Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity

The obesity epidemic brought a need for accessible methods to monitor body composition, as excess adiposity has been associated with cardiovascular disease, metabolic disorders, and some cancers. Recent 3-dimensional optical (3DO) imaging advancements have provided opportunities for assessing body c...

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Veröffentlicht in:The American journal of clinical nutrition 2023-09, Vol.118 (3), p.657-671
Hauptverfasser: Wong, Michael C., Bennett, Jonathan P., Quon, Brandon, Leong, Lambert T., Tian, Isaac Y., Liu, Yong E., Kelly, Nisa N., McCarthy, Cassidy, Chow, Dominic, Pujades, Sergi, Garber, Andrea K., Maskarinec, Gertraud, Heymsfield, Steven B., Shepherd, John A.
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container_issue 3
container_start_page 657
container_title The American journal of clinical nutrition
container_volume 118
creator Wong, Michael C.
Bennett, Jonathan P.
Quon, Brandon
Leong, Lambert T.
Tian, Isaac Y.
Liu, Yong E.
Kelly, Nisa N.
McCarthy, Cassidy
Chow, Dominic
Pujades, Sergi
Garber, Andrea K.
Maskarinec, Gertraud
Heymsfield, Steven B.
Shepherd, John A.
description The obesity epidemic brought a need for accessible methods to monitor body composition, as excess adiposity has been associated with cardiovascular disease, metabolic disorders, and some cancers. Recent 3-dimensional optical (3DO) imaging advancements have provided opportunities for assessing body composition. However, the accuracy and precision of an overall 3DO body composition model in specific subgroups are unknown. This study aimed to evaluate 3DO’s accuracy and precision by subgroups of age, body mass index, and ethnicity. A cross-sectional analysis was performed using data from the Shape Up! Adults study. Each participant received duplicate 3DO and dual-energy X-ray absorptiometry (DXA) scans. 3DO meshes were digitally registered and reposed using Meshcapade. Principal component analysis was performed on 3DO meshes. The resulting principal components estimated DXA whole-body and regional body composition using stepwise forward linear regression with 5-fold cross-validation. Duplicate 3DO and DXA scans were used for test–retest precision. Student’s t tests were performed between 3DO and DXA by subgroup to determine significant differences. Six hundred thirty-four participants (females = 346) had completed the study at the time of the analysis. 3DO total fat mass in the entire sample achieved R2 of 0.94 with root mean squared error (RMSE) of 2.91 kg compared to DXA in females and similarly in males. 3DO total fat mass achieved a % coefficient of variation (RMSE) of 1.76% (0.44 kg), whereas DXA was 0.98% (0.24 kg) in females and similarly in males. There were no mean differences for total fat, fat-free, percent fat, or visceral adipose tissue by age group (P > 0.068). However, there were mean differences for underweight, Asian, and Black females as well as Native Hawaiian or other Pacific Islanders (P < 0.038). A single 3DO body composition model produced accurate and precise body composition estimates that can be used on diverse populations. However, adjustments to specific subgroups may be warranted to improve the accuracy in those that had significant differences. This trial was registered at clinicaltrials.gov as NCT03637855 (Shape Up! Adults).
doi_str_mv 10.1016/j.ajcnut.2023.07.010
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Recent 3-dimensional optical (3DO) imaging advancements have provided opportunities for assessing body composition. However, the accuracy and precision of an overall 3DO body composition model in specific subgroups are unknown. This study aimed to evaluate 3DO’s accuracy and precision by subgroups of age, body mass index, and ethnicity. A cross-sectional analysis was performed using data from the Shape Up! Adults study. Each participant received duplicate 3DO and dual-energy X-ray absorptiometry (DXA) scans. 3DO meshes were digitally registered and reposed using Meshcapade. Principal component analysis was performed on 3DO meshes. The resulting principal components estimated DXA whole-body and regional body composition using stepwise forward linear regression with 5-fold cross-validation. Duplicate 3DO and DXA scans were used for test–retest precision. Student’s t tests were performed between 3DO and DXA by subgroup to determine significant differences. 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Six hundred thirty-four participants (females = 346) had completed the study at the time of the analysis. 3DO total fat mass in the entire sample achieved R2 of 0.94 with root mean squared error (RMSE) of 2.91 kg compared to DXA in females and similarly in males. 3DO total fat mass achieved a % coefficient of variation (RMSE) of 1.76% (0.44 kg), whereas DXA was 0.98% (0.24 kg) in females and similarly in males. There were no mean differences for total fat, fat-free, percent fat, or visceral adipose tissue by age group (P &gt; 0.068). However, there were mean differences for underweight, Asian, and Black females as well as Native Hawaiian or other Pacific Islanders (P &lt; 0.038). A single 3DO body composition model produced accurate and precise body composition estimates that can be used on diverse populations. However, adjustments to specific subgroups may be warranted to improve the accuracy in those that had significant differences. 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subjects Absorptiometry, Photon - methods
Accuracy
Adipose tissue
Adult
Age
Body Composition
Body fat
Body mass
Body Mass Index
Body size
Cardiovascular diseases
Coefficient of variation
Computer Science
Computer Vision and Pattern Recognition
Cross-Sectional Studies
diversity
Dual energy X-ray absorptiometry
DXA
Epidemics
Ethnicity
Female
Females
Human health and pathology
Humans
Life Sciences
Male
Males
Medical imaging
Metabolic disorders
Minority & ethnic groups
Monitoring methods
Obesity - diagnostic imaging
Optical Imaging
Original
Principal components analysis
Root-mean-square errors
Subgroups
three-dimensional optical
Underweight
title Accuracy and Precision of 3-dimensional Optical Imaging for Body Composition by Age, BMI, and Ethnicity
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