Directionally Sensitive Fractal Radiomics Compatible With Irregularly Shaped Magnetic Resonance Tumor Regions of Interest: Association With Osteosarcoma Chemoresistance.

BACKGROUND: Computational analysis of routinely acquired MRI has potential to improve the tumor chemoresistance prediction and to provide decision support in precision medicine, which may extend patient survival. Most radiomic analytical methods are compatible only with rectangular regions of interest (ROIs) and irregular tumor shape is therefore an important limitation. Furthermore, the currently used analytical methods are not directionally sensitive. PURPOSE: To implement a tumor analysis that is directionally sensitive and compatible with irregularly shaped ROIs. STUDY TYPE: Retrospective. SUBJECTS: A total of 54 patients with histopathologic diagnosis of primary osteosarcoma on tubular long bones and with prechemotherapy MRI. FIELD STRENGTH/SEQUENCE: A 1.5 T, T2-weighted-short-tau-inversion-recovery-fast-spin-echo. ASSESSMENT: A model to explore associations with osteosarcoma chemo-responsiveness included MRI data obtained before OsteoSa MAP neoadjuvant cytotoxic chemotherapy. Osteosarcoma morphology was analyzed in the MRI data by calculation of the nondirectional two-dimensional (2D) and directional and nondirectional one-dimensional (1D) Higuchi dimensions (Dh). MAP chemotherapy response was assessed by histopathological necrosis. STATISTICAL TESTS: The area under the receiver operating characteristic (ROC) curve (AUC) evaluated the association of the calculated features with the actual chemoresponsiveness, using tumor histopathological necrosis (95%) as the endpoint. Least absolute shrinkage and selection operator (LASSO) machine learning and multivariable regression were used for feature selection. Significance was set at <0.05. RESULTS: The nondirectional 1D Dh reached an AUC of 0.88 in association with the 95% tumor necrosis, while the directional 1D analysis along 180 radial lines significantly improved this association according to the Hanley/McNeil test, reaching an AUC of 0.95. The model defined by variable selection using LASSO reached an AUC of 0.98. The directional analysis showed an optimal predictive range between 90° and 97° and revealed structural osteosarcoma anisotropy manifested by its directionally dependent textural properties. DATA CONCLUSION: Directionally sensitive radiomics had superior predictive performance in comparison to the standard nondirectional image analysis algorithms with AUCs reaching 0.95 and full compatibility with irregularly shaped ROIs. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Subcutaneous fat patterning in athletes: selection of appropriate sites and standardisation of a novel ultrasound measurement technique: ad hoc working group on body composition, health and performance, under the auspices of the IOC Medical Commission.

BACKGROUND: Precise and accurate field methods for body composition analyses in athletes are needed urgently. AIM: Standardisation of a novel ultrasound (US) technique for accurate and reliable measurement of subcutaneous adipose tissue (SAT). METHODS: Three observers captured US images of uncompressed SAT in 12 athletes and applied a semiautomatic evaluation algorithm for multiple SAT measurements. RESULTS: Eight 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): R(2)=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. CONCLUSIONS: A 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.

Pyramidal fractal dimension for high resolution images.

Fractal analysis (FA) should be able to yield reliable and fast results for high-resolution digital images to be applicable in fields that require immediate outcomes. Triggered by an efficient implementation of FA for binary images, we present three new approaches for fractal dimension (D) estimation of images that utilize image pyramids, namely, the pyramid triangular prism, the pyramid gradient, and the pyramid differences method (PTPM, PGM, PDM). We evaluated the performance of the three new and five standard techniques when applied to images with sizes up to 8192 × 8192 pixels. By using artificial fractal images created by three different generator models as ground truth, we determined the scale ranges with minimum deviations between estimation and theory. All pyramidal methods (PM) resulted in reasonable D values for images of all generator models. Especially, for images with sizes ≥1024×1024 pixels, the PMs are superior to the investigated standard approaches in terms of accuracy and computation time. A measure for the possibility to differentiate images with different intrinsic D values did show not only that the PMs are well suited for all investigated image sizes, and preferable to standard methods especially for larger images, but also that results of standard D estimation techniques are strongly influenced by the image size. Fastest results were obtained with the PDM and PGM, followed by the PTPM. In terms of absolute D values best performing standard methods were magnitudes slower than the PMs. Concluding, the new PMs yield high quality results in short computation times and are therefore eligible methods for fast FA of high-resolution images.

