Moran Artzi

Abnormal White Matter Integrity in Young Children with Autism

This study investigated white matter integrity in young children with autism using diffusion tensor imaging (DTI). Twenty‐two children with autism, mean age 3:2 years, and 32 controls, mean age 3:4 years, participated in the study. Tract‐based spatial statistics (TBSS) revealed white matter abnormalities in several distinct clusters within the genu and body of the corpus callosum (CC), left superior longitudinal fasciculus (SLF) and right and left cingulum (Cg). TBSS–VOIs analysis was performed in the clusters where differences in fractional anisotropy (FA) were detected to investigate the relationship between changes in FA and diffusivity indices. In all VOIs, increase in FA was caused by a decrease in radial diffusivity (Dr), while no changes in axial diffusivity (Da) or mean diffusivity (MD) were observed. Tractography analysis was applied to further study the CC, SLF, and Cg. Witelson parcellation scheme was used for the CC. Significant increase in FA was seen in children with autism in the mid‐body of the CC as well as in the left Cg. It is suggested that such abnormal white matter integrity in young children with autism may adversely affect connectivity between different brain regions and may be linked to some of the behavioral impairments apparent in autism. Hum Brain Mapp, 2011.

Differentiation between vasogenic-edema versus tumor-infiltrative area in patients with glioblastoma during bevacizumab therapy: A longitudinal MRI study

BACKGROUND Treatment with bevacizumab is associated with substantial radiologic response in patients with glioblastoma (GB). However, following this initial response, changes in T2-weighted MRI signal may develop, suggesting an infiltrative pattern of tumor progression. The aim of this study was to differentiate between vasogenic-edema versus tumor-infiltrative area in GB patients. METHODS AND MATERIALS Fourteen patients with GB were longitudinally scanned, before and during intravenous bevacizumab therapy (5/10mg/kg every 2-weeks). A total of 40 MR scans including conventional, diffusion, dynamic susceptibility contrast, dynamic contrast enhancement imaging, and MR-spectroscopy (MRS) were analyzed. Classification of non-enhancing fluid-attenuation-inversion-recovery (FLAIR) area was performed based on mean diffusivity, cerebral blood volume and flow maps, and further characterized using multiple MRI parameters. RESULTS The non-enhancing FLAIR lesion area was classified into: vasogenic-edema, characterized by reduced perfusion and increased FLAIR values; or tumor-infiltrative area, characterized by increased perfusion. Tumor-infiltrative area demonstrated a higher malignant pattern on MRS compared to areas of vasogenic-edema. Substantial reductions of the enhanced T1-weighted (58 ± 10%) and hyperintense FLAIR (53 ± 9%) lesion volumes were detected mainly during the first weeks of therapy, with a shift to an infiltrative pattern of tumor progression thereafter, as detected by an increase in tumor-infiltrative area in the majority of patients, which correlated with progression-free survival (week 8: r=-0.86, p=0.003, week 16: r=-0.99, p=0.001). CONCLUSION Characterization of non-enhancing hyperintense FLAIR lesion area in GB patients can provide an MR-based biomarker, indicating a shift to an infiltrative progression pattern, and may improve therapy response assessment in patients following bevacizumab therapy.

FLAIR lesion segmentation: Application in patients with brain tumors and acute ischemic stroke

BACKGROUND Lesion size in fluid attenuation inversion recovery (FLAIR) images is an important clinical parameter for patient assessment and follow-up. Although manual delineation of lesion areas considered as ground truth, it is time-consuming, highly user-dependent and difficult to perform in areas of indistinct borders. In this study, an automatic methodology for FLAIR lesion segmentation is proposed, and its application in patients with brain tumors undergoing therapy; and in patients following stroke is demonstrated. MATERIALS AND METHODS FLAIR lesion segmentation was performed in 57 magnetic resonance imaging (MRI) data sets obtained from 44 patients: 28 patients with primary brain tumors; 5 patients with recurrent-progressive glioblastoma (rGB) who were scanned longitudinally during anti-angiogenic therapy (18 MRI scans); and 11 patients following ischemic stroke. RESULTS FLAIR lesion segmentation was obtained in all patients. When compared to manual delineation, a high visual similarity was observed, with an absolute relative volume difference of 16.80% and 20.96% and a volumetric overlap error of 24.87% and 27.50% obtained for two raters: accepted values for automatic methods. Quantitative measurements of the segmented lesion volumes were in line with qualitative radiological assessment in four patients who received anti-anogiogenic drugs. In stroke patients the proposed methodology enabled identification of the ischemic lesion and differentiation from other FLAIR hyperintense areas, such as pre-existing disease. CONCLUSION This study proposed a replicable methodology for FLAIR lesion detection and quantification and for discrimination between lesion of interest and pre-existing disease. Results from this study show the wide clinical applications of this methodology in research and clinical practice.

Hemodynamic response imaging: a potential tool for the assessment of angiogenesis in brain tumors.

