Impact of retinal vascular tortuosity on retinal circulation

3D Tortuosity computation as a shape descriptor and its application to brain structure analysis

In this study, we propose a novel method for quantifying tortuosity in 3D voxelized objects. As a shape characteristic, tortuosity has been widely recognized as a valuable feature in image analysis, particularly in the field of medical imaging. Our proposed method extends the two-dimensional approach of the Slope Chain Code (SCC) which creates a one-dimensional representation of curves. The utility of 3D tortuosity ( τ 3 D ) as a shape descriptor was investigated by characterizing brain structures. The results of the τ 3 D computation on the central sulcus and the main lobes revealed significant differences between Alzheimer's disease (AD) patients and control subjects, suggesting its potential as a biomarker for AD. We found a p < 0.05 for the left central sulcus and the four brain lobes.

Unbiased analysis of mouse brain endothelial networks from two- or three-dimensional fluorescence images

Significance: A growing body of research supports the significant role of cerebrovascular abnormalities in neurological disorders. As these insights develop, standardized tools for unbiased and high-throughput quantification of cerebrovascular structure are needed. Aim: We provide a detailed protocol for performing immunofluorescent labeling of mouse brain vessels, using thin ( 25    μ m ) or thick (50 to 150    μ m ) tissue sections, followed respectively by two- or three-dimensional (2D or 3D) unbiased quantification of vessel density, branching, and tortuosity using digital image processing algorithms. Approach: Mouse brain sections were immunofluorescently labeled using a highly selective antibody raised against mouse Cluster of Differentiation-31 (CD31), and 2D or 3D microscopy images of the mouse brain vasculature were obtained using optical sectioning. An open-source toolbox, called Pyvane, was developed for analyzing the imaged vascular networks. The toolbox can be used to identify the vasculature, generate the medial axes of blood vessels, represent the vascular network as a graph, and calculate relevant measurements regarding vascular morphology. Results: Using Pyvane, vascular parameters such as endothelial network density, number of branching points, and tortuosity are quantified from 2D and 3D immunofluorescence micrographs. Conclusions: The steps described in this protocol are simple to follow and allow for reproducible and unbiased analysis of mouse brain vascular structure. Such a procedure can be applied to the broader field of vascular biology.

Tortuosity of branch retinal artery is more associated with the genesis and progress of diabetic retinopathy

OBJECTIVE

The purpose of this study is to investigate the potential of using the tortuosity of branch retinal artery as a more promising indicator for early detection and accurate assessment of diabetic retinopathy (DR).

DESIGN AND METHOD

The diagnoses, consisting of whether DR or not as well as DR severity, were given by ophthalmologists upon the assessment of those fundus images from 495 diabetic patients. Meanwhile, benefiting from those good contrast and high optical resolution fundus images taken by confocal scanning laser ophthalmoscope, the branch arteries, branch veins, main arteries and main veins in retina can be segmented independently, and the tortuosity values of them were further extracted to investigate their potential correlations with DR genesis and progress based on one-way ANOVA test.

RESULTS

For both two comparisons, i.e., between non-DR group and DR group as well as among groups with different DR severity levels, larger tortuosity increments were always observed in retinal arteries and the increments in branch retinal vessels were even larger. Furthermore, it was newly found that branch arterial tortuosity was significantly associated with both DR genesis (p=0.030) and DR progress (p<0.001).

CONCLUSION

Based on this cohort study of 495 diabetic patients without DR and with different DR severity, the branch arterial tortuosity has been found to be more closely associated with DR genesis as well as DR progress. Therefore, the branch arterial tortuosity is expected to be a more direct and specific indicator for early detection of DR as well as accurate assessment of DR severity, which can further guide timely and rational management of DR to prevent from visual impairment or even blindness resulting from DR.

Ocular Fluid Mechanics and Drug Delivery: A Review of Mathematical and Computational Models

The human eye is a complex biomechanical structure with a range of biomechanical processes involved in various physiological as well as pathological conditions. Fluid flow inside different domains of the eye is one of the most significant biomechanical processes that tend to perform a wide variety of functions and when combined with other biophysical processes play a crucial role in ocular drug delivery. However, it is quite difficult to comprehend the effect of these processes on drug transport and associated treatment experimentally because of ethical constraints and economic feasibility. Computational modeling on the other hand is an excellent means to understand the associated complexity between these aforementioned processes and drug delivery. A wide range of computational models specific to different types of fluids present in different domains of the eye as well as varying drug delivery modes has been established to understand the fluid flow behavior and drug transport phenomenon in an insilico manner. These computational models have been used as a non-invasive tool to aid ophthalmologists in identifying the challenges associated with a particular drug delivery mode while treating particular eye diseases and to advance the understanding of the biomechanical behavior of the eye. In this regard, the author attempts to summarize the existing computational and mathematical approaches proposed in the last two decades for understanding the fluid mechanics and drug transport associated with different domains of the eye, together with their application to modify the existing treatment processes.

Computational modeling of PET tracer distribution in solid tumors integrating microvasculature

BACKGROUND

We present computational modeling of positron emission tomography radiotracer uptake with consideration of blood flow and interstitial fluid flow, performing spatiotemporally-coupled modeling of uptake and integrating the microvasculature. In our mathematical modeling, the uptake of fluorodeoxyglucose F-18 (FDG) was simulated based on the Convection-Diffusion-Reaction equation given its high accuracy and reliability in modeling of transport phenomena. In the proposed model, blood flow and interstitial flow are solved simultaneously to calculate interstitial pressure and velocity distribution inside cancer and normal tissues. As a result, the spatiotemporal distribution of the FDG tracer is calculated based on velocity and pressure distributions in both kinds of tissues.

RESULTS

Interstitial pressure has maximum value in the tumor region compared to surrounding tissue. In addition, interstitial fluid velocity is extremely low in the entire computational domain indicating that convection can be neglected without effecting results noticeably. Furthermore, our results illustrate that the total concentration of FDG in the tumor region is an order of magnitude larger than in surrounding normal tissue, due to lack of functional lymphatic drainage system and also highly-permeable microvessels in tumors. The magnitude of the free tracer and metabolized (phosphorylated) radiotracer concentrations followed very different trends over the entire time period, regardless of tissue type (tumor vs. normal).

CONCLUSION

Our spatiotemporally-coupled modeling provides helpful tools towards improved understanding and quantification of in vivo preclinical and clinical studies.

Imaging the Retinal Vasculature

Advances in retinal imaging are enabling researchers and clinicians to make precise noninvasive measurements of the retinal vasculature in vivo. This includes measurements of capillary blood flow, the regulation of blood flow, and the delivery of oxygen, as well as mapping of perfused blood vessels. These advances promise to revolutionize our understanding of vascular regulation, as well as the management of retinal vascular diseases. This review provides an overview of imaging and optical measurements of the function and structure of the ocular vasculature. We include general characteristics of vascular systems with an emphasis on the eye and its unique status. The functions of vascular systems are discussed, along with physical principles governing flow and its regulation. Vascular measurement techniques based on reflectance and absorption are briefly introduced, emphasizing ways of generating contrast. One of the prime ways to enhance contrast within vessels is to use techniques sensitive to the motion of cells, allowing precise measurements of perfusion and blood velocity. Finally, we provide a brief introduction to retinal vascular diseases.

Retinal vascular tortuosity: Mechanisms and measurements

Retinal vessel tortuosity has been used in the diagnosis and management of different clinical situations. Notwithstanding, basic concepts, standards and tools of measurement, reliable normative data and clinical applications have many gaps or points of divergence. In this review we discuss triggering causes of retinal vessel tortuosity and resources used to assess and quantify it, as well as current limitations.

