted research; is a member of the Scientific Advisory Board of Sensorium Therapeutics (with equity); has received an honorarium for an internal seminar at Tempus Labs and Biogen, Inc; and is PI of a study sponsored by 23andMe. Dr Tawakol has received grants from the National Institutes of Health, International Atomic Energy Agency, Osler/Harvard, and Lung Biotechnologies for work outside the submitted research. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Objective: The effect of mitral valve (MV) surgery on the natural history of ventricular arrhythmia (VA) in patients with arrhythmic MV prolapse remains unknown. We sought to evaluate the cumulative incidence of VA at 1 year after surgical mitral repair., Methods: A retrospective review of progressively captured data identified 204 consecutive patients who underwent elective MV repair for significant degenerative mitral regurgitation as a first-time cardiovascular intervention in a quaternary reference center between January 2018 and December 2020. A subset of 62 consecutive patients with diagnosed arrhythmic MV prolapse was further evaluated for recurrent VA after MV repair., Results: The median age was 62 years (range, 27-77 years) and 26 of 62 (41.9%) were female. The median time from initial mitral regurgitation/MV prolaspe diagnosis-to-referral was 13.8 years (interquartile range [IQR], 5.4-25) and from VA diagnosis-to-referral was 8 years (IQR, 3-10.6). Using the Lown-Wolf classification, complex VA (Lown grade ≥3) was identified in 36 of 62 patients (58%) at baseline, whereas 8 of 62 (13%) had a cardioverter/defibrillator implanted for primary (4/8) or secondary (4/8) prevention. Left ventricular myocardial scar was confirmed in 23 of 34 (68%) of patients scanned at baseline. The prevailing valve phenotype was bileaflet Barlow (59/62; 95.2%). All patients underwent surgical MV repair by the same team. Surgical repair was stabilized with an annuloplasty prosthesis (median size 36 mm [IQR, 34-38]). Concomitant procedures included tricuspid valve repair (51/62; 82.3%), cryo-maze ± left atrial appendage exclusion (14/62, 23%), and endocardial cryoablation of VA ectopy (4/62; 6.5%). The 30-day and 1-year freedom from recurrent VA were 98.4% and 75.9%, respectively. Absent VA after mitral repair was uniformly observed in patients with minor VA at baseline. Absent VA after mitral repair was uniformly observed in patients with minor VA preoperatively. Complex baseline VA was the strongest predictor of recurrent VA (hazard ratio, 10.8; 95% confidence interval, 1.4-84.2; P  = .024), irrespective of myocardial fibrosis., Conclusions: In a series of 62 consecutive patients operated electively for arrhythmic mitral prolapse, VA remained undetected in 75.9% of patients at 1 year. Freedom from recurrent VA was greater among patients without complex VA preoperatively, whereas baseline Lown grade ≥3 was the strongest independent risk factor for recurrent VA at 1 year. These findings attest to the importance of early recognition and prompt referral of patients with mitral prolapse and progressive VA to specialty interdisciplinary care., Competing Interests: D.P. received nonfinancial support from TOMTEC Imaging Systems GmbH (PI - research license for myocardial strain analysis software). M.M. has served as a consultant to Boston Scientific. D.A. is the National co-Principal Investigator for the Triluminate-II US Pivotal Trials, the Medtronic Apollo and CoreValve US Pivotal Trials, and ReChord US Pivotal Trial, respectively. The Icahn School of Medicine at Mount Sinai receives royalty payments from Edwards Lifesciences and Medtronic for intellectual property related to D.A.’s involvement in the development of 3 mitral valve repair rings and a tricuspid valve repair ring. All other authors reported no conflicts of interest. The Journal policy requires editors and reviewers to disclose conflicts of interest and to decline handling or reviewing manuscripts for which they may have a conflict of interest. The editors and reviewers of this article have no conflicts of interest., (© 2024 The Author(s).)

Background: Imaging with late gadolinium enhancement (LGE) magnetic resonance (MR) and 18 F-fluorodeoxyglucose ( 18 F-FDG) PET allows complementary assessment of myocardial injury and disease activity and has shown promise for improved characterization of active cardiac sarcoidosis (CS) based on the combined positive imaging outcome, MR(+)PET(+)., Objectives: This study aims to evaluate qualitative and quantitative assessments of hybrid MR/PET imaging in CS and to evaluate its association with cardiac-related outcomes., Methods: A total of 148 patients with suspected CS underwent hybrid MR/PET imaging. Patients were classified based on the presence/absence of LGE (MR+/MR-), presence/absence of 18 F-FDG (PET+/PET-), and pattern of 18 F-FDG uptake (focal/diffuse) into the following categories: MR(+)PET(+) FOCAL , MR(+)PET(+) DIFFUSE , MR(+)PET(-), MR(-)PET(+) FOCAL , MR(-)PET(+) DIFFUSE , MR(-)PET(-). Further analysis classified MR positivity based on %LGE exceeding 5.7% as MR(+/-) 5.7% . Quantitative values of standard uptake value, target-to-background ratio, target-to-normal-myocardium ratio (TNMRmax), and T2 were measured. The primary clinical endpoint was met by the occurrence of cardiac arrest, ventricular tachycardia, or secondary prevention implantable cardioverter-defibrillator (ICD) before the end of the study. The secondary endpoint was met by any of the primary endpoint criteria plus heart failure or heart block. MR/PET imaging results were compared between those meeting or not meeting the clinical endpoints., Results: Patients designated MR(+) 5.7% PET(+) FOCAL had increased odds of meeting the primary clinical endpoint compared to those with all other imaging classifications (unadjusted OR: 9.2 [95% CI: 3.0-28.7]; P = 0.0001), which was higher than the odds based on MR or PET alone. TNMRmax achieved an area under the receiver-operating characteristic curve of 0.90 for separating MR(+)PET(+) FOCAL from non-MR(+)PET(+) FOCAL , and 0.77 for separating those reaching the clinical endpoint from those not reaching the clinical endpoint., Conclusions: Hybrid MR/PET image-based classification of CS was statistically associated with clinical outcomes in CS. TNMRmax had modest sensitivity and specificity for quantifying the imaging-based classification MR(+)PET(+) FOCAL and was associated with outcomes. Use of combined MR and PET image-based classification may have use in prognostication and treatment management in CS., Competing Interests: Funding Support and Author Disclosures This work was supported by National Institutes of Health (NIH) grant R01 HL071021 (ZAF), NIH grant KL2 TR001435 (MGT), and AHA grant 20CDA35310099 (MGT). The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024. Published by Elsevier Inc.)

Nanomaterials have revolutionized medicine by enabling control over drugs' pharmacokinetics, biodistribution, and biocompatibility. However, most nanotherapeutic batches are highly heterogeneous, meaning they comprise nanoparticles that vary in size, shape, charge, composition, and ligand functionalization. Similarly, individual nanotherapeutics often have heterogeneously distributed components, ligands, and charges. This review discusses nanotherapeutic heterogeneity's sources and effects on experimental readouts and therapeutic efficacy. Among other topics, it demonstrates that heterogeneity exists in nearly all nanotherapeutic types, examines how nanotherapeutic heterogeneity arises, and discusses how heterogeneity impacts nanomaterials' in vitro and in vivo behavior. How nanotherapeutic heterogeneity skews experimental readouts and complicates their optimization and clinical translation is also shown. Lastly, strategies for limiting nanotherapeutic heterogeneity are reviewed and recommendations for developing more reproducible and effective nanotherapeutics provided., (© 2023 Wiley‐VCH GmbH.)

