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Brain partial volume correction with point spreading function reconstruction in high-resolution digital PET:
Masanobu Ibaraki1, Keisuke Matsubara2,3, Yuki Shinohara2
1Department of Radiology and Nuclear Medicine, Akita Research Institute of Brain and Blood Vessels, 6-10 Senshu-Kubota Machi, Akita, 010-0874, Japan. iba@akita-noken.jp.
Point spread function (PSF) reconstruction improves partial volume correction (PVC) in brain PET imaging on digital scanners. While not fully recovering resolution, PSF PVC accurately measures tracer uptake in small brain structures compared to MRI-based methods.
Area of Science:
- Nuclear Medicine
- Radiology
- Neuroimaging
Background:
- Quantitative brain PET imaging is prone to errors from partial volume effects due to limited scanner resolution.
- Accurate measurement of tracer uptake, especially in small brain structures like the cerebral cortex, is crucial for diagnosis and research.
Purpose of the Study:
- To evaluate the effectiveness of point spread function (PSF) reconstruction for partial volume correction (PVC) in brain PET.
- To compare PSF reconstruction performance against MRI-based PVC using a digital PET scanner.
Main Methods:
- Ten healthy subjects underwent 18F-FDG PET scans on a digital PET/CT system and T1-weighted MRI.
- PSF reconstruction was applied with varying iterations (4-256).
- Cerebral cortical uptake was assessed using standardized uptake value ratio (SUVR) and compared between PSF reconstruction and MRI-based PVC.
Main Results:
- PSF reconstruction visualized cortical structures well, matching MR-derived segments.
- Higher iterations in PSF reconstruction increased cortical SUVRs, approaching MRI-based PVC values.
- Maximum iterations yielded SUVRs 16% lower than MRI-PVC, with an effective resolution of ~1.5-mm FWHM.
Conclusions:
- PSF reconstruction is a viable PVC technique for brain PET on modern digital scanners, despite suboptimal resolution recovery.
- PSF reconstruction offers an advantage in assessing small brain structures, including nuclei, which are challenging for MRI-based PVC.
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