Lung transplant patients often suffer from posttransplant airway pathologies that require placement of endobronchial stents. In addition to surveillance bronchoscopy, patients often undergo ...radiographic stent evaluations. Chest x-rays are extremely limited in their ability to diagnose stent complications, so many patients require chest computed tomography (CT) scans for stent evaluation. Chest CT scans are costly and expose patients to higher cumulative radiation doses. Digital tomosynthesis (DTS) is an imaging modality that provides high-resolution images using limited angle tomography. The costs and radiation doses are comparable to conventional x-ray. We present a series of 4 postlung transplant patients with bronchial stents in whom we performed DTS and chest x-ray simultaneously. The DTS images were far superior to chest x-ray and comparable with CT in evaluating the placement and patency of the stents, especially in the case of silicone stents. Furthermore, the improved resolution provided clinically relevant diagnostic information that resulted in therapeutic bronchoscopy for suctioning of mucus impaction in one of the patients.
To identify stable and discriminating radiomic features on non-contrast CT scans to develop more generalisable radiomic classifiers for distinguishing granulomas from adenocarcinomas.
In total, 412 ...patients with adenocarcinomas and granulomas from three institutions were retrospectively included. Segmentations of the lung nodules were performed manually by an expert radiologist in a 2D axial view. Radiomic features were extracted from intra- and perinodular regions. A total of 145 patients were used as part of the training set (Str), whereas 205 patients were used as part of test set I (Ste1) and 62 patients were used as part of independent test set II (Ste2). To mitigate the variation of CT acquisition parameters, we defined ‘stable’ radiomic features as those for which the feature expression remains relatively unchanged between different sites, as assessed using a Wilcoxon rank-sum test. These stable features were used to develop more generalisable radiomic classifiers that were more resilient to variations in lung CT scans. Features were ranked based on two criteria, firstly based on discriminability (i.e. maximising AUC) alone and subsequently based on maximising both feature stability and discriminability. Different machine-learning classifiers (Linear discriminant analysis, Quadratic discriminant analysis, Support vector machines and random forest) were trained with features selected using the two different criteria and then compared on the two independent test sets for distinguishing granulomas from adenocarcinomas, in terms of area under the receiver operating characteristic curve.
In the test sets, classifiers constructed using the criteria involving maximising feature stability and discriminability simultaneously achieved higher AUC compared with the discriminating alone criteria (Ste1 n = 205: maximum AUCs of 0.85versus . 0.80; p-value = 0.047 and Ste2 n = 62: maximum AUCs of 0.87 versus. 0.79; p-value = 0.021). These differences held for features extracted from scans with <3 mm slice thickness (AUC = 0.88 versus. 0.80; p-value = 0.039, n = 100) and for the ≥3 mm cases (AUC = 0.81 versus. 0.76; p-value = 0.034, n = 105). In both experiments, shape and peritumoural texture features had a higher stability compared with intratumoural texture features.
Our study suggests that explicitly accounting for both stability and discriminability results in more generalisable radiomic classifiers to distinguish adenocarcinomas from granulomas on non-contrast CT scans. Our results also showed that peritumoural texture and shape features were less affected by the scanner parameters compared with intratumoural texture features; however, they were also less discriminating compared with intratumoural features.
•Intramodular Gabor and Law features are highly discriminating–stable radiomic features.•Shape features are highly stable but less accurate for distinguishing malignant from benign nodules.•Perinodular Gabor features are highly discriminating–stable radiomic features in CTs with slice thickness <3 mm.•In slice CTs with thickness >3 mm, most radiomic features tend to become unstable.
Late gadolinium enhancement (LGE) cardiac magnetic resonance (MR) imaging sequence is increasingly used in the evaluation of pediatric cardiovascular disorders, and although LGE might be a normal ...feature at the sites of previous surgeries, it is pathologically seen as a result of extracellular space expansion, either from acute cell damage or chronic scarring or fibrosis. LGE is broadly divided into ischemic and non-ischemic patterns. LGE caused by myocardial infarction occurs in a vascular distribution and always involves the subendocardial portion, progressively involving the outer regions in a waveform pattern. Non-ischemic cardiomyopathies can have a mid-myocardial (either linear or patchy), subepicardial or diffuse subendocardial distribution. Idiopathic dilated cardiomyopathy can have a linear mid-myocardial pattern, while hypertrophic cardiomyopathy can have fine, patchy enhancement in hypertrophied and non-hypertrophied segments as well as right ventricular insertion points. Myocarditis and sarcoidosis have a mid-myocardial or subepicardial pattern of LGE. Fabry disease typically affects the basal inferolateral segment while Danon disease typically spares the septum. Pericarditis is characterized by diffuse or focal pericardial thickening and enhancement. Thrombus, the most common non-neoplastic cardiac mass, is characterized by absence of enhancement in all sequences, while neoplastic masses show at least some contrast enhancement, depending on the pathology. Regardless of the etiology, presence of LGE is associated with a poor prognosis. In this review, we describe the technical modifications required for performing LGE cardiac MR sequence in children, review and illustrate the patterns of LGE in children, and discuss their clinical significance.
Purpose
Distinguishing between benign granulmoas and adenocarcinomas is confounded by their similar visual appearance on routine CT scans. Unfortunately, owing to the inability to discriminate these ...lesions radigraphically, many patients with benign granulomas are subjected to unnecessary surgical wedge resections and biopsies for pathologic confirmation of cancer presence or absence. This suggests the need for improved computerized characterization of these nodules in order to distinguish between these two classes of lesions on CT scans. While there has been substantial interest in the use of textural analysis for radiomic characterization of lung nodules, relatively less work has been done in shape based characterization of lung nodules, particularly with respect to granulmoas and adenocarcinomas. The primary goal of this study is to evaluate the role of 3D shape features for discrimination of benign granulomas from malignant adenocarcinomas on lung CT images. Towards this end we present an integrated framework for segmentation, feature characterization and classification of these nodules on CT.
