Semi-automated 18F-FDG PET segmentation methods for tumor volume determination in Non-Hodgkin lymphoma patients: a literature review, implementation and multi-threshold evaluation

Kylie Keijzer; Anne G H Niezink; Janneke W de Boer; Jaap A van Doesum; Walter Noordzij; Tom van Meerten; Lisanne V van Dijk

doi:10.1016/j.csbj.2023.01.023

Semi-automated ¹⁸F-FDG PET segmentation methods for tumor volume determination in Non-Hodgkin lymphoma patients: a literature review, implementation and multi-threshold evaluation

Comput Struct Biotechnol J. 2023 Jan 20:21:1102-1114. doi: 10.1016/j.csbj.2023.01.023. eCollection 2023.

Authors

Kylie Keijzer^{1

2}, Anne G H Niezink², Janneke W de Boer¹, Jaap A van Doesum¹, Walter Noordzij³, Tom van Meerten¹, Lisanne V van Dijk²

Affiliations

¹ Department of Hematology, University Medical Center Groningen, Hanzeplein 1, 9713GZ Groningen, the Netherlands.
² Department of Radiation Oncology, University Medical Center Groningen, Hanzeplein 1, 9713GZ Groningen, the Netherlands.
³ Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Hanzeplein 1, 9713GZ Groningen, the Netherlands.

Abstract

In the treatment of Non-Hodgkin lymphoma (NHL), multiple therapeutic options are available. Improving outcome predictions are essential to optimize treatment. The metabolic active tumor volume (MATV) has shown to be a prognostic factor in NHL. It is usually retrieved using semi-automated thresholding methods based on standardized uptake values (SUV), calculated from ¹⁸F-Fluorodeoxyglucose Positron Emission Tomography (¹⁸F-FDG PET) images. However, there is currently no consensus method for NHL. The aim of this study was to review literature on different segmentation methods used, and to evaluate selected methods by using an in house created software tool. A software tool, MUltiple SUV Threshold (MUST)-segmenter was developed where tumor locations are identified by placing seed-points on the PET images, followed by subsequent region growing. Based on a literature review, 9 SUV thresholding methods were selected and MATVs were extracted. The MUST-segmenter was utilized in a cohort of 68 patients with NHL. Differences in MATVs were assessed with paired t-tests, and correlations and distributions figures. High variability and significant differences between the MATVs based on different segmentation methods (p < 0.05) were observed in the NHL patients. Median MATVs ranged from 35 to 211 cc. No consensus for determining MATV is available based on the literature. Using the MUST-segmenter with 9 selected SUV thresholding methods, we demonstrated a large and significant variation in MATVs. Identifying the most optimal segmentation method for patients with NHL is essential to further improve predictions of toxicity, response, and treatment outcomes, which can be facilitated by the MUST-segmenter.

Keywords: 18F-FDG PET; AT, adaptive thresholding methods; CAR, chimeric antigen receptor; CT, computed tomography; DICOM, Digital Imaging and Communications in Medicine; DLBCL, Diffuse large B-cell lymphoma; EANM, European Association of Nuclear Medicine; EARL, EANM Research Ltd.; FDG, fluorodeoxyglucose; HL, Hodgkin lymphoma; IMG, robustness across image reconstruction methods; IQR, interquartile range; LBCL, Large B-cell lymphoma; LDH, lactate dehydrogenase; MAN, clinician based evaluation using manual segmentations; MATV, Metabolic active tumor volume; MIP, Maximum Intensity Projection; MUST, Multiple SUV Thresholding; Metabolic tumor volume; NHL, Non-Hodgkin lymphoma; Non-Hodgkin lymphoma; OBS, robustness across observers; OS, overall survival; PD-L1, programmed cell death ligand-1; PET segmentation; PET, positron emission tomography; PFS, progression free survival; PROG, progression vs non-progression; PTCL, Peripheral T-cell lymphoma; PTLD, Post-transplant lymphoproliferative disorder; QS, quality scores; SOFT, robustness across software; SUV thresholding; SUV, standardized uptake value; Segmentation software; TCL, T-cell lymphoma; UMCG, University Medical Center Groningen; VOI, volume of interest; cc, cubic centimeter.