Background: The aim of this study was to evaluate the impact of tumour region of interest (ROI) delineation method on mid-treatment F-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) response prediction in mucosal head and neck squamous cell carcinoma during radiotherapy.

Methods: A total of 52 patients undergoing definitive radiotherapy with or without systemic therapy from two prospective imaging biomarker studies were analysed. FDG-PET was performed at baseline and during radiotherapy (week 3). Primary tumour was delineated using a fixed SUV 2.5 threshold (MTV2.5), relative threshold (MTV40%) and a gradient based segmentation method (PET Edge). PET parameters SUV, SUV, metabolic tumour volume (MTV) and total lesion glycolysis (TLG) were calculated using different ROI methods. Absolute and relative change (∆) in PET parameters were correlated to 2-year locoregional recurrence. Strength of correlation was tested using receiver operator characteristic analysis using area under the curve (AUC). Response was categorized using optimal cut-off (OC) values. Correlation and agreement between different ROI methods was determined using Bland-Altman analysis.

Results: A significant difference in SUV, MTV and TLG values were noted between ROI delineation methods. When measuring relative change at week 3, a greater agreement was seen between PET Edge and MTV2.5 methods with average difference in ∆SUV, ∆SUV, ∆MTV and ∆TLG of 0.0%, 3.6%, 10.3% and 13.6% respectively. A total of 12 patients (22.2%) experienced locoregional recurrence. ∆MTV using PET Edge was the best predictor of locoregional recurrence (AUC =0.761, 95% CI: 0.573-0.948, P=0.001; OC ∆>50%). The corresponding 2-year locoregional recurrence rate was 7% . 35%, P=0.001.

Conclusions: Our findings suggest that it is preferable to use gradient based method to assess volumetric tumour response during radiotherapy and offers advantage in predicting treatment outcomes compared with threshold-based methods. This finding requires further validation and can assist in future response-adaptive clinical trials.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10167452PMC
http://dx.doi.org/10.21037/qims-22-798DOI Listing

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