Cortico-limbic interactions and carotid atherosclerotic burden during chronic stress exposure.

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.

Achieving Better Understanding of Obstructive Sleep Apnea Treatment Effects on Cardiovascular Disease Outcomes through Machine Learning Approaches: A Narrative Review.

Obstructive sleep apnea (OSA) affects almost a billion people worldwide and is associated with a myriad of adverse health outcomes. Among the most prevalent and morbid are cardiovascular diseases (CVDs). Nonetheless, randomized controlled trials (RCTs) of OSA treatment have failed to show improvements in CVD outcomes. A major limitation in our field is the lack of precision in defining OSA and specifically subgroups with the potential to benefit from therapy. Further, this has called into question the validity of using the time-honored apnea-hypopnea index as the ultimate defining criteria for OSA. Recent applications of advanced statistical methods and machine learning have brought to light a variety of OSA endotypes and phenotypes. These methods also provide an opportunity to understand the interaction between OSA and comorbid diseases for better CVD risk stratification. Lastly, machine learning and specifically heterogeneous treatment effects modeling can help uncover subgroups with differential outcomes after treatment initiation. In an era of data sharing and big data, these techniques will be at the forefront of OSA research. Advanced data science methods, such as machine-learning analyses and artificial intelligence, will improve our ability to determine the unique influence of OSA on CVD outcomes and ultimately allow us to better determine precision medicine approaches in OSA patients for CVD risk reduction. In this narrative review, we will highlight how team science via machine learning and artificial intelligence applied to existing clinical data, polysomnography, proteomics, and imaging can do just that.

Hybrid Magnetic Resonance Positron Emission Tomography Is Associated With Cardiac-Related Outcomes in Cardiac Sarcoidosis.

BACKGROUND: Imaging with late gadolinium enhancement (LGE) magnetic resonance (MR) and 18F-fluorodeoxyglucose (18F-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 18F-FDG (PET+/PET-), and pattern of 18F-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.

18F-FDG PET/CT in left ventricular assist device infections: In-depth characterization and clinical implications.

BACKGROUND: Previous retrospective studies suggest a good diagnostic performance of 18F-fluorodeoxyglucose positron emission tomography (18F-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 18F-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 (SUVmax) were higher in the infection than in the control group: SUVmax (average all components): 6.9 (5.1-8.5) vs 3.8 (3.7-4.3), p = 0.002; SUVmax (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: 18F-FDG-PET/CT enables the diagnosis and characterization of the extent of LVAD infections, which can significantly affect the clinical management of these patients.

Semi-Automatic Graphical Tool for Measuring Coronary Artery Spatially Weighted Calcium Score from Gated Cardiac Computed Tomography Images.

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 mm2. 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.

Exploring the Utility of Cardiovascular Magnetic Resonance Radiomic Feature Extraction for Evaluation of Cardiac Sarcoidosis.

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 (CSactive) and inactive cardiac sarcoidosis (CSinactive) based on PET-CMR imaging. CSactive was classified as featuring patchy [18F]fluorodeoxyglucose ([18F]FDG) uptake on PET and presence of late gadolinium enhancement (LGE) on CMR, while CSinactive was classified as featuring no [18F]FDG uptake in the presence of LGE on CMR. Among those screened, thirty CSactive and thirty-one CSinactive patients met these criteria. A total of 94 radiomic features were subsequently extracted using PyRadiomics. The values of individual features were compared between CSactive and CSinactive 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 CSactive and CSinactive 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.

Arrhythmic Mitral Valve Prolapse With Only Mild or Moderate Mitral Regurgitation: Characterization of Myocardial Substrate.

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 18F-fluorodeoxyglucose (18F-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 18F-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.

Reducing cardiovascular risk with immunomodulators: a randomised active comparator trial among patients with rheumatoid arthritis.

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 18F-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 (ß=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.

Pharyngeal Inflammation on Positron Emission Tomography/Magnetic Resonance Imaging Before and After Obstructive Sleep Apnea Treatment.