Tug-of-war lacunarity-A novel approach for estimating lacunarity.

Modern instrumentation provides us with massive repositories of digital images that will likely only increase in the future. Therefore, it has become increasingly important to automatize the analysis of digital images, e.g., with methods from pattern recognition. These methods aim to quantify the visual appearance of captured textures with quantitative measures. As such, lacunarity is a useful multi-scale measure of texture's heterogeneity but demands high computational efforts. Here we investigate a novel approach based on the tug-of-war algorithm, which estimates lacunarity in a single pass over the image. We computed lacunarity for theoretical and real world sample images, and found that the investigated approach is able to estimate lacunarity with low uncertainties. We conclude that the proposed method combines low computational efforts with high accuracy, and that its application may have utility in the analysis of high-resolution images.

Is a two-dimensional generalization of the Higuchi algorithm really necessary?

Fractal dimensions of data series, particularly time series can be estimated very well by using Higuchi's algorithm. Without phase space constructions, the fractal dimension of a one-dimensional data stream is calculated. Higuchi's method is well accepted and widely applied, because it is very reliable and easy to implement. A generalization of the genuine 1D algorithm to two dimensions would be desirable in order to investigate digital images. In this study, we propose several 2D generalization algorithms and evaluate differences between them. Additionally, a comparison to previously published pseudo 2D generalizations, and to the Fourier and the Blanket method are presented. The algorithms were tested on artificially generated grey value and red-green-blue colour images. It turned out that the proposed 2D generalized Higuchi algorithms are very robust, but differences in between the generalizations as well as differences to the pseudo 2D algorithms are astonishingly small.

Fractals in the Neurosciences: A Translational Geographical Approach.

The chapter presents three new fractal indices (fractal fragmentation index, fractal tentacularity index, and fractal anisotropy index) and normalized Kolmogorov complexity with proven applicability in geographic research, developed by the authors, and the possibility of their future use in neuroscience. The research demonstrates the relevance of fractal analysis in different fields and the basic concepts and principles of fractal geometry being sufficient for the development of models relevant to the studied reality. Also, the research highlighted the need to continue interdisciplinary research based on known fractal indicators, as well as the development of new analysis methods with the translational potential between fields.

Body composition in sport: a comparison of a novel ultrasound imaging technique to measure subcutaneous fat tissue compared with skinfold measurement.

BACKGROUND: Extremely low weight and rapid changes in weight and body composition have become major concerns in many sports, but sufficiently accurate field methods for body composition assessment in athletes are missing. This study aimed to explore the use of ultrasound methods for assessment of body fat content in athletes. METHODS: 19 female athletes (stature: 1.67(± 0.06) m, weight: 59.6(± 7.6) kg; age: 19.5(± 3.3) years) were investigated by three observers using a novel ultrasound method for thickness measurement of uncompressed subcutaneous adipose tissue and of embedded structures. Two observers also measured skinfold thickness at eight International Society for the Advancement of Kinanthrometry (ISAK) sites; mean skinfold values were compared to mean subcutaneous adipose tissue thicknesses measured by ultrasound. Interobserver reliability of imaging and evaluation obtained by this ultrasound technique: intraclass correlation coefficient ICC=0.968 (95% CI 0.957 to 0.977); evaluation of given images: ICC=0.997 (0.993 to 0.999). RESULTS: Skinfold compared to ultrasound thickness showed that compressibility of subcutaneous adipose tissue depends largely on the site and the person: regression slopes ranged from 0.61 (biceps) to 1.59 (thigh) and CIs were large. Limits of agreement ranged from 2.6 to 8.6 mm. Regression lines did not intercept the skinfold axis at zero because of the skin thickness being included in the skinfold. The four ISAK trunk sites caused ultrasound imaging problems in 13 of 152 sites (8 ISAK sites, 19 athletes). CONCLUSIONS: 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.

