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Updated: May 29, 2026
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Continuous Blood Sampling in Small Animal Positron Emission Tomography/Computed Tomography Enables the Measurement of the Arterial Input Function
Published on: August 8, 2019
A method of generating image-derived input function in a quantitative ¹⁸F-FDG PET study based on the shape of the
Shan Zhou1, Kewei Chen, Eric M Reiman
1Physical Science and Technology College, Zhengzhou University, Zhengzhou, China.
Nuclear Medicine Communications
|September 28, 2011
Summary
A new method for creating an image-derived input function (IDIF) from positron emission tomography (PET) scans accurately quantifies glucose metabolism in the brain. This technique offers a convenient and precise alternative to traditional methods.
Area of Science:
- Nuclear medicine
- Medical imaging
- Neuroscience
Background:
- Accurate quantification of regional cerebral metabolic rate of glucose (rCMRglc) is crucial in positron emission tomography (PET) studies.
- Traditional methods rely on plasma-derived input functions, which can be invasive and time-consuming.
- Developing an image-derived input function (IDIF) can simplify and improve the efficiency of PET quantification.
Purpose of the Study:
- To introduce and evaluate a novel method for defining an image-derived input function (IDIF).
- To assess the accuracy of the proposed IDIF method for quantifying regional cerebral metabolic rate of glucose (rCMRglc) in dynamic PET studies.
- To compare the performance of the IDIF method against the conventional plasma-derived input function.
Main Methods:
- A cubic region of interest encompassing the carotid artery was defined in dynamic PET images.
- Time-activity curves (TACs) from selected voxels showing decreasing activity were averaged to obtain a raw IDIF.
- The raw IDIF was corrected for partial volume and spillover effects using blood sample data.
- The Patlak approach was employed to calculate net ¹⁸F-fluoro-2-deoxyglucose (FDG) clearance using both plasma-derived and the generated IDIF.
Main Results:
- Net FDG clearances calculated using the generated IDIF were consistent with those obtained using the plasma-derived input function.
- The relative error between the net FDG clearances calculated by the two methods was approximately 5%.
- The proposed IDIF method demonstrated high accuracy in quantifying cerebral glucose metabolism.
Conclusions:
- A novel and accurate method for generating an input function directly from dynamic PET images was successfully developed.
- The proposed IDIF method provides a convenient and reliable alternative for PET-based quantification of rCMRglc.
- This technique enhances the practicality and efficiency of quantitative PET imaging in clinical and research settings.
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