Fast Dynamic Measurement of Functional T1 and Grey Matter Thickness Changes During Brain Activation at 7T
Laurentius Huber1, Sean Marrett1, Daniel A Handwerker1, Adam Thomas1, Benjamin Gutierrez1, Dimo Ivanov2, Benedikt A Poser2, and Peter A Bandettini1

1Section of Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, United States, 2MBIC, Maastricht University, Maastricht, Netherlands

Synopsis

We present a fast new method for obtaining quantitative T1 maps with high spatial (1 mm) and temporal resolutions (3 s). This method can be useful to investigate morphological dynamics of brain GM, e.g. during brain activity changes, plasticity changes, or pathology. The robustness of the developed method is demonstrated with a finger tapping fMRI experiment. We report a functional GM T1 increase of up to 100 ms, and a GM thickness increase by up to 0.25 mm.

Purpose

The current MRI-based neuro-imaging methods can be separated in two independent categories. A) Anatomical T1-weighted imaging methods to investigate structural features, e.g., investigating pathology or plasticity [1]; and B) Fast T2*-weighted functional imaging methods to investigate transient brain activity changes. Here we sought to develop, apply, and evaluate a new method that combines the advantages of both imaging approaches: We combine the quantifiability, the tissue type specificity, and the high spatial resolution of anatomical MRI with the high temporal resolution of EPI-based fMRI. This new approach will enable research into the underlying mechanisms associated with GM density change and T1 changes as seen in studies about plasticity, sleep, learning etc., and furthermore to investigate the structural changes during increased brain activity as in conventional fMRI experiments. The new imaging method for simultaneous acquisition of T1 and T2*-weighted signal is based on a multi-contrast inversion-recovery (IR) simultaneous multi-slice (SMS) EPI with blipped CAIPI [2] and a new MRI signal processing pipeline similar to the one of MP2RAGE [1].

Methods

Experiments were performed on a 7T Siemens scanner with a 32-channel NOVA head-coil. Four volunteers participated in six experiments. The sequence parameters were: TI1/TI2/TR=0.9/2.4/3.0 s (as indicated in Fig. 1), SMS-factor=3 with a FoV/3 blipped-CAIPI EPI [3], GRAPPA-2 with FLEET [4]. Image reconstruction was performed online using split-Slice GRAPPA [5] as implemented in MGH C2P (http://www.nmr.mgh.harvard.edu/software/c2p/sms), #slices=30, nominal resolution=1×1×1.3mm3 and 0.7mm inter-slice gap. Slices were positioned as depicted in Fig. 1F. T1-weighting was achieved by an optimized TR-FOCI inversion. To determine T1, a Bloch-equation model of the sequence was fitted to the multi-TI data (similar to MP2RAGE [1]) by numerically inverting Eq. 1.

$$$\frac{S(\color{red}{TI_1})}{S(\color{green}{TI_2})}= \overbrace{\frac{sin(\alpha)}{sin(\alpha)}}^{=1}\times \overbrace{ \frac{M_0}{M_0} }^{=1} \times \overbrace{ \frac{e^{-\frac{TE}{T_2^\star}}}{e^{-\frac{TE}{T_2^\star}}} }^{=1} \times \frac{ \frac{1-(1+\chi) e^{-\frac{\color{red}{TI_1}}{T_1}} +\chi e^{-\frac{TR}{2T_1}} - cos (\alpha) e^{-\frac{TR}{2T_1}}+ cos (\alpha) e^{-\frac{TR}{T_1}} }{1+cos^2 (\alpha)e^{-\frac{TR}{T_1}}}}{1-e^{-\frac{2TR}{T_1}} \left(1- \left(\frac{1-(1+\chi) e^{-\frac{\color{green}{TI_2}}{T_1}} +\chi e^{-\frac{TR}{2T_1}} - cos (\alpha) e^{-\frac{TR}{2T_1}}+ cos (\alpha) e^{-\frac{TR}{T_1}} }{1+cos^2 (\alpha)e^{-\frac{TR}{T_1}}}\right)\right)}$$$

The pulse-specific B1+-independent inversion-efficiency $$$\chi$$$ had previously been determined to be 0.8, the flip angle $$$\alpha$$$ is taken from the acquired B1+-map with MAFI [6], and TI is the effective slice-specific inversion time. Segmentation and cortical layering algorithms were implemented in C++ and applied on the EPI-based T1-maps using the equi-volume approach [7]. A 12-min finger-tapping paradigm was used here to investigate the performance and feasibility of the proposed technique.