Background: Previous retrospective studies suggest a good diagnostic performance of 18 F-fluorodeoxyglucose positron emission tomography ( 18 F-FDG-PET)/computed tomography (CT) in left ventricular assist device (LVAD) infections. Our aim was to prospectively evaluate the role of PET/CT in the characterization and impact on clinical management of LVAD infections., Methods: A total of 40 patients (aged 58 [53-62] years) with suspected LVAD infection and 5 controls (aged 69 [64-71] years) underwent 18 F-FDG-PET/CT. Four LVAD components were evaluated: exit site and subcutaneous driveline (peripheral), pump pocket, and outflow graft. The location with maximal uptake was considered the presumed site of infection. Infection was confirmed by positive culture (exit site or blood) and/or surgical findings., Results: Visual uptake was present in 40 patients (100%) in the infection group vs 4 (80%) control subjects. For each individual component, the presence of uptake was more frequent in the infection than in the control group. The location of maximal uptake was most frequently the pump pocket (48%) in the infection group and the peripheral components (75%) in the control group. Maximum standard uptake values (SUV max ) were higher in the infection than in the control group: SUV max (average all components): 6.9 (5.1-8.5) vs 3.8 (3.7-4.3), p = 0.002; SUV max (location of maximal uptake): 10.6 ± 4.0 vs 5.4 ± 1.9, p = 0.01. Pump pocket infections were more frequent in patients with bacteremia than without bacteremia (79% vs 31%, p = 0.011). Pseudomonas (32%) and methicillin-susceptible Staphylococcus aureus (29%) were the most frequent pathogens and were associated with pump pocket infections, while Staphylococcus epidermis (11%) was associated with peripheral infections. PET/CT affected the clinical management of 83% of patients with infection, resulting in surgical debridement (8%), pump exchange (13%), and upgrade in the transplant listing status (10%), leading to 8% of urgent transplants., Conclusions: 18 F-FDG-PET/CT enables the diagnosis and characterization of the extent of LVAD infections, which can significantly affect the clinical management of these patients., (Copyright © 2023 International Society for the Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.)

While posttraumatic stress disorder (PTSD) is known to associate with an elevated risk for major adverse cardiovascular events (MACE), few studies have examined mechanisms underlying this link. Recent studies have demonstrated that neuro-immune mechanisms, (manifested by heightened stress-associated neural activity (SNA), autonomic nervous system activity, and inflammation), link common stress syndromes to MACE. However, it is unknown if neuro-immune mechanisms similarly link PTSD to MACE. The current study aimed to test the hypothesis that upregulated neuro-immune mechanisms increase MACE risk among individuals with PTSD. This study included N = 118,827 participants from a large hospital-based biobank. Demographic, diagnostic, and medical history data collected from the biobank. SNA (n = 1,520), heart rate variability (HRV; [n = 11,463]), and high sensitivity C-reactive protein (hs-CRP; [n = 15,164]) were obtained for a subset of participants. PTSD predicted MACE after adjusting for traditional MACE risk factors (hazard ratio (HR) [95 % confidence interval (CI)] = 1.317 [1.098, 1.580], β = 0.276, p = 0.003). The PTSD-to-MACE association was mediated by SNA (CI = 0.005, 0.133, p < 0.05), HRV (CI = 0.024, 0.056, p < 0.05), and hs-CRP (CI = 0.010, 0.040, p < 0.05). This study provides evidence that neuro-immune pathways may play important roles in the mechanisms linking PTSD to MACE. Future studies are needed to determine if these markers are relevant targets for PTSD treatment and if improvements in SNA, HRV, and hs-CRP associate with reduced MACE risk in this patient population., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Visual interpretation of PET and CMR may fail to identify cardiac sarcoidosis (CS) with high specificity. This study aimed to evaluate the role of [ 18 F]FDG PET and late gadolinium enhancement (LGE)-CMR radiomic features in differentiating CS from another cause of myocardial inflammation, in this case patients with cardiac-related clinical symptoms following COVID-19., Methods: [ 18 F]FDG PET and LGE-CMR were treated separately in this work. There were 35 post-COVID-19 (PC) and 40 CS datasets. Regions of interest were delineated manually around the entire left ventricle for the PET and LGE-CMR datasets. Radiomic features were then extracted. The ability of individual features to correctly identify image data as CS or PC was tested to predict the clinical classification of CS vs. PC using Mann-Whitney U -tests and logistic regression. Features were retained if the P -value was <0.00053, the AUC was >0.5, and the accuracy was >0.7. After applying the correlation test, uncorrelated features were used as a signature (joint features) to train machine learning classifiers. For LGE-CMR analysis, to further improve the results, different classifiers were used for individual features besides logistic regression, and the results of individual features of each classifier were screened to create a signature that included all features that followed the previously mentioned criteria and used it them as input for machine learning classifiers., Results: The Mann-Whitney U -tests and logistic regression were trained on individual features to build a collection of features. For [ 18 F]FDG PET analysis, the maximum target-to-background ratio ( TBR max ) showed a high area under the curve (AUC) and accuracy with small P -values (<0.00053), but the signature performed better (AUC 0.98 and accuracy 0.91). For LGE-CMR analysis, the Gray Level Dependence Matrix (gldm)-Dependence Non-Uniformity showed good results with small error bars (accuracy 0.75 and AUC 0.87). However, by applying a Support Vector Machine classifier to individual LGE-CMR features and creating a signature, a Random Forest classifier displayed better AUC and accuracy (0.91 and 0.84, respectively)., Conclusion: Using radiomic features may prove useful in identifying individuals with CS. Some features showed promising results in differentiating between PC and CS. By automating the analysis, the patient management process can be accelerated and improved., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declared that they were editorial board members of Frontiers at the time of submission. This had no impact on the peer review process or the final decision., (© 2024 Mushari, Soultanidis, Duff, Trivieri, Fayad, Robson and Tsoumpas.)

Macrophages are key inflammatory mediators in many pathological conditions, including cardiovascular disease (CVD) and cancer, the leading causes of morbidity and mortality worldwide. This makes macrophage burden a valuable diagnostic marker and several strategies to monitor these cells have been reported. However, such strategies are often high-priced, non-specific, invasive, and/or not quantitative. Here, we developed a positron emission tomography (PET) radiotracer based on apolipoprotein A1 (ApoA1), the main protein component of high-density lipoprotein (HDL), which has an inherent affinity for macrophages. We radiolabeled an ApoA1-mimetic peptide (mA1) with zirconium-89 ( 89 Zr) to generate a lipoprotein-avid PET probe ( 89 Zr-mA1). We first characterized 89 Zr-mA1's affinity for lipoproteins in vitro by size exclusion chromatography. To study 89 Zr-mA1's in vivo behavior and interaction with endogenous lipoproteins, we performed extensive studies in wildtype C57BL/6 and Apoe -/- hypercholesterolemic mice. Subsequently, we used in vivo PET imaging to study macrophages in melanoma and myocardial infarction using mouse models. The tracer's cell specificity was assessed by histology and mass cytometry (CyTOF). Our data show that 89 Zr-mA1 associates with lipoproteins in vitro. This is in line with our in vivo experiments, in which we observed longer 89 Zr-mA1 circulation times in hypercholesterolemic mice compared to C57BL/6 controls. 89 Zr-mA1 displayed a tissue distribution profile similar to ApoA1 and HDL, with high kidney and liver uptake as well as substantial signal in the bone marrow and spleen. The tracer also accumulated in tumors of melanoma-bearing mice and in the ischemic myocardium of infarcted animals. In these sites, CyTOF analyses revealed that nat Zr-mA1 was predominantly taken up by macrophages. Our results demonstrate that 89 Zr-mA1 associates with lipoproteins and hence accumulates in macrophages in vivo. 89 Zr-mA1's high uptake in these cells makes it a promising radiotracer for non-invasively and quantitatively studying conditions characterized by marked changes in macrophage burden., Competing Interests: Competing interestsW.J.M.M. is a founder and CSO of Trained Therapeutix Discovery. Z.A.F. is a founder and member of the board of Trained Therapeutix Discovery. T.R. is now an employee of and shareholder in Novartis AG. No other potential financial or non-financial conflicts of interest relevant to this article exist., (© The Author(s) 2024.)