Image-based spatio-temporal model of drug delivery in a heterogeneous vasculature of a solid tumor - Computational approach

The solute transport distribution in a tumor is an important criterion in the evaluation of the cancer treatment efficacy. The fraction of killed cells after each treatment can quantify the therapeutic effect and plays as a helpful tool to evaluate the chemotherapy treatment schedules. In the present study, an image-based spatio-temporal computational model of a solid tumor is provided for calculation of interstitial fluid flow and solute transport. Current model incorporates heterogeneous microvasculature for angiogenesis instead of synthetic mathematical modeling. In this modeling process, a comprehensive model according to Convection-Diffusion-Reaction (CDR) equations is employed due to its high accuracy for simulating the binding and the uptake of the drug by tumor cells. Based on the velocity and the pressure distribution, transient distribution of the different drug concentrations (free, bound, and internalized) is calculated. Then, the fraction of killed cells is obtained according to the internalized concentration. Results indicate the dependence of the drug distribution on both time and space, as well as the microvasculature density. Free and bound drug concentration have the same trend over time, whereas, internalized and total drug concentration increases over time and reaches a constant value. The highest amount of concentration occurred in the tumor region due to the higher permeability of the blood vessels. Moreover, the fraction of killed cells is approximately 78.87% and 24.94% after treatment with doxorubicin for cancerous and normal tissues, respectively. In general, the presented methodology may be applied in the field of personalized medicine to optimize patient-specific treatments. Also, such image-based modeling of solid tumors can be used in laboratories that working on drug delivery and evaluating new drugs before using them for any in vivo or clinical studies.

Association of serum lutein and zeaxanthin with quantitative measures of retinal vascular parameters

To evaluate the association between serum carotenoids and quantitative measures of retinal vasculature in elderly Singapore Chinese subjects. The following details were collected in 128 healthy subjects: sociodemographics, lifestyle information, medical and drug history, and anthropometric measurements. Serum concentrations of carotenoids were estimated in fasting venous blood using high performance liquid chromatography. Retinal vascular parameters were quantitatively measured from retinal photographs using a computer-assisted program (Singapore I Vessel Assessment). The mean age of the population was 54.1 years (range 40 to 81 years). In multiple linear regression analysis, per SD decrease in retinal arteriolar caliber [β = 0.045 (0.003 to 0.086), p = 0.036], per SD increase in retinal venular caliber [β = -0.045 (-0.086 to -0.003), p = 0.036] and per SD increase in arteriolar branching angle [β = -0.039 (-0.072 to -0.006), p = 0.021] were associated with decreased serum lutein. Per SD increase in retinal venular tortuosity [β = -0.0075 (-0.0145 to -0.0004), p = 0.039] and per SD increase in arteriolar branching angle (β = -0.0073 [-0.0142 to -0.0059], p = 0.041) were associated with decreased serum zeaxanthin. None of the other carotenoids demonstrated meaningful relationship with quantitative measures of retinal vasculature. Lower levels of lutein and zeaxanthin demonstrated significant relationship with adverse quantitative measures of retinal vasculature in elderly healthy subjects.

Automatic extraction of blood vessels in the retinal vascular tree using multiscale medialness

We propose an algorithm for vessel extraction in retinal images. The first step consists of applying anisotropic diffusion filtering in the initial vessel network in order to restore disconnected vessel lines and eliminate noisy lines. In the second step, a multiscale line-tracking procedure allows detecting all vessels having similar dimensions at a chosen scale. Computing the individual image maps requires different steps. First, a number of points are preselected using the eigenvalues of the Hessian matrix. These points are expected to be near to a vessel axis. Then, for each preselected point, the response map is computed from gradient information of the image at the current scale. Finally, the multiscale image map is derived after combining the individual image maps at different scales (sizes). Two publicly available datasets have been used to test the performance of the suggested method. The main dataset is the STARE project's dataset and the second one is the DRIVE dataset. The experimental results, applied on the STARE dataset, show a maximum accuracy average of around 94.02%. Also, when performed on the DRIVE database, the maximum accuracy average reaches 91.55%.