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.
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).
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).
For predicting the consistency of intracranial meningiomas.
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).
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).
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).