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

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 18F-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 SUVmax (41max) and a contrast-corrected 50% of SUVpeak (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 18F-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 18F-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 18F-FDG-avidity lesions should be addressed in a larger cohort of cHL patients.

The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) and how to select an outcome measurement instrument

Background: COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) is an initiative of an international multidisciplinary team of researchers who aim to improve the selection of outcome measurement instruments both in research and in clinical practice by developing tools for selecting the most appropriate available instrument. Method: In this paper these tools are described, i.e. the COSMIN taxonomy and definition of measurement properties; the COSMIN checklist to evaluate the methodological quality of studies on measurement properties; a search filter for finding studies on measurement properties; a protocol for systematic reviews of outcome measurement instruments; a database of systematic reviews of outcome measurement instruments; and a guideline for selecting outcome measurement instruments for Core Outcome Sets in clinical trials. Currently, we are updating the COSMIN checklist, particularly the standards for content validity studies. Also new standards for studies using Item Response Theory methods will be developed. Additionally, in the future we want to develop standards for studies on the quality of non-patient reported outcome measures, such as clinician-reported outcomes and performance-based outcomes. Conclusions: In summary, we plea for more standardization in the use of outcome measurement instruments, for conducting high quality systematic reviews on measurement instruments in which the best available outcome measurement instrument is recommended, and for stopping the use of poor outcome measurement instruments.

The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) and how to select an outcome measurement instrument.

BACKGROUND: COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) is an initiative of an international multidisciplinary team of researchers who aim to improve the selection of outcome measurement instruments both in research and in clinical practice by developing tools for selecting the most appropriate available instrument. METHOD: In this paper these tools are described, i.e. the COSMIN taxonomy and definition of measurement properties; the COSMIN checklist to evaluate the methodological quality of studies on measurement properties; a search filter for finding studies on measurement properties; a protocol for systematic reviews of outcome measurement instruments; a database of systematic reviews of outcome measurement instruments; and a guideline for selecting outcome measurement instruments for Core Outcome Sets in clinical trials. Currently, we are updating the COSMIN checklist, particularly the standards for content validity studies. Also new standards for studies using Item Response Theory methods will be developed. Additionally, in the future we want to develop standards for studies on the quality of non-patient reported outcome measures, such as clinician-reported outcomes and performance-based outcomes. CONCLUSIONS: In summary, we plea for more standardization in the use of outcome measurement instruments, for conducting high quality systematic reviews on measurement instruments in which the best available outcome measurement instrument is recommended, and for stopping the use of poor outcome measurement instruments.