Innate immune memory, also called "trained immunity," is a functional state of myeloid cells enabling enhanced immune responses. This phenomenon is important for host defense, but also plays a role in various immune-mediated conditions. We show that exogenously administered sphingolipids and inhibition of sphingolipid metabolizing enzymes modulate trained immunity. In particular, we reveal that acid ceramidase, an enzyme that converts ceramide to sphingosine, is a potent regulator of trained immunity. We show that acid ceramidase regulates the transcription of histone-modifying enzymes, resulting in profound changes in histone 3 lysine 27 acetylation and histone 3 lysine 4 trimethylation. We confirm our findings by identifying single-nucleotide polymorphisms in the region of ASAH1, the gene encoding acid ceramidase, that are associated with the trained immunity cytokine response. Our findings reveal an immunomodulatory effect of sphingolipids and identify acid ceramidase as a relevant therapeutic target to modulate trained immunity responses in innate immune-driven disorders., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The rapid rise of artificial intelligence (AI) in medicine in the last few years highlights the importance of developing bigger and better systems for data and model sharing. However, the presence of Protected Health Information (PHI) in medical data poses a challenge when it comes to sharing. One potential solution to mitigate the risk of PHI breaches is to exclusively share pre-trained models developed using private datasets. Despite the availability of these pre-trained networks, there remains a need for an adaptable environment to test and fine-tune specific models tailored for clinical tasks. This environment should be open for peer testing, feedback, and continuous model refinement, allowing dynamic model updates that are especially important in the medical field, where diseases and scanning techniques evolve rapidly. In this context, the Discovery Viewer (DV) platform was developed in-house at the Biomedical Engineering and Imaging Institute at Mount Sinai (BMEII) to facilitate the creation and distribution of cutting-edge medical AI models that remain accessible after their development. The all-in-one platform offers a unique environment for non-AI experts to learn, develop, and share their own deep learning (DL) concepts. This paper presents various use cases of the platform, with its primary goal being to demonstrate how DV holds the potential to empower individuals without expertise in AI to create high-performing DL models. We tasked three non-AI experts to develop different musculoskeletal AI projects that encompassed segmentation, regression, and classification tasks. In each project, 80% of the samples were provided with a subset of these samples annotated to aid the volunteers in understanding the expected annotation task. Subsequently, they were responsible for annotating the remaining samples and training their models through the platform's "Training Module". The resulting models were then tested on the separate 20% hold-off dataset to assess their performance. The classification model achieved an accuracy of 0.94, a sensitivity of 0.92, and a specificity of 1. The regression model yielded a mean absolute error of 14.27 pixels. And the segmentation model attained a Dice Score of 0.93, with a sensitivity of 0.9 and a specificity of 0.99. This initiative seeks to broaden the community of medical AI model developers and democratize the access of this technology to all stakeholders. The ultimate goal is to facilitate the transition of medical AI models from research to clinical settings.

Background: The main advantage of ultra-high field (UHF) magnetic resonance neuroimaging is theincreased signal-to-noise ratio (SNR) compared with lower field strength imaging. However, the wavelength effect associated with UHF MRI results in radiofrequency (RF) inhomogeneity, compromising whole brain coverage for many commercial coils. Approaches to resolving this issue of transmit field inhomogeneity include the design of parallel transmit systems (PTx), RF pulse design, and applying passive RF shimming such as high dielectric materials. However, these methods have some drawbacks such as unstable material parameters of dielectric pads, high-cost, and complexity of PTx systems. Metasurfaces are artificial structures with a unique platform that can control the propagation of the electromagnetic (EM) waves, and they are very promising for engineering EM device. Implementation of meta-arrays enhancing MRI has been explored previously in several studies., Purpose: The aim of this study was to assess the effect of new meta-array technology on enhancing the brain MRI at 7T. A meta-array based on a hybrid structure consisting of an array of broadside-coupled split-ring resonators and high-permittivity materials was designed to work at the Larmor frequency of a 7 Tesla (7T) MRI scanner. When placed behind the head and neck, this construct improves the SNR in the region of the cerebellum,brainstem and the inferior aspect of the temporal lobes., Methods: Numerical electromagnetic simulations were performed to optimize the meta-array design parameters and determine the RF circuit configuration. The resultant transmit-efficiency and signal sensitivity improvements were experimentally analyzed in phantoms followed by healthy volunteers using a 7T whole-body MRI scanner equipped with a standard one-channel transmit, 32-channel receive head coil. Efficacy was evaluated through acquisition with and without the meta-array using two basic sequences: gradient-recalled-echo (GRE) and turbo-spin-echo (TSE)., Results: Experimental phantom analysis confirmed two-fold improvement in the transmit efficiency and 1.4-fold improvement in the signal sensitivity in the target region. In vivo GRE and TSE images with the meta-array in place showed enhanced visualization in inferior regions of the brain, especially of the cerebellum, brainstem, and cervical spinal cord., Conclusion: Addition of the meta-array to commonly used MRI coils can enhance SNR to extend the anatomical coverage of the coil and improve overall MRI coil performance. This enhancement in SNR can be leveraged to obtain a higher resolution image over the same time slot or faster acquisition can be achieved with same resolution. Using this technique could improve the performance of existing commercial coils at 7T for whole brain and other applications., (© 2023 American Association of Physicists in Medicine.)

Background: The increasing use of smartphones, wearables, and connected devices has enabled the increasing application of digital technologies for research. Remote digital study platforms comprise a patient-interfacing digital application that enables multimodal data collection from a mobile app and connected sources. They offer an opportunity to recruit at scale, acquire data longitudinally at a high frequency, and engage study participants at any time of the day in any place. Few published descriptions of centralized digital research platforms provide a framework for their development., Objective: This study aims to serve as a road map for those seeking to develop a centralized digital research platform. We describe the technical and functional aspects of the ehive app, the centralized digital research platform of the Hasso Plattner Institute for Digital Health at Mount Sinai Hospital, New York, New York. We then provide information about ongoing studies hosted on ehive, including usership statistics and data infrastructure. Finally, we discuss our experience with ehive in the broader context of the current landscape of digital health research platforms., Methods: The ehive app is a multifaceted and patient-facing central digital research platform that permits the collection of e-consent for digital health studies. An overview of its development, its e-consent process, and the tools it uses for participant recruitment and retention are provided. Data integration with the platform and the infrastructure supporting its operations are discussed; furthermore, a description of its participant- and researcher-facing dashboard interfaces and the e-consent architecture is provided., Results: The ehive platform was launched in 2020 and has successfully hosted 8 studies, namely 6 observational studies and 2 clinical trials. Approximately 1484 participants downloaded the app across 36 states in the United States. The use of recruitment methods such as bulk messaging through the EPIC electronic health records and standard email portals enables broad recruitment. Light-touch engagement methods, used in an automated fashion through the platform, maintain high degrees of engagement and retention. The ehive platform demonstrates the successful deployment of a central digital research platform that can be modified across study designs., Conclusions: Centralized digital research platforms such as ehive provide a novel tool that allows investigators to expand their research beyond their institution, engage in large-scale longitudinal studies, and combine multimodal data streams. The ehive platform serves as a model for groups seeking to develop similar digital health research programs., International Registered Report Identifier (irrid): DERR1-10.2196/49204., (©Robert P Hirten, Matteo Danieletto, Kyle Landell, Micol Zweig, Eddye Golden, Georgy Orlov, Jovita Rodrigues, Eugenia Alleva, Ipek Ensari, Erwin Bottinger, Girish N Nadkarni, Thomas J Fuchs, Zahi A Fayad. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 16.11.2023.)

Background: Early prediction of the need for invasive mechanical ventilation (IMV) in patients hospitalized with COVID-19 symptoms can help in the allocation of resources appropriately and improve patient outcomes by appropriately monitoring and treating patients at the greatest risk of respiratory failure. To help with the complexity of deciding whether a patient needs IMV, machine learning algorithms may help bring more prognostic value in a timely and systematic manner. Chest radiographs (CXRs) and electronic medical records (EMRs), typically obtained early in patients admitted with COVID-19, are the keys to deciding whether they need IMV., Objective: We aimed to evaluate the use of a machine learning model to predict the need for intubation within 24 hours by using a combination of CXR and EMR data in an end-to-end automated pipeline. We included historical data from 2481 hospitalizations at The Mount Sinai Hospital in New York City., Methods: CXRs were first resized, rescaled, and normalized. Then lungs were segmented from the CXRs by using a U-Net algorithm. After splitting them into a training and a test set, the training set images were augmented. The augmented images were used to train an image classifier to predict the probability of intubation with a prediction window of 24 hours by retraining a pretrained DenseNet model by using transfer learning, 10-fold cross-validation, and grid search. Then, in the final fusion model, we trained a random forest algorithm via 10-fold cross-validation by combining the probability score from the image classifier with 41 longitudinal variables in the EMR. Variables in the EMR included clinical and laboratory data routinely collected in the inpatient setting. The final fusion model gave a prediction likelihood for the need of intubation within 24 hours as well., Results: At a prediction probability threshold of 0.5, the fusion model provided 78.9% (95% CI 59%-96%) sensitivity, 83% (95% CI 76%-89%) specificity, 0.509 (95% CI 0.34-0.67) F 1 -score, 0.874 (95% CI 0.80-0.94) area under the receiver operating characteristic curve (AUROC), and 0.497 (95% CI 0.32-0.65) area under the precision recall curve (AUPRC) on the holdout set. Compared to the image classifier alone, which had an AUROC of 0.577 (95% CI 0.44-0.73) and an AUPRC of 0.206 (95% CI 0.08-0.38), the fusion model showed significant improvement (P<.001). The most important predictor variables were respiratory rate, C-reactive protein, oxygen saturation, and lactate dehydrogenase. The imaging probability score ranked 15th in overall feature importance., Conclusions: We show that, when linked with EMR data, an automated deep learning image classifier improved performance in identifying hospitalized patients with severe COVID-19 at risk for intubation. With additional prospective and external validation, such a model may assist risk assessment and optimize clinical decision-making in choosing the best care plan during the critical stages of COVID-19., (©Kim-Anh-Nhi Nguyen, Pranai Tandon, Sahar Ghanavati, Satya Narayana Cheetirala, Prem Timsina, Robert Freeman, David Reich, Matthew A Levin, Madhu Mazumdar, Zahi A Fayad, Arash Kia. Originally published in JMIR Formative Research (https://formative.jmir.org), 26.10.2023.)

