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Published on: December 16, 2022
Whole-Body [18F]FDG-PET/CT Imaging of Healthy Controls: Test/Retest Data for Systemic, Multi-Organ Analysis
Sebastian Gutschmayer1, Josef Yu1,2, Barbara Katharina Geist2
1QIMP Team, Medical University of Vienna, Vienna, Austria.
This study develops a normative Positron Emission Tomography (PET) database using [18F]FDG in healthy individuals. This reference aids in detecting metabolic changes in cancer patients, potentially revealing systemic treatment effects beyond tumor imaging.
Area of Science:
- Nuclear medicine
- Radiomics
- Oncology imaging
Background:
- Positron Emission Tomography (PET) with 2-deoxy-2-[18F]fluoro-D-glucose (FDG) and Computed Tomography (CT) are crucial in cancer diagnostics, primarily for tumor detection.
- Current PET applications often overlook the systemic effects and the broader metabolic macroenvironment.
- A comprehensive understanding of metabolic changes beyond tumor sites is needed to improve patient care and treatment strategies.
Purpose of the Study:
- To establish a normative FDG-PET database using healthy controls.
- To provide a reference for identifying voxel-level metabolic aberrations in cancer patients.
- To explore the potential of FDG-PET for assessing systemic treatment interactions and changes beyond primary tumor detection.
Main Methods:
- Acquisition of dynamic test-retest whole-body PET/CT imaging with [18F]FDG in 48 healthy controls.
- Reconstruction of static PET images (57-62 min post-injection) using CT-based corrections and iterative reconstruction with resolution recovery and time-of-flight.
- Calculation of Standardized Uptake Values (SUVs), Hounsfield Units (HU), and volumes for 135 organs using in-house segmentation software.
Main Results:
- A dataset of anonymized PET/CT images and CT-derived segmentations in NIfTI format was created from healthy controls.
- The methodology supports the development of a normative FDG-PET database.
- The data enables multi-organ analyses of metabolic activity using PET/CT imaging.
Conclusions:
- A normative FDG-PET database derived from healthy individuals is feasible and valuable.
- This database can serve as a reference for detecting subtle metabolic alterations in cancer patients.
- The approach holds promise for uncovering systemic treatment-related changes and enhancing patient management in oncology.
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