Body composition in sport: interobserver reliability of a novel ultrasound measure of subcutaneous fat tissue.

BACKGROUND: Very low body mass, extreme mass changes, and extremely low per cent body fat are becoming increasingly common in many sports, but sufficiently reliable and accurate field methods for body composition assessment in athletes are missing. METHODS: Nineteen female athletes were investigated (mean (SD) age: 19.5 (± 3.3) years; body mass: 59.6 (± 7.6) kg; height: 1.674 (± 0.056) m; BMI: 21.3 (± 2.3) kg/m(2)). Three observers applied diagnostic B-mode-ultrasound (US) combined with the evaluation software for subcutaneous adipose tissue measurements at eight ISAK sites (International Society for the Advancement of Kinanthrometry). Regression and reliability analyses are presented. RESULTS: US measurements and evaluation of subcutaneous adipose tissue (SAT) thicknesses (including fibrous structures: D(included); n=378) resulted in an SE of estimate SEE=0.60 mm, R(2)=0.98 (p<0.001), limit of agreement LOA=1.18, ICC=0.968 (0.957-0.977). Similar values were found for D(excluded): SEE=0.68 mm, R(2)=0.97 (p<0.001). D(included) at individual ISAK sites: at biceps, R(2)=0.87 and intraclass-correlation coefficient ICC=0.811 were lowest and SEE=0.79 mm was highest. Values at all other sites ranged from R(2): 0.94-0.99, SEE: 0.42-0.65 mm, and ICC: 0.917-0.985. Interobserver coefficients ranged from 0.92 to 0.99, except for biceps (0.74, 0.83 and 0.87). Evaluations of 20 randomly selected US images by three observers (D(included)) resulted in: SEE=0.15 mm, R(2)=0.998(p<0.001), ICC=0.997 (0.993, 0999). CONCLUSIONS: Subject to optimal choice of sites and certain standardisations, US can offer a highly reliable field method for measurement of uncompressed thickness of the SAT. High accuracy and high reliability of measurement, as obtained with this US approach, are essential for protection of the athlete's health and also for optimising performance.

ComsystanJ: A collection of Fiji/ImageJ2 plugins for nonlinear and complexity analysis in 1D, 2D and 3D.

Complex systems such as the global climate, biological organisms, civilisation, technical or social networks exhibit diverse behaviours at various temporal and spatial scales, often characterized by nonlinearity, feedback loops, and emergence. These systems can be characterized by physical quantities such as entropy, information, chaoticity or fractality rather than classical quantities such as time, velocity, energy or temperature. The drawback of these complexity quantities is that their definitions are not always mathematically exact and computational algorithms provide estimates rather than exact values. Typically, evaluations can be cumbersome, necessitating specialized tools. We are therefore introducing ComsystanJ, a novel and user-friendly software suite, providing a comprehensive set of plugins for complex systems analysis, without the need for prior programming knowledge. It is platform independent, end-user friendly and extensible. ComsystanJ combines already known algorithms and newer methods for generalizable analysis of 1D signals, 2D images and 3D volume data including the generation of data sets such as signals and images for testing purposes. It is based on the framework of the open-source image processing software Fiji and ImageJ2. ComsystanJ plugins are macro recordable and are maintained as open-source software. ComsystanJ includes effective surrogate analysis in all dimensions to validate the features calculated by the different algorithms. Future enhancements of the project will include the implementation of parallel computing for image stacks and volumes and the integration of artificial intelligence methods to improve feature recognition and parameter calculation.

Lack of acyl-CoA:diacylglycerol acyltransferase 1 reduces intestinal cholesterol absorption and attenuates atherosclerosis in apolipoprotein E knockout mice.

Triacylglycerols (TG) are the major storage molecules of metabolic energy and fatty acids in several tissues. The final step in TG biosynthesis is catalyzed by acyl-CoA:diacylglycerol acyltransferase (DGAT) enzymes. Lack of whole body DGAT1 is associated with reduced lipid-induced inflammation. Since one major component of atherosclerosis is chronic inflammation we hypothesized that DGAT1 deficiency might ameliorate atherosclerotic lesion development. We therefore crossbred Apolipoprotein E-deficient (ApoE(-/-)) mice with Dgat1(-/-) mice. ApoE(-/-) and ApoE(-/-)Dgat1(-/-) mice were fed Western-type diet (WTD) for 9weeks and thereafter examined for plaque formation. The mean atherosclerotic lesion area was substantially reduced in ApoE(-/-)Dgat1(-/-) compared with ApoE(-/-) mice in en face and aortic valve section analyses. The reduced lesion size was associated with decreased cholesterol uptake and absorption by the intestine, reduced plasma TG and cholesterol concentrations and increased cholesterol efflux from macrophages. The expression of adhesion molecules was reduced in aortas of ApoE(-/-)Dgat1(-/-) mice, which might be the reason for less migration capacities of monocytes and macrophages and the observed decreased amount of macrophages within the plaques. From our results we conclude that the lack of DGAT1 is atheroprotective, implicating an additional application of DGAT1 inhibitors with regard to maintaining cholesterol homeostasis and attenuating atherosclerosis.

Kolmogorov compression complexity may differentiate different schools of Orthodox iconography.

The complexity in the styles of 1200 Byzantine icons painted between 13th and 16th from Greece, Russia and Romania was investigated through the Kolmogorov algorithmic information theory. The aim was to identify specific quantitative patterns which define the key characteristics of the three different painting schools. Our novel approach using the artificial surface images generated with Inverse FFT and the Midpoint Displacement (MD) algorithms, was validated by comparison of results with eight fractal and non-fractal indices. From the analyzes performed, normalized Kolmogorov compression complexity (KC) proved to be the best solution because it had the best complexity pattern differentiations, is not sensitive to the image size and the least affected by noise. We conclude that normalized KC methodology does offer capability to differentiate the icons within a School and amongst the three Schools.

Determination of Heart Rate Changes using Simulated Head Up Tilt Test for Syncope Patient Assessment.

Home-based self-training can be beneficial to neurocardiogenic patients, particularly for those who experience a decreased heart rate during the clinical head up tilt test (HUT). Many patients, however, may not be able to attend a clinic and/or attend clinics which lack HUT devices. Individualized heart rate prediction based on a simulated HUT (sHUT) model may address this gap in clinical practice. The proposed sHUT model aims to predict whether home-based self-training is an appropriate beneficial intervention based on the calculated decrease in heart rate from the model. The results obtained with the model are in agreement with previous clinical findings with greater than 80% accuracy in identifying patients who could benefit from home training. The predicted home-based training efficacy of syncope against the control group had a corresponding p-value of p<0.0001. Based on these results, physicians may be able to recommend home training as part of online or telemedicine consultation.Clinical Relevance- The simulated Head Up Tilt model predicts the patient-specific efficacy of tilt-training for patients at home diagnosed with syncope.

Relative Body Weight and Standardised Brightness-Mode Ultrasound Measurement of Subcutaneous Fat in Athletes: An International Multicentre Reliability Study, Under the Auspices of the IOC Medical Commission.

