Synopsis

We demonstrate high-resolution quantitative multiparametric mapping in the rat: scanning animals before and after adolescence and comparing them to the adult. We produce maps sensitive to myelin signal throughout the brain that complement volumetric information normally used in developmental studies. The aim is to better exploit models of neuropsychiatric disorders, particularly those with developmental components.

Introduction

Animals and image acquisition

Cohorts of rats were scanned at post-natal day (PND) 21 (n=21), 35 (n=9), 63 (n=9), with a separate cohort of mature adulthood rats for comparison (PND>200, n=7). Rats were anaesthetised with isoflurane (1-2% in 1l/min O2, adjusted to keep respiratory rates in the normal range).

Scans were performed on a Bruker BioSpec 94/20 system at 9.4T using the manufacturer supplied birdcage transmission coil and rat brain receiver coil (4ch array). Multiparametric mapping (MPM) sequences following¹ were based on a multi-gradient echo sequence with RF spoiling at 117°. Echoes were obtained from 2.41ms with a spacing of 2.1ms. For the three contrast weightings MT/PD/T1 parameters were: TR=25/25/18ms, FA=6/6/40° and number of echoes 6/8/6. The matrix was 192×160×128 with field of view 30.72×25.60×20.48mm yielding an isotropic spatial resolution of 160µm. For MT images, a single 4ms (BW 685Hz) Gaussian preparation pulse 2kHz off resonance of 10µT was applied. With acceleration of 1.6 achieved by zero-filling in the phase encoding directions, the total scan time for the MPM sequences was 17m 46s.

In addition to the MPM images, B0 and B1 maps were acquired to correct for static and transmission field homogeneities.

Image processing

Processing followed^{1, 2} to produce maps of T1 and MTsat for each animal. Images were registered using SPM12 with the SPMMouse toolbox³. Unified segmentation was used to prepare grey matter, white matter and cerebrospinal fluid (GM/WM/CSF) maps for non-linear registration with DARTEL.

Templates were thus generated separately at age PND21, 35, 63 and adulthood. The mean images were registered in turn to facilitate comparison between age points. Jacobian determinants were calculated to give maps of local volume change in the same space for each animal at each age. Delineation of brain regions was based on the Paxinos and Watson rat atlas⁴, with some cortical segmentations obtained from⁵. The rat GM and WM masks from SPMMouse were used to calculate summary statistics of parameters at each age.

Results and discussion

Figure 1 shows typical images at different age points with calculated MTsat and T1 maps, figure 2 shows minimum-deformation templates at each age based on magnetisation transfer weighted images. Figure 3 shows the ROIs at each time point illustrating volume change during this period. Figure 4 shows the MTsat map average for the registered PND63 animals. Quantitative parameters over time for selected regions are shown in Figures 5.

Note that the RF inhomogeneity evident in the raw images of Figure 1 does not affect the quantitative maps. Within both GM and WM, MTsat increases with age (from 0.0115±13% at PND21 to 0.014±14% at adulthood in GM; and 0.013±12% to 0.018±16% in WM). Within CSF, as expected, values are low and do not change over time (0.006±53%).

Consistent with increasing myelin levels, T1 values fell from 2002ms±11% to 1886ms±10% within GM and 1919±8% to 1633±13% within WM over the same age range. The greatest changes occur before PND63, where values become similar to those of mature adults. Detailed WM features are visible in these maps, particularly within heterogeneous structures such as the thalamus and the brainstem. Further work will assess myelin content histologically in the same rats to quantify the extent to which non-myelin contributors to the MTsat signal (e.g. cell membranes etc.) are important.

In sum, we have demonstrated that quantitative multiparametric mapping is a successful approach in the rat. Furthermore, the high-resolution maps presented here allow the assessment of myelin development within distinct cortical layers, which in humans continues to change well into adolescence⁶ and is emerging as a key area to find abnormalities that may lie behind symptoms associated with neuropsychiatric disorders.

Acknowledgements

References

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