Background: The optimal treatment of intermediate-risk pulmonary embolism (PE) in hemodynamically stable patients remains unknown. Fibrinolytics reduce the risk of hemodynamic deterioration but increase bleeding risk. DS-1040, an inhibitor of thrombin-activatable fibrinolysis inhibitor, enhanced endogenous fibrinolytic activity without increasing bleeding risk in preclinical studies., Objectives: To evaluate the tolerability and explore the efficacy of DS-1040 in patients with acute PE., Methods: In this multicenter, randomized, double-blind, placebo-controlled study, ascending doses of intravenous DS-1040 (20-80 mg) or placebo were added to enoxaparin (1 mg/kg twice daily) in patients with intermediate-risk PE. The primary endpoint was the number of patients with major or clinically relevant nonmajor bleeding. The percentage change in thrombus volume and right-to-left ventricular dimensions, assessed using quantitative computed tomography pulmonary angiography, at baseline and after 12 to 72 hours were used to explore the efficacy of DS-1040., Results: Of 125 patients with all available data, 38 were randomized to placebo and 87 to DS-1040. The primary endpoint occurred in 1 patient in the placebo group (2.6%) and 4 patients who received DS-1040 (4.6%). One subject experienced major bleeding (DS-1040 80 mg group); no fatal or intracranial bleeding occurred. Thrombus volume was 25% to 45% lower after infusion, with no differences between the DS-1040 and placebo groups. There was no difference in the change from baseline right-to-left ventricular dimensions between the DS-1040 and placebo groups., Conclusion: In patients with acute PE, adding DS-1040 to standard anticoagulation was not associated with an increase in bleeding but did not improve thrombus resolution or right ventricular dilation., (Copyright © 2023 International Society on Thrombosis and Haemostasis. All rights reserved.)

Background: Substantial effort has been directed toward demonstrating uses of predictive models in health care. However, implementation of these models into clinical practice may influence patient outcomes, which in turn are captured in electronic health record data. As a result, deployed models may affect the predictive ability of current and future models., Objective: To estimate changes in predictive model performance with use through 3 common scenarios: model retraining, sequentially implementing 1 model after another, and intervening in response to a model when 2 are simultaneously implemented., Design: Simulation of model implementation and use in critical care settings at various levels of intervention effectiveness and clinician adherence. Models were either trained or retrained after simulated implementation., Setting: Admissions to the intensive care unit (ICU) at Mount Sinai Health System (New York, New York) and Beth Israel Deaconess Medical Center (Boston, Massachusetts)., Patients: 130 000 critical care admissions across both health systems., Intervention: Across 3 scenarios, interventions were simulated at varying levels of clinician adherence and effectiveness., Measurements: Statistical measures of performance, including threshold-independent (area under the curve) and threshold-dependent measures., Results: At fixed 90% sensitivity, in scenario 1 a mortality prediction model lost 9% to 39% specificity after retraining once and in scenario 2 a mortality prediction model lost 8% to 15% specificity when created after the implementation of an acute kidney injury (AKI) prediction model; in scenario 3, models for AKI and mortality prediction implemented simultaneously, each led to reduced effective accuracy of the other by 1% to 28%., Limitations: In real-world practice, the effectiveness of and adherence to model-based recommendations are rarely known in advance. Only binary classifiers for tabular ICU admissions data were simulated., Conclusion: In simulated ICU settings, a universally effective model-updating approach for maintaining model performance does not seem to exist. Model use may have to be recorded to maintain viability of predictive modeling., Primary Funding Source: National Center for Advancing Translational Sciences., Competing Interests: Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M23-0949.

The current standard for measuring coronary artery calcification to determine the extent of atherosclerosis is by calculating the Agatston score from computed tomography (CT). However, the Agatston score disregards pixel values less than 130 Hounsfield Units (HU) and calcium regions less than 1 mm 2 . Due to this thresholding, the score is not sensitive to small, weakly attenuating regions of calcium deposition and may not detect nascent micro-calcification. A recently proposed metric called the spatially weighted calcium score (SWCS) also utilizes CT but does not include a threshold for HU and does not require elevated signals in contiguous pixels. Thus, the SWCS is sensitive to weakly attenuating, smaller calcium deposits and may improve the measurement of coronary heart disease risk. Currently, the SWCS is underutilized owing to the added computational complexity. To promote translation of the SWCS into clinical research and reliable, repeatable computation of the score, the aim of this study was to develop a semi-automatic graphical tool that calculates both the SWCS and the Agatston score. The program requires gated cardiac CT scans with a calcium hydroxyapatite phantom in the field of view. The phantom allows for deriving a weighting function, from which each pixel's weight is adjusted, allowing for the mitigation of signal variations and variability between scans. With all three anatomical views visible simultaneously, the user traces the course of the four main coronary arteries by placing points or regions of interest. Features such as scroll-to-zoom, double-click to delete, and brightness/contrast adjustment, along with written guidance at every step, make the program user-friendly and easy to use. Once tracing the arteries is complete, the program generates reports, which include the scores and snapshots of any visible calcium. The SWCS may reveal the presence of subclinical disease, which may be used for early intervention and lifestyle changes.

Immunoparalysis is a compensatory and persistent anti-inflammatory response to trauma, sepsis or another serious insult, which increases the risk of opportunistic infections, morbidity and mortality. Here, we show that in cultured primary human monocytes, interleukin-4 (IL4) inhibits acute inflammation, while simultaneously inducing a long-lasting innate immune memory named trained immunity. To take advantage of this paradoxical IL4 feature in vivo, we developed a fusion protein of apolipoprotein A1 (apoA1) and IL4, which integrates into a lipid nanoparticle. In mice and non-human primates, an intravenously injected apoA1-IL4-embedding nanoparticle targets myeloid-cell-rich haematopoietic organs, in particular, the spleen and bone marrow. We subsequently demonstrate that IL4 nanotherapy resolved immunoparalysis in mice with lipopolysaccharide-induced hyperinflammation, as well as in ex vivo human sepsis models and in experimental endotoxemia. Our findings support the translational development of nanoparticle formulations of apoA1-IL4 for the treatment of patients with sepsis at risk of immunoparalysis-induced complications., (© 2023. The Author(s).)

Competing Interests: Disclosures None.