Methods
The nodule segmentation method starts with separation of lung regions from the surrounding lung anatomy. Next, the lung CT scans are projected into and represented in a three dimensional spectral embedding (SE) space, allowing for better determination of the boundaries of the nodule. This then enables the application of a gradient vector flow active contour (SEGvAC) model for nodule boundary extraction. A set of 24 shape features from both 2D slices and 3D surface of the segmented nodules are extracted, including features pertaining to the angularity, spiculation, elongation and nodule compactness. A feature selection scheme, PCA‐VIP, is employed to identify the most discriminating set of features to distinguish granulmoas from adenocarcinomas within a learning set of 82 patients. The features thus identified were then combined with a support vector machine classifier and independently validated on a distinct test set comprising 67 patients. The performance of the classifier for both of the training and validation cohorts was evaluated by the area under receiver characteristic curve (ROC).
Results
We used 82 and 67 studies from two different institutions respectively for training and independent validation of the model and the shape features. The Dice coefficient between automatically segmented nodules by SEGvAC and the manual delineations by expert radiologists (readers) was 0.84± 0.04 whereas inter‐reader segmentation agreement was 0.79± 0.12. We also identified a set of consistent features (Roughness, Convexity and Spherecity) that were found to be strongly correlated across both manual and automated nodule segmentations (R > 0.80, p < 0.0001) and capture the marginal smoothness and 3D compactness of the nodules. On the independent validation set of 67 studies our classifier yielded a ROC AUC of 0.72 and 0.64 for manually‐ and automatically segmented nodules respectively. On a subset of 20 studies, the AUCs for the two expert radiologists and 1 pulmonologist were found to be 0.82, 0.68 and 0.58 respectively.
Conclusions
The major finding of this study was that certain shape features appear to differentially express between granulomas and adenocarcinomas and thus computer extracted shape cues could be used to distinguish these radiographically similar pathologies.
Systemic sclerosis (SSc) is a multisystem autoimmune disorder that has an unclear etiology and disproportionately affects women and African Americans. Despite this, African Americans are dramatically ...underrepresented in SSc research. Additionally, monocytes show heightened activation in SSc and in African Americans relative to European Americans. In this study, we sought to investigate DNA methylation and gene expression patterns in classical monocytes in a health disparity population.
Classical monocytes (CD14+ + CD16-) were FACS-isolated from 34 self-reported African American women. Samples from 12 SSc patients and 12 healthy controls were hybridized on MethylationEPIC BeadChip array, while RNA-seq was performed on 16 SSc patients and 18 healthy controls. Analyses were computed to identify differentially methylated CpGs (DMCs), differentially expressed genes (DEGs), and CpGs associated with changes in gene expression (eQTM analysis).
We observed modest DNA methylation and gene expression differences between cases and controls. The genes harboring the top DMCs, the top DEGs, as well as the top eQTM loci were enriched for metabolic processes. Genes involved in immune processes and pathways showed a weak upregulation in the transcriptomic analysis. While many genes were newly identified, several other have been previously reported as differentially methylated or expressed in different blood cells from patients with SSc, supporting for their potential dysregulation in SSc.
While contrasting with results found in other blood cell types in largely European-descent groups, the results of this study support that variation in DNA methylation and gene expression exists among different cell types and individuals of different genetic, clinical, social, and environmental backgrounds. This finding supports the importance of including diverse, well-characterized patients to understand the different roles of DNA methylation and gene expression variability in the dysregulation of classical monocytes in diverse populations, which might help explaining the health disparities.
Involvement of the coronary arteries by immunoglobulin G4‐related disease is rare. It can cause coronary artery aneurysm and arterial wall thickening. Imaging plays a key role in the assessment of ...the coronary arteries and multimodality approach imaging is helpful to make the diagnosis and provide functional and prognostic information.
To use multimodality imaging to explore the relationship of biomarkers of inflammation, T-cell activation and monocyte activation with coronary calcification and subclinical vascular disease in a ...population of HIV-infected patients on antiretroviral therapy (ART).
Cross-sectional.
A panel of soluble and cellular biomarkers of inflammation and immune activation was measured in 147 HIV-infected adults on ART with HIV RNA less than 1000 copies/ml and low-density lipoprotein cholesterol (LDL-C) 130 mg/dl or less. We examined the relationship of biomarkers to coronary calcium (CAC) score and multiple ultrasound measures of subclinical vascular disease.
Overall, median (interquartile range, IQR) age was 46 (40-53) years; three-quarters of participants were male and two-thirds African-American. Median 10-year Framingham risk score was 6%. Participants with CAC more than 0 were older, less likely to be African-American and had higher current and lower nadir CD4 T-cell counts. Most biomarkers were similar between those with and without CAC; however, soluble CD14 was independently associated with CAC after adjustment for traditional risk factors. Among those with a CAC score of zero, T-cell activation and systemic inflammation correlated with carotid intima-media thickness and brachial hyperemic velocity, respectively. Compared with normal participants and those with CAC only, participants with increasing degrees of subclinical vascular disease had higher levels of sCD14, hs-CRP and fibrinogen (all P<0.05).
Soluble CD14 is independently associated with coronary artery calcification, and, among those with detectable calcium, predicts the extent of subclinical disease in other vascular beds. Future studies should investigate the utility of multimodality imaging to characterize vascular disease phenotypes in this population.
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