Results

Raw EPI images for the two TIs are shown in Fig. 1A-B for a single TR. A representative single-TR T1-map is shown in Fig. 2A. Voxels with T1 increases of more than 2.5% are shown in red overplayed to a T1-map averaged over all 240 time steps (Fig. 2B). The estimated T1 values increase by up to 100 ms during the task condition. The temporal evolution of T1 and simultaneous T2*-weighted signal can be seen in Fig. 2C averaged across voxels within M1. Single-TR T1-maps have enough SNR to apply tissue segmentation and layering (Fig. 2D) to provide measures of cortical thickness and cortical profiles of T1. T1-increases within GM are dominated from upper cortical layers (Fig. 2E). Cortical thickness seems to increase up to 4% during neural activity (Fig. 2F), where the GM band seems to expand towards WM and not so much towards CSF [8].

Discussion

The results presented here demonstrate that advanced EPI-based imaging methods are robust enough to provide anatomical information that is conventionally achievable only with lengthy (and therefore more motion-sensitive) so-called “anatomical” sequences. Both, the T1-increase and the “swelling” of the GM might be interpreted as a volume increase of blood, which has a longer T1 than GM (a.k.a. the VASO contrast). A CBF and inflow contribution to the contrast seems unlikely, as two modules of QUIPPS [9] saturation pulses are played out below the imaging slab right prior imaging (yellow Fig. 1E). The quantitative nature of the method may be particularly appealing when comparing conditions across a long time (longer than scanner drift), across days, and across, scanners and platforms. The fact of having only two TI for T1-estimation makes the method very fast and minimizes MT-effects, however, it cannot be used for fitting to multi-compartment models. More research is needed to validate the quantitative T1 values with more established ‘anatomical’ sequences.

Conclusion

We developed a multi-contrast inversion recovery SMS CAIPI EPI MR sequence for fast dynamic high-resolution whole brain quantitative T1-mapping. With this new method, we could observe functional changes of GM morphology during neural activation, such as T1-increases of up to 100 ms and GM “swelling” of up to 4%. This method may prove important in quantitative, non-invasive studies investigating morphological GM changes in neural activity, plasticity, sleep and pathology.

Acknowledgements

Supported by the NIMH Intramural Research Program.

References

[1] Marques et al., NeuroImage, 2010, 1271-1281; [2] Setsompop et al., MRM, 2012, 67:1210-1224; [4] Polimeni et al., MRM, 2015, doi:10.1002/mrm.25628; [5] Cauley et al., MRM, 2013, 72:93-102; [6] Boulant et al., MRM, 2009, 61:1165-1172; [7] Waehnert et al., NeuroImage, 2014, 93:210-220; [8] Renvall et al., ISMRM, 2014, #1488; [9] Wong et al., MRM, 998, 39:702-708.

Figures

Proposed T1-mapping sequence for one TR with example. (A/B) example MR images fro the two imaging blocks, (C) sequence diagram, (D) expected in-plane Mz-magnetization evolution, (E) zoomed view into important RF/Gradient modules within one TR, (G) position of those modules.

Results: (A) Representative T1-map, (B) Map of significant T1 changes on top of mean T1-map. (C) time course of T1 and simultaneously acquired T2*-weighted signal averaged of a single-subject M1 ROI, (D) equi-volume layers implemented in EPI-space, (E) cortical profile of T1-changes, (F) averaged time course of M1 cortical thickness.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
0633