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A combined dual-tracer PET/diffusion tractometry analysis of the posterior cingulum in a mild cognitive impairment ketogenic intervention
Maggie Roy1, Stephen Cunnane1, Étienne Croteau1, Alexandre Castellano1, Mélanie Fortier1, Félix C Morency2, Jean-Christophe Houde1, and Maxime Descoteaux1

1Université de Sherbrooke, Sherbrooke, QC, Canada, 2Imeka Solutions Inc., Sherbrooke, QC, Canada

Synopsis

In mild cognitive impairment (MCI), posterior cingulate cortex glucose hypometabolism may results from posterior cingulum (PCg) alterations. We suggest that raising ketone availability to the brain may overcome the brain energy deficit. We developed a dual-tracer PET/dMRI tractometry method to assess whether a ketogenic supplement has impact on fuel uptake in the PCg of MCI participants. Mean fuel uptake in the PCg was unchanged post-supplementation, but tract-profiling enabled the identification of sections with lower glucose uptake. Energy supply in white matter fascicles is crucial to sustain adequate axonal function and may be linked to the pathogenesis of MCI.

Introduction

Lower fractional anisotropy in the white matter (WM) cingulum fasciculus is consistently reported in diffusion (dMRI) studies of mild cognitive impairment (MCI)1,2. Furthermore, the posterior cingulate cortex (PCC) is the first region to present glucose hypometabolism in MCI3,4. It was proposed that PCC glucose hypometabolism results from hippocampal atrophy through posterior cingulum (PCg) dysfunction and atrophy2,5-7. On the other hand, we previously showed that brain ketone uptake, the main alternative brain fuel to glucose, is normal in MCI5. Thus, we suggest that a supplement raising ketone availability to the brain may overcome the brain energy deficit by supplying an alternative fuel to brain cells8,9. The assessment of WM fuel uptake may enable the evaluation of WM metabolic integrity. We therefore developed a new combined dual-tracer PET/dMRI tractometry method to assess whether a ketogenic supplement impacts fuel uptake and dMRI properties of the PCg in MCI participants.

Methods

MCI participants were randomized to the placebo (N=11) or medium chain triglyceride (MCT; N=12) groups. Participants underwent multi-modal brain imaging before and after a 6-month daily supplement of 30 g/day MCT. The protocol consisted of a 3T MRI session on a Philips Ingenia system: a 1 mm T1 image, followed by a 1.8 mm isotropic high angular resolution diffusion imaging (HARDI; 60 directions, b=1500 s/mm2), and a blip-up/blip-down b=0 s/mm2 acquisition to correct for distortions. Diffusion tensor measures10, free-water index11, total apparent fiber density12 and number of fiber orientations13 were computed. Anatomically-constrained probabilistic particle filter tractography that is robust to crossing fibers and partial volume effect was used to reconstruct the PCg14. Streamlines connecting the parahippocampal cortex (PHC) to the isthmus cingulate cortex (ICC) and the ICC to the PCC15 were automatically extracted using the Desikan/Killiany FreeSurfer atlas and WM query language (Fig. 1)16. The MRI protocol was followed by a dual PET tracer session: AcAc (11C-acetoacetate) first, followed by FDG (18F-Fluorodeoxyglucose)4. SUV (standardized uptake values) summed-images from dynamic acquisitions were used. PET images were co-registered to dMRI data. Average PET tracer uptake and tract-profiling along 10 sections of the PCg (Fig. 3A)17 were measured. Data are expressed as delta (post- minus pre-supplementation).

Results

Pre-supplementation, the placebo and MCT groups did not differ in age (75 ± 6 years) or Mini-Mental State Examination score (28/30 ± 2). Mean Δdiffusion tensor measures, mean Δfree-water index, fascicle Δvolume and streamline Δmean length in the PCg were not statistically different between the groups. Mean ΔAcAc and ΔFDG uptake in the PCg did not differ statistically between groups. Using tract-profiling, ΔAcAc uptake was slightly higher in several sections along the streamlines in the MCT group, but with the current number of participants, no statistical difference was found (Fig. 3B). ΔFDG uptake (Fig. 3C) was globally lower for the MCT group in the 10 sections of the PCg with a statistical difference in section 6 (p= 0.04; medial part of the ICC) and a trend in sections 7 and 10 (p= 0.06 and 0.08 respectively).

