Dual-encoded magnetization transfer and diffusion imaging and its application to tract-specific microstructure mapping

Abstract

We present a novel dual-encoded magnetization transfer (MT) and diffusion-weighted sequence and demonstrate its potential to resolve distinct properties of white matter fiber tracts at the sub-voxel level. The sequence was designed and optimized for maximal MT ratio (MTR) efficiency. The resulting whole brain 2.6 mm isotropic protocol to measure tract-specific MTR has a scan time under 7 minutes. Ten healthy subjects were scanned twice to assess repeatability. Two different analysis methods were contrasted: a technique to extract tract-specific MTR using Convex Optimization Modeling for Microstructure Informed Tractography (COMMIT), a global optimization technique; and conventional MTR tractometry. The results demonstrate that the tract-specific method can reliably resolve the MT ratios of major white matter fiber pathways and is less affected by partial volume effects than conventional multi-modal tractometry. By reducing the contamination due to partial volume averaging of tracts, dual-encoded MT and diffusion may increase the sensitivity to microstructure alterations of specific tracts due to disease, aging, or learning, as well as lead to weighted structural connectomes with more anatomical specificity.

Keywords: connectome; diffusion; dual-encoding; magnetization transfer; microstructure; myelin.

Fig. 1.

Sequence diagram of co-encoded MT-diffusion: A pulsed MT module inserted prior to the diffusion preparation of the 2D-EPI acquisition of each slice. The polarity (+/-), the duration (τ), inter-pulse time gap (Δt), number of pulses, and the flip angle of the MT pulse (FA_MT) can be controlled as well as the duration of the excitation (T_exc) and refocusing pulses (T_ref). The MT preparation is repeated for each slice and each diffusion encoding. The sequence repetition time is given by TR = TR_MT*slices.

Fig. 2.

Processing pipeline: The MT_off data are used to generate the tractogram, which is then used with COMMIT to produce the MIT_on and MT_off connectomes. These connectomes are then combined to get tract-specific MTR values using Eqn 3.

Fig. 3.

Simulated results of MTR efficiency: (A) Number of saturation pulses vs TR_MT (B) Offset frequency vs TR_MT and (C) Saturation pulse durations vs number of saturation pulses. Red circle highlights the optimal protocol and the green, sub-optimal.

Fig. 4.

MTR efficiency (MTR/time) of optimal (TR_MT = 90 ms, red outline) and sub-optimal (TR_MT = 110 ms, green outline) protocols of the b = 0 and of the average over 30 diffusion directions (DiffAVG).

Fig. 5.

Reducing sources of unwanted SAR and MT by avoiding MB and replacing standard fat saturation by using a ratio of pulse lengths for fat suppression. (A) diffusion-weighted image (B) the MTR of the b = 0 images.

Fig. 6.

(A) Percent difference between tract-specific and tractometry MTR for selected bundles (B) Average tract-specific MTR (C) Average tractometry MTR and (D,E) corresponding scan-rescan repeatability across 10 subjects (* denotes significance at p < 0.01; n.s. not significant).

Fig. 7.

Example of tract-specific and tractometry bundle MTR results for one subject. Open arrows highlight the regions where a single fiber population is dominating the voxel (e.g., in (A): the pons (yellow) and CST (red) and (B): the PrCG-Thal connection (orange)), which gives an indication of the non-partial-volumed MTR_dw value along each tract (blue color scale). The overlayed MTR results (hot color scale) for the tract-specific method show better agreement with the underlying scalar map and higher contrast between tracts compared to conventional tractometry.

Fig. 8.

Percent difference between single-fiber voxel MTRdw values and tract-specific MTR and tractometry MTR values, respectively for the pons and bilateral cortico-spinal tracts.