Blood oxygenation level dependence (BOLD) imaging under either hypercapnia or hyperoxia has been used to study neuronal activation and for assessment of various brain pathologies. We evaluated the benefit of a combined protocol of BOLD imaging during both hyperoxic and hypercapnic challenges (termed hemodynamic response imaging (HRI)). Nineteen healthy controls and seven patients with primary brain tumors were included: six with glioblastoma (two newly diagnosed and four with recurrent tumors) and one with atypical-meningioma. Maps of percent signal intensity changes (ΔS) during hyperoxia (carbogen; 95%O2+5%CO2) and hypercapnia (95%air+5%CO2) challenges and vascular reactivity mismatch maps (VRM; voxels that responded to carbogen with reduced/absent response to CO2) were calculated. VRM values were measured in white matter (WM) and gray matter (GM) areas of healthy subjects and used as threshold values in patients. Significantly higher response to carbogen was detected in healthy subjects, compared to hypercapnia, with a GM/WM ratio of 3.8 during both challenges. In patients with newly diagnosed/treatment-naive tumors (n = 3), increased response to carbogen was detected with substantially increased VRM response (compared to threshold values) within and around the tumors. In patients with recurrent tumors, reduced/absent response during both challenges was demonstrated. An additional finding in 2 of 4 patients with recurrent glioblastoma was a negative response during carbogen, distant from tumor location, which may indicate steal effect. In conclusion, the HRI method enables the assessment of blood vessel functionality and reactivity. Reference values from healthy subjects are presented and preliminary results demonstrate the potential of this method to complement perfusion imaging for the detection and follow up of angiogenesis in patients with brain tumors.

A potential tool for the diagnosis of ALS based on diffusion tensor imaging

Abstract Our objective was to quantify and better understand white matter (WM) impairment in patients with amyotrophic lateral sclerosis (ALS) and to propose a model based on diffusion tensor imaging (DTI) for diagnosing patients with suspected ALS with upper motor neuron (UMN) signs. Twenty-six ALS patients (24 with prominent UMN signs and two with an isolated lower-motor neuron (LMN) syndrome) and 22 healthy volunteers were examined using DTI. Data analysis included voxel-based WM tract-based spatial statistics (TBSS), volume-of-interest analysis of the TBSS results and stream-line tractography analysis. Converging evidence revealed WM impairment along the corticospinal tracts and in the mid-body of the corpus callosum. This was demonstrated by reduced fractional anisotropy values caused by increased radial diffusivity, without significant changes in axial diffusivity. There were no significant correlations between diffusivity indices and patients’ disability or disease duration. A discriminant analysis model based on the tractography results was designed to distinguish between patients with UMN signs and controls, yielding 87.5% sensitivity and 85% specificity. In conclusion, DTI can detect WM impairment in patients with ALS in several brain regions, and might be a sensitive tool for the diagnosis of ALS in the early stages of the disease with UMN involvement.

1H-MRS for the diagnosis of acute disseminated encephalomyelitis: insight into the acute-disease stage.

BackgroundAcute disseminated encephalomyelitis (ADEM) is a demyelinating disorder of the central nervous system (CNS). Differentiating ADEM from other inflammatory disorders, such as multiple sclerosis, is not always conclusive using conventional MRI.ObjectiveTo evaluate longitudinal magnetic resonance spectroscopy (MRS) changes that distinguish ADEM from other inflammatory disorders.Materials and methodsMRI/MRS scans were performed in seven patients with ADEM during the acute and chronic phases of the disease.ResultsPartial recovery was detected between the acute and chronic phases in choline/creatine ratio. Major elevation of lipids and reduction in myo-inositol/creatine ratio was detected in all patients during the acute phase, followed by a reduction in lipids peak and elevation above normal in myo-inositol/creatine ratio during the chronic phase.ConclusionConsistent and unique MRS changes in metabolite ratios between the acute and chronic presentations of the disease were found. To the best of our knowledge, these patterns have not been described in other inflammatory disorders and might assist in the early diagnosis of ADEM.

A Voxel-Based Morphometry and Diffusion Tensor Imaging Analysis of Asymptomatic Parkinson's Disease-Related G2019S LRRK2 Mutation Carriers

Patients with Parkinsons disease have reduced gray matter volume and fractional anisotropy in both cortical and sub‐cortical structures, yet changes in the pre‐motor phase of the disease are unknown.

