Shape-based three-dimensional body composition extrapolation using multimodality registration

Whilst the assessment of body composition is routine practice in sport, there remains considerable debate on the best tools available, with the chosen technique often based upon convenience rather than understanding the method and its limitations. The aim of this manuscript was threefold: (1) provide an overview of the common methodologies used within sport to measure body composition, specifically hydro-densitometry, air displacement plethysmography, bioelectrical impedance analysis and spectroscopy, ultra-sound, three-dimensional scanning, dual-energy x-ray absorptiometry (DXA) and skinfold thickness; (2) compare the efficacy of what are widely believed to be the most accurate (DXA) and practical (skinfold thickness) assessment tools and (3) provide a framework to help select the most appropriate assessment in applied sports practice including insights from the authors’ experiences working in elite sport. Traditionally, skinfold thickness has been the most popular method of body composition but the use of DXA has increased in recent years, with a wide held belief that it is the criterion standard. When bone mineral content needs to be assessed, and/or when it is necessary to take limb-specific estimations of fat and fat-free mass, then DXA appears to be the preferred method, although it is crucial to be aware of the logistical constraints required to produce reliable data, including controlling food intake, prior exercise and hydration status. However, given the need for simplicity and after considering the evidence across all assessment methods, skinfolds appear to be the least affected by day-to-day variability, leading to the conclusion ‘come back skinfolds, all is forgiven’.

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Artificial intelligence-aided CT segmentation for body composition analysis: a validation study

European Radiology Experimental ◽

10.1186/s41747-021-00210-8 ◽

2021 ◽

Vol 5 (1) ◽

Author(s):

Pablo Borrelli ◽

Reza Kaboteh ◽

Olof Enqvist ◽

Johannes Ulén ◽

Elin Trägårdh ◽

...

Keyword(s):

Artificial Intelligence ◽

Body Composition ◽

Three Dimensional ◽

Test Group ◽

Training Group ◽

Ct Images ◽

Composition Analysis ◽

Individual Subject ◽

Body Composition Analysis ◽

Ct Segmentation

Abstract Background Body composition is associated with survival outcome in oncological patients, but it is not routinely calculated. Manual segmentation of subcutaneous adipose tissue (SAT) and muscle is time-consuming and therefore limited to a single CT slice. Our goal was to develop an artificial-intelligence (AI)-based method for automated quantification of three-dimensional SAT and muscle volumes from CT images. Methods Ethical approvals from Gothenburg and Lund Universities were obtained. Convolutional neural networks were trained to segment SAT and muscle using manual segmentations on CT images from a training group of 50 patients. The method was applied to a separate test group of 74 cancer patients, who had two CT studies each with a median interval between the studies of 3 days. Manual segmentations in a single CT slice were used for comparison. The accuracy was measured as overlap between the automated and manual segmentations. Results The accuracy of the AI method was 0.96 for SAT and 0.94 for muscle. The average differences in volumes were significantly lower than the corresponding differences in areas in a single CT slice: 1.8% versus 5.0% (p < 0.001) for SAT and 1.9% versus 3.9% (p < 0.001) for muscle. The 95% confidence intervals for predicted volumes in an individual subject from the corresponding single CT slice areas were in the order of ± 20%. Conclusions The AI-based tool for quantification of SAT and muscle volumes showed high accuracy and reproducibility and provided a body composition analysis that is more relevant than manual analysis of a single CT slice.

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Validity of a Three-Dimensional Body Scanner: Comparison Against a 4-Compartment Model and Dual Energy X-Ray Absorptiometry

Applied Physiology Nutrition and Metabolism ◽

10.1139/apnm-2020-0744 ◽

2020 ◽

Author(s):

Hannah E. Cabre ◽

Malia N.M. Blue ◽

Katie R. Hirsch ◽

Gabrielle J Brewer ◽

Lacey Marie Gould ◽

...

