Follow-up analyses on the effects of long-term use of high fat diet on hippocampal volumes and hippocampal metabolite concentrations in Wistar rats: a voxel based morphology and 1H MRS approach
Piotr Majka1, Bartosz Kossowski2, Jarosław Orzeł2, Piotr Bogorodzki2, Zuzanna Setkowicz3, and Stefan P. Gazdzinski4

1Nencki Institute for Experimenal Biology, Warsaw, Poland, 2Warsaw University of Technology, Warsaw, Poland, 3Neuroanatomy, Jagiellonian University, Krakow, Poland, 4CNS Lab, Military Institute for Aviation Medicine, Warsaw, Poland


Our study of long-term use of high fat diet inducing mild ketonemia in Wistar rats showed improvements in learning and memory, as well as larger hippocampi and higher concentrations of tNAA (marker of neuronal viability), tCho (involved in metabolite turnover), and tCr (involved in cell energetics). Here, we applied voxel based morphometry (VBM) for structural images and used TARQUIN for 1H MRS data obtained at 7T. Results of VBM and TARQUIN provided results consistent with previous analyses. However, the use of a literature-based template lead to tissue contractions not detectable with study specific template.


Our study of long-term use of high fat diet that lead to mild ketonemia in Wistar rats showed improvements in learning and memory, as well as larger hippocampi and higher concentrations of tNAA (marker of neuronal viability), tCho (involved in metabolite turnover), and tCr (involved in cell energetics). Here, we apply independent post-processing methodology to ascertain that our findings were genuine.


We have recently observed that one-year use of high fat diet (HFD) that induced mild ketonemia lead to better learning and memory, larger hippocampi volumes without any changes to cortical volumes, as well as higher concentrations of total NAA (tNAA: N-acetylaspartate and N-acetylaspartateglutame; marker of neuronal viability), total Cho (tCho: Glycerophosphocholine +Phosphocholine, which are believed to be primarily involved in cell membrane breakdown and synthesis) and total Cr (tCr: creatine + phospo-creatine – involved in cell bioenergetics)1. We performed ROI analyses and used LC Model for spectral processing. Here, we applied voxel-wise analysis to determine focal changes in brain tissue structure. Furthermore, we compared the effects of template selection (Valdés-Hernández et. al. template2 vs. study specific template) on the results. Moreover, for spectral processing we used TARQUIN3, an open source alternative that was demonstrated to work comparably well to LCModel with wide range of 1.5T and 3.0T proton spectra. However, it has not been used to fit proton, animal spectra acquired at 7.0T.


Twenty five male Wistar rats were put on HFD (~60% energy from fat, ~28% from carbohydrates) on their 55th day of life, while 22 control male rats (CON) remained on chow. Structural T2-weighted TurboRARE (TR/TE=4700/30ms, RARE factor=4, resolution=125x125x500μm, no gap, NEX=7, TA=27 min) acquired on Bruker BioSpin working at 7T, with a transmit cylindrical radiofrequency coil (15 cm inner diameter) and a receive-only coil array (2x2 elements) positioned over the animal’s head. Localized proton spectroscopy at short echo was performed using PRESS sequence (TR/TE = 3500/20 ms, 256 averages, 8,192 points, TA=15min) with VAPOR water suppression, the outer volume suppression, and frequency drift correction (flip angle 7 deg.) was performed to obtain metabolite concentrations. Each measurement was carried out in a single volume of interest (8 x 2 x 2 mm3) encompassing hippocampus.

For volume based morphology, 18 images acquired for CON, 18 datasets for HFD were selected. Images were resampled to isotropic resolution of 125μm/vox and processed with N4 algorithm to correct for intensity inhomogenity. Image of each specimen was registered into the Valdés-Hernández et. al. template2 or study-specific template using SyN algorithm4 resulting in a series of deformation field. Jacobian determinant of each deformation field was then computed and modulated with a gray matter probability, blurred with Gaussian filter of 250μm. Significance of differences between CON and HFD was determined with two-sample unpaired t-test. Threshold-Free Cluster Enhancement permutation method5 was used to threshold t-maps (FSL-randomise software). 10,000 permutations were used in tests and p=0.05 was chosen as a significance threshold.

Spectroscopic data was reanalyzed in TARQUIN3 which differs from LC Model in fitting domain and algorithm. We had adapted TARQUIN's 7T basis set to be consistent with the LCModel's one.


Hippocampal volume are larger in HFD-fed rats than in controls, especially in hippocampal CA1 field, but also in surrounding cortical areas, regardless of used template. Results obtained using Valdés-Hernández et. al. template2 show areas of tissue expansion and areas of tissue contraction (Figure 1). Study specific template-based results do not show regions of smaller volumes in HFD fed group compared to control (Figure 2). Moreover, the concentration of tNAA, Glx and tCr were higher in the HFD-fed group than in controls (6.8%, p=0.01, 6.5%, p=0.03, and 4.5%, p=0.03, respectively), consistent with the results obtained by LC Model. Method specific differences between processing with TARQUIN and LC Model were analyzed with Bland Altman and the coefficients of variation for Glx, tNAA, and tCr are < 7%. Concentrations of selected metabolites are compared between groups in Figure 3.


The results confirm our ROI findings of larger hippocampal volumes in HFD fed rats, but also point to focal volume increases in temporal association cortex and ectorhinal cortex. Moreover, use of study specific template yielded similar regions of tissue expansion due to HFD, but regions of tissue contraction were absent. Spectral analysis with TARQUIN yielded similar results as those obtained with LC Model, showing that they are genuine, not a product of a certain post-processing methodology. In summary, our results support the use of study specific templates in animal studies. Furthermore, they do not support the thesis that HFD per se leads to degeneration of the nervous system.


Polish National Science Centre, grants no: 2011/03/B/NZ4/03771 and 2013/09/B/NZ7/03763.


1. Setkowicz, Z., Gazdzinska, A., Osoba, J. J., Karwowska, K., Majka, P., Orzel, J., … Gazdzinski, S. P. (2015). Does Long-Term High Fat Diet Always Lead to Smaller Hippocampi Volumes, Metabolite Concentrations, and Worse Learning and Memory? A Magnetic Resonance and Behavioral Study in Wistar Rats. Plos One, 10(10), e0139987.

2. Valdes-Hernandez PA, Sumiyoshi A, Nonaka H, et al. An in vivo MRI Template Set for Morphometry, Tissue Segmentation, and fMRI Localization in Rats. Frontiers in neuroinformatics 2011;5:26-26.

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4. Avants BB, Epstein CL, Grossman M, Gee JC. Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain. Medical Image Analysis 2008;12:26-41.

5. Smith, S. M., & Nichols, T. E. (2009). Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. NeuroImage, 44(1), 83–98. doi:10.1016/j.neuroimage.2008.03.061


Figure 1. Regions of larger volume in HFD fed rats than in CONs ; Valdés-Hernández template was used. Please note focal contractions.

Figure 2. Regions of larger volume in HFD fed rats than in CONs; study specific template was used. No volume contractions visible.

Figure 3. Effects of HFD on selected metabolite concentrations. tCr = Cr+PCr; tNAA = NAA+NAAG; Glx = Glu+Gln; tCho = GPC+PCh; Glc = brain glucose concentrations.

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)