High‐Resolution Three‐Dimensional Photonic Scan‐Derived Equations Improve Body Surface Area Prediction in Diverse Populations

Abstract

Objective Equations for predicting body surface area (BSA) produce flawed estimates, especially for individuals with obesity. This study aimed to compare BSA measured by a three‐dimensional photonic scanner (3DPS) with BSA predicted by six commonly cited prediction equations and to develop new prediction equations if warranted. Methods The 3DPS was validated against manual measurements by breadth caliper for body thicknesses measured at three anatomical sites on a mannequin. BSA was derived from 3DPS whole‐body scans of 67 males and 201 females, aged 18 to 83 years, with BMI between 17.8 and 77.8 kg/m2 and varied races/ethnicities. Results Width and depth measurements by 3DPS and caliper were within 1%, except for hip, with an error of 1.8%. BSA3DPS differed from BSA predicted by each equation (P < 0.05), except for males by DuBois and DuBois (P = 0.60), Tikuisis (P = 0.27), and Yu (P = 0.45) and for females by Tikuisis (P = 0.70). The combined and sex‐specific equations obtained by regressing ln(BSA) on ln(weight in kilograms [W]) and ln(height in meters [H]) are as follows (R2 and SEE correspond to ln[BSA]): combined, BSA3DPS = 0.03216 × W0.4904 × H0.3769, R2 = 0.982, SEE = 0.021; males, BSA3DPS = 0.01624 × W0.4725 × H0.5231; and females, BSA3DPS = 0.01522 × W0.4921 × H0.5231, R2 = 0.986, SEE = 0.019. Conclusions New height and weight BSA equations improve BSA estimation in individuals with BMI ≥ 40 and in African Americans, Hispanic Americans, and Asian Americans.

Repository Describing the Anatomical, Physiological, and Biological Changes in an Obese Population to Inform Physiologically Based Pharmacokinetic Models

“…When covariates were missing, these were estimated using our derived equations, as done by Williams and Leggett [ 19 ]; primary covariates, such as anthropometric variables, were derived only for the verification dataset, while secondary covariates, such as cardiac output or adipose tissue weight, were also derived for the development dataset. The body surface area (BSA) was calculated according to the Ashby–Thompson equation (not using the mostly commonly used DuBois and DuBois equation) because it was developed using a new technology (three-dimensional photonic scanner), a richer dataset (268 vs. 9 individuals) and wider BMI range (17.8–77.8 vs. 15.3–41.5 kg/m 2 ), and the authors found it improved the BSA prediction in individuals with a BMI ≥ 40 [ 20 ].…”

The effect of female breast surface area on heat‐activated sweat gland density and output

“…It is worth nothing that, as far as the authors are aware, no BSA prediction equation currently exists which accounts for BrSA in women. For example, equations to better estimate BSA in specific populations, including women, have been recently published (Ashby‐Thompson et al., 2020 ), and they (somewhat) overcome previous limitations with, for example, Du Bois and Du Bois equations, particularly in larger individuals. Yet, these corrected equations still do not account for variation in BrSA in women.…”

Investigation of Underlying Association between Anthropometric and Cardiorespiratory Fitness Markers among Overweight and Obese Adolescents in Canada

“…Body surface area (BSA) is a measure of the total surface area of the human body. Given the substantial variability in body size across individuals, BSA has emerged as a standardization tool for various clinical assessments of biological function [30]. BSA is particularly useful in children and adolescents because it gives a more accurate assessment of morphological changes during growth.…”