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Arterial spin labeling in the hybrid PET/MRI workup of dementia patients

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Mildner,  Toralf
Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Möller,  Harald E.
Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Barthel, H., Werner, P., Rullmann, M., Mildner, T., Jochimsen, T., Tiepolt, S., et al. (2017). Arterial spin labeling in the hybrid PET/MRI workup of dementia patients. Journal of Cerebral Blood Flow and Metabolism, 37(Suppl. 1): PS01-095, 157-158. doi:10.1177/0271678X17695982.


Cite as: https://hdl.handle.net/21.11116/0000-0004-F89B-6
Abstract
Biomarkers are increasingly employed to supplement clinical diagnosis of Alzheimer's disease (AD). For that purpose, amyloid pathology and neuronal injury biomarkers are used. However, so far it was not possible to derive biomarkers of both categories within one imaging session. This project investigated the respective potential of arterial spin labeling (ASL) within simultaneous PET/MRI protocols.

Two scenarios were explored: (1) 37 patients (67 ± 9 yrs, 16 female) with cognitive and/or movement symptoms, simultaneous [18F]FDG brain PET/ASL MRI (Siemens 3T mMR). ASL: PICORE Q2TIPS, 18 slices a 4 mm in 64 × 64 matrix, TE/TI/TR = 16/ 2400 / 3400 ms, 55–60 min p.i.. (2) 65 subjects (68 ± 10 yrs, 31 female) with cognitive deficits, simultaneous [18F]Florbetaben amyloid PET/ASL MRI. Image data analysis: Visual (image quality, binary judgment: normal/abnormal, pattern recognition), VOI-based (AAL template, PMOD), and voxel-based (SPM).

70 % (1) and 68 % (2) of the ASL images were visually judged as of appropriate quality for further analysis. Of the remaining image pairs, in (1), binary visual ASL analysis had an extrapolated specificity and specificity of 72 % and 88 %, respectively, as compared to [18F]FDG. Signal distribution pattern was matched between ASL and [18F]FDG in 65 % of the cases. VOI-based analysis showed a positive correlation between rCBF and rCMRGlu in 29/70 cortical and subcortical VOIs. Of the remaining cases in (2) with pathological amyloid PET images, 79 % had AD patterns in ASL MRI, while 53/17/30 % of the remaining cases with normal amyloid PET images had normal/FTLD/AD patterns in ASL MRI. SPM analysis confirmed these ASL MRI differences.

In conclusion, more work is needed to improve data quality of ASL MRI, especially to derive individual diagnostic quality. Then, ASL MRI might have the potential of providing [18F]FDG-like biomarker information, an opportunity which is of special interest for combined amyloid PET/MRI in which differential dementia diagnosis solely based on the amyloid information is limited.