Paper 15.038

D. B. Stefan and D. A. Gilbert, "Categorizing the Morbidly Obese Body Shape and Estimating Body Appearance Outcome before Weight Loss Surgery Using 3D Anthropometric Data", in Proc. of 6th Int. Conf. on 3D Body Scanning Technologies, Lugano, Switzerland, 2015, pp. 38-53, doi:10.15221/15.038.


Categorizing the Morbidly Obese Body Shape and Estimating Body Appearance Outcome before Weight Loss Surgery Using 3D Anthropometric Data


David B. STEFAN 1, David A. GILBERT 2

1 Novaptus Systems Inc., Chesapeake, VA, USA;
2 The Hague Plastic and Cosmetic Surgery Center, Norfolk, VA, USA


Background. Categorizing the physical shape of the morbidly obese has been an inexact science. Surgeons can readily identify extreme shapes such as "android" or "gynecoid" but will have various opinions as to the shape of the individual that presents between these two extremes. Yet the physical shape of the patient is often an indicator as to the potential difficulty of the pending surgery. Using linear, circumferential, volume and surface area data provided by scanning morbidly obese individuals, a set of mathematical equations has been developed that classifies their primary shape and their shape tendency. With some exceptions, it has been found that these shape indicators remain consistent throughout the massive weight loss experience. This finding, combined with longitudinal data collected by scanning, aggregating and de-identifying thousands of surgical weight loss individuals allows the capability to estimate body appearance outcome prior to actual weight loss surgery, thus providing a realistic motivational tool to the pre-operative surgical candidate.
Methods. 1000 bariatric surgery candidates were scanned using a commercial 3D scanning device. The body image produced was measured using embedded measurement tools. Measurements included linear, circumferential, volume and surface area information. Torso height was determined, as was the height of the maximum circumference of the torso. The mid-point height of the torso was also determined. Ratios were developed that used this information to create a Shape Descriptor Scale. The Shape Descriptor Scale defines the shape of the bariatric individual, as well as the tendency of their shape. Individuals were scanned periodically after surgery and their Shape Descriptors calculated. Circumferential measurement, surface area and volume changes were normalized to excess weight lost during the period between scans. Predictive models were developed based on the standard 75% excess weight loss expected in one year after bypass or sleeve weight loss surgery.
Results. Categorizing the morbidly obese shape numerically using this technique is repeatable and not subject to various opinion. Those classified as android have a tendency to be more difficult and lengthier surgeries. Most of the morbidly obese, with some exceptions, appear to have the same numerical shape descriptors even after massive weight loss. This allows the ability to create a realistic predictive model of how the morbidly obese individual would appear at various intervals along the weight loss curve and at the end of the expected excess weight loss.
Conclusion. The development of the Shape Descriptor Scale and associated algorithms were made possible by the insight gained from having surface area and volume data along with heights of certain measurements. This information was created by 3D booth scanning, and combined in such a way to not only determine the shape of the morbidly obese, but also to use these shape characteristics along with other multidimensional data provided by the scanner and the individual's weight at the time of the scan to develop statistically accurate predictive weight loss models.


Full paper: 15.038.pdf
Proceedings: 3DBST 2015, 27-28 Oct. 2015, Lugano, Switzerland
Pages: 38-53
DOI: 10.15221/15.038

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