The overall objective of this project is to dramatically improve the capability of fetal MRI for diagnosis, analysis, and prognosis of high-risk pregnancies. Accurate analysis obtained by fetal MRI is crucial in evaluating the highly variable aetiology and poorly understood pathophysiology of fetal central nervous system developmental disorders which affect about one-half percent of pregnancies. Nevertheless, fetal MRI is limited to two- dimensional acquisitions by the small signal available from the small fetal brain, and by intermittent fetal motion that disrupts spatial encoding necessary for advanced three-dimensional volumetric MRI. In order to address this limitation and reveal the power of fetal MRI, we propose novel imaging and image processing technology pursuing four specific aims in this project;
Aim 1, which is pivotal to our overall objective, involves super- resolution reconstruction of three-dimensional high spatial resolution volumetric T2w images of the fetal brain.
Aim 2 involves the construction of a spatiotemporal fetal brain atlas.
Aim 3 involves the comparison of fetal brain biometry and evaluation using 2D MRI, 2D sonography and 3D MRI. Finally in Aim 4 improved assessment of ventriculomegaly is considered using 3D fetal MRI. Ventriculomegaly is the most frequently observed fetal brain abnormality affecting about 0.1-0.2 percent of fetuses.
Aims 1 and 2 involve the development of new technology for clinical use and Aims 3 and 4 involve both technical developments and hypothesis tests to see how much improvement is achieved in the evaluation, diagnosis, and analysis of fetal brain abnormalities using the developed technology as compared to the current practice.
This research challenges current fetal brain MRI practice, which is limited to expert evaluation of 2D slices. This research will develop 3D fetal brain MRI reconstruction, and quantitative 3D fetal biometry, and demonstrate the superiority of 3D fetal brain MRI for the in vivo evaluation of fetal brain developmental disorders. This will lead to more accurate diagnosis and prognosis, and improved patient outcomes.
|Chamberland, Maxime; Scherrer, Benoit; Prabhu, Sanjay P et al. (2017) Active delineation of Meyer's loop using oriented priors through MAGNEtic tractography (MAGNET). Hum Brain Mapp 38:509-527|
|Gholipour, Ali; Rollins, Caitlin K; Velasco-Annis, Clemente et al. (2017) A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth. Sci Rep 7:476|
|Jia, Yuanyuan; Gholipour, Ali; He, Zhongshi et al. (2017) A New Sparse Representation Framework for Reconstruction of an Isotropic High Spatial Resolution MR Volume From Orthogonal Anisotropic Resolution Scans. IEEE Trans Med Imaging 36:1182-1193|
|Tourbier, Sébastien; Velasco-Annis, Clemente; Taimouri, Vahid et al. (2017) Automated template-based brain localization and extraction for fetal brain MRI reconstruction. Neuroimage 155:460-472|
|Marami, Bahram; Scherrer, Benoit; Afacan, Onur et al. (2016) Motion-Robust Reconstruction based on Simultaneous Multi-Slice Registration for Diffusion-Weighted MRI of Moving Subjects. Med Image Comput Comput Assist Interv 9902:544-552|
|Pier, Danielle B; Gholipour, Ali; Afacan, Onur et al. (2016) 3D Super-Resolution Motion-Corrected MRI: Validation of Fetal Posterior Fossa Measurements. J Neuroimaging 26:539-44|
|Akhondi-Asl, Alireza; Afacan, Onur; Balasubramanian, Mukund et al. (2016) Fast myelin water fraction estimation using 2D multislice CPMG. Magn Reson Med 76:1301-13|
|Marami, Bahram; Scherrer, Benoit; Afacan, Onur et al. (2016) Motion-Robust Diffusion-Weighted Brain MRI Reconstruction Through Slice-Level Registration-Based Motion Tracking. IEEE Trans Med Imaging 35:2258-2269|
|Afacan, Onur; Erem, Burak; Roby, Diona P et al. (2016) Evaluation of motion and its effect on brain magnetic resonance image quality in children. Pediatr Radiol 46:1728-1735|
|Scherrer, Benoit; Schwartzman, Armin; Taquet, Maxime et al. (2016) Characterizing brain tissue by assessment of the distribution of anisotropic microstructural environments in diffusion-compartment imaging (DIAMOND). Magn Reson Med 76:963-77|
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