It is well established that microglial form and function are inextricably linked. In recent years, the traditional view that microglial form ranges between “ramified resting” and “activated amoeboid” has been emphasized through advancing imaging techniques that point to microglial form being highly dynamic even within the currently accepted morphological categories. Moreover, microglia adopt meaningful intermediate forms between categories, with considerable crossover in function and varying morphologies as they cycle, migrate, wave, phagocytose, and extend and retract fine and gross processes. From a quantitative perspective, it is problematic to measure such variability using traditional methods, but one way of quantitating such detail is through fractal analysis. The techniques of fractal analysis have been used for quantitating microglial morphology, to categorize gross differences but also to differentiate subtle differences (e.g., amongst ramified cells). Multifractal analysis in particular is one technique of fractal analysis that may be useful for identifying intermediate forms. Here we review current trends and methods of fractal analysis, focusing on box counting analysis, including lacunarity and multifractal analysis, as applied to microglial morphology.

BackgroundPrecise and accurate field methods for body composition analyses in athletes are needed urgently.AimStandardisation of a novel ultrasound (US) technique for accurate and reliable measurement of subcutaneous adipose tissue (SAT).MethodsThree observers captured US images of uncompressed SAT in 12 athletes and applied a semiautomatic evaluation algorithm for multiple SAT measurements.ResultsEight new sites are recommended: upper abdomen, lower abdomen, erector spinae, distal triceps, brachioradialis, lateral thigh, front thigh, medial calf. Obtainable accuracy was 0.2 mm (18 MHz probe; speed of sound: 1450 m/s). Reliability of SAT thickness sums (N=36): R2=0.998, SEE=0.55 mm, ICC (95% CI) 0.998 (0.994 to 0.999); observer differences from their mean: 95% of the SAT thickness sums were within ±1 mm (sums of SAT thicknesses ranged from 10 to 50 mm). Embedded fibrous tissues were also measured.ConclusionsA minimum of eight sites is suggested to accommodate inter-individual differences in SAT patterning. All sites overlie muscle with a clearly visible fascia, which eases the acquisition of clear images and the marking of these sites takes only a few minutes. This US method reaches the fundamental accuracy and precision limits for SAT measurements given by tissue plasticity and furrowed borders, provided the measurers are trained appropriately.

The ultrasound method allows measurement of uncompressed subcutaneous adipose tissue thickness with an accuracy of 0.1-0.5 mm, depending on the probe frequency. Compressibility of the skinfold depends on the anatomical site, and skin thickness varies by a factor of two. This inevitably limits the skinfold methods for body fat estimation. Ultrasound accuracy for subcutaneous adipose tissue measurement is limited by the plasticity of fat and furrowed tissue borders. Comparative US measurements show that skinfold measurements do not allow accurate assessment of subcutaneous adipose tissue thickness.

A recently standardized ultrasound technique for measuring subcutaneous adipose tissue (SAT) was applied to normal-weight, overweight and obese persons. Eight measurement sites were used: upper abdomen, lower abdomen, erector spinae, distal triceps, brachioradialis, lateral thigh, front thigh and medial calf. Fat compression was avoided. Fat patterning in 38 participants (body mass index: 18.6-40.3 kgm; SAT thickness sums from eight sites: 12-245 mm) was evaluated using a software specifically designed for semi-automatic multiple thickness measurements in SAT (sound speed: 1450 m/s) that also quantifies embedded fibrous structures. With respect to ultrasound intra-observer results, the correlation coefficient ρ = 0.999 (p < 0.01), standard error of the estimate = 1.1 mm and 95% of measurements were within ±2.2 mm. For the normal-weight subgroup, the median measurement deviation was 0.43 mm (1.1% of mean thickness), and for the obese/overweight subgroup it was 0.89 mm (0.5%). The eight sites used here are suggested to represent inter-individual differences in SAT patterning. High measurement accuracy and reliability can be obtained in all groups, from lean to overweight and obese, provided that measurers are trained appropriately.

Significant advancements in imaging technology and the dramatic increase in computer power over the last few years broke the ground for the construction of anatomically realistic models of the heart at an unprecedented level of detail. To effectively make use of high-resolution imaging datasets for modeling purposes, the imaged objects have to be discretized. This procedure is trivial for structured grids. However, to develop generally applicable heart models, unstructured grids are much preferable. In this study, a novel image-based unstructured mesh generation technique is proposed. It uses the dual mesh of an octree applied directly to segmented 3-D image stacks. The method produces conformal, boundary-fitted, and hexahedra-dominant meshes. The algorithm operates fully automatically with no requirements for interactivity and generates accurate volume-preserving representations of arbitrarily complex geometries with smooth surfaces. The method is very well suited for cardiac electrophysiological simulations. In the myocardium, the algorithm minimizes variations in element size, whereas in the surrounding medium, the element size is grown larger with the distance to the myocardial surfaces to reduce the computational burden. The numerical feasibility of the approach is demonstrated by discretizing and solving the monodomain and bidomain equations Correspondence to: Gernot Plank, gernot.plank@medunigraz.at. on the generated grids for two preparations of high experimental relevance, a left ventricular wedge preparation, and a papillary muscle. NIH Public Access