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diffusion_tensor_imaging

Diffusion tensor imaging

J.Sales-Llopis

Neurosurgery Department, University General Hospital of Alicante, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region (FISABIO), Alicante, Spain

Since its introduction, diffusion tensor imaging (DTI) has become an important tool in neuroscience given its unprecedented ability to image brain white matter in vivo.

The interest in understanding the mechanisms of action of Deep Brain Stimulation in different targets and indications, together with the constant drive towards the improvement in long-term clinical outcomes, has found a logical complement in the application of tractography in this field. Diffusion tensor imaging has been traditionally associated with an increased susceptibility to MRI artifacts, and expensive computational resources. Recent advances have however improved these restrictions, allowing for countless applications in Neurosurgery, as demonstrated by the large number of original research papers published in the last decade 1).

Diffusion tensor imaging (DTI) for the assessment of fractional anisotropy (FA) and involving measurements of mean diffusivity (MD) and apparent diffusion coefficient (ADC) represents a, MRI-based, noninvasive technique that may delineate microstructural changes in cerebral white matter (WM).

Diffusion tensor imaging (DTI) provides a measure of the directional diffusion of water molecules in tissues and can noninvasively detect in vivo white matter (WM) abnormalities on the basis of anisotropic diffusion properties.

From the diffusion tensor, the principal direction of the diffusion tensor can be used to infer the white-matter connectivity of the brain (i.e. tractography; trying to see which part of the brain is connected to which other part).

Diffusion tensor imaging (DTI) attempts to aid in the preservation of subcortical networks by providing a framework for localizing tracts in relation to the surgical target. DTI takes advantage of the anisotropic diffusion of water along white matter fiber bundles, which can be assessed with magnetic resonance imaging (MRI). Postprocessing platforms are used to map the tracts, which can then be integrated into neuronavigation. This permits the neurosurgeon to ascertain the location and orientation of major white matter tracts for preoperative and intraoperative decision making.

Indications

Spinal cord

The measurement of DTI indexes within the spinal cord provides a quantitative assessment of neural damage in various spinal cord pathologies. DTI studies in animal models of spinal cord injury indicate that DTI is a reliable imaging technique with important histological and functional correlates.

DTI is a noninvasive marker of microstructural change within the spinal cord. In human studies, spinal cord DTI shows definite changes in subjects with acute and chronic spinal cord injury, as well as cervical spondylotic myelopathy. Interestingly, changes in DTI indexes are visualized in regions of the cord, which appear normal on conventional magnetic resonance imaging and are remote from the site of cord compression. Spinal cord DTI provides data that can help us understand underlying microstructural changes within the cord and assist in prognostication and planning of therapies 2).

Pediatric stroke

Plasticity of the developing motor tracts is a contributor to recovery of motor function after pediatric stroke. The mechanism of these plastic changes may be functional and/or structural in nature.

In a case of a 3-year-old girl demonstrating reorganization of the pyramidal tracts after an extensive left MCA territory stroke secondary to head trauma. Reorganization is characterized using serial diffusion tensor imaging (DTI) of the pyramidal tracts which contain the CST.

Imaging shows decreased ipsi-lesional fractional anisotropy (FA) suggestive of Wallerian degeneration and increased contralesional FA.

These results point to plastic reorganization of the pyramidal tract post-stroke and the utility of DTI in recognizing these changes 3).

Pulsed arterial spin labeling, DTI, and MR spectroscopy are useful for predicting glioma grade. Additionally, the parameters obtained on DTI and MR spectroscopy closely correlated with the proliferative potential of gliomas 4).

Intracranial meningiomas

For predicting the consistency of intracranial meningiomas.

Traumatic brain injury

DTI parameters, assessed at approximately day 12 after injury, correlated with mortality at 6 months in patients with severe TBI or aSAH. Similar patterns were found for both TBI and aSAH patients. This supports a potential role of DTI as early endpoint for clinical studies and a predictor of late mortality 5).

Hydrocephalus

A retrospective DTI study demonstrated significant WM abnormalities in infants with hydrocephalus in both the corpus callosum and internal capsule. The results also showed evidence that the impact of hydrocephalus on WM was different in the corpus callosum and internal capsule 6).


A study provides initial evidence of DTI's sensitivity to detect subtle WM changes associated with performance improvements in response to a 6-week occupational therapy (OT) intervention in children with surgically treated hydrocephalus (HCP) 7).


DTI may be used for the diagnosis and differentiation of idiopathic normal pressure hydrocephalus (iNPH) from other neurodegenerative diseases with similar imaging findings and clinical symptoms and signs. The goal of a study was to identify and analyze recently published series on the use of DTI as a diagnostic tool. Moreover, Siasios et al., also explored the utility of DTI in identifying patients with iNPH who could be managed by surgical intervention.

The authors performed a literature search of the PubMed database by using any possible combinations of the following terms: “Alzheimer's disease,” “brain,” “cerebrospinal fluid,” “CSF,” “diffusion tensor imaging,” “DTI,” “hydrocephalus,” “idiopathic,” “magnetic resonance imaging,” “normal pressure,” “Parkinson's disease,” and “shunting.” Moreover, all reference lists from the retrieved articles were reviewed to identify any additional pertinent articles.