Background: Sustained ventricular tachycardia and sudden cardiac death due to degenerative mitral valve prolapse (MVP) can occur in the absence of severe mitral regurgitation (MR). A significant percentage of patients with MVP-related sudden death do not have any evidence of replacement fibrosis, suggesting other unrecognized proarrhythmic factors may place these patients at risk., Objectives: This study aims to characterize myocardial fibrosis/inflammation and ventricular arrhythmia complexity in patients with MVP and only mild or moderate MR., Methods: Prospective observational study of patients with MVP and only mild or moderate MR underwent ventricular arrhythmia characterization and hybrid positron emission tomography (PET)/magnetic resonance imaging (MRI). Coregistered hybrid 18 F - fluorodeoxyglucose ( 18 F-FDG)-PET and MRI late gadolinium enhancement images were assessed and categorized. Recruitment occurred in the cardiac electrophysiology clinic., Results: In 12 patients with degenerative MVP with only mild or moderate MR, of which a majority had complex ventricular ectopy (n = 10, 83%), focal (or focal-on-diffuse) uptake of 18 F-FDG (PET-positive) was detected in 83% (n = 10) of patients. Three-quarters of the patients (n = 9, 75%) had FDG uptake that coexisted with areas of late gadolinium enhancement (PET/MRI-positive). Abnormal T1, T2 and extracellular volume (ECV) values were observed in 58% (n = 7), 25% (n = 3), and 16% (n = 2), respectively., Conclusions: Most patients with degenerative MVP, ventricular ectopy, and mild or moderate MR show myocardial inflammation that is concordant with myocardial scar. Further study is needed to determine whether these findings contribute to the observation that most MVP-related sudden deaths occur in patients with less than severe MR., Competing Interests: Funding Support and Author Disclosures This work was supported by National Institutes of Health grant R01 HL071021 (Dr Fayad) and the KL2 TR001435 (Dr Trivieri). Dr Devesa is recipient of the “Alfonso Martin Escudero” grant. Dr Miller has served as a consultant to Boston Scientific. Dr Dukkipati has received research grant support from Biosense Webster. Dr Reddy has received research grants from and served as a consultant for Biosense Webster, Boston Scientific, Biotronik, and Abbott. Dr Adams declares that The Icahn School of Medicine at Mount Sinai receives royalty payments from Edwards Lifesciences for intellectual property related to the development of 2 mitral valve repair rings, and from Medtronic for intellectual property related to the development of two tricuspid valve repair rings; is the National Co-Principal Investigator for the Medtronic CoreValve, NeoChord System, Medtronic Apollo, and Triluminate-II U.S. Pivotal Trials, respectively. Icahn School of Medicine receives royalties for Dr Adam’s intellectual property from Edwards Lifesciences and Medtronic, related to valve repair rings. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023. Published by Elsevier Inc.)

Background: Patellofemoral anatomy has not been well characterized. Applying deep learning to automatically measure knee anatomy can provide a better understanding of anatomy, which can be a key factor in improving outcomes., Methods: 483 total patients with knee CT imaging (April 2017-May 2022) from 6 centers were selected from a cohort scheduled for knee arthroplasty and a cohort with healthy knee anatomy. A total of 7 patellofemoral landmarks were annotated on 14,652 images and approved by a senior musculoskeletal radiologist. A two-stage deep learning model was trained to predict landmark coordinates using a modified ResNet50 architecture initialized with self-supervised learning pretrained weights on RadImageNet. Landmark predictions were evaluated with mean absolute error, and derived patellofemoral measurements were analyzed with Bland-Altman plots. Statistical significance of measurements was assessed by paired t -tests., Results: Mean absolute error between predicted and ground truth landmark coordinates was 0.20/0.26 cm in the healthy/arthroplasty cohort. Four knee parameters were calculated, including transepicondylar axis length, transepicondylar-posterior femur axis angle, trochlear medial asymmetry, and sulcus angle. There were no statistically significant parameter differences ( p > 0.05) between predicted and ground truth measurements in both cohorts, except for the healthy cohort sulcus angle., Conclusion: Our model accurately identifies key trochlear landmarks with ~0.20-0.26 cm accuracy and produces human-comparable measurements on both healthy and pathological knees. This work represents the first deep learning regression model for automated patellofemoral annotation trained on both physiologic and pathologic CT imaging at this scale. This novel model can enhance our ability to analyze the anatomy of the patellofemoral compartment at scale.

Background: Chronic stress associates with major adverse cardiovascular events (MACE) via increased stress-related neural network activity (SNA). Light/moderate alcohol consumption (AC l/m ) has been linked to lower MACE risk, but the mechanisms are unclear., Objectives: The purpose of this study was to evaluate whether the association between AC l/m and MACE is mediated by decreased SNA., Methods: Individuals enrolled in the Mass General Brigham Biobank who completed a health behavior survey were studied. A subset underwent 18 F-fluorodeoxyglucose positron emission tomography, enabling assessment of SNA. Alcohol consumption was classified as none/minimal, light/moderate, or high (<1, 1-14, or >14 drinks/week, respectively)., Results: Of 53,064 participants (median age 60 years, 60% women), 23,920 had no/minimal alcohol consumption and 27,053 AC l/m . Over a median follow-up of 3.4 years, 1,914 experienced MACE. AC l/m (vs none/minimal) associated with lower MACE risk (HR: 0.786; 95% CI: 0.717-0.862; P < 0.0001) after adjusting for cardiovascular risk factors. In 713 participants with brain imaging, AC l/m (vs none/minimal) associated with decreased SNA (standardized beta -0.192; 95% CI: -0.338 to -0.046; P = 0.01). Lower SNA partially mediated the beneficial effect of AC l/m on MACE (log OR: -0.040; 95% CI: -0.097 to -0.003; P < 0.05). Further, AC l/m associated with larger decreases in MACE risk among individuals with (vs without) prior anxiety (HR: 0.60 [95% CI: 0.50-0.72] vs 0.78 [95% CI: 0.73-0.80]; P interaction = 0.003)., Conclusions: AC l/m associates with reduced MACE risk, in part, by lowering activity of a stress-related brain network known for its association with cardiovascular disease. Given alcohol's potential health detriments, new interventions with similar effects on SNA are needed., Competing Interests: Funding Support and Author Disclosures This study was in part supported by National Institutes of Health grants 1R01AR077187 (to Dr Tawakol), 5P01HL131478 (to Dr Tawakol), K23HL151909 (to Dr Osborne). Dr Osborne has served as a consultant to WCG Intrinsic Imaging, LLC, unrelated to this work. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

The development of new immunotherapies to treat the inflammatory mechanisms that sustain atherosclerotic cardiovascular disease (ASCVD) is urgently needed. Herein, we present a path to drug repurposing to identify immunotherapies for ASCVD. The integration of time-of-flight mass cytometry and RNA sequencing identified unique inflammatory signatures in peripheral blood mononuclear cells stimulated with ASCVD plasma. By comparing these inflammatory signatures to large-scale gene expression data from the LINCS L1000 dataset, we identified drugs that could reverse this inflammatory response. Ex vivo screens, using human samples, showed that saracatinib-a phase 2a-ready SRC and ABL inhibitor-reversed the inflammatory responses induced by ASCVD plasma. In Apoe -/- mice, saracatinib reduced atherosclerosis progression by reprogramming reparative macrophages. In a rabbit model of advanced atherosclerosis, saracatinib reduced plaque inflammation measured by [ 18 F] fluorodeoxyglucose positron emission tomography-magnetic resonance imaging. Here we show a systems immunology-driven drug repurposing with a preclinical validation strategy to aid the development of cardiovascular immunotherapies., Competing Interests: Competing Interests statement C.G. is listed as an inventor on patent application Tech 160808G PCT/US2022/017777, filed by the Icahn School of Medicine at Mount Sinai (patent applicant), that is directly related to the method used in this manuscript to identify saracatinib as an antiatherosclerotic agent. The remaining authors declare no competing interests.

Background: The aim of this study is to explore the utility of cardiac magnetic resonance (CMR) imaging of radiomic features to distinguish active and inactive cardiac sarcoidosis (CS)., Methods: Subjects were classified into active cardiac sarcoidosis (CS active ) and inactive cardiac sarcoidosis (CS inactive ) based on PET-CMR imaging. CS active was classified as featuring patchy [ 18 F]fluorodeoxyglucose ([ 18 F]FDG) uptake on PET and presence of late gadolinium enhancement (LGE) on CMR, while CS inactive was classified as featuring no [ 18 F]FDG uptake in the presence of LGE on CMR. Among those screened, thirty CS active and thirty-one CS inactive patients met these criteria. A total of 94 radiomic features were subsequently extracted using PyRadiomics. The values of individual features were compared between CS active and CS inactive using the Mann-Whitney U test. Subsequently, machine learning (ML) approaches were tested. ML was applied to two sub-sets of radiomic features (signatures A and B) that were selected by logistic regression and PCA, respectively., Results: Univariate analysis of individual features showed no significant differences. Of all features, gray level co-occurrence matrix (GLCM) joint entropy had a good area under the curve (AUC) and accuracy with the smallest confidence interval, suggesting it may be a good target for further investigation. Some ML classifiers achieved reasonable discrimination between CS active and CS inactive patients. With signature A, support vector machine and k-neighbors showed good performance with AUC (0.77 and 0.73) and accuracy (0.67 and 0.72), respectively. With signature B, decision tree demonstrated AUC and accuracy around 0.7; Conclusion: CMR radiomic analysis in CS provides promising results to distinguish patients with active and inactive disease.

