Quantification of Body Shape, Surface Area and Volume with White Light Scanning in Human Subjects

John Pender, MD, Konstantinos Spaniolas, MD, William Chapman, MD, Edgar Moore, MD, Lynis Dohm, MD, Stephen Wohlgemuth, MD, Walter Pories, MD. East Carolina University and Easter Virgina Medical School.

Objective: At present there are no clinically feasible methods for accurately quantifying morbid obesity. BMI, while convenient, fails to distinguish fat from fitness. More complex and expensive techniques limit accessibility and provide limited anthropometrical information. All current techniques do not take into account the physical shape of the subject. Commercially available, economical and compact 3D body scanners offer extensive measurement capabilities, including surface area and volume. Combining common measurements with multidimensional information offers an accurate approach to measuring body shape and volume which, in turn, yields potential insight into the metabolic syndrome.

Technology:  3D body scanners have made great strides in lowering cost, reducing their footprint and adopting widely available imaging technology to such a point that their operation in a clinical environment has been initiated. Originally (and currently) used in the custom tailored clothing industry for made-to-measure garments, the measurement software associated with these scanners has been modified to investigate categorizing morbidly obese subjects.

There are 3 steps to capturing an accurate 3D whole body model of the subject standing in the scan chamber. The first is to capture multiple images from cameras placed at fixed angles to the subject. Earlier versions of 3D scanners employed white light. Projectors would flash a pattern of light on the subject, and cameras would receive the reflection. Upgraded technology has replaced the white light sensors with near-field infrared cameras. These cameras sense the body heat of the subject within a short distance. Regardless of the imaging technique utilized, the raw images taken from various camera angles are collected.

The second step is to process the collected images into an accurate composite binary 3D body model of the subject. This is done using fractal geometry techniques. Once the binary 3D body model is produced, the software then searches for specific landmarks on the body surface. It then produces a measurable body model separated into its constituent parts (torso, right and left legs, right and left arms, right and left hands).

The third and final step is to apply specific measurement templates to the reduced 3D body model. One can apply any number of measurement templates to this body model to extract linear and circumferential measurements (including the height of each measurement) and surface area and volume calculations.

 

Significance/Future Direction: These 3D body scanners, when employed in a clinical environment, offer the ability to perform a quick, complete spatial categorization of the obese subject. Measurement techniques have been developed to mathematically quantify the shape of the subject, determine the “space” the subject occupies without regard to weight, and indicate the subject’s Central Obesity Tendency. This technology promises to be an accurate and safe tool for the evaluation of severe obesity and its comorbidities.

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