Discussion

The cingulum fasciculus consists of multiple sub-connections18. We therefore extracted the ones which are crucial for episodic memory and have implications in MCI (PHC-ICC)19 and applied a multi-modal PET/dMRI tractometry pipeline to quantify their integrity. As expected, no structural changes, revealed by dMRI measures, were noted in the placebo group after the 6-month period, which confirmed the test-retest reliability of our method. Tract-profiling showed differences in FDG uptake between the two groups, which were not found when only the average FDG uptake in the PCg was compared. FDG uptake near the streamline’s terminations (close to grey matter), seemed more affected by the MCT supplementation compared to the inner sections of the streamlines. Lower FDG uptake in these cortical areas was also reported after a ketogenic intervention in healthy adults9. To our knowledge, this is the first report of FDG uptake in any WM fascicles in humans. The assessment of WM FDG uptake using PET enables the evaluation of WM energy metabolism in vivo20. WM energy supply (axonal and oligodendrocytes), which serves mainly for resting potentials, myelin synthesis and intracellular trafficking of molecules21, is crucial to sustain adequate axonal function22 and may be linked to the pathogenesis of MCI.

Conclusion

A 6-month ketogenic MCT supplementation changes FDG uptake in the PCg in MCI and tract-profiling is useful to identify these changes. These results will be extended to more participants and combined with grey matter analysis to further evaluate the role of WM connections in cognitive impairment. Our dual-tracer PET/dMRI tractometry approach to evaluate energy use in WM fascicles could be helpful to better understand changes occurring in neurological disorders.

Acknowledgements

The authors wish to thank Sébastien Tremblay, Christine Brodeur-Dubreuil, Éric Lavallée, and the clinical MRI and PET group (CIMS) for their technical assistance. This work was supported by CIHR (MOP-102648), CFI (201796), FRQS and the Université de Sherbrooke (University Research Chair to SCC).

References

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Figures

Fig. 1. Sagittal view of the left posterior cingulum (PCg) from one MCI participant at pre-supplementation. Anatomically-constrained probabilistic particle filter tractography that is robust to crossing fibers and partial volume effect was used to reconstruct the PCg. We can dissociate the green streamlines connecting the parahippocampal (PHC) and isthmus cingulate cortices (ICC) from the ones connecting the ICC to the posterior cingulate cortices (PCC) in pink. Streamlines were automatically extracted using the Desikan/Killiany FreeSurfer atlas and a white matter query language. The left PCg is overlaid on the t1-weighted image (registered on diffusion MRI data).

Fig. 2. Mean 11C-acetoacetate (AcAc; A) and 18F-fluorodeoxyglucose (FDG; B) uptake in the left posterior cingulum (PCg). Data are expressed as delta (post- minus pre-supplementation). Mean ΔAcAc and ΔFDG uptake in the PCg did not differ statistically between the placebo (black) and MCT (red) groups. Data are mean + SEM.

Fig. 3. The left posterior cingulum (PCg) from one MCI participant at pre-supplementation (A). The PCg was subsampled in 10 sections colored independently. Sections 1-5 are the parahippocampal-isthmus cingulate cortices connections; sections 6-10 are the isthmus cingulate-posterior cingulate cortices connections. (B) 11C-acetoacetate (AcAc) and (C) 18F-fluorodeoxyglucose (FDG) uptake along the 10 subsections of the left PCg. ΔFDG uptake was significantly lower for the MCT group in section 6 (p= 0.04; medial part of the isthmus cingulate cortex) with a trend in sections 7 and 10 (p= 0.06 and 0.08 respectively). Data are expressed as delta (post- minus pre-supplementation) and mean ± SEM.

Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)
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