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.

Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis.

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 [18F] 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.

Erratum: Publisher Correction: Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis.

[This corrects the article DOI: 10.1038/s44161-023-00278-y.].

Systematically evaluating DOTATATE and FDG as PET immuno-imaging tracers of cardiovascular inflammation.

In recent years, cardiovascular immuno-imaging by positron emission tomography (PET) has undergone tremendous progress in preclinical settings. Clinically, two approved PET tracers hold great potential for inflammation imaging in cardiovascular patients, namely FDG and DOTATATE. While the former is a widely applied metabolic tracer, DOTATATE is a relatively new PET tracer targeting the somatostatin receptor 2 (SST2). In the current study, we performed a detailed, head-to-head comparison of DOTATATE-based radiotracers and [18F]F-FDG in mouse and rabbit models of cardiovascular inflammation. For mouse experiments, we labeled DOTATATE with the long-lived isotope [64Cu]Cu to enable studying the tracer's mode of action by complementing in vivo PET/CT experiments with thorough ex vivo immunological analyses. For translational PET/MRI rabbit studies, we employed the more widely clinically used [68Ga]Ga-labeled DOTATATE, which was approved by the FDA in 2016. DOTATATE's pharmacokinetics and timed biodistribution were determined in control and atherosclerotic mice and rabbits by ex vivo gamma counting of blood and organs. Additionally, we performed in vivo PET/CT experiments in mice with atherosclerosis, mice subjected to myocardial infarction and control animals, using both [64Cu]Cu-DOTATATE and [18F]F-FDG. To evaluate differences in the tracers' cellular specificity, we performed ensuing ex vivo flow cytometry and gamma counting. In mice subjected to myocardial infarction, in vivo [64Cu]Cu-DOTATATE PET showed higher differential uptake between infarcted (SUVmax 1.3, IQR, 1.2-1.4, N = 4) and remote myocardium (SUVmax 0.7, IQR, 0.5-0.8, N = 4, p = 0.0286), and with respect to controls (SUVmax 0.6, IQR, 0.5-0.7, N = 4, p = 0.0286), than [18F]F-FDG PET. In atherosclerotic mice, [64Cu]Cu-DOTATATE PET aortic signal, but not [18F]F-FDG PET, was higher compared to controls (SUVmax 1.1, IQR, 0.9-1.3 and 0.5, IQR, 0.5-0.6, respectively, N = 4, p = 0.0286). In both models, [64Cu]Cu-DOTATATE demonstrated preferential accumulation in macrophages with respect to other myeloid cells, while [18F]F-FDG was taken up by macrophages and other leukocytes. In a translational PET/MRI study in atherosclerotic rabbits, we then compared [68Ga]Ga-DOTATATE and [18F]F-FDG for the assessment of aortic inflammation, combined with ex vivo radiometric assays and near-infrared imaging of macrophage burden. Rabbit experiments showed significantly higher aortic accumulation of both [68Ga]Ga-DOTATATE and [18F]F-FDG in atherosclerotic (SUVmax 0.415, IQR, 0.338-0.499, N = 32 and 0.446, IQR, 0.387-0.536, N = 27, respectively) compared to control animals (SUVmax 0.253, IQR, 0.197-0.285, p = 0.0002, N = 10 and 0.349, IQR, 0.299-0.423, p = 0.0159, N = 11, respectively). In conclusion, we present a detailed, head-to-head comparison of the novel SST2-specific tracer DOTATATE and the validated metabolic tracer [18F]F-FDG for the evaluation of inflammation in small animal models of cardiovascular disease. Our results support further investigations on the use of DOTATATE to assess cardiovascular inflammation as a complementary readout to the widely used [18F]F-FDG.

Atherosclerosis inflammation and burden in young adult smokers and vapers measured by PET/MR.

BACKGROUND AND AIMS: Electronic cigarette (EC) use is popular among youth, touted as a safer alternative to smoking and promoted as a tool to aid in smoking cessation. EC cardiovascular safety however is not well established. The aim of this study was to examine cardiovascular consequences of EC use by evaluating their effect on the entire atherosclerotic cascade in young adults using noninvasive combined positron emission tomography (PET)/magnetic resonance imaging (MR) and comparing EC use with age matched smokers of traditional cigarettes and nonsmoking controls. METHODS: Carotid PET/MR was applied to look at vascular inflammation (18-fluorodeoxyglucose (FDG)-PET) and plaque burden (multi-contrast MR of vessel wall) from 60 18-30 year-old subjects (20 electronic cigarette users, 20 traditional smokers and 20 nonsmokers). RESULTS: Groups were reasonably well balanced in terms of age, gender, demographics, cardiovascular risk and most biomarkers. There were no differences in vascular inflammation as measured by 18-FDG-PET target to background ratios (TBR) between EC users, traditional cigarette smokers and nonsmokers. However, measures of carotid plaque burden - wall area, normalized wall index, and wall thickness - measured from MR were significantly higher in both traditional smokers and EC users than in nonsmokers. CONCLUSIONS: Young adult EC users, smokers and nonsmokers in our study did not exhibit vascular inflammation as defined by 18-F-FDG-PET TBR max, but smokers and EC users had significantly more carotid plaque burden compared to matched nonsmokers. Results could indicate that vaping does not cause an increase in vascular inflammation as measured by FDG-PET.