INTRODUCTION: Fat is a metabolic fuel, but excess body fat is ballast mass, and therefore, many elite athletes reduce body fat to dangerously low levels. Uncompressed subcutaneous adipose tissue (SAT) thickness measured by brightness-mode ultrasound (US) provides an estimate of body fat content. METHODS: The accuracy for determining tissue borders is about 0.1-0.2 mm and reliability (experienced measurers) was within ± 1.4 mm (95% limit of agreement, LOA). We present here inter- and intra-measurer scores of three experienced US measurers from each of the centres C1 and C2, and of three novice measurers from each of the centres C3-C5. Each of the five centres measured 16 competitive adult athletes of national or international level, except for one centre where the number was 12. The following sports were included: artistic gymnastics, judo, pentathlon, power lifting, rowing, kayak, soccer, tennis, rugby, basketball, field hockey, water polo, volleyball, American football, triathlon, swimming, cycling, long-distance running, mid-distance running, hurdles, cross-country skiing, snowboarding, and ice hockey. SAT contour was detected semi-automatically: typically, 100 thicknesses of SAT at a given site (i.e., in a given image), with and without fibrous structures, were measured. RESULTS: At SAT thickness sums DI (of eight standardised sites) between 6.0 and 70.0 mm, the LOA of experienced measurers was 1.2 mm, and the intra-class correlation coefficient ICC was 0.998; novice measurers: 3.1 mm and 0.988. Intra-measurer differences were similar. The median DI value of all 39 female participants was 51 mm (11% fibrous structures) compared to 17 mm (18%) in the 37 male participants. DISCUSSION: DI measurement accuracy and precision enables detection of fat mass changes of approximately 0.2 kg. Such reliability has not been reached with any other method. Although females' median body mass index and mass index were lower than those of males, females' median DI was three times higher, and their percentage of fibrous structures was lower. The standardised US method provides a highly accurate and reliable tool for measuring SAT and thus changes in body fat, but training of measurers is important.

GIRK1 triggers multiple cancer-related pathways in the benign mammary epithelial cell line MCF10A.

Excessive expression of subunit 1 of GIRK1 in ER+ breast tumors is associated with reduced survival times and increased lymph node metastasis in patients. To investigate possible tumor-initiating properties, benign MCF10A and malign MCF7 mammary epithelial cells were engineered to overexpress GIRK1 neoplasia associated vital parameters and resting potentials were measured and compared to controls. The presence of GIRK1 resulted in resting potentials negative to the controls. Upon GIRK1 overexpression, several cellular pathways were regulated towards pro-tumorigenic action as revealed by comparison of transcriptomes of MCF10AGIRK1 with the control (MCF10AeGFP). According to transcriptome analysis, cellular migration was promoted while wound healing and extracellular matrix interactions were impaired. Vital parameters in MCF7 cells were affected akin the benign MCF10A lines, but to a lesser extent. Thus, GIRK1 regulated cellular pathways in mammary epithelial cells are likely to contribute to the development and progression of breast cancer.

Dynamics of Forest Fragmentation and Connectivity Using Particle and Fractal Analysis.

The ever decreasing area of forests has lead to environmental and economical challenges and has brought with it a renewed interest in developing methodologies that quantify the extent of deforestation and reforestation. In this study we analyzed the deforested areas of the Apuseni Mountains, which has been under economic pressure in recent years and resulted in widespread deforestation as a means of income. Deforested surface dynamics modeling was based on images contained in the Global Forest Database, provided by the Department of Geographical Sciences at Maryland University between 2000 and 2014. The results of the image particle analysis and modelling were based on Total Area (ha), Count of patches and Average Size whereas deforested area distribution was based on the Local Connected Fractal Dimension, Fractal Fragmentation Index and Tug-of-War Lacunarity as indicators of forest fragmentation or heterogeneity. The major findings of the study indicated a reduction of the tree cover area by 3.8%, an increase in fragmentation of 17.7% and an increase in heterogeneity by 29%, while fractal connectivity decreased only by 0.1%. The fractal and particle analysis showed a clustering of forest loss areas with an average increase from 1.1 to 3.0 ha per loss site per year. In conclusion, the fractal and particle analysis provide a relevant methodological framework to further our understanding of the spatial effects of economic pressure on forestry.

