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Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

A. Martinez-Möller, R. Bundschuh, N. Navab, S. I. Ziegler, M. Schwaiger, S. Nekolla
Determination of Body Surface Area from a whole-body CT scan and its impact for SUV normalization
Journal of Nuclear Medicine 2007, 48 (suppl. 2), p44. Proceedings of Annual Meeting of Society of Nuclear Medicine (SNM), held in Washington D.C., USA, June 2007 (bib)

Objectives Body Surface Area (BSA) is often employed to standardize measurements and therapies. It has been reported to be superior to weight for normalization of 18FDG SUVs. Formulae derived empirically (DuBois? and Gehan) are being routinely applied to estimate the BSA using weight and height of the patients, although they are known to be inaccurate especially for obese patients and children. We propose a method to automatically determine the BSA out of a whole-body CT or MR scan. Methods The whole-body scan was segmented in air and tissue compartments using a simple thresholding. Then, the surface separating both compartments was polygonized by means of the so-called marching cubes algorithm, providing the total geometrical surface. Measurements were performed using a Siemens Biograph 16 PET/CT. A cylindrical phantom with known dimensions was used to determine the accuracy of the method, and the data corresponding to 9 oncology patients examined using 18FDG were compared to the estimation by the empirical formulae. Furthermore, the feasibility of the technique with MR data was shown with a whole-body T1-weighted acquisition from a volunteer using a 1.5T Philips ACS-NT scanner. Results The accuracy for the phantom measurements was 3.2% independently of the CT parameters used for the acquisition. From the 9 patients, one had to be discarded due to a massive metal implant in the hip which created large artifacts. For the other 8 patients, the BSA was determined successfully and presented an average difference of 2.2% and 2.5% as compared to the DuBois? and Gehan formulae. The maximum observed difference for a patient was 6.3% with the DuBois? formula. Conclusions BSA can be automatically determined with high accuracy out of a whole-body CT scan even when performing ultra-low dose acquisitions. Feasibility with MR scans was also proved. In the small patient population examined, the method gave very similar results to the ones predicted by the empirical formulae, so that the impact for SUV normalization was small for these patients. However, the method could be superior in those patients where the formulae have been reported to be inaccurate.
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