Regions of the human renal artery: histomorphometric analysis.

The renal artery is frequently involved in the pathogenesis of vasculorenal diseases, and it is a target in kidney surgery and therapeutic techniques for refractory hypertension. However, few detailed structural studies on the human renal artery have been conducted. Using histocytochemistry, immunohistochemistry, and quantitative image analysis, the wall thickness, structure, smooth muscle cells, extracellular matrix, and proportion of elastic tissue in the tunica media of main human renal arteries were used estimated. Ninety-six tissue samples were collected from sections of the right and left main renal arteries. The results showed that the renal artery changed from an elastic vessel in its proximal segment to a muscular artery in its distal part. A critical characteristic of the renal artery was the presence of longitudinal smooth muscle cell formations in the tunica adventitia of middle and distal segments but not in the proximal part of the artery. In addition, the tunica adventitia of the renal artery showed a rich vascularization and the presence of numerous nerves profiles. The artery's regional structural and morphometric features explain that a particular arterial pathology is more frequent in a specific vessel sector than in others. In addition, those characteristics could determine a different therapeutic response attending to the arterial sector.

Infrared Illumination and Subcutaneous Venous Network: Can it be of Help for the Study of CEAP C1 Limbs?

OBJECTIVE: The subcutaneous venous network (SVN) is difficult to see with the naked eye. Near infrared illumination (NIr-I) claims to improve this. The aims of this observational study were to investigate whether there are differences between the different methods; to quantify the length and diameter of SVNs; and to confirm if they differ between C0A and C1 CEAP limbs. METHODS: In total, 4 796 images, half of them from the visible spectrum (VS) and the other half from the nearninfrared spectrum (NIrS), belonging to 109 females (C0A: n = 50; C1 CEAP: n = 59) were used to establish the morphological characteristics of the SVN by visual analysis. With Photoshop CS4, SVN diameters and lengths were obtained by digital analysis of 3 052 images, once the images of whole extremities were excluded. RESULTS: On NIr-I, the diameters, trajectories, and colouration of SVNs of C1 limbs appeared more irregular than SVNs of C0A limbs. Compared with the VS images, NIr-I allowed visualisation of a greater length of the SVN in both groups (p < .010). This capacity varied from 2.6 ± 0.9 times (C1) to 16.2 ± 11.9 (C0A). While the SVN length seen in the VS images from C1 limbs was greater than observed in C0A limbs (p < .001), differences between NIr-I images only existed in the lateral part of the lower leg (p = .016). With NIr-I, the median diameter of the C1 CEAP SVN veins was 5.8 mm (interquartile range [IQR] 4.3-7.5 mm), while the median diameter in C0A SVN limbs was 2.6 mm (IQR 2.0-3.6 mm) (p < .001). CONCLUSION: The NIr-I reveals the characteristics of the SVN better than the naked eye. Further studies are required to determine the significance of the changes in the SVN in C0A and C1 limbs, and the factors causing them.

Segmentation of elastic fibres in images of vessel wall sections stained with Weigert's resorcin-fuchsin.

BACKGROUND AND OBJECTIVE: The elastic fibres are an essential component of the extracellular matrix in blood vessel walls that allows a long-range of deformability and passive recoil without energy input. The quantitative determination of elastic fibres will provide information on the state of the vascular wall and to determine the role and behaviour of this key structural element in different physiological and pathological vascular processes. METHODS: We present a segmentation method to identify and quantify elastic fibres based on a local threshold technique and some morphological characteristics measured on the segmented objects that facilitate the discrimination between elastic fibres and other image components. The morphological characteristics analysed are the thickness and the length of an object. RESULTS: The segmentation method was evaluated using an image database of vein sections stained with Weigert's resorcin-fuchsin. The performance results are based on a ground truth generated manually resulting in values of sensitivity greater than 80% with the exception in two samples, and specificity values above 90% for all samples. Medical specialists carried out a visual evaluation where the observations indicate a general agreement on the segmentation results' visual quality, and the consistency between the methodology proposed and the subjective observation of the doctors for the evaluation of pathological changes in vessel wall. CONCLUSIONS: The proposed methodology provides more objective measurements than the qualitative methods traditionally used in the histological analysis, with a significant potential for this method to be used as a diagnostic aid for many other vascular pathological conditions and in similar tissues such as skin and mucous membranes.

Quantification and Statistical Analysis Methods for Vessel Wall Components from Stained Images with Masson's Trichrome.

PURPOSE: To develop a digital image processing method to quantify structural components (smooth muscle fibers and extracellular matrix) in the vessel wall stained with Masson's trichrome, and a statistical method suitable for small sample sizes to analyze the results previously obtained. METHODS: The quantification method comprises two stages. The pre-processing stage improves tissue image appearance and the vessel wall area is delimited. In the feature extraction stage, the vessel wall components are segmented by grouping pixels with a similar color. The area of each component is calculated by normalizing the number of pixels of each group by the vessel wall area. Statistical analyses are implemented by permutation tests, based on resampling without replacement from the set of the observed data to obtain a sampling distribution of an estimator. The implementation can be parallelized on a multicore machine to reduce execution time. RESULTS: The methods have been tested on 48 vessel wall samples of the internal saphenous vein stained with Masson's trichrome. The results show that the segmented areas are consistent with the perception of a team of doctors and demonstrate good correlation between the expert judgments and the measured parameters for evaluating vessel wall changes. CONCLUSION: The proposed methodology offers a powerful tool to quantify some components of the vessel wall. It is more objective, sensitive and accurate than the biochemical and qualitative methods traditionally used. The permutation tests are suitable statistical techniques to analyze the numerical measurements obtained when the underlying assumptions of the other statistical techniques are not met.

A Low Complexity System Based on Multiple Weighted Decision Trees for Indoor Localization.

Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity. The localization system is built using a dataset from sensor fusion, which combines the strength of radio signals from different wireless local area network access points and device orientation information from a digital compass built-in mobile device, so that extra sensors are unnecessary. Experimental results indicate that the proposed system leads to substantial improvements on computational complexity over the widely-used traditional fingerprinting methods, and it has a better accuracy than they have.