RESUMEN
White matter (WM) abnormalities are commonly reported in schizophrenia but whether these arise from the axon or myelin compartments or both is not known. In addition, the relationship between WM abnormalities and cognitive function is not fully explored in this condition. We recruited 39 individuals with schizophrenia spectrum disorders and 37 healthy comparison subjects. All participants underwent MRI scanning at 4 Tesla to collect data in the prefrontal white matter on magnetization transfer ratio (MTR) and diffusion tensor spectroscopy (DTS) which provide information on myelin and axon compartments, respectively. We also collected Matrics Composite Cognitive Battery (MCCB) and Stroop cognitive data. We found an elevated N-acetylaspartate (NAA) apparent diffusion coefficient in schizophrenia in this cohort as in our previous work; we also observed poorer performance on both the MCCB composite and the Stroop in schizophrenia patients compared to controls. The MTR measure was correlated with the MCCB composite (r = 0.363, p = 0.032) and Stroop scores (r = 0.387, p = 0.029) in healthy individuals but not in schizophrenia. Since this is the first exploration of the relationship between these WM and cognitive measures, we consider our analyses exploratory and did not adjust for multiple comparisons; the findings are not statistically significant if adjusted for multiple comparisons. These findings indicate that WM integrity is associated with cognitive function in healthy individuals but this relationship breaks down in patients with schizophrenia.
RESUMEN
OBJECTIVE 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 novel, MRI-based, noninvasive technique that may delineate microstructural changes in cerebral white matter (WM). For example, 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 the current study was to identify and analyze recently published series on the use of DTI as a diagnostic tool. Moreover, the authors also explored the utility of DTI in identifying patients with iNPH who could be managed by surgical intervention. METHODS 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. RESULTS 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. CONCLUSIONS 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.