Retrospective Analysis of Interobserver Spatial Variability in the Localization of Broca's and Wernicke's Areas Using Three Different fMRI Language Paradigms

Effects of tDCS applied over the left IFG and pSTG language areas on verb recognition task performance

Knowledge about the relevance of the left inferior frontal gyrus (lIFG) and the left posterior superior temporal gyrus (lpSTG) in visual recognition of word categories is limited at present. tDCS is a non-invasive brain stimulation method that alters cortical activity and excitability, and thus might be a useful tool for delineating the specific impact of both areas on word recognition. The objective of this study was to explore whether the visual recognition process of verb categories is improved by a single tDCS session. lIFG and lpSTG areas were separately modulated by anodal tDCS to evaluate its effects on verbal recognition. Compared to sham stimulation, motor reaction times (RTs) were reduced after anodal tDCS over the lpSTG, and this effect was independent of the performing hand (right/left). These findings suggest that this region is involved in visual word recognition independently from the performing hand.

Functional MRI Task Comparison for Language Mapping in Neurosurgical Patients

BACKGROUND AND PURPOSE

Language task-based functional MRI (fMRI) is increasingly used for presurgical planning in patients with brain lesions. Different paradigms elicit activations of different components of the language network. The aim of this study is to optimize fMRI clinical usage by comparing the effectiveness of three language tasks for language lateralization and localization in a large group of patients with brain lesions.

METHODS

We analyzed fMRI data from a sequential retrospective cohort of 51 patients with brain lesions who underwent presurgical fMRI language mapping. We compared the effectiveness of three language tasks (Antonym Generation, Sentence Completion (SC), and Auditory Naming) for lateralizing language function and for activating cortex within patient-specific regions-of-interest representing eloquent language areas, and assessed the degree of spatial overlap of the areas of activation elicited by each task.

RESULTS

The tasks were similarly effective for lateralizing language within the anterior language areas. The SC task produced higher laterality indices within the posterior language areas and had a significantly higher agreement with the clinical report. Dice coefficients between the task pairs were in the range of .351-.458, confirming substantial variation in the components of the language network activated by each task.

CONCLUSIONS

SC task consistently produced large activations within the dominant hemisphere and was more effective for lateralizing language within the posterior language areas. The low degree of spatial overlap among the tasks strongly supports the practice of using a battery of tasks to help the surgeon to avoid eloquent language areas.

Diffusion tensor imaging detects early brain microstructure changes before and after ventriculoperitoneal shunt in children with high intracranial pressure hydrocephalus

To explore the use of diffusion tensor imaging (DTI) parameters in the quantitative assessment of early brain microstructure changes before and after ventriculoperitoneal shunt in children with high intracranial pressure hydrocephalus.Ten patients with communicating hydrocephalus (age: 2-36 months) and 14 age-/gender-matched controls (age: 2-36 months) were enrolled in this study. All patients underwent the ventriculoperitoneal shunt procedure. The imaging data were collected before and 3 months after the operation. Regions of interests (ROIs) included the white matter near the frontal horn of the lateral ventricles (FHLV), the occipital horn of the lateral ventricles (OHLV), occipital subcortical (OS) area, frontal subcortical (FS) area, and thalamus. Fractional anisotropies (FA) and apparent diffusion coefficients (ADC) of the ROIs before and after ventriculoperitoneal shunt were compared between the patients and the controls.Three months after surgery, the patients recovered from the surgery with ameliorated intracranial pressure and slight improvement of clinical intelligence scale and motor scale. Before ventriculoperitoneal shunt, the FA values (except the right FHLV) were significantly decreased and the ADC values were significantly increased in the patients with hydrocephalus, compared with the controls. After the ventriculoperitoneal shunt, the FA values in the FHLV and OHLV of the patients were similar to the controls, but the FA values in other ROIs were still significantly lower than controls. The ADC values in the FS and OS white matter areas of the patients were similar to the controls; however, the ADC values in other ROIs were still significantly higher in patients.The increase of FA and the reduction in ADC in the ROIs preceded the clinical function improvement in patients with high intracranial pressure hydrocephalus and reflected the early changes in brain tissue microstructure, such as the compression of the white matter areas in the ROIs.

Radiomic Texture Analysis Mapping Predicts Areas of True Functional MRI Activity

Individual analysis of functional Magnetic Resonance Imaging (fMRI) scans requires user-adjustment of the statistical threshold in order to maximize true functional activity and eliminate false positives. In this study, we propose a novel technique that uses radiomic texture analysis (TA) features associated with heterogeneity to predict areas of true functional activity. Scans of 15 right-handed healthy volunteers were analyzed using SPM8. The resulting functional maps were thresholded to optimize visualization of language areas, resulting in 116 regions of interests (ROIs). A board-certified neuroradiologist classified different ROIs into Expected (E) and Non-Expected (NE) based on their anatomical locations. TA was performed using the mean Echo-Planner Imaging (EPI) volume, and 20 rotation-invariant texture features were obtained for each ROI. Using forward stepwise logistic regression, we built a predictive model that discriminated between E and NE areas of functional activity, with a cross-validation AUC and success rate of 79.84% and 80.19% respectively (specificity/sensitivity of 78.34%/82.61%). This study found that radiomic TA of fMRI scans may allow for determination of areas of true functional activity, and thus eliminate clinician bias.