Objective: To assess whether an individual's degree of psychological resilience can be determined from physiological metrics passively collected from a wearable device., Materials and Methods: Data were analyzed in this secondary analysis of the Warrior Watch Study dataset, a prospective cohort of healthcare workers enrolled across 7 hospitals in New York City. Subjects wore an Apple Watch for the duration of their participation. Surveys were collected measuring resilience, optimism, and emotional support at baseline., Results: We evaluated data from 329 subjects (mean age 37.4 years, 37.1% male). Across all testing sets, gradient-boosting machines (GBM) and extreme gradient-boosting models performed best for high- versus low-resilience prediction, stratified on a median Connor-Davidson Resilience Scale-2 score of 6 (interquartile range = 5-7), with an AUC of 0.60. When predicting resilience as a continuous variable, multivariate linear models had a correlation of 0.24 ( P  = .029) and RMSE of 1.37 in the testing data. A positive psychological construct, comprised of resilience, optimism, and emotional support was also evaluated. The oblique random forest method performed best in estimating high- versus low-composite scores stratified on a median of 32.5, with an AUC of 0.65, a sensitivity of 0.60, and a specificity of 0.70., Discussion: In a post hoc analysis, machine learning models applied to physiological metrics collected from wearable devices had some predictive ability in identifying resilience states and a positive psychological construct., Conclusions: These findings support the further assessment of psychological characteristics from passively collected wearable data in dedicated studies., Competing Interests: DC is a coinventor on patents filed by the Icahn School of Medicine at Mount Sinai (ISMMS) relating to the treatment for treatment-resistant depression, suicidal ideation, and other disorders. ISMMS has entered into a licensing agreement with Janssen Pharmaceuticals, Inc, and it has received and will receive payments from Janssen under the license agreement related to these patents for the treatment of treatment-resistant depression and suicidal ideation. Consistent with the ISMMS Faculty Handbook (the medical school policy), DC is entitled to a portion of the payments received by the ISMMS. Because SPRAVATO has received regulatory approval for treatment-resistant depression, through the ISMMS, DC will be entitled to additional payments beyond those already received under the license agreement. DC is a named coinventor on several patents filed by ISMMS for a cognitive training intervention to treat depression and related psychiatric disorders. The ISMMS has entered into a licensing agreement with Click Therapeutics, Inc and has received and will receive payments related to the use of this cognitive training intervention for the treatment of psychiatric disorders. In accordance with the ISMMS Faculty Handbook, DC has received a portion of these payments and is entitled to a portion of any additional payments that the medical school may receive from this license with Click Therapeutics. DC is a named coinventor on a patent application filed by the ISMMS for the use of intranasally administered Neuropeptide Y for the treatment of mood and anxiety disorders. This intellectual property has not been licensed. DC is a named coinventor on a patent application in the United States and several issued patents outside the United States filed by the ISMMS related to the use of ketamine for the treatment of posttraumatic stress disorder. This intellectual property has not been licensed. EPB reports consultancy agreements with Deloitte and Roland Berger; ownership interest in Digital Medicine E. Böttinger GmbH, EBCW GmbH, and Ontomics, Inc; receiving honoraria from Bayer, Bosch Health Campus, Sanofi, and Siemens; and serving as a scientific advisor or member of Bosch Health Campus and Seer Biosciences Inc. LK declares research funding from Abbvie and Pfizer, consulting for Abbvie and Pfizer, and equity ownership/stock options in MetaMe Health and Trellus Health. MS-F declares research support from Novartis and Allergenis. GNN reports employment with, consultancy agreements with, and ownership interest in Pensieve Health and Renalytix AI; receiving consulting fees from AstraZeneca, BioVie, GLG Consulting, and Reata; and serving as a scientific advisor or member of Pensieve Health and Renalytix AI. ZAF discloses consulting fees from Alexion, GlaxoSmithKline, and Trained Therapeutix Discovery and research funding from Daiichi Sankyo, Amgen, Bristol Myers Squibb, and Siemens Healthineers. ZAF receives financial compensation as a board member and advisor to Trained Therapeutix Discovery and owns equity in Trained Therapeutix Discovery as a cofounder. The remaining authors declare no conflicts of interest., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Introduction: Interpretation of high-resolution CT images plays an important role in the diagnosis and management of interstitial lung diseases. However, interreader variation may exist due to varying levels of training and expertise. This study aims to evaluate interreader variation and the role of thoracic radiology training in classifying interstitial lung disease (ILD)., Methods: This is a retrospective study where seven physicians (radiologists, thoracic radiologists, and a pulmonologist) classified the subtypes of ILD of 128 patients from a tertiary referral center, all selected from the Interstitial Lung Disease Registry which consists of patients from November 2014 to January 2021. Each patient was diagnosed with a subtype of interstitial lung disease by a consensus diagnosis from pathology, radiology, and pulmonology. Each reader was provided with only clinical history, only CT images, or both. Reader sensitivity and specificity and interreader agreements using Cohen's κ were calculated., Results: Interreader agreement based only on clinical history, only on radiologic information, or combination of both was most consistent amongst readers with thoracic radiology training, ranging from fair (Cohen's κ: 0.2-0.46), moderate to almost perfect (Cohen's κ: 0.55-0.92), and moderate to almost perfect (Cohen's κ: 0.53-0.91) respectively. Radiologists with any thoracic training showed both increased sensitivity and specificity for NSIP as compared to other radiologists and the pulmonologist when using only clinical history, only CT information, or combination of both (p < 0.05)., Conclusions: Readers with thoracic radiology training showed the least interreader variation and were more sensitive and specific at classifying certain subtypes of ILD., Summary Sentence: Thoracic radiology training may improve sensitivity and specificity in classifying ILD based on HRCT images and clinical history., (Copyright © 2023 Elsevier Inc. All rights reserved.)

For accurate diagnosis of interstitial lung disease (ILD), a consensus of radiologic, pathological, and clinical findings is vital. Management of ILD also requires thorough follow-up with computed tomography (CT) studies and lung function tests to assess disease progression, severity, and response to treatment. However, accurate classification of ILD subtypes can be challenging, especially for those not accustomed to reading chest CTs regularly. Dynamic models to predict patient survival rates based on longitudinal data are challenging to create due to disease complexity, variation, and irregular visit intervals. Here, we utilize RadImageNet pretrained models to diagnose five types of ILD with multimodal data and a transformer model to determine a patient's 3-year survival rate. When clinical history and associated CT scans are available, the proposed deep learning system can help clinicians diagnose and classify ILD patients and, importantly, dynamically predict disease progression and prognosis., (© 2023. The Author(s).)

In the past 2 decades, research on atherosclerotic cardiovascular disease has uncovered inflammation to be a key driver of the pathophysiological process. A pressing need therefore exists to quantitatively and longitudinally probe inflammation, in preclinical models and in cardiovascular disease patients, ideally using non-invasive methods and at multiple levels. Here, we developed and employed in vivo multiparametric imaging approaches to investigate the immune response following myocardial infarction. The myocardial infarction models encompassed either transient or permanent left anterior descending coronary artery occlusion in C57BL/6 and Apoe -/- mice. We performed nanotracer-based fluorine magnetic resonance imaging and positron emission tomography (PET) imaging using a CD11b-specific nanobody and a C-C motif chemokine receptor 2-binding probe. We found that immune cell influx in the infarct was more pronounced in the permanent occlusion model. Further, using 18 F-fluorothymidine and 18 F-fluorodeoxyglucose PET, we detected increased hematopoietic activity after myocardial infarction, with no difference between the models. Finally, we observed persistent systemic inflammation and exacerbated atherosclerosis in Apoe -/- mice, regardless of which infarction model was used. Taken together, we showed the strengths and capabilities of multiparametric imaging in detecting inflammatory activity in cardiovascular disease, which augments the development of clinical readouts., Competing Interests: This work was supported by National Institute of Health grants R01HL143814 (to Dr Fayad), P01HL131478 (Drs Fayad and Mulder), P41EB025815 (Drs Liu and Gropler ), R35HL145212 (Dr Liu), and R35HL139598 (Dr Nahrendorf) and award K22CA226040 (Dr Rashidian). This work was also supported by an Innovation Research Fund Basic Research Award from the Dana-Farber Cancer Institute (Dr Rashidian). Dr Maier was supported by Deutsche Forschungsgemeinschaft grants (MA 7059/1 and MA 7059/3-1) and is part of SFB1425 funded by the Deutsche Forschungsgemeinschaft (project no. 422681845). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2023 The Authors.)

