The Impact of Semiautomatic Segmentation Methods on Metabolic Tumor Volume, Intensity, and Dissemination Radiomics in 18 F-FDG PET Scans of Patients with Classical Hodgkin Lymphoma.

Autor: Driessen J; Department of Hematology, Amsterdam UMC, University of Amsterdam, LYMMCARE (Lymphoma and Myeloma Center, Amsterdam), Cancer Center Amsterdam, Amsterdam, The Netherlands., Zwezerijnen GJC; Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands., Schöder H; Department of Molecular Imaging and Therapy Service, Memorial Sloan Kettering Cancer Center, New York, New York., Drees EEE; Department of Pathology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands., Kersten MJ; Department of Hematology, Amsterdam UMC, University of Amsterdam, LYMMCARE (Lymphoma and Myeloma Center, Amsterdam), Cancer Center Amsterdam, Amsterdam, The Netherlands., Moskowitz AJ; Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York., Moskowitz CH; Department of Medicine, Sylvester Comprehensive Cancer Center, Miami, Florida., Eertink JJ; Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands; and., Vet HCW; Department of Epidemiology and Data Science, Amsterdam Public Health research institute, Amsterdam, Netherlands., Hoekstra OS; Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands., Zijlstra JM; Department of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands; and., Boellaard R; Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands; r.boellaard@amsterdamumc.nl.
Jazyk: angličtina
Zdroj: Journal of nuclear medicine : official publication, Society of Nuclear Medicine [J Nucl Med] 2022 Sep; Vol. 63 (9), pp. 1424-1430. Date of Electronic Publication: 2022 Jan 06.
DOI: 10.2967/jnumed.121.263067
Abstrakt: Consensus about a standard segmentation method to derive metabolic tumor volume (MTV) in classical Hodgkin lymphoma (cHL) is lacking, and it is unknown how different segmentation methods influence quantitative PET features. Therefore, we aimed to evaluate the delineation and completeness of lesion selection and the need for manual adaptation with different segmentation methods, and to assess the influence of segmentation methods on the prognostic value of MTV, intensity, and dissemination radiomics features in cHL patients. Methods: We analyzed a total of 105 18 F-FDG PET/CT scans from patients with newly diagnosed ( n = 35) and relapsed/refractory ( n = 70) cHL with 6 segmentation methods: 2 fixed thresholds on SUV4.0 and SUV2.5, 2 relative methods of 41% of SUV max (41max) and a contrast-corrected 50% of SUV peak (A50P), and 2 combination majority vote (MV) methods (MV2, MV3). Segmentation quality was assessed by 2 reviewers on the basis of predefined quality criteria: completeness of selection, the need for manual adaptation, and delineation of lesion borders. Correlations and prognostic performance of resulting radiomics features were compared among the methods. Results: SUV4.0 required the least manual adaptation but tended to underestimate MTV and often missed small lesions with low 18 F-FDG uptake. SUV2.5 most frequently included all lesions but required minor manual adaptations and generally overestimated MTV. In contrast, few lesions were missed when using 41max, A50P, MV2, and MV3, but these segmentation methods required extensive manual adaptation and overestimated MTV in most cases. MTV and dissemination features significantly differed among the methods. However, correlations among methods were high for MTV and most intensity and dissemination features. There were no significant differences in prognostic performance for all features among the methods. Conclusion: A high correlation existed between MTV, intensity, and most dissemination features derived with the different segmentation methods, and the prognostic performance is similar. Despite frequently missing small lesions with low 18 F-FDG avidity, segmentation with a fixed threshold of SUV4.0 required the least manual adaptation, which is critical for future research and implementation in clinical practice. However, the importance of small, low 18 F-FDG-avidity lesions should be addressed in a larger cohort of cHL patients.
(© 2022 by the Society of Nuclear Medicine and Molecular Imaging.)
Databáze: MEDLINE
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