Rationale: There is upper airway inflammation in patients with obstructive sleep apnea (OSA), which reduces with continuous positive airway pressure (CPAP) therapy. Objectives: Validate the use of positron emission tomography (PET)/magnetic resonance imaging (MRI) to quantify metabolic activity within the pharyngeal mucosa of patients with OSA against nasal lavage proteomics and assess the impact of CPAP therapy. Methods: Adults with OSA underwent [18F]-Fluoro-2-deoxy-D-glucose PET/MRI of the neck before and 3 months after initiating CPAP. Nasal lavage samples were collected. Inflammatory protein expression from samples was analyzed using the Olink platform. Upper airway imaging segmentation was performed. Target-to-background ratio (TBRmax) was calculated from target pharyngeal maximum standard uptake values (SUV) and personalized background mean SUV. Most-diseased segment TBRmax was identified per participant at locations with the highest PET avidity. Correlation analysis was performed between baseline TBRmax and nasal lavage proteomics. TBRmax was compared before and after CPAP using linear mixed-effect models. Results: Among 38 participants, the baseline mean age was 46.3 years (standard deviation [SD], 12.5), 21% were female, the mean body mass index was 30.9 kg/m2 (SD, 4.6), and the mean respiratory disturbance index measured by peripheral arterial tonometry was 31 events/h (SD, 16.4). There was a significant positive correlation between pharyngeal mucosa most-diseased segment TBRmax and nasal lavage proteomic inflammation (r = 0.41 [P < 0.001, false discovery rate = 0.002]). Primary analysis revealed a reduction in the most-diseased segment TBRmax after a median of 2.91 months of CPAP therapy (-0.86 [standard error (SE) ± 0.30; P = 0.007]). Stratified analysis by smoking status revealed a significantly decreased most-diseased segment TBRmax after CPAP therapy among never-smokers but not among ever-smokers (-1.01 [SE ± 0.39; P = 0.015] vs. -0.64 [SE ± 0.49; P = 0.201]). Conclusions: CPAP therapy reduces metabolic activity measured by PET/MRI within the upper airway of adults with OSA. Furthermore, PET/MRI measures of upper airway metabolic activity correlate with a noninvasive marker of inflammation (i.e., nasal lavage inflammatory protein expression).

RadImageNet: An Open Radiologic Deep Learning Research Dataset for Effective Transfer Learning.

Purpose: To demonstrate the value of pretraining with millions of radiologic images compared with ImageNet photographic images on downstream medical applications when using transfer learning. Materials and Methods: This retrospective study included patients who underwent a radiologic study between 2005 and 2020 at an outpatient imaging facility. Key images and associated labels from the studies were retrospectively extracted from the original study interpretation. These images were used for RadImageNet model training with random weight initiation. The RadImageNet models were compared with ImageNet models using the area under the receiver operating characteristic curve (AUC) for eight classification tasks and using Dice scores for two segmentation problems. Results: The RadImageNet database consists of 1.35 million annotated medical images in 131 872 patients who underwent CT, MRI, and US for musculoskeletal, neurologic, oncologic, gastrointestinal, endocrine, abdominal, and pulmonary pathologic conditions. For transfer learning tasks on small datasets-thyroid nodules (US), breast masses (US), anterior cruciate ligament injuries (MRI), and meniscal tears (MRI)-the RadImageNet models demonstrated a significant advantage (P < .001) to ImageNet models (9.4%, 4.0%, 4.8%, and 4.5% AUC improvements, respectively). For larger datasets-pneumonia (chest radiography), COVID-19 (CT), SARS-CoV-2 (CT), and intracranial hemorrhage (CT)-the RadImageNet models also illustrated improved AUC (P < .001) by 1.9%, 6.1%, 1.7%, and 0.9%, respectively. Additionally, lesion localizations of the RadImageNet models were improved by 64.6% and 16.4% on thyroid and breast US datasets, respectively. Conclusion: RadImageNet pretrained models demonstrated better interpretability compared with ImageNet models, especially for smaller radiologic datasets.Keywords: CT, MR Imaging, US, Head/Neck, Thorax, Brain/Brain Stem, Evidence-based Medicine, Computer Applications-General (Informatics) Supplemental material is available for this article. Published under a CC BY 4.0 license.See also the commentary by Cadrin-Chênevert in this issue.

Inflammatory Diseases of the Aorta: JACC Focus Seminar, Part 2.

Inflammatory aortitis is most often caused by large vessel vasculitis (LVV), including giant cell arteritis, Takayasu's arteritis, immunoglobulin G4-related aortitis, and isolated aortitis. There are distinct differences in the clinical presentation, imaging findings, and natural history of LVV that are important for the cardiovascular provider to know. If possible, histopathologic specimens should be obtained to aide in accurate diagnosis and management of LVV. In most cases, corticosteroids are utilized in the acute phase, with the addition of steroid-sparing agents to achieve disease remission while sparing corticosteroid toxic effects. Endovascular and surgical procedures have been described with success but should be delayed until disease control is achieved whenever possible. Long-term management should include regular follow-up with rheumatology and surveillance imaging for sequelae of LVV.

Exploring the Utility of Radiomic Feature Extraction to Improve the Diagnostic Accuracy of Cardiac Sarcoidosis Using FDG PET.

Background: This study aimed to explore the radiomic features from PET images to detect active cardiac sarcoidosis (CS). Methods: Forty sarcoid patients and twenty-nine controls were scanned using FDG PET-CMR. Five feature classes were compared between the groups. From the PET images alone, two different segmentations were drawn. For segmentation A, a region of interest (ROI) was manually delineated for the patients' myocardium hot regions with standardized uptake value (SUV) higher than 2.5 and the controls' normal myocardium region. A second ROI was drawn in the entire left ventricular myocardium for both study groups, segmentation B. The conventional metrics and radiomic features were then extracted for each ROI. Mann-Whitney U-test and a logistic regression classifier were used to compare the individual features of the study groups. Results: For segmentation A, the SUVmin had the highest area under the curve (AUC) and greatest accuracy among the conventional metrics. However, for both segmentations, the AUC and accuracy of the TBRmax were relatively high, >0.85. Twenty-two (from segmentation A) and thirty-five (from segmentation B) of 75 radiomic features fulfilled the criteria: P-value < 0.00061 (after Bonferroni correction), AUC >0.5, and accuracy >0.7. Principal Component Analysis (PCA) was conducted, with five components leading to cumulative variance higher than 90%. Ten machine learning classifiers were then tested and trained. Most of them had AUCs and accuracies ≥0.8. For segmentation A, the AUCs and accuracies of all classifiers are >0.9, but k-neighbors and neural network classifiers were the highest (=1). For segmentation B, there are four classifiers with AUCs and accuracies ≥0.8. However, the gaussian process classifier indicated the highest AUC and accuracy (0.9 and 0.8, respectively). Conclusions: Radiomic analysis of the specific PET data was not proven to be necessary for the detection of CS. However, building an automated procedure will help to accelerate the analysis and potentially lead to more reproducible findings across different scanners and imaging centers and consequently improve standardization procedures that are important for clinical trials and development of more robust diagnostic protocols.

18F-fluoride PET/MR in cardiac amyloid: A comparison study with aortic stenosis and age- and sex-matched controls.