The literature search retrieved 19 studies in which DTI was used for the identification and differentiation of iNPH from other neurodegenerative diseases. The DTI protocols involved different approaches, such as region of interest (ROI) methods, tract-based spatial statistics, voxel-based analysis, and delta-ADC analysis. The most studied anatomical regions were the periventricular WM areas, such as the internal capsule (IC), the corticospinal tract (CST), and the corpus callosum (CC). Patients with iNPH had significantly higher MD in the periventricular WM areas of the CST and the CC than had healthy controls. In addition, FA and ADCs were significantly higher in the CST of iNPH patients than in any other patients with other neurodegenerative diseases. Gait abnormalities of iNPH patients were statistically significantly and negatively correlated with FA in the CST and the minor forceps. Fractional anisotropy had a sensitivity of 94% and a specificity of 80% for diagnosing iNPH. Furthermore, FA and MD values in the CST, the IC, the anterior thalamic region, the fornix, and the hippocampus regions could help differentiate iNPH from Alzheimer or Parkinson disease. Interestingly, CSF drainage or ventriculoperitoneal shunting significantly modified FA and ADCs in iNPH patients whose condition clinically responded to these maneuvers.

Measurements of FA and MD significantly contribute to the detection of axonal loss and gliosis in the periventricular WM areas in patients with iNPH. Diffusion tensor imaging may also represent a valuable noninvasive method for differentiating iNPH from other neurodegenerative diseases. Moreover, DTI can detect dynamic changes in the WM tracts after lumbar drainage or shunting procedures and could help identify iNPH patients who may benefit from surgical intervention 8).

Diffusion tensor imaging for trigeminal neuralgia

Diffusion tensor imaging for brain tumor resection

Limitations

DTI, has limitations that include its inability to resolve multiple crossing fibers and its susceptibility to partial volume effects.

Therefore, recent focus has shifted to more advanced WM imaging techniques such as high-definition fiber tractography (HDFT).

Abhinav et al. illustrate the application of HDFT, which in their preliminary experience has enabled accurate depiction of perilesional tracts in a 3-dimensional manner in multiple anatomical compartments including edematous zones around high-grade gliomas. This has facilitated accurate surgical planning. This is illustrated by using case examples of patients with glioblastoma multiforme. They also discuss future directions in the role of these techniques in surgery for gliomas 9).

1)
Sammartino F, Hodaie M. Diffusion Tensor Imaging of the Basal Ganglia for Functional Neurosurgery Applications. Prog Neurol Surg. 2018;33:62-79. doi: 10.1159/000480766. Epub 2018 Jan 12. PubMed PMID: 29332074.
2)
Vedantam A, Jirjis MB, Schmit BD, Wang MC, Ulmer JL, Kurpad SN. Diffusion tensor imaging of the spinal cord: insights from animal and human studies. Neurosurgery. 2014 Jan;74(1):1-8. doi: 10.1227/NEU.0000000000000171. PubMed PMID: 24064483.
3)
George E, Heier L, Kovanlikaya I, Greenfield J. Diffusion tensor imaging of pyramidal tract reorganization after pediatric stroke. Childs Nerv Syst. 2014 Jan 14. [Epub ahead of print] PubMed PMID: 24420673.
4)
Fudaba H, Shimomura T, Abe T, Matsuta H, Momii Y, Sugita K, Ooba H, Kamida T, Hikawa T, Fujiki M. Comparison of Multiple Parameters Obtained on 3T Pulsed Arterial Spin-Labeling, Diffusion Tensor Imaging, and MRS and the Ki-67 Labeling Index in Evaluating Glioma Grading. AJNR Am J Neuroradiol. 2014 Jul 3. [Epub ahead of print] PubMed PMID: 24994829.
5)
Sener S, Van Hecke W, Feyen BF, Van der Steen G, Pullens P, Van de Hauwe L, Menovsky T, Parizel PM, Jorens PG, Maas AI. Diffusion Tensor Imaging: A Possible Biomarker in Severe Traumatic Brain Injury and Aneurysmal Subarachnoid Hemorrhage? Neurosurgery. 2016 Jun 27. [Epub ahead of print] PubMed PMID: 27352277.
6)
Yuan W, Mangano FT, Air EL, Holland SK, Jones BV, Altaye M, Bierbrauer K. Anisotropic diffusion properties in infants with hydrocephalus: a diffusion tensor imaging study. AJNR Am J Neuroradiol. 2009 Oct;30(9):1792-8. doi: 10.3174/ajnr.A1663. Epub 2009 Aug 6. PubMed PMID: 19661167.
7)
Yuan W, Harpster K, Jones BV, Shimony JS, McKinstry RC, Weckherlin N, Powell SS, Barnard H, Engsberg J, Kadis DS, Dodd J, Altaye M, Limbrick DD, Holland SK, Simpson SM, Bidwell S, Mangano FT. Changes of White Matter Diffusion Anisotropy in Response to a 6-Week iPad Application-Based Occupational Therapy Intervention in Children with Surgically Treated Hydrocephalus: A Pilot Study. Neuropediatrics. 2016 Jul 20. [Epub ahead of print] PubMed PMID: 27438376.
8)
Siasios I, Kapsalaki EZ, Fountas KN, Fotiadou A, Dorsch A, Vakharia K, Pollina J, Dimopoulos V. The role of diffusion tensor imaging and fractional anisotropy in the evaluation of patients with idiopathic normal pressure hydrocephalus: a literature review. Neurosurg Focus. 2016 Sep;41(3):E12. doi: 10.3171/2016.6.FOCUS16192. PubMed PMID: 27581308.
9)
Abhinav K, Yeh FC, Mansouri A, Zadeh G, Fernandez-Miranda JC. High-definition fiber tractography for the evaluation of perilesional white matter tracts in high-grade glioma surgery. Neuro Oncol. 2015 Jun 27. pii: nov113. [Epub ahead of print] Review. PubMed PMID: 26117712.
diffusion_tensor_imaging.txt · Last modified: 2018/06/02 18:52 by administrador