Andrew J. Vercnocke

PurposeThe onset of atherosclerosis is preceded by changes in blood perfusion within the arterial wall due to localized proliferation of the vasa vasorum. The purpose of this study was to quantify these changes in spatial density of the vasa vasorum using a research whole-body photon-counting detector CT (PCD-CT) scanner and a porcine model.ApproachVasa vasorum angiogenesis was stimulated in the left carotid artery wall of anesthetized pigs (n = 5) while the right carotid served as a control. After a 6-week recovery period, the animals were scanned on the PCD-CT prior to and after injection of iodinated contrast. Annular regions of interest were used to measure wall enhancement in the injured and control arteries. The exact Wilcoxon-signed rank test was used to determine whether a significant difference in contrast enhancement existed between the injured and control arterial walls.ResultsThe greatest arterial wall enhancement was observed following contrast recirculation. The wall enhancement measurements made over these time points revealed that the enhancement was greater in the injured artery for 13/16 scanned arterial regions. Using an exact Wilcoxon-signed rank test, a significantly increased enhancement ratio was found in injured arteries compared with control arteries (p = 0.013). Vasa vasorum angiogenesis was confirmed in micro-CT scans of excised arteries.ConclusionsWhole-body PCD-CT scanners can be used to detect and quantify the increased perfusion occurring within the porcine carotid arterial wall resulting from an increased density of vasa vasorum.

Objective: Investigate the performance of multiparametric MRI radiomic features, alone or combined with current standard-of-care methods, for pulmonary nodule classification. Assess the impact of segmentation variability on feature reproducibility and reliability. Methods: Radiomic features were extracted from 74 pulmonary nodules of 68 patients who underwent nodule resection or biopsy after MRI exam. The MRI features were compared with histopathology and conventional quantitative imaging values (maximum standardized uptake value [SUVmax] and mean Hounsfield unit [HU]) to determine whether MRI radiomic features can differentiate types of nodules and associate with SUVmax and HU using Wilcoxon rank sum test and linear regression. Diagnostic performance of features and four machine learning (ML) models were evaluated with area under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CIs). Concordance correlation coefficient (CCC) assessed the segmentation variation impact on feature reproducibility and reliability. Results: Elevn diffusion-weighted features distinguished malignant from benign nodules (adjusted p < 0.05, AUC: 0.73–0.81). No features differentiated cancer types. Sixty-seven multiparametric features associated with mean CT HU and 14 correlated with SUVmax. All significant MRI features outperformed traditional imaging parameters (SUVmax, mean HU, apparent diffusion coefficient [ADC], T1, T2, dynamic contrast-enhanced imaging values) in distinguishing malignant from benign nodules with some achieving statistical significance (p < 0.05). Adding ADC and smoking history improved feature performance. Machine learning models demonstrated strong performance in nodule classification, with extreme gradient boosting (XGBoost) having the highest discrimination (AUC = 0.83, CI=[0.727, 0.932]). We found good to excellent inter- and intrareader feature reproducibility and reliability (CCC≥0.80). Conclusion: Eleven MRI radiomic features differentiated malignant from benign lung nodules, outperforming traditional quantitative methods. MRI radiomic ML models demonstrated good nodule classification performances with XGBoost superior to three others. There was good to excellent inter- and intrareader feature reproducibility and reliability. Advances in knowledge: Our study identified MRI radiomic features that successfully differentiated malignant from benign lung nodules and demonstrated high performance of our MR radiomic feature-based ML models for nodule classification. These new findings could help further establish thoracic MRI as a non-invasive and radiation-free alternative to standard practice for pulmonary nodule assessment.

Paracrine signaling between hepatic stellate cells (HSCs) and liver endothelial cells (LECs) modulates fibrogenesis, angiogenesis, and portal hypertension. However, mechanisms regulating these processes are not fully defined. Sorafenib is a receptor tyrosine kinase inhibitor that blocks growth factor signaling in tumor cells but also displays important and not yet fully characterized effects on liver nonparenchymal cells including HSCs and LECs. The aim of this study was to test the hypothesis that sorafenib influences paracrine signaling between HSCs and LECs and thereby regulates matrix and vascular changes associated with chronic liver injury. Complementary magnetic resonance elastography, micro–computed tomography, and histochemical analyses indicate that sorafenib attenuates the changes in both matrix and vascular compartments that occur in response to bile duct ligation–induced liver injury in rats. Cell biology studies demonstrate that sorafenib markedly reduces cell–cell apposition and junctional complexes, thus reducing the proximity typically observed between these sinusoidal barrier cells. At the molecular level, sorafenib down-regulates angiopoietin-1 and fibronectin, both released by HSCs in a manner dependent on the transcription factor Kruppel-like factor 6, suggesting that this pathway underlies both matrix and vascular changes associated with chronic liver disease. Conclusion: Collectively, the results of this study demonstrate that sorafenib inhibits both matrix restructuring and vascular remodeling that accompany chronic liver diseases and characterize cell and molecular mechanisms underlying this effect. These data may help to refine future therapies for advanced gastrointestinal and liver diseases characterized by abundant fibrosis and neovascularization. (Hepatology 2011;)

This study addresses whether the vasculature grows in proportion to the myocardium as the rat heart develops. The volume of myocardium and coronary vessels were estimated from micro-CT images of the hearts injected with Microfil(R) contrast agent. Young (n=5) and adult (n=5) hearts were scanned, resulting in 3D images comprised of 20μm on-a-side cubic voxels. The myocardial muscle and vessel lumen volumes were measured for all vessels 40 to 320μm in diameter by an erosion and dilation method applied to the binary images in which the contrast in the vessels were assigned "1" and all non-opacified entities were assigned "0". The average total muscle volume increases by 50%, 129.4 to 237.4mm³, from young to adult rats, while the luminal volume increases by 10%, 16.6 to 18.6mm³. The vessel volume is 12% of the total muscle volume in young and 8% in adults. For a given vessel volume, the muscle volume in the young is 82% of the muscle volume in adults. We conclude that as the heart matures, the myocardium grows more rapidly than the vasculature. This may result in greater angles of separation between vessel branches, and the increase in myocardial coronary volume. The ratio suggests either higher blood flow velocity or a lower metabolic rate in adults.

Repeated micro-CT scanning of a number of iliac crest biopsies enabled us to quantitate the variation in CT image gray-scale and spatial geometry due to variables such as specimen orientation, projection magnification, voxel size and slight differences in x-ray photon energy in each of the different scans. Using the micro-CT scanner on beamline X2B at the Brookhaven National Laboratory's National Synchrotron Light Source, we rescanned several iliac crest bone biopsy specimens, and a test phantom made of calcium hydroxyapatite, at repeated scanning sessions and evaluated the reproducibility of the spatial geometry and gray-scale haracteristics of the specimens. This scanner consists of a Bragg diffiaction source of monochromatic x-rays, a computer controlled high precision specimen rotation and translation stage assembly, and a fluorescent crystal and CCD array system for imaging the specimen at each of the angles of view around its axis of rotation during the scanning sequence. The 3-D micro-CT images consisted of up to 1024x2400², 4 μm, cubic voxels, each with 16-bit gray-scale. We also reconstructed the images at 16,32 and 48 μm voxel resolution. Partial volume effects at the surface of the bone were diminished by 'eroding' the surface voxels in the 4 μm images, but significantly changed the outcome at greater voxel size. Reproducibility of the mineral content of bone, at mean bone opacity value, was ± 28.8 mg/cm³, i.e., 2.56%, in a 4 μm cubic voxel at the 95% confidence level.