Zijing Dong1, Erpeng Dai1, Fuyixue Wang1,2, Zhe Zhang1, Xiaodong Ma1, Chun Yuan1,3, Hua Guo1. 1. Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China. 2. Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA. 3. Department of Radiology, University of Washington, Seattle, WA, USA.
Abstract
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.
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.