Magnetic resonance imaging (MRI) with diffusion approaches (dMRI) is consistently used to understand neuronal connectivity in trials involving animal models.1 MRI is one of the most widely utilized techniques in small animal research into neurological development.2,3,4 MRI is a non-invasive method for evaluating neuronal pathways in neurodegenerative diseases, such as Alzheimer's disease.5
dMRI is an outstanding tool for studying brain function and disorders and allows the follow up in longitudinal research. However, imaging times can be long.
Most clinics rely on standard MRI imaging for the analysis of neurodegenerative diseases. dis utilized for diagnosing stroke, in circumstances when time is not a top priority.6,7
Research conducted by Yepes-Calderon et al describes an approach for improving dMRI dataset quality obtained over short acquisition times, developed with the end goal of encouraging wider usage of dMRI.8
The novel methodology uses a post-scanning approach, which allows images acquired by short imaging times to be enhanced. The new system was developed based on the hypothesis that the majority of the time spent in dMRI may be better allocated to the tensor domain compared with the diffusion weight imaging domain.
The investigators scanned their mouse model twice with their developed strategy, using the 9.4 Tesla Bruker BioSpec MRI. A third scan was obtained using the conventional DWI averaging method. They demonstrated that deteriorated diffusion images could readily be converted into meaningful ones comparable to those obtained in the conventional manner.
The new dMRI methodology report represents a cost- and time-effective neurological research tool that also has potential for being used in clinical practice.
1. Le Bihan D, Mangin JF, Poupon C, et al. Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging. 2001;13(4):534-546.
2. Schaefer PW, Grant PE, Gonzalez RG. Diffusion-weighted MR imaging of the brain. Radiology. 2000;217(2):331-345.
3. Puligheddu M, Laccu I, Gioi G, et al. Diffusion tensor imaging tractography and MRI perfusion in post traumatic brain injury hypersomnia. Sleep Med. 2017;34:96-98.
4. Wu D, Zhang J. In vivo mapping of macroscopic neuronal projections in the mouse hippocampus using high-resolution diffusion MRI. Neuroimage. 2016;125:84-93.
5. Hall JM, Ehgoetz Martens KA, Walton CC, et al. Diffusion alterations associated with Parkinson's disease symptomatology: A review of the literature. Parkinsonism Relat Disord. 2016;33:12-26.
6. Kunimatsu A, Aoki S, Masutani Y, et al. Three-dimensional white matter tractography by diffusion tensor imaging in ischaemic stroke involving the corticospinal tract. Neuroradiology. 2003;45(8):532-535.
7. Yao Y, Zhang S, Tang X, et al. Intravoxel incoherent motion diffusion-weighted imaging in stroke patients: initial clinical experience. Clin Radiol. 2016;71(9):938.e11-e16.
8. Yepes-Calderon F, Medina FM. Template-like Tensor Domain Operations to Enhancing Diffusion Datasets Quality. Advances in Science, Technology and Engineering Systems Journal. 2017;2(3):987-995.
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