Background: Air pollution and noise exposures individually associate with major adverse cardiovascular events (MACE) via a mechanism involving arterial inflammation (ArtI); however, their combined impact on ArtI and MACE remains unknown. We tested whether dual (vs. one or neither) exposure associates with greater ArtI and MACE risk and whether MACE risk is mediated via ArtI., Methods: Individuals (N = 474) without active cancer or known cardiovascular disease with clinical 18 F-FDG-PET/CT imaging were followed for 5 years for MACE. ArtI was measured. Average air pollution (particulate matter ≤ 2.5 μm, PM 2.5 ) and transportation noise exposure were determined at individual residences. Higher exposures were defined as noise > 55 dBA (World Health Organization cutoff) and PM 2.5 ≥ sample median., Results: At baseline, 46%, 46%, and 8% were exposed to high levels of neither, one, or both pollutants; 39 experienced MACE over a median 4.1 years. Exposure to an increasing number of pollutants associated with higher ArtI (standardized β [95% CI: .195 [.052, .339], P = .008) and MACE (HR [95% CI]: 2.897 [1.818-4.615], P < .001). In path analysis, ArtI partially mediated the relationship between pollutant exposures and MACE (P < .05)., Conclusion: Air pollution and transportation noise exposures contribute incrementally to ArtI and MACE. The mechanism linking dual exposure to MACE involves ArtI., (© 2022. The Author(s) under exclusive licence to American Society of Nuclear Cardiology.)

Purpose: To further characterize the relationship between obstructive sleep apnea (OSA) and carotid atherosclerosis, we examined the structural and metabolic features of carotid plaque using hybrid 18-F-fluorodeoxyglucose (FDG) Positron Emission Tomography/Magnetic Resonance Imaging (PET/MRI) in the Multi-Ethnic Study of Atherosclerosis (MESA)., Methods: We studied 46 individuals from the MESA-PET and MESA-Sleep ancillary studies. OSA was defined as an apnea hypopnea index [AHI] ≥ 15 events per hour (4% desaturation). PET/MRI was used to measure carotid plaque inflammation (using target-to-background-ratios [TBR]) and carotid wall thickness (CWT). Linear regression was used to assess the associations between OSA, CWT and TBR., Results: The mean age was 67.9 years (SD 8.53) and the mean BMI was 28.9 kg/m 2 (SD 4.47). There was a trend toward a higher mean CWT in the OSA (n = 11) vs. non-OSA group (n = 35), 1.51 vs. 1.41 (p = 0.098). TBR did not differ by OSA groups, and there was no significant association between OSA and carotid plaque inflammation (TBR) in adjusted analyses. Although there was a significant interaction between OSA and obesity, there were no statistically significant associations between OSA and vascular inflammation in stratified analysis by obesity., Conclusion: Despite a trend toward a higher carotid wall thickness in OSA vs. non-OSA participants, we did not find an independent association between OSA and carotid plaque inflammation using PET/MRI in MESA. Our findings suggest that simultaneous assessments of structural and metabolic features of atherosclerosis may fill current knowledge gaps pertaining to the influence of OSA on atherosclerosis prevalence and progression., (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)

Myocardial infarction, stroke, mental disorders, neurodegenerative processes, autoimmune diseases, cancer and the human immunodeficiency virus impact the haematopoietic system, which through immunity and inflammation may aggravate pre-existing atherosclerosis. The interplay between the haematopoietic system and its modulation of atherosclerosis has been studied by imaging the cardiovascular system and the activation of haematopoietic organs via scanners integrating positron emission tomography and resonance imaging (PET/MRI). In this Perspective, we review the applicability of integrated whole-body PET/MRI for the study of immune-mediated phenomena associated with haematopoietic activity and cardiovascular disease, and discuss the translational opportunities and challenges of the technology., (© 2022. Springer Nature Limited.)

Objective: Recent large-scale randomised trials demonstrate that immunomodulators reduce cardiovascular (CV) events among the general population. However, it is uncertain whether these effects apply to rheumatoid arthritis (RA) and if certain treatment strategies in RA reduce CV risk to a greater extent., Methods: Patients with active RA despite use of methotrexate were randomly assigned to addition of a tumour necrosis factor (TNF) inhibitor (TNFi) or addition of sulfasalazine and hydroxychloroquine (triple therapy) for 24 weeks. Baseline and follow-up 18 F-fluorodeoxyglucose-positron emission tomography/CT scans were assessed for change in arterial inflammation, an index of CV risk, measured as an arterial target-to-background ratio (TBR) in the carotid arteries and aorta., Results: 115 patients completed the protocol. The two treatment groups were well balanced with a median age of 58 years, 71% women, 57% seropositive and a baseline disease activity score in 28 joints of 4.8 (IQR 4.0, 5.6). Baseline TBR was similar across the two groups. Significant TBR reductions were observed in both groups-ΔTNFi: -0.24 (SD=0.51), Δtriple therapy: -0.19 (SD=0.51)-without difference between groups (difference in Δs: -0.02, 95% CI -0.19 to 0.15, p=0.79). While disease activity was significantly reduced across both treatment groups, there was no association with change in TBR (β=0.04, 95% CI -0.03 to 0.10)., Conclusion: We found that addition of either a TNFi or triple therapy resulted in clinically important improvements in vascular inflammation. However, the addition of a TNFi did not reduce arterial inflammation more than triple therapy., Trial Registration Number: NCT02374021., Competing Interests: Competing interests: DHS receives research support through his institution from Abbvie, Amgen, CorEvitas and Moderna. He receives royalties from UpToDate on unrelated chapters. JTG has been a consultant for AbbVie, Pfizer, Eli Lilly and Company, Bristol Meyers Squibb, Gilead, Novartis in the last 3 years and received an unrestricted grant from Pfizer. Over the past 36 months, PMR received investigator-initiated research grant support from Novartis, Kowa, Amarin, Pfizer, Esperion, NHLBI, NCI and Operation Warp Speed; served as a consultant to Corvidia, Novartis, Flame, Agepha, Alynlam, IQVIA, R-Pharma, Horizon Therapeutics, Inflazome, AstraZeneca, Jannsen, Civi Biopharm, SOCAR, Novo Nordisk, Health Outlook, Omeicos, the Baim Institute, Boehringer-Ingelheim, Montai Health, Cardiol Therapeutics, the Peter Munk Institute (University of Toronto); and the Foundation Leducq (Paris, FR); and received non-monetary research support from the Pfizer Bristol Myers Squibb Alliance and from Quidel, Inc to conduct federally funded COVID-19 research. PMRo is also listed as a co-inventor on patents held by his institution, the Brigham and Women’s Hospital. None of these conflicts relate to the current manuscript. JMB has nothing to declare., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Patients recovered from COVID-19 may develop long-COVID symptoms in the lung. For this patient population (post-COVID patients), they may benefit from longitudinal, radiation-free lung MRI exams for monitoring lung lesion development and progression. The purpose of this study was to investigate the performance of a spiral ultrashort echo time MRI sequence (Spiral-VIBE-UTE) in a cohort of post-COVID patients in comparison with CT and to compare image quality obtained using different spiral MRI acquisition protocols. Lung MRI was performed in 36 post-COVID patients with different acquisition protocols, including different spiral sampling reordering schemes (line in partition or partition in line) and different breath-hold positions (inspiration or expiration). Three experienced chest radiologists independently scored all the MR images for different pulmonary structures. Lung MR images from spiral acquisition protocol that received the highest image quality scores were also compared against corresponding CT images in 27 patients for evaluating diagnostic image quality and lesion identification. Spiral-VIBE-UTE MRI acquired with the line in partition reordering scheme in an inspiratory breath-holding position achieved the highest image quality scores (score range = 2.17-3.69) compared to others (score range = 1.7-3.29). Compared to corresponding chest CT images, three readers found that 81.5% (22 out of 27), 81.5% (22 out of 27) and 37% (10 out of 27) of the MR images were useful, respectively. Meanwhile, they all agreed that MRI could identify significant lesions in the lungs. The Spiral-VIBE-UTE sequence allows for fast imaging of the lung in a single breath hold. It could be a valuable tool for lung imaging without radiation and could provide great value for managing different lung diseases including assessment of post-COVID lesions., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Assessing inflammatory disease activity in large vessel vasculitis (LVV) can be challenging by conventional measures., Objectives: We aimed to investigate somatostatin receptor 2 (SST 2 ) as a novel inflammation-specific molecular imaging target in LVV., Methods: In a prospective, observational cohort study, in vivo arterial SST 2 expression was assessed by positron emission tomography/magnetic resonance imaging (PET/MRI) using 68 Ga-DOTATATE and 18 F-FET-βAG-TOCA. Ex vivo mapping of the imaging target was performed using immunofluorescence microscopy; imaging mass cytometry; and bulk, single-cell, and single-nucleus RNA sequencing., Results: Sixty-one participants (LVV: n = 27; recent atherosclerotic myocardial infarction of ≤2 weeks: n = 25; control subjects with an oncologic indication for imaging: n = 9) were included. Index vessel SST 2 maximum tissue-to-blood ratio was 61.8% (P < 0.0001) higher in active/grumbling LVV than inactive LVV and 34.6% (P = 0.0002) higher than myocardial infarction, with good diagnostic accuracy (area under the curve: ≥0.86; P < 0.001 for both). Arterial SST 2 signal was not elevated in any of the control subjects. SST 2 PET/MRI was generally consistent with 18 F-fluorodeoxyglucose PET/computed tomography imaging in LVV patients with contemporaneous clinical scans but with very low background signal in the brain and heart, allowing for unimpeded assessment of nearby coronary, myocardial, and intracranial artery involvement. Clinically effective treatment for LVV was associated with a 0.49 ± 0.24 (standard error of the mean [SEM]) (P = 0.04; 22.3%) reduction in the SST 2 maximum tissue-to-blood ratio after 9.3 ± 3.2 months. SST 2 expression was localized to macrophages, pericytes, and perivascular adipocytes in vasculitis specimens, with specific receptor binding confirmed by autoradiography. SSTR2-expressing macrophages coexpressed proinflammatory markers., Conclusions: SST 2 PET/MRI holds major promise for diagnosis and therapeutic monitoring in LVV. (PET Imaging of Giant Cell and Takayasu Arteritis [PITA], NCT04071691; Residual Inflammation and Plaque Progression Long-Term Evaluation [RIPPLE], NCT04073810)., Competing Interests: Funding Support and Author Disclosures This work was funded by grants to Dr Tarkin from the Wellcome Trust (Clinical Research Career Development Fellowship 211100/Z/18/Z), the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (BRC); and the British Heart Foundation (BHF) (Clinical Research Training Fellowship for Dr Ćorović [FS/CRTF/20/24035]). This work was additionally supported by the Cambridge BHF Centre of Research Excellence (18/1/34212) and the Cancer Research UK Cambridge Centre (A25177). For the purpose of open access, the lead author has applied a CC BY public copyright license to any Author Accepted Manuscript. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. Dr Nus; authors Imaz and Lambert; Dr Frontini (FS/18/53/33863); Dr Davenport (TG/18/4/33770); and Drs Huang, Mallat, Dweck, Newby, and Bennett are supported by the BHF. Author Zulcinski is supported by the European Union’s Horizon 2020 Research and Innovation Programme (Marie Skłodowska-Curie grant agreement no. 813545). Drs Jayne, Rassl, and Graves are supported by the NIHR Cambridge BRC. Dr Fayad is supported by the National Institutes of Health/National Heart, Lung, and Blood Institute (R01HL135878). Dr Reynolds is supported by the Wellcome Trust. Dr Morgan is supported by the Medical Research Council (MRC) (MR/N011775/1), the NIHR Leeds BRC, the NIHR Leeds Medtech, and In Vitro Diagnostics Co-operative as well as an NIHR Senior Investigator award. Dr Aboagye acknowledges support from Imperial Experimental Cancer Research Centre and MRC (MR/J007986/1, MR/N020782/1); and is an inventor on the patent that developed the (18)F-FET-βAG-TOCA radiotracer. Dr Peters is supported by a UK Research and Innovation Fellowship at Health Data Research UK (MR/S004068/2). Dr Rudd is partly supported by the NIHR Cambridge BRC, the BHF, the Higher Education Funding Council for England, the Engineering and Physical Sciences Research Council, and the Wellcome Trust. Drs Gopalan, Maughan, Pericleous, Barwick, Aboagye, Peters, and Mason acknowledge support from the NIHR Imperial BRC. The authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

