The Impact of Semiautomatic Segmentation Methods on Metabolic Tumor Volume, Intensity, and Dissemination Radiomics in <sup>18</sup>F-FDG PET Scans of Patients with Classical Hodgkin Lymphoma
Julia Driessen, Gerben J.C. Zwezerijnen, Heiko Schöder, Esther E.E. Drees, Marie José Kersten, Alison J. Moskowitz, Craig H. Moskowitz, Jakoba J. Eertink, Henrica C. W. de Vet, Otto S. Hoekstra, Josée M. Zijlstra, Ronald Boellaard
Abstract
<b>Introduction:</b> 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. <b>Methods:</b> We analyzed a total of 105 <sup>18</sup>F-FDG PET-CT scans from patients with newly diagnosed (<i>n</i> = 35) and relapsed/refractory (<i>n</i> = 70) cHL with six segmentation methods: two fixed thresholds on SUV4.0 and SUV2.5, two relative methods of 41% of SUV<sub>max</sub> (41max), and a contrast-corrected 50% of SUVpeak (A50P) and two combination ‘majority vote’ methods (MV2, MV3). Segmentation quality was assessed by two reviewers based on pre-defined 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. <b>Results:</b> SUV4.0 required the least manual adaptation but tended to underestimate MTV and often missed small lesions with low 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. <b>Conclusion:</b> There is a high correlation 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 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-avid lesions should be addressed in a larger cohort of cHL patients.