Keyword(s):

Body Composition ◽

Total Error ◽

Three Dimensional ◽

Bioelectrical Impedance ◽

Compartment Model ◽

3D Scanner ◽

Body Composition Assessment ◽

Air Displacement Plethysmography ◽

X Ray ◽

Body Scanner

Three-dimensional (3D) body scanner technology for body composition assessment is expanding. The aim of this study was to assess the validity of a 3D body scanner. 194 participants (43% male; Age: 23.52±5.47 yrs; BMI: 23.98±3.24 kg·m-2) were measured using 3D scanner and a 4-compartment (4C) model utilizing DXA, air displacement plethysmography, and bioelectrical impedance spectroscopy. Dependent t-tests, validity statistics including total error (TE), standard error of the estimate (SEE), constant error, and Bland-Altman analyses were utilized. Compared to 4C, 3D scanner FM [mean difference (MD; 3D- 4C): 2.66 kg±3.32 kg] and %BF (MD: 4.13%±5.36%) were significantly (p<0.001) over-predicted; FFM was significantly underpredicted (MD: -3.15 kg±4.75 kg; p<0.001). 3D demonstrated poor validity indicated by TE (%BF: 5.61%; FM: 4.50 kg; FFM: 5.69 kg). In contrast, there were no significant differences between 3D and DXA measures; 3D scanner demonstrated acceptable measurement for %BF (TE: 4.25%), FM (TE: 2.92 kg), and LM (TE: 3.86 kg). Compared to the 4C criterion, high TE values indicated 3D estimates were not valid. In contrast, 3D estimates produced acceptable measurement agreement when compared to DXA; an average overestimation of %BF by 5.31% (vs. 4C) and 4.20% (vs. DXA) may be expected. Novelty: • 3D body composition estimates are not valid compared to the 4-compartment criterion model. • 3D estimates appeared to be more valid in females, compared to males. • When compared to DXA, 3D estimates were acceptable.

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Correlation between indicators of a three-dimensional scan of the spine, body composition and stabilometry in weightlifters with supreme sports skills

Bulletin of the South Ural State University Series Education health physical culture ◽

10.14529/ozfk150103 ◽

2015 ◽

Vol 15 (1) ◽

pp. 14-23

Author(s):

A Isaev ◽

K Alekseev ◽

N Menshikova ◽

A Smirnov ◽

R Homenko ◽

...

Keyword(s):

Body Composition ◽

Three Dimensional ◽

Sports Skills

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Validation of a Three-Dimensional Body Scanner for Body Composition Measures

Medicine & Science in Sports & Exercise ◽

10.1249/01.mss.0000517564.64788.c7 ◽

2017 ◽

Vol 49 (5S) ◽

pp. 259

Author(s):

Michelle M. Harbin

Keyword(s):

Body Composition ◽

Three Dimensional ◽

Body Scanner

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New techniques in nutritional assessment: Body composition methods

Proceedings of The Nutrition Society ◽

10.1079/pns19990005 ◽

1999 ◽

Vol 58 (1) ◽

pp. 33-38 ◽

Cited By ~ 18

Author(s):

M. Elia ◽

L. C. Ward

Keyword(s):

Body Composition ◽

Nutritional Assessment ◽

Fat Body ◽

Three Dimensional ◽

Area Under The Curve ◽

Bioelectrical Impedance ◽

The Body ◽

Measurement Instruments ◽

New Techniques ◽

Bod Pod

New techniques in air-displacement plethysmography seem to have overcome many of the previous problems of poor reproducibility and validity. These have made body-density measurements available to a larger range of individuals, including children, elderly and sick patients who often have difficulties in being submerged underwater in hydrodensitometry systems. The BOD POD air-displacement system (BOD POD body composition system; Life Measurement Instruments, Concord, CA, USA) is more precise than hydrodensitometry, is simple and rapid to operate (approximately 1 min measurements) and the results agree closely with those of hydrodensitometry (e.g. ± 3.4 % for estimation of body fat). Body line scanners employing the principles of three-dimensional photography are potentially able to measure the surface area and volume of the body and its segments even more rapidly (approximately 10s), but the validity of the measurements needs to be established. Advances in i.r. spectroscopy and mathematical modelling for calculating the area under the curve have improved precision for measuring enrichment of 2H2O in studies of water dilution (CV 0.1–0.9 % within the range of 400–1000 μl/1) in saliva, plasma and urine. The technique is rapid and compares closely with mass spectrometry (bias 1 (SD 2) %). Advances in bedside bioelectrical-impedance techniques are making possible potential measurements of skinfold thicknesses and limb muscle mass electronically. Preliminary results suggest that the electronic method is more reproducible (intra- and inter-individual reproducibility for measuring skinfold thicknesses) and associated with less bias (+ 12 %), than anthropometry (+40%). In addition to these selected examples, the ‘mobility’ or transfer of reference methods between centres has made the distinction between reference and bedside or field techniques less distinct than in the past.

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