High-risk atherosclerotic plaques are characterized by active inflammation and abundant leaky microvessels. We present a self-gated, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquisition with compressed sensing reconstruction and apply it to assess longitudinal changes in endothelial permeability in the aortic root of Apoe -/- atherosclerotic mice during natural disease progression. Twenty-four, 8-week-old, female Apoe -/- mice were divided into four groups (n = 6 each) and imaged with self-gated DCE-MRI at 4, 8, 12, and 16 weeks after high-fat diet initiation, and then euthanized for CD68 immunohistochemistry for macrophages. Eight additional mice were kept on a high-fat diet and imaged longitudinally at the same time points. Aortic-root pseudo-concentration curves were analyzed using a validated piecewise linear model. Contrast agent wash-in and washout slopes (b 1 and b 2 ) were measured as surrogates of aortic root endothelial permeability and compared with macrophage density by immunohistochemistry. b 2 , indicating contrast agent washout, was significantly higher in mice kept on an high-fat diet for longer periods of time (p = 0.03). Group comparison revealed significant differences between mice on a high-fat diet for 4 versus 16 weeks (p = 0.03). Macrophage density also significantly increased with diet duration (p = 0.009). Spearman correlation between b 2 from DCE-MRI and macrophage density indicated a weak relationship between the two parameters (r = 0.28, p = 0.20). Validated piecewise linear modeling of the DCE-MRI data showed that the aortic root contrast agent washout rate is significantly different during disease progression. Further development of this technique from a single-slice to a 3D acquisition may enable better investigation of the relationship between in vivo imaging of endothelial permeability and atherosclerotic plaques' genetic, molecular, and cellular makeup in this important model of disease., (© 2022 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Pharmacological and genetic studies over the past decade have established the follicle-stimulating hormone (FSH) as an actionable target for diseases affecting millions, namely osteoporosis, obesity, and Alzheimer's disease. Blocking FSH action prevents bone loss, fat gain, and neurodegeneration in mice. We recently developed a first-in-class, humanized, epitope-specific FSH-blocking antibody, MS-Hu6, with a K D of 7.52 nM. Using a Good Laboratory Practice (GLP)-compliant platform, we now report the efficacy of MS-Hu6 in preventing and treating osteoporosis in mice and parameters of acute safety in monkeys. Biodistribution studies using 89 Zr-labeled, biotinylated or unconjugated MS-Hu6 in mice and monkeys showed localization to bone and bone marrow. The MS-Hu6 displayed a β phase t ½ of 7.5 days (180 hr) in humanized Tg32 mice. We tested 217 variations of excipients using the protein thermal shift assay to generate a final formulation that rendered MS-Hu6 stable in solution upon freeze-thaw and at different temperatures, with minimal aggregation, and without self-, cross-, or hydrophobic interactions or appreciable binding to relevant human antigens. The MS-Hu6 showed the same level of "humanness" as human IgG1 in silico and was non-immunogenic in ELISpot assays for IL-2 and IFN-γ in human peripheral blood mononuclear cell cultures. We conclude that MS-Hu6 is efficacious, durable, and manufacturable, and is therefore poised for future human testing., Competing Interests: SG, TK, AG, FK, DS, VD, KS, AP, GP, JM, AT, Mv, TP, JF, JN, FS, ES, SR, PK, LC, JC, AP, SM, HK, MB, PS, KI, VM, RB, CR, AM, SH, MS, MM, JC, MN, VR, SK, JC, NZ, ZF, DL, CR No competing interests declared, JI, TY Reviewing editor, eLife, MZ is an inventor on issued patents on inhibiting FSH for the prevention and treatment of osteoporosis and obesity (U.S. Patent 8,435,948 and 11,034,761). M.Z. is also an inventor on pending patent application on composition and use of humanized monoclonal anti-FSH antibodies, and is co-inventor of a pending patent on the use of FSH as a target for preventing Alzheimer's disease. These patents are owned by Icahn School of Medicine at Mount Sinai (ISMMS), and M.Z. would be recipient of royalties, per institutional policy. M.Z. also consults for several financial platforms, including Gerson Lehman Group and Guidepoint, on drugs for osteoporosis and genetic bone diseases. Deputy editor, eLife, (© 2022, Gera, Kuo, Gumerova et al.)