Abstract
BackgroundWe have previously developed a novel and highly consistent PET segmentation algorithm using a multi-level Otsu method (MO-PET). The aim of this study was to evaluate the reliability of MO-PET compared to conventional PET segmentation methods for measuring 18F-FDG (FDG) PET metabolic tumor volume (MTV) in patients with soft tissue sarcoma (STS). Clinical and imaging data were obtained from the Cancer Imaging Archive. Forty-eight STS patients with FDG PET/CT and MR prior to therapy were analyzed. MTV of the tumor using MO-PET was compared to other conventional methods (absolute SUV threshold values of 2.0, 2.5, or 3.0 and percentage of tumor SUVmax values of 30, 40, 50, or 60%) and gradient-based method (PET Edge™). The reference volume was defined as an MR-based gross tumor volume (GTV). Spearman, intra-class correlation, and Bland-Altman analysis were performed to evaluate the correlation and agreement of MTV to GTV.ResultsMTVs obtained using each conventional SUV parameter, PET Edge™, and MO-PET were highly correlated with the GTV in Spearman and intra-class correlation analysis (p < 0.05). MO-PET and PET Edge™ showed high intra-class correlation coefficient of MTV to GTV (0.93 and 0.84, respectively). The Bland-Altman bias results showed the highest agreement for MTV using MO-PET with GTV (26.0 ± 489.6 cm3) compared to other methods (SUV 2.0 with − 69.3 ± 765.8, 30% SUVmax with − 255.0 ± 876.6, and PET Edge™ with − 26.46 ± 668.82 cm3).ConclusionsPET MTV segmented with MO-PET showed higher correlation and agreement with GTV in comparison to conventional percentage SUVmax and absolute SUV threshold-based PET segmentation methods. MO-PET is comparable to PET Edge™. MO-PET is a reliable and consistent method for measuring tumor MTV.
Highlights
We have previously developed a novel and highly consistent PET segmentation algorithm using a multi-level Otsu method (MO-PET)
Image analysis All positron emission tomography/computed tomography (PET/CT) and MRI images were analyzed with Mirada RTx (Mirada Medical Ltd., Denver, CO, USA), with additional method to PET segmentation (MO-PET) segmentation algorithm developed and implemented as a plugin tool to use with ImageJ, an image processing program developed by NIH
metabolic tumor volume (MTV) was measured with PET EdgeTM (MIM software Inc., Cleveland, OH, USA), a gradient-based PET segmentation method
Summary
We have previously developed a novel and highly consistent PET segmentation algorithm using a multi-level Otsu method (MO-PET). The aim of this study was to evaluate the reliability of MO-PET compared to conventional PET segmentation methods for measuring 18F-FDG (FDG) PET metabolic tumor volume (MTV) in patients with soft tissue sarcoma (STS). It was reported that tumor maximum SUV (SUVmax) is related with the prognosis of cancers [3,4,5]. Due to the limitations of the SUV, it is difficult to use only SUVmax for the prediction of tumor prognosis, and other significant PET indexes are needed. It was reported that MTV (one of the PET parameters) is related to the prognosis of various cancers [1, 3, 9, 10]
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