PT - JOURNAL ARTICLE AU - Huang, Emerald AU - Solaiyappan, Meiyappan AU - Cho, Steve TI - <strong>Improved Stability and Performance of <sup>18</sup>F-FDG PET Automated Tumor Segmentation Using Multi-level Maximization of Inter-class Variance Method</strong> DP - 2015 May 01 TA - Journal of Nuclear Medicine PG - 452--452 VI - 56 IP - supplement 3 4099 - http://jnm.snmjournals.org/content/56/supplement_3/452.short 4100 - http://jnm.snmjournals.org/content/56/supplement_3/452.full SO - J Nucl Med2015 May 01; 56 AB - 452 Objectives There is an emerging need for a stable and consistent method for volumetric delineation of tumor PET data as current methods can produce varying results depending on the tumor sizes and FDG uptake levels. We developed a novel automated threshold method and tested its accuracy across different tumor sizes and PET standardized uptake values (SUVs) compared to current methods.Methods Twenty-five tumors of varying sizes (range: 0.59 to 21.01 cm3) and SUVs (range: 3.17 to 25.80) on FDG PET were segmented using a multi-Otsu based (MO) method, which maximized inter-class variance, to derive metabolic tumor volume (MTV). Results were compared with MTVs from 7 different PET threshold methods: 20%, 40%, 60%, or 80% of the maximum SUV (SUVmax), and mean liver SUV + 1, +2, and +3 standard deviations (SD). CT-based gross tumor volume (GTV) was used as a reference standard. To evaluate segmentation accuracy, we compared volume ratio (VR) or the ratio of MTV to GTV. VR closer to 1 pointed toward a better segmentation strategy.Results MO method, among all tested methods, resulted in the most consistent mean VR (closest to 1) for a wide range of tumor sizes: 0 to 1 cm3 tumors (mean VR ± SD = 1.33 ± 0.32), 1 to 2 cm3 tumors (mean VR ± SD = 1.10 ± 0.41), 2 to 3 cm3 tumors (mean VR ± SD = 1.09 ± 0.22), and tumors greater than 3 cm3 (mean VR ± SD = 1.06 ± 0.17). MO method also consistently produced VR that is closest to 1 for tumors with varying PET SUVs or FDG uptake levels: SUVmax 0 to 5 (mean VR ± SD = 1.32 ± 0.32), SUVmax 5 to 10 (mean VR ± SD = 1.16 ± 0.30), SUVmax 10 to 15 (mean VR ± SD = 1.00 ± 0.19), and SUVmax &gt; 15 (mean VR ± SD = 1.09 ± 0.10).Conclusions We have demonstrated a novel PET tumor segmentation method, which allows for stable and consistent delineation across a range of clinically applicable tumor sizes and PET SUV values compared to current methods.