Optimizing Diffusion-Tensor Imaging Acquisition for Spinal Cord Assessment: Physical Basis and Technical Adjustments.
Teodoro Martín NoguerolRafael BarousseTimothy J AmrheinJavier Royuela-Del-ValPaula MontesinosAntonio Luna-AlcaláPublished in: Radiographics : a review publication of the Radiological Society of North America, Inc (2021)
Diffusion-tensor imaging (DTI) has been used in the assessment of the central nervous system for the past 3 decades and has demonstrated great utility for the functional assessment of normal and pathologic white matter. Recent technical advances have permitted the expansion of DTI applications to the spinal cord. MRI of the spinal cord has traditionally been limited to conventional sequences, which provide information regarding changes in the anatomic shape of a structure or its signal intensity, suggesting the presence of a pathologic entity. However, conventional MRI lacks the ability to provide pathophysiologic information. DTI of the spinal cord can deliver pathophysiologic information on a molecular basis and thereby has several adjunctive uses. These advantages have yet to be fully evaluated, and therefore spinal DTI lacks widespread adoption. The barriers to implementation include a lack of understanding of the underlying physics principles needed to make necessary technical adjustments to obtain diagnostic images, as well as the need for standardization of protocols and postprocessing methods. The authors provide a comprehensive review of the physics of spinal cord DTI and the technical adjustments required to obtain diagnostic images and describe tips and tricks for accurate postprocessing. The primary clinical applications for spinal cord DTI are reviewed. Online supplemental material is available for this article. ©RSNA, 2020 See discussion on this article by Smith.
Keyphrases
- spinal cord
- white matter
- neuropathic pain
- spinal cord injury
- multiple sclerosis
- magnetic resonance imaging
- deep learning
- contrast enhanced
- neoadjuvant chemotherapy
- convolutional neural network
- physical activity
- primary care
- mental health
- optical coherence tomography
- squamous cell carcinoma
- computed tomography
- magnetic resonance
- social media
- high intensity
- mass spectrometry
- locally advanced
- rectal cancer