Introduction: The orbital subarachnoid space surrounding the optic nerve is continuous with the circulation system for cerebrospinal fluid (CSF) and can be visualized by using magnetic resonance imaging (MRI). We hypothesized that the orbital subarachnoid space width (OSASW) is correlated with and can serve as a surrogate for intracranial pressure (ICP). Our aim was to develop a method for a noninvasive measurement of the intracranial CSF-pressure (CSF-P) based on MRI-assisted OSASW. Methods: The prospective observational comparative study included neurology patients who underwent lumbar CSF-P measurement and 3.0-Tesla orbital magnetic resonance imaging (MRI) for other clinical reasons. The width of the orbital subarachnoid space (OSASW) around the optic nerve was measured with MRI at 3, 9, and 15 mm behind the globe. The study population was randomly divided into a training group and a test group. After adjusting for body mass index (BMI) and mean arterial blood pressure (MABP), algorithms for the associations between CSF-P and OSASW were calculated in the training group. The algorithms were subsequently verified in the test group. Main outcome measures were the width of the orbital subarachnoid space (OSASW) and the lumbar cerebrospinal fluid pressure (CSF-P). Results: Seventy-two patients were included in the study. In the training group, the algorithms for the associations between CSF-P and OSASW were as follows: (a) CSF-P = 9.31 × OSASW (at 3 mm) + 0.48 × BMI + 0.14 × MABP-19.94; (b) CSF-P = 16.95 × OSASW (at 9 mm) + 0.39 × BMI + 0.14 × MABP-20.90; and (c) CSF-P = 17.54 × OSASW (at 15 mm) + 0.47 × BMI + 0.13 × MABP-21.52. Applying these algorithms in the independent test group, the measured lumbar CSF-P (13.6 ± 5.1 mm Hg) did not differ significantly from the calculated MRI-derived CSF-P (OSASW at 3 mm: 12.7 ± 4.2 mm Hg (P = 0.07); at 9 mm: 13.4 ± 5.1 mm Hg (P = 0.35); and at 15 mm: 14.0 ± 4.9 mm Hg (P = 0.87)). Intraclass correlation coefficients (ICCs) were higher for the CSF-P assessment based on OSASW at 9 mm and at 15 mm behind the globe (all ICCs, 0.87) than for OSASW measurements at 3 mm (ICC, 0.80). Conclusions: In patients with normal, moderately decreased or elevated ICP, MRI-assisted measurement of the OSASW appears to be useful for the noninvasive quantitative estimation of ICP, if BMI and MABP as contributing parameters are taken into account. Trial registration: Clinical trial registered with the Chinese Clinical Trial Registry: ChiCTR-OCC-11001271

Glaucoma is not only an eye disease but is also associated with degeneration of brain structures. We now investigated the pattern of visual and non-visual brain structural changes in 25 primary open angle glaucoma (POAG) patients and 25 age-gender-matched normal controls using T1-weighted imaging. MRI images were subjected to volume-based analysis (VBA) and surface-based analysis (SBA) in the whole brain as well as ROI-based analysis of the lateral geniculate nucleus (LGN), visual cortex (V1/2), amygdala and hippocampus. While VBA showed no significant differences in the gray matter volumes of patients, SBA revealed significantly reduced cortical thickness in the right frontal pole and ROI-based analysis volume shrinkage in LGN bilaterally, right V1 and left amygdala. Structural abnormalities were correlated with clinical parameters in a subset of the patients revealing that the left LGN volume was negatively correlated with bilateral cup-to-disk ratio (CDR), the right LGN volume was positively correlated with the mean deviation of the right visual hemifield and the right V1 cortical thickness was negatively correlated with the right CDR in glaucoma. These results demonstrate that POAG affects both vision-related structures and non-visual cortical regions. Moreover, alterations of the brain visual structures reflect the clinical severity of glaucoma.

Purpose.: To analyze the altered amplitude of low-frequency fluctuation (ALFF) of the brain using resting-state functional magnetic resonance imaging (fMRI) in patients with primary open-angle glaucoma (POAG). Methods.: Resting-state fMRI was conducted in 21 POAG patients and 22 age-matched healthy control subjects. After the ALFF and fractional amplitude of low-frequency fluctuation (fALFF) for slow 4 and slow 5 bands were calculated, the results between POAG patients and healthy controls were compared. Then the correlations between ALFF/fALFF values and the disease stage of POAG were analyzed. Results.: Compared with controls, POAG patients showed significantly decreased ALFF/fALFF values in the visual cortices, posterior regions of the default-mode network (DMN), and motor and sensory cortices. Meanwhile, ALFF/fALFF values in the prefrontal cortex, left superior temporal gyrus (STG), right middle cingulate cortex (MCC), and left inferior parietal lobule (IPL) significantly increased in POAG patients. Hodapp-Anderson-Parrish (HAP) score for POAG was positively correlated with ALFF values of the right superior frontal gyrus (SFG) and negatively correlated with that of the left cuneus. For the slow 5 band, the fALFF values of the bilateral middle temporal gyri (MTG) of POAG patients were negatively correlated with HAP score. Conclusions.: Primary open-angle glaucoma is a neurodegenerative disease involving multiple brain regions, including the visual cortices, DMN, limbic system, and motor and sensory networks. Moreover, the alterations in some of these networks are correlated with the progression of POAG; for the abnormal spontaneous neural activities in the left cuneus, bilateral MTG and right prefrontal cortex are correlated with glaucoma severity.

Objective It is important to distinguish between orbital cavernous haemangioma and schwannoma because the treatments of choice for the two tumours are different. The aim was to evaluate MR imaging findings distinguishing the two tumours. Methods Magnetic resonance imaging including T1- and T2-weighted imaging and contrast-enhanced MR imaging was performed in 43 patients with cavernous haemangiomas and 16 patients with schwannomas confirmed by pathology. Location, configuration, margins, signal intensity, homogeneity and enhancement pattern of the tumour were retrospectively evaluated. Results There was a significant difference between cavernous haemangiomas and schwannomas regarding the location, configuration and margins of the mass, signal intensity and homogeneity on T1- and T2-weighted imaging, the spread pattern of contrast enhancement, the enhancement pattern and the type of time–intensity curve (P < 0.05). Markedly homogeneous hyperintensity signal on T2-weighted imaging and the spread pattern of the contrast enhancement favoured cavernous haemangioma rather than schwannoma (P < 0.01). Conclusion Cavernous haemangiomas and schwannomas have different MR imaging features that could be helpful in the differentiation between the tumours. The spread pattern of the contrast enhancement on dynamic contrast-enhanced MR imaging is the most reliable finding distinguishing cavernous haemangiomas from schwannomas.