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Related Experiment Video

Updated: May 5, 2026

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research
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Artificial intelligence-driven body surface area (BSA) estimation using computed tomography: Comparative evaluation

Ronnie Sebro1,2,3, Mahmoud Elmahdy4

  • 1Department of Epidemiology, MD Anderson Cancer Center, University of Texas, 1515 Holcombe Blvd, Unit 1475, Houston, TX.

Medicine
|May 4, 2026
PubMed
Summary
This summary is machine-generated.

New formulas estimate total body surface area (BSA) more accurately than existing methods. This advancement improves drug dosing by providing a better measure of metabolic mass, accounting for factors like race and sex.

Keywords:
body surface areadoseequationspharmacologyrace/ethnicity

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Area of Science:

  • Medical Imaging and Radiology
  • Biostatistics
  • Clinical Pharmacology

Background:

  • Total body surface area (BSA) is crucial for drug dosing and predicting metabolic mass, often preferred over body weight due to its reduced sensitivity to abnormal adipose tissue.
  • Existing BSA estimation formulas primarily rely on 2D measurements and may use outdated statistical methods, potentially limiting their accuracy.
  • The need for precise BSA estimation is critical in clinical medicine for safe and effective therapeutic interventions.

Purpose of the Study:

  • To develop and validate novel formulas for estimating total body surface area (BSA) using 3D imaging data.
  • To improve the accuracy of BSA estimation by incorporating patient demographics such as sex and race, alongside height and weight.
  • To compare the performance of the newly developed BSA formulas against established methods.

Main Methods:

  • Analysis of 3D whole-body positron emission tomography/computed tomography (PET/CT) scans from 698 patients to derive BSA measurements.
  • Utilized TotalSegmentator software on CT components for accurate 3D BSA quantification.
  • Employed multivariable ridge regression with 5-fold cross-validation to create new BSA estimation formulas, adjusting for sex, race, height, and weight.

Main Results:

  • Established a strong positive correlation between BSA and both height (R=0.49) and weight (R=0.83).
  • Developed an optimal formula for BSA estimation: [Formula].
  • Demonstrated that the new formulas significantly outperformed all previously existing BSA formulas in accuracy, with lower mean absolute error and mean squared error.

Conclusions:

  • The newly derived BSA estimation formulas offer superior accuracy compared to traditional methods.
  • These advanced formulas provide a more reliable tool for clinical applications, particularly in drug dosing.
  • The study highlights the importance of utilizing 3D imaging data and robust statistical techniques for precise physiological measurements.