OBJECTIVES: Cardiac MR is widely used to diagnose cardiac amyloid, but cannot differentiate AL and ATTR subtypes: an important distinction given their differing treatments and prognoses. We used PET/MR imaging to quantify myocardial uptake of 18F-fluoride in ATTR and AL amyloid patients, as well as participants with aortic stenosis and age/sex-matched controls. METHODS: In this prospective multicenter study, patients were recruited in Edinburgh and New York and underwent 18F-fluoride PET/MR imaging. Standardized volumes of interest were drawn in the septum and areas of late gadolinium enhancement to derive myocardial standardized uptake values (SUV) and tissue-to-background ratio (TBRMEAN) after correction for blood pool activity in the right atrium. RESULTS: 53 patients were scanned: 18 with cardiac amyloid (10 ATTR and 8 AL), 13 controls, and 22 with aortic stenosis. No differences in myocardial TBR values were observed between participants scanned in Edinburgh and New York. Mean myocardial TBRMEAN values in ATTR amyloid (1.13 ± 0.16) were higher than controls (0.84 ± 0.11, P = .0006), aortic stenosis (0.73 ± 0.12, P < .0001), and those with AL amyloid (0.96 ± 0.08, P = .01). TBRMEAN values within areas of late gadolinium enhancement provided discrimination between patients with ATTR (1.36 ± 0.23) and all other groups (e.g., AL [1.06 ± 0.07, P = .003]). A TBRMEAN threshold >1.14 in areas of LGE demonstrated 100% sensitivity (CI 72.25 to 100%) and 100% specificity (CI 67.56 to 100%) for ATTR compared to AL amyloid (AUC 1, P = .0004). CONCLUSION: Quantitative 18F-fluoride PET/MR imaging can distinguish ATTR amyloid from other similar phenotypes and holds promise in improving the diagnosis of this condition.

Pulmonary Artery 18F-Fluorodeoxyglucose Uptake by PET/CMR as a Marker of Pulmonary Hypertension in Sarcoidosis.

OBJECTIVES: This study investigated whether pulmonary artery (PA) 18F-FDG uptake is associated with hypertension, and if it correlates to elevated pulmonary pressures. BACKGROUND: 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with computed tomography or cardiac magnetic resonance (CMR) has been used to assess inflammation mostly in large arteries of the systemic circulation. Much less is known about inflammation of the vasculature of the pulmonary system and its relationship to pulmonary hypertension (PH). METHODS: In a single-center cohort of 175 patients with suspected cardiac sarcoidosis, who underwent hybrid thoracic PET/CMR, 18F-FDG uptake in the PA was quantified according to maximum standardized uptake value (SUVmax) and target-to-background ratio (TBR) and compared with available results from right heart catheterization (RHC) or transthoracic echocardiography (TTE). RESULTS: Thirty-three subjects demonstrated clear 18F-FDG uptake in the PA wall. In the subgroup of patients who underwent RHC (n = 10), the mean PA pressure was significantly higher in the group with PA 18F-FDG uptake compared with the group without uptake (34.4 ± 7.2 mm Hg vs 25.6 ± 9.3 mm Hg; P = 0.003), and 9 (90%) patients with PA 18F-FDG uptake had PH when a mean PA pressure cutoff of 25 mm Hg was used compared with 18 (45%) in the nonuptake group (P < 0.05). In the subgroup that underwent TTE, signs of PH were present in a significantly higher number of patients with PA 18F-FDG uptake (14 [51.9%] vs 37 [29.8%]; P < 0.05). Qualitative assessment of 18F-FDG uptake in the PA wall showed a sensitivity of 33% and specificity of 96% for separating patients with PH based on RHC-derived PA pressures. SUVmax and TBR in the PA wall correlated with PA pressure derived from RHC and/or TTE. CONCLUSIONS: We demonstrate that 18F-FDG uptake by PET/CMR in the PA is associated with PH and that its intensity correlates with PA pressure.

Scan-rescan measurement repeatability of 18F-FDG PET/MR imaging of vascular inflammation.

Non-invasive positron emission tomography (PET) of vascular inflammation and atherosclerotic plaque by identifying increased uptake of 18F-fluordeoxyglucose (18F-FDG) is a powerful tool for monitoring disease activity, progression, and its response to therapy. 18F-FDG PET/computed tomography (PET/CT) of the aorta and carotid arteries has become widely used to assess changes in inflammation in clinical trials. However, the recent advent of hybrid PET/magnetic resonance (PET/MR) scanners has advantages for vascular imaging due to the reduction in radiation exposure and improved soft tissue contrast of MR compared to CT. Important for research and clinical use is an understanding of the scan-rescan repeatability of the PET measurement. While this has been studied for PET/CT, no data is currently available for vascular PET/MR imaging. In this study, we determined the scan-rescan measurement repeatability of 18F-FDG PET/MR in the aorta and carotid arteries was less than 5%, comparable to similar findings for 18F-FDG PET/CT.

