Targeted superparamagnetic iron oxide (SPIO) nanoparticles have emerged as a promising biomarker detection tool for molecular magnetic resonance (MR) image diagnosis. To identify patients who could benefit from Epidermal growth factor receptor (EGFR)-targeted therapies, we introduce lipid-encapsulated SPIO nanoparticles and hypothesized that anti-EGFR antibody cetuximab conjugated of such nanoparticles can be used to identify EGFR-positive glioblastomas in non-invasive T2 MR image assays. The newly introduced lipid-coated SPIOs, which imitate biological cell surface and thus inherited innate nonfouling property, were utilized to reduce nonspecific binding to off-targeted cells and prevent agglomeration that commonly occurs in nanoparticles. The synthesized targeted EGFR-antibody-conjugated SPIO (EGFR-SPIO) nanoparticles were characterized using dynamic light scattering, zeta potential assays, gel electrophoresis mobility shift assays, transmission electron microscopy (TEM) images, and cell line affinity assays, and the results showed that the conjugation was successful. The targeting efficiency of the synthesized EGFR-SPIO nanoparticles was confirmed through Prussian blue staining and TEM images by using glioblastoma cell lines with high or low EGFR expression levels. The EGFR-SPIO nanoparticles preferentially targeted U-251 cells, which have high EGFR expression, and were internalized by cells in a prolonged incubation condition. Moreover, the T2 MR relaxation time of EGFR-SPIO nanoparticles could be used for successfully identifying glioblastoma cells with elevated EGFR expression in vitro and distinguishing U-251 cells from U-87MG cells, which have low EFGR expression. These findings reveal that the lipid-encapsulated EGFR-SPIO nanoparticles can specifically target cells with elevated EGFR expression in the three tested human glioblastoma cell lines. The results of this study can be used for noninvasive molecular MR image diagnosis in the future.

In addition to cerebellar degeneration symptoms, patients with spinocerebellar ataxia type 3 (SCA3) exhibit extensive involvements with damage in the prefrontal cortex. A network model has been proposed for investigating the structural organization and functional mechanisms of clinical brain disorders. For neural degenerative diseases, a cortical feature-based structural connectivity network can locate cortical atrophied regions and indicate how their connectivity and functions may change. The brain network of SCA3 has been minimally explored. In this study, we investigated this network by enrolling 48 patients with SCA3 and 48 healthy subjects. A novel three-dimensional fractal dimension-based network was proposed to detect differences in network parameters between the groups. Copula correlations and modular analysis were then employed to categorize and construct the structural networks. Patients with SCA3 exhibited significant lateralized atrophy in the left supratentorial regions and significantly lower modularity values. Their cerebellar regions were dissociated from higher-level brain networks, and demonstrated decreased intra-modular connectivity in all lobes, but increased inter-modular connectivity in the frontal and parietal lobes. Our results suggest that the brain networks of patients with SCA3 may be reorganized in these regions, with the introduction of certain compensatory mechanisms in the cerebral cortex to minimize their cognitive impairment syndrome.

Although changes in diffusion characteristics of the brain parenchyma in neurological disorders are widely studied and used in clinical practice, the change in diffusivity in the cerebrospinal fluid (CSF) system is rarely reported. In this study, free water diffusion in the subarachnoid cisterns and ventricles of the rat brain was examined using diffusion magnetic resonance imaging (MRI), and the effects of neurological disorders on diffusivity in CSF system were investigated. Diffusion MRI and T₂-weighted images were obtained in the intact rats, 24 h after ischemic stroke, and 50 days after mild traumatic brain injury (mTBI). We conducted the assessment of diffusivity in the rat brain in the subarachnoid cisterns around the midbrain, as well as the lateral ventricles. One-way ANOVA and Kruskal–Wallis test were used to evaluate the change in mean diffusivity (MD) and MD histogram, respectively, in CSF system following different neurological disease. A significant decrease in the mean MD value of the subarachnoid cisterns was observed in the stroke rats compared with the intact and mTBI rats (p < 0.005). In addition, the skewness (p < 0.002), maximum MD (p < 0.002), and MD percentiles (p < 0.002) in the stroke rats differed significantly from those in the intact and mTBI rats. By contrast, no difference was observed in the mean MD value of the lateral ventricles among three groups of rats. We proposed that the assessment of the subarachnoid cisterns, rather than the lateral ventricles, in the rat brain would be useful in providing diffusion information in the CSF system. Alterations in MD parameters of the subarachnoid cisterns after stroke provide evidence that brain injury may alter the characteristics of free water diffusion not only in the brain parenchyma but also in the CSF system.

Extraction of various perfusion components from dynamic-susceptibility-contrast (DSC) MR brain images is critical for the analysis of brain perfusion. According to the variation of temporal signal on different brain tissues, one can segment whole brain area into distinct blood supply patterns which are vital for the profound analysis of cerebral hemodynamics. In this study, independent component analysis (ICA) is used to project the perfusion image data into independent components from which each elucidated tissue cluster can be automatically segment out by using the hierarchical clustering (HC). Five normal subjects and a case of internal carotid artery stenosis subjects were analyzed. The results demonstrated that ICA-HC is effective in multi-tissue hemodynamic classification which improves differentiation of pathological and physiological hemodynamics.