Review of radiographic findings in COVID-19.

The purpose of this study is to review the published literature for the range of radiographic findings present in patients suffering from coronavirus disease 2019 infection. This novel corona virus is currently the cause of a worldwide pandemic. Pulmonary symptoms and signs dominate the clinical picture and radiologists are called upon to evaluate chest radiographs (CXR) and computed tomography (CT) images to assess for infiltrates and to define their extent, distribution and progression. Multiple studies attempt to characterize the disease course by looking at the timing of imaging relative to the onset of symptoms. In general, plain CXR show bilateral disease with a tendency toward the lung periphery and have an appearance most consistent with viral pneumonia. Chest CT images are most notable for showing bilateral and peripheral ground glass and consolidated opacities and are marked by an absence of concomitant pulmonary nodules, cavitation, adenopathy and pleural effusions. Published literature mentioning organ systems aside from pulmonary manifestations are relatively less common, yet present and are addressed in this review. Similarly, publications focusing on imaging modalities aside from CXR and chest CT are sparse in this evolving crisis and are likewise addressed in this review. The role of imaging is examined as it is currently being debated in the medical community, which is not at all surprising considering the highly infectious nature of Severe Acute Respiratory Syndrome coronavirus 2.

Segmentation of carotid arterial walls using neural networks.

BACKGROUND: Automated, accurate, objective, and quantitative medical image segmentation has remained a challenging goal in computer science since its inception. This study applies the technique of convolutional neural networks (CNNs) to the task of segmenting carotid arteries to aid in the assessment of pathology. AIM: To investigate CNN's utility as an ancillary tool for researchers who require accurate segmentation of carotid vessels. METHODS: An expert reader delineated vessel wall boundaries on 4422 axial T2-weighted magnetic resonance images of bilateral carotid arteries from 189 subjects with clinically evident atherosclerotic disease. A portion of this dataset was used to train two CNNs (one to segment the vessel lumen and the other to segment the vessel wall) with the remaining portion used to test the algorithm's efficacy by comparing CNN segmented images with those of an expert reader. RESULTS: Overall quantitative assessment between automated and manual segmentations was determined by computing the DICE coefficient for each pair of segmented images in the test dataset for each CNN applied. The average DICE coefficient for the test dataset (CNN segmentations compared to expert's segmentations) was 0.96 for the lumen and 0.87 for the vessel wall. Pearson correlation values and the intra-class correlation coefficient (ICC) were computed for the lumen (Pearson = 0.98, ICC = 0.98) and vessel wall (Pearson = 0.88, ICC = 0.86) segmentations. Bland-Altman plots of area measurements for the CNN and expert readers indicate good agreement with a mean bias of 1%-8%. CONCLUSION: Although the technique produces reasonable results that are on par with expert human assessments, our application requires human supervision and monitoring to ensure consistent results. We intend to deploy this algorithm as part of a software platform to lessen researchers' workload to more quickly obtain reliable results.

An iterative sparse deconvolution method for simultaneous multicolor 19 F-MRI of multiple contrast agents.

PURPOSE: 19 F-MRI is gaining widespread interest for cell tracking and quantification of immune and inflammatory cells in vivo. Different fluorinated compounds can be discriminated based on their characteristic MR spectra, allowing in vivo imaging of multiple 19 F compounds simultaneously, so-called multicolor 19 F-MRI. We introduce a method for multicolor 19 F-MRI using an iterative sparse deconvolution method to separate different 19 F compounds and remove chemical shift artifacts arising from multiple resonances. METHODS: The method employs cycling of the readout gradient direction to alternate the spatial orientation of the off-resonance chemical shift artifacts, which are subsequently removed by iterative sparse deconvolution. Noise robustness and separation was investigated by numerical simulations. Mixtures of fluorinated oils (PFCE and PFOB) were measured on a 7T MR scanner to identify the relation between 19 F signal intensity and compound concentration. The method was validated in a mouse model after intramuscular injection of fluorine probes, as well as after intravascular injection. RESULTS: Numerical simulations show efficient separation of 19 F compounds, even at low signal-to-noise ratio. Reliable chemical shift artifact removal and separation of PFCE and PFOB signals was achieved in phantoms and in vivo. Signal intensities correlated excellently to the relative 19 F compound concentrations (r-2 = 0.966/0.990 for PFOB/PFCE). CONCLUSIONS: The method requires minimal sequence adaptation and is therefore easily implemented on different MRI systems. Simulations, phantom experiments, and in-vivo measurements in mice showed effective separation and removal of chemical shift artifacts below noise level. We foresee applicability for simultaneous in-vivo imaging of 19 F-containing fluorine probes or for detection of 19 F-labeled cell populations.