Quantitative analysis of vascular parameters for micro-CT imaging of vascular networks with multi-resolution

Quantifying Vascular Changes Surrounding Bone Regeneration in a Porcine Mandibular Defect Using Computed Tomography

Angiogenesis is a critical process essential for optimal bone healing. Several in vitro and in vivo systems have been previously used to elucidate some of the mechanisms involved in the process of angiogenesis, and at the same time, to test potential therapeutic agents and bioactive factors that play important roles in neovascularization. Computed tomography (CT) is a noninvasive imaging technique that has recently allowed investigators to obtain a diverse range of high-resolution, three-dimensional characterization of structures, such as bone formation within bony defects. Unfortunately, to date, angiogenesis evaluation relies primarily on histology, or ex vivo imaging and few studies have utilized CT to qualitatively and quantitatively study the vascular response during bone repair. In the current study a clinical CT-based technique was used to evaluate the effects of rhBMP-2 eluting graft treatment on soft tissue vascular architecture surrounding a large segmental bone defect model in the minipig mandible. The objective of this study was to demonstrate the efficacy of contrast-enhanced, clinical 64-slice CT technology in extracting quantitative metrics of vascular architecture over a 12-week period. The results of this study show that the presence of rhBMP-2 had a positive effect on vessel volume from 4 to 12 weeks, which was explained by a concurrent increase in vessel number, which was also significantly higher at 4 weeks for the rhBMP-2 treatment. More importantly, analysis of vessel architecture showed no changes throughout the duration of the study, indicating therapeutic safety. This study validates CT analysis as a relevant imaging method for quantitative and qualitative analysis of morphological characteristics of vascular tissue around a bone healing site. Also important, the study shows that CT technology can be used in large animal models and potentially be translated into clinical models for the development of improved methods to evaluate tissue healing and vascular adaptation processes over the course of therapy. This methodology has demonstrated sensitivity to tracking spatial and temporal changes in vascularization and has the potential to be applied to studying changes in other high-contrast tissues as well. Impact Statement Tissue engineering solutions depend on the surrounding tissue response to support regeneration. The inflammatory environment and surrounding vascular supply are critical to determining if therapies will survive, engraftment occurs, and native physiology is restored. This study for the first time evaluates the blood vessel network changes in surrounding soft tissue to a bone defect site in a large animal model, using clinically available computed tomography tools and model changes in vessel number, size, and architecture. While this study focuses on rhBMP2 delivery impacting surrounding vasculature, this validated method can be extended to studying the vascular network changes in other tissues as well.

Simultaneous detection of cerebral blood perfusion and cerebral edema using swept-source optical coherence tomography

The progression of ischemic cerebral edema (CE) is closely related to the level of cerebral blood perfusion (CBP) and affects each other. Simultaneous detection of CBP and CE is helpful in understanding the mechanisms of ischemic CE development. In this article, a wide field of view swept-source optical coherence tomography system was used to detect CE status and CBP levels simultaneously in middle cerebral artery occlusion rats. Images reflecting these two physiological states can be reconstructed with only one C-scan. We quantify these two physiological states into four parameters, which contain two vascular parameters (vascular displacement distance and vascular perfusion density) and two edema parameters (optical attenuation coefficient and edema area). The association between the two vascular parameters and the two edema parameters was analyzed. The results show that there is a strong linear relationship between blood flow parameters and edema parameters. This work provides a new option for CE in vivo detection, and is very likely to play an important role in the development of relevant drugs or in selection of treatment options.

An automatic multi-class coronary atherosclerosis plaque detection and classification framework

Detection of different classes of atherosclerotic plaques is important for early intervention of coronary artery diseases. However, previous methods focused either on the detection of a specific class of coronary plaques or on the distinction between plaques and normal arteries, neglecting the classification of different classes of plaques. Therefore, we proposed an automatic multi-class coronary atherosclerosis plaque detection and classification framework. Firstly, we retrieved the transverse cross sections along centerlines from the computed tomography angiography. Secondly, we extracted the region of interests based on coarse segmentation. Thirdly, we extracted a random radius symmetry (RRS) feature vector, which incorporates multiple descriptions into a random strategy and greatly augments the training data. Finally, we fed the RRS feature vector into the multi-class coronary plaque classifier. In experiments, we compared our proposed framework with other methods on the cross sections of Rotterdam Coronary Datasets, including 729 non-calcified plaques, 511 calcified plaques, and 546 mixed plaques. Our RRS with support vector machine outperforms the intensity feature vector and the random forest classifier, with the average precision of 92.6 ± 1.9% and average recall of 94.3 ± 2.1%. The proposed framework provides a computer-aided diagnostic method for multi-class plaque detection and classification. Graphical abstract Diagram of the proposed automatic multi-class coronary atherosclerosis plaque detection and classification framework. ᅟ.

Impact of Temporomandibular Joint Discectomy on Condyle Morphology: An Animal Study

PURPOSE

Temporomandibular disorders lead to parafunctional activity that may alter bone remodeling of mandibular components. This animal study aimed to assess the impact of temporomandibular joint discectomy on condylar bone microarchitecture.

MATERIALS AND METHODS

A total of 30 one-month-old Wistar rats were assessed and divided into 3 equal groups (2 test groups and 1 control group) of 10. The first test group underwent disc removal, the second test group underwent disc and condylar cartilage removal, and the 10 remaining rats were analyzed as sham-operated controls, following a split-mouth design. The rats were killed humanely 2 months after surgery, and the respective mandibles were scanned with micro-computed tomography for quantitative morphometric analysis.

RESULTS

There were significant differences among the 3 groups analyzed (disc removal, disc and condylar cartilage removal, and sham-operated control) for bone volume fraction (ratio of bone volume to total volume, P = .044), structure model index (P < .001), fractal dimension (P = .024), and porosity (P = .023). In addition, operated and contralateral nonoperated sides significantly differed for all variables in at least 1 of the test groups (P < .05) but not in the control group (P > .05).

CONCLUSIONS

Within the limitations of this study, our results suggest that discectomy may lead to alterations of the mandibular condylar morphology.

Automated tracking and quantification of angiogenic vessel formation in 3D microfluidic devices

Angiogenesis, the growth of new blood vessels from pre-existing vessels, is a critical step in cancer invasion. Better understanding of the angiogenic mechanisms is required to develop effective antiangiogenic therapies for cancer treatment. We culture angiogenic vessels in 3D microfluidic devices under different Sphingosin-1-phosphate (S1P) conditions and develop an automated vessel formation tracking system (AVFTS) to track the angiogenic vessel formation and extract quantitative vessel information from the experimental time-lapse phase contrast images. The proposed AVFTS first preprocesses the experimental images, then applies a distance transform and an augmented fast marching method in skeletonization, and finally implements the Hungarian method in branch tracking. When applying the AVFTS to our experimental data, we achieve 97.3% precision and 93.9% recall by comparing with the ground truth obtained from manual tracking by visual inspection. This system enables biologists to quantitatively compare the influence of different growth factors. Specifically, we conclude that the positive S1P gradient increases cell migration and vessel elongation, leading to a higher probability for branching to occur. The AVFTS is also applicable to distinguish tip and stalk cells by considering the relative cell locations in a branch. Moreover, we generate a novel type of cell lineage plot, which not only provides cell migration and proliferation histories but also demonstrates cell phenotypic changes and branch information.