Measuring Visceral Adipose Tissue Metabolic Activity in Sleep Apnea Utilizing Hybrid 18F-FDG PET/MRI: A Pilot Study.

PURPOSE: Visceral adipose tissue (VAT) is proinflammatory and is associated with cardiovascular (CV) disease. We investigated the relationship between obstructive sleep apnea (OSA) and visceral adipose tissue (VAT) metabolic activity in a pilot group of patients using positron-emission tomography/magnetic resonance imaging (PET/MRI) with 18F-fluorodeoxyglucose (FDG) tracer as a novel marker of adipose tissue inflammation. PATIENTS AND METHODS: We analyzed patients from an ongoing study, recruiting those with newly diagnosed, untreated OSA (Respiratory Disturbance Index [RDI] ≥ 5), using home sleep apnea testing (WatchPAT-200 Central-Plus). PET/MRI scans were acquired before continuous positive airway pressure (CPAP)-initiation, and after 3 months of CPAP therapy. Adipose tissue metabolic activity (18F-FDG-uptake) was measured using standardized uptake values (SUV) within the adipose tissue depots. The primary outcome was VAT SUVmean, and secondary outcomes included VAT volume, and subcutaneous adipose tissue (SAT) volume/SUVmean. Reproducibility and reliability of outcome measures were analyzed using intraclass correlation coefficients (ICC). Multivariable linear regression was used to evaluate the association between OSA and primary/secondary outcomes. RESULTS: Our analytical sample (n = 16) was 81% male (mean age 47 ± 15 years, mean BMI of 29.9 ± 4.8kg/m2). About 56% had moderate to severe OSA (mean RDI 23 ± 6 events/hour), and 50% were adherent to CPAP. We demonstrated excellent inter/intra-rater reliability and reproducibility for the primary and secondary outcomes. Patients with moderate-to-severe OSA had a higher VAT SUV mean compared to those with mild OSA (0.795 ± 0.154 vs 0.602 ± 0.19, p = 0.04). OSA severity was positively associated with VAT SUVmean (primary outcome), adjusted for age and BMI (B [SE] = 0.013 ± 0.005, p = 0.03). Change in VAT volume was inversely correlated with CPAP adherence in unadjusted analysis (B [SE] = -48.4 ± 18.7, p = 0.02). CONCLUSION: Derangements in VAT metabolic activity are implicated in adverse cardiometabolic outcomes and may be one of the key drivers of CV risk in OSA. Our results are hypothesis-generating, and suggest that VAT should be investigated in future studies using multi-modal imaging to understand its role as a potential mediator of adverse cardiometabolic risk in OSA.

Improvement of magnetic resonance imaging using a wireless radiofrequency resonator array.

In recent years, new human magnetic resonance imaging systems operating at static magnetic fields strengths of 7 Tesla or higher have become available, providing better signal sensitivity compared with lower field strengths. However, imaging human-sized objects at such high field strength and associated precession frequencies is limited due to the technical challenges associated with the wavelength effect, which substantially disturb the transmit field uniformity over the human body when conventional coils are used. Here we report a novel passive inductively-coupled radiofrequency resonator array design with a simple structure that works in conjunction with conventional coils and requires only to be tuned to the scanner's operating frequency. We show that inductive-coupling between the resonator array and the coil improves the transmit efficiency and signal sensitivity in the targeted region. The simple structure, flexibility, and cost-efficiency make the proposed array design an attractive approach for altering the transmit field distribution specially at high field systems, where the wavelength is comparable with the tissue size.