Model-based reconstruction for simultaneous multislice and parallel imaging accelerated multishot diffusion tensor imaging.

PURPOSE: Multishot interleaved echo-planar imaging (iEPI) can achieve higher image resolution than single-shot EPI for diffusion tensor imaging (DTI), but its application is limited by the prolonged acquisition time. To reduce the acquisition time, a novel model-based reconstruction for simultaneous multislice (SMS) and parallel imaging (PI) accelerated iEPI DTI is proposed.

MATERIALS AND METHODS: DTI datasets acquired by iEPI with SMS and PI acceleration can be regarded as 3D k-space data, which is undersampled along both the slice and phase encoding directions. Instead of reconstruction of individual diffusion-weighted image, diffusion tensors are directly estimated by the joint reconstruction of undersampled 3D k-space from all diffusion-encoding directions using a model-based formulation to exploit the correlation across different directions. DTI simulation and in vivo acquisition were used to demonstrate the superior performance of the proposed method.

RESULTS: The proposed method reduced the estimation errors and artifacts than traditional parallel imaging reconstruction in DTI simulation. In the in vivo DTI experiment, the acquisition time of 4-shot iEPI was reduced from 11 min 7 s to 3 min 53 s with an acceleration factor of 4, and the image quality and precision of quantitative parameters were comparable with the fully sampled acquisition.

CONCLUSIONS: The proposed model-based reconstruction for iEPI DTI with SMS and PI can achieve fourfold acceleration while maintaining high accuracy for tensor measurements.