Diffusion tensor based motion correction enables multi-parametric imaging of human placenta microstructures

Abstract

Background: Non-invasive in vivo diffusion-weighted magnetic resonance imaging (DWI) of the human placenta allows safe imaging and accurate characterization of the microstructure of the placenta during pregnancy. However, misalignment of different diffusion-weighted images caused by the maternal and fetal motion severely compromised the accuracy of diffusion magnetic resonance imaging (MRI) quantification. In this study, we proposed a diffusion tensor-based registration method customized to correct the image misalignment in DWI and enhance the multi-parametric imaging of human placenta microstructures. Method: We developed a novel registration method based on the diffusion tensor imaging (DTI) model and Fourier-approximated Lie Algebras for Shooting (FLASHC). We extensively tested and validated our method using simulated DWI images, which were contaminated by motion and deformation of the placenta. DWI of the entire uterus was acquired in 86 different directions with bmax = 2000 s/mm2. Our method is quantitatively evaluated using the continuous dice coefficient (cDC) and fitting residue from DTI and diffusion basis spectrum imaging (DBSI). Our method enables the application of advanced and complicated diffusion analysis models and detailed cotyledon-wise quantification of human placenta microstructural features. Result: The proposed method was proven efficient in registering simulated DWI deformed by motion, with increase mean cDC (from 0.78 to 0.93) and decrease mean fitting residue (DTI from 10.95% to 9.01%, DBSI from 8.01% to 3.07%). Similar improvements were found in registering DWI from clinical patients (cDC from 0.79 to 0.86 , DTI from 34.7 to 28.2%, DBSI from 6.5 to 2.8%.). Also, DBSI derived maps showed reasonable pattern after registration. After cotyledon-wise segmentation, region regional increased cellularity ratio was found in one patient with placental cyst and infarction. Conclusion: The proposed registration method provides a robust framework for motion correction in diffusion-weighted MR images and enabled the detailed and accurate quantification of human placenta microstructures.