ESTRO 2023 - Abstract Book

S809

Monday 15 May 2023

ESTRO 2023

in LBCL, as the disease is often widespread through the body with nodal and extranodal involvement, and with a wide range in tumor volumes. In addition, delineation of MATV is not a standard procedure in the response assessment of LBCL patients. Multiple semi-automated SUV thresholding methods are used in research practice. However, it is currently unclear which thresholding method is optimal for prediction of treatment outcome. The aim of this study was to develop a semi-automatic multi-threshold PET segmentation approach, to extract MATVs with a one-click-per-lesion approach in a publicly accessible software tool, and evaluate the methods in a LBCL patient cohort. Materials and Methods A software tool was developed as an extension for 3D Slicer, where tumor locations are identified by placing seed-points on the PET images, followed by subsequent region growing. Based on previous studies, selected SUV thresholding methods included fixed, relative and majority voting based methods. MATVs were extracted from the resulting segmentations. Our software tool was utilized in a use-case cohort of 68 patients with LBCL. Significant differences in MATVs between the SUV thresholding methods were assessed with paired t-tests. Kaplan-Meier analysis was used on a sub-selection of 50 patients, of which a pre-treatment PET/CT was available, to estimate 2-year overall survival (OS), for low (< 200 cc) and high ( ≥ 200 cc) MATV groups. Results Nine SUV thresholding methods were identified and selected. High variability was observed for MATVs extracted with our software tool and significantly differed between segmentation methods ( p < 0.05) (Figure 1). Median MATVs ranged from 35 to 211 cc, where most variability was observed between relative SUV thresholding methods.

Contribution of MATV to overall survival (OS) prediction differed between SUV threshold methods using the same cut-off (Figure 2). MATV of 2 fixed methods did not significantly associate with OS (log-rank p -value < 0.05). The MATV retrieved with a relative- and a majority voting method did significantly associate with OS ( p = 0.0059 for PERCIST, p = 0.034 for MV3).