Measurement of metabolic tumor volume: static versus dynamic FDG scans
1 Department of Nuclear Medicine & PET Research, VU University Medical Center, P.O. Box 7057, Amsterdam, 1007 MB, The Netherlands
2 Department of Nuclear Medicine, Jeroen Bosch Hospital, 's-Hertogenbosch, 5223 GZ, The Netherlands
3 Bristol-Myers Squibb, Princeton, NJ, 08543, USA
EJNMMI Research 2011, 1:35 doi:10.1186/2191-219X-1-35Published: 14 December 2011
Metabolic tumor volume assessment using positron-emission tomography [PET] may be of interest for both target volume definition in radiotherapy and monitoring response to therapy. It has been reported, however, that metabolic volumes derived from images of metabolic rate of glucose (generated using Patlak analysis) are smaller than those derived from standardized uptake value [SUV] images. The purpose of this study was to systematically compare metabolic tumor volume assessments derived from SUV and Patlak images using a variety of (semi-)automatic tumor delineation methods in order to identify methods that can be used reliably on (whole body) SUV images.
Dynamic [18F]-fluoro-2-deoxy-D-glucose [FDG] PET data from 10 lung and 8 gastrointestinal cancer patients were analyzed retrospectively. Metabolic tumor volumes were derived from both Patlak and SUV images using five different types of tumor delineation methods, based on various thresholds or on a gradient.
In general, most tumor delineation methods provided more outliers when metabolic volumes were derived from SUV images rather than Patlak images. Only gradient-based methods showed more outliers for Patlak-based tumor delineation. Median measured metabolic volumes derived from SUV images were larger than those derived from Patlak images (up to 59% difference) when using a fixed percentage threshold method. Tumor volumes agreed reasonably well (< 26% difference) when applying methods that take local signal-to-background ratio [SBR] into account.
Large differences may exist in metabolic volumes derived from static and dynamic FDG image data. These differences depend strongly on the delineation method used. Delineation methods that correct for local SBR provide the most consistent results between SUV and Patlak images.