Age is reflected in the Fractal Dimensionality of MRI Diffusion Based Tractography.

Fractal analysis is a widely used tool to analyze the geometrical complexity of biological structures. The geometry of natural objects such as plants, clouds, cellular structures, blood vessel, and many others cannot be described sufficiently with Euclidian geometric properties, but can be represented by a parameter called the fractal dimension. Here we show that a specific estimate of fractal dimension, the correlation dimension, is able to describe changes in the structural complexity of the human brain, based on data from magnetic resonance diffusion imaging. White matter nerve fiber bundles, represented by tractograms, were analyzed with regards to geometrical complexity, using fractal geometry. The well-known age-related change of white matter tissue was used to verify changes by means of fractal dimension. Structural changes in the brain were successfully be observed and quantified by fractal dimension and compared with changes in fractional anisotropy.

Sinoatrial Beat to Beat Variability Assessed by Contraction Strength in Addition to the Interbeat Interval.

Beat to beat variability of cardiac tissue or isolated cells is frequently investigated by determining time intervals from electrode measurements in order to compute scale dependent or scale independent parameters. In this study, we utilize high-speed video camera recordings to investigate the variability of intervals as well as mechanical contraction strengths and relative contraction strengths with nonlinear analyses. Additionally, the video setup allowed us simultaneous electrode registrations of extracellular potentials. Sinoatrial node tissue under control and acetylcholine treated conditions was used to perform variability analyses by computing sample entropies and Higuchi dimensions. Beat to beat interval variabilities measured by the two recording techniques correlated very well, and therefore, validated the video analyses for this purpose. Acetylcholine treatment induced a reduction of beating rate and contraction strength, but the impact on interval variability was negligible. Nevertheless, the variability analyses of contraction strengths revealed significant differences in sample entropies and Higuchi dimensions between control and acetylcholine treated tissue. Therefore, the proposed high-speed video camera technique might represent a non-invasive tool that allows long-lasting recordings for detecting variations in beating behavior over a large range of scales.

Advantages and problems of nonlinear methods applied to analyze physiological time signals: human balance control as an example.

Physiological processes are regulated by nonlinear dynamical systems. Various nonlinear measures have frequently been used for characterizing the complexity of fractal time signals to detect system features that cannot be derived from linear analyses. We analysed human balance dynamics ranging from simple standing to balancing on one foot with closed eyes to study the inherent methodological problems when applying fractal dimension analysis to real-world signals. Higuchi dimension was used as an example. Choice of measurement and analysis parameters has a distinct influence on the computed dimension. Noise increases the fractional dimension which may be misinterpreted as a higher complexity of the signal. Publications without specifying the parameter setting, or without analysing the noise-sensitivity are not comparable to findings of others and therefore of limited scientific value.

Training echo state networks for rotation-invariant bone marrow cell classification.

The main principle of diagnostic pathology is the reliable interpretation of individual cells in context of the tissue architecture. Especially a confident examination of bone marrow specimen is dependent on a valid classification of myeloid cells. In this work, we propose a novel rotation-invariant learning scheme for multi-class echo state networks (ESNs), which achieves very high performance in automated bone marrow cell classification. Based on representing static images as temporal sequence of rotations, we show how ESNs robustly recognize cells of arbitrary rotations by taking advantage of their short-term memory capacity. The performance of our approach is compared to a classification random forest that learns rotation-invariance in a conventional way by exhaustively training on multiple rotations of individual samples. The methods were evaluated on a human bone marrow image database consisting of granulopoietic and erythropoietic cells in different maturation stages. Our ESN approach to cell classification does not rely on segmentation of cells or manual feature extraction and can therefore directly be applied to image data.

Standardized Ultrasound Measurement of Subcutaneous Fat Patterning: High Reliability and Accuracy in Groups Ranging from Lean to Obese.

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-2; 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.