Cognitive state following mild stroke: A matter of hippocampal mean diffusivity

The hippocampus is known to play a vital role in learning and memory and was demonstrated as an early imaging marker for Alzheimers disease (AD). However, its role as a predictor for mild cognitive impairment and dementia following stroke is unclear. The main purpose of this study was to examine the associations between hippocampal volume, mean diffusivity (MD) and connectivity and cognitive state following stroke. Eighty three consecutive first ever mild to moderate stroke or transient ischemic attack (TIA) survivors from our ongoing prospective TABASCO (Tel Aviv Brain Acute Stroke Cohort) study underwent magnetic resonance imaging scans within 7 days of stroke onset. Hippocampal volume was measured from T1 weighted images, hippocampal mean diffusivity was calculated from diffusion tensor imaging and connectivity was calculated from resting state fMRI. Global cognitive assessments were evaluated during hospitalization and 6 and 12 months later using a computerized neuropsychological battery. Multiple linear regression analysis was used to test which of the hippocampi measurements best predict cognitive state. All three imaging parameters were significantly correlated to each other (|rs| >0.3, Ps < 0.005), and with cognitive state 6 and 12 months after the event. Multiple regression analyses demonstrated the predictive role of hippocampal mean diffusivity (β = −0.382, P = 0.026) on cognitive state, above and beyond that of volume and connectivity of this structure. To our knowledge, the combination of hippocampal volume, mean diffusivity and connectivity in first ever post stroke or TIA patients has not yet been considered in relation to cognitive state. The results demonstrate the predictive role of hippocampal mean diffusivity, suggesting that these changes may precede and contribute to volumetric and connectivity changes in the hippocampi, potentially serving as a marker for early identification of patients at risk of developing cognitive impairment or dementia.

Neonatal neuropsychology: Emerging relations of neonatal sensory-motor responses to white matter integrity

The neonatal period is considered to be essential for neurodevelopment and wellbeing throughout the life span, yet little is known about brain-behavior relationships in the neonatal period. The aim of this study was to evaluate the association between neonatal sensory-motor regulation and white-matter (WM) integrity of major fiber tracts in the neonatal period. We hypothesized that WM integrity of sensory-motor systems would predict neurobehavioral maturation during the first month of life. Forty-nine premature neonates underwent magnetic-resonance-imaging at term. Diffusion-tensor-imaging analysis was performed in major WM tracts along with repeated neonatal neurobehavioral evaluations assessing sensory reactivity and motor regulation. Difficulties in one or more behavioral sub-category, mostly in auditory and visual attention, hypotonicity and jitteriness, were documented in 78.3% infants at term. Sixty-six percent of infants experienced difficulties, mostly in auditory attention, head-neck control, hypotonicity and motor asymmetry, at 44 weeks. Attention difficulties were associated with reduced integrity of cerebral and superior cerebellar peduncles; while tonicity was associated with reduced integrity of the corpus-callosum and inferior-posterior tracts. Overall, results showed that early maturing tracts were related with the degree of typicality of sensory reactivity status while late maturing tracts were related with the degree of typicality of tonic regulation. WM integrity and maturation factors explained 40.2% of the variance in neurobehavior at 44 weeks. This study suggests that in preterm neonates, deviant sensory-motor reactivity can be detected very early in development in manners that are related to lower integrity/maturational level of early and late maturing fiber tracts.

DaT-SPECT assessment depicts dopamine depletion among asymptomatic G2019S LRRK2 mutation carriers

Identification of early changes in Dopamine-Transporter (DaT) SPECT imaging expected in the prodromal phase of Parkinson’s disease (PD), are usually overlooked. Carriers of the G2019S LRRK2 mutation are known to be at high risk for developing PD, compared to non-carriers. In this work we aimed to study early changes in Dopamine uptake in non-manifesting PD carriers (NMC) of the G2019S LRRK2 mutation using quantitative DaT-SPECT analysis and to examine the potential for early prediction of PD. Eighty Ashkenazi-Jewish subjects were included in this study: eighteen patients with PD; thirty-one NMC and thirty-one non-manifesting non-carriers (NMNC). All subjects underwent a through clinical assessment including evaluation of motor, olfactory, affective and non-motor symptoms and DaT-SPECT imaging. A population based DaT-SPECT template was created based on the NMNC cohort, and data driven volumes-of-interest (VOIs) were defined. Comparisons between groups were performed based on VOIs and voxel-wise analysis. The striatum area of all three cohorts was segmented into four VOIs, corresponding to the right/left dorsal and ventral striatum. Significant differences in clinical measures were found between patients with PD and non-manifesting subjects with no differences between NMC and NMNC. Significantly lower uptake (p<0.001) was detected in the right and left dorsal striatum in the PD group (2.2±0.3, 2.3±0.4) compared to the NMC (4.2±0.6, 4.3±0.5) and NMNC (4.5±0.6, 4.6±0.6), and significantly (p = 0.05) lower uptake in the right dorsal striatum in the NMC group compared to NMNC. Converging results were obtained using voxel-wise analysis. Two NMC participants, who later phenoconverted into PD, demonstrated reduced uptake mainly in the dorsal striatum. No significant correlations were found between the DaT-SPECT uptake in the different VOIs and clinical and behavioral assessments in the non-manifesting groups. This study shows the clinical value of quantitative assessment of DaT-SPECT imaging and the potential for predicting PD by detection of dopamine depletion, already at the pre-symptomatic stage. Clinical registration numbers: NCT01089270 and NCT01089283.