Feasibility of different meningioma delineation approaches on [18F]SiTATE PET/CT imaging

  • Background Somatostatin receptor (SSTR)-targeted PET is valuable for meningioma imaging due to high SSTR expression. [18F]SiTATE, a novel tracer, is not only promising for imaging neuroendocrine tumors but also for meningiomas. Standardized delineation methods on [18F]SiTATE PET are lacking. This study correlates CT-based volumes with PET-based delineation approaches to identify a threshold for standardized [18F]SiTATE PET volume assessment. Methods Patients with well-delineated, extraosseous meningioma on CT (≥ 1mL) who underwent [18F]SiTATE PET/CT were included. Volumes were assessed on contrast-enhanced CT and correlated with PET-based delineation approaches: (I) fixed SUV threshold, (II) isocontour thresholding relative to SUVmax (SUV%), and thresholds relative to (III) bone marrow (SUVBM), (IV) parotid gland (SUVparotis) and (V) pituitary gland (SUVsella). Results 19 meningiomas in 17 PET/CT scans (16 patients) were included. A fixed SUV of 4.0 (r = 0.783, p < 0.001) showedBackground Somatostatin receptor (SSTR)-targeted PET is valuable for meningioma imaging due to high SSTR expression. [18F]SiTATE, a novel tracer, is not only promising for imaging neuroendocrine tumors but also for meningiomas. Standardized delineation methods on [18F]SiTATE PET are lacking. This study correlates CT-based volumes with PET-based delineation approaches to identify a threshold for standardized [18F]SiTATE PET volume assessment. Methods Patients with well-delineated, extraosseous meningioma on CT (≥ 1mL) who underwent [18F]SiTATE PET/CT were included. Volumes were assessed on contrast-enhanced CT and correlated with PET-based delineation approaches: (I) fixed SUV threshold, (II) isocontour thresholding relative to SUVmax (SUV%), and thresholds relative to (III) bone marrow (SUVBM), (IV) parotid gland (SUVparotis) and (V) pituitary gland (SUVsella). Results 19 meningiomas in 17 PET/CT scans (16 patients) were included. A fixed SUV of 4.0 (r = 0.783, p < 0.001) showed good correlation with CT volumes without skewed distribution on Bland-Altman-Plot analysis. Using isocontour-based thresholds, 45% SUVmax (r = 0.496, p = 0.031) showed the highest concordance. Best reference-based approaches were achieved by 150% SUVBM (r = 0.859, p < 0.001), 250% SUVparotis (r = 0.460, p = 0.047) and 70% SUVsella (r = 0.819, p < 0.001). However, background-based approaches showed a trend towards overestimation of PET-volumes in larger meningiomas as assessed on Bland-Altman-Plot analyses. Uptake intensities of reference tissues (SUVBM, SUVparotis and SUVsella) were not inter-correlated (p > 0.05 each). Conclusion A fixed SUV threshold of 4.0 showed strong agreement with CT-based volumes in well-delineated, extraosseous meningiomas which offers a simple, clinically applicable method without technical requirements. Reference tissue-based methods showed similar correlations but tended to overestimate volumes in larger lesions.…show moreshow less

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Metadaten
Author:Sophie C. Kunte, Lena M. UnterrainerGND, Simon Lindner, Adrien Holzgreve, Wolfgang G. Kunz, Michael Winkelmann, Alexander Nitschmann, Klaus Jurkschat, Carmen Wängler, Björn Wängler, Ralf Schirrmacher, Claus Belka, Niklas Thon, Christian Schichor, Peter Bartenstein, Marcus Unterrainer
URN:urn:nbn:de:bvb:384-opus4-1336372
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/133637
ISSN:2730-6011OPAC
Parent Title (English):Discover Oncology
Publisher:Springer Science and Business Media LLC
Place of publication:Berlin
Type:Article
Language:English
Year of first Publication:2025
Publishing Institution:Universität Augsburg
Release Date:2026/10/09
Volume:16
Issue:1
First Page:2189
DOI:https://doi.org/10.1007/s12672-025-04079-6
Institutes:Medizinische Fakultät
Medizinische Fakultät / Universitätsklinikum
Medizinische Fakultät / Professur für Nuklearmedizin mit einem Schwerpunkt für Translationale Theranostik
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung