Roughness of retinal layers in Alzheimer's disease.

There is growing evidence that thinned retinal regions are interspersed with thickened regions in all retinal layers of patients with Alzheimer's disease (AD), causing roughness to appear on layer thickness maps. The hypothesis is that roