Attenuation Correction Using Template PET Registration for Brain PET: A Proof-of-Concept Study.
Markus JehlEkaterina MikhaylovaValerie TreyerMarlena HofbauerMartin W HuellnerPhilipp A KaufmannAlfred BuckGeoff WarnockViet DaoCharalampos TsoumpasDaniel DeiddaKris ThielemansMax Ludwig AhnenJannis FischerPublished in: Journal of imaging (2022)
NeuroLF is a dedicated brain PET system with an octagonal prism shape housed in a scanner head that can be positioned around a patient's head. Because it does not have MR or CT capabilities, attenuation correction based on an estimation of the attenuation map is a crucial feature. In this article, we demonstrate this method on [ 18 F]FDG PET brain scans performed with a low-resolution proof of concept prototype of NeuroLF called BPET. We perform an affine registration of a template PET scan to the uncorrected emission image, and then apply the resulting transform to the corresponding template attenuation map. Using a whole-body PET/CT system as reference, we quantitively show that this method yields comparable image quality (0.893 average correlation to reference scan) to using the reference µ-map as obtained from the CT scan of the imaged patient (0.908 average correlation). We conclude from this initial study that attenuation correction using template registration instead of a patient CT delivers similar results and is an option for patients undergoing brain PET.
Keyphrases
- computed tomography
- positron emission tomography
- pet ct
- image quality
- dual energy
- contrast enhanced
- resting state
- pet imaging
- white matter
- magnetic resonance imaging
- patients undergoing
- case report
- functional connectivity
- molecularly imprinted
- cerebral ischemia
- machine learning
- magnetic resonance
- subarachnoid hemorrhage
- liquid chromatography
- brain injury
- optic nerve
- neural network