Fig. 1
From: Extracting value from total-body PET/CT image data - the emerging role of artificial intelligence
Multifaceted 18F-FDG PET Imaging Analysis of Follicular Lymphoma with AI-Assisted Tumor Detection. Presented here is a comprehensive visualization of follicular lymphoma characterized by diverse 18F-FDG uptake patterns across nodal and extranodal sites. The illustration captures the Molecular Imaging Tumor Volume (MTV) on 18F-FDG PET, delineated using the LION (Lesion Segmentation) algorithm, a native AI tool that identifies lymphoma lesions without the pre-setting of SUV thresholds. This intelligent segmentation excludes physiological uptakes in the kidneys, bladder, and brain for enhanced specificity in oncological imaging. Complementing this, the Multi-Organ Objective Segmentation (MOOSE) automatically defines organ contours, with a focus on the spleen in this instance. MOOSE enables the precise determination of the fraction of the spleen infiltrated by lymphoma, which is computed to be 56% of the total organ volume. The deployment of these AI algorithms for tumour and tissue segmentation provides a robust and reproducible quantitative assessment, offering novel prognostic insights into the extent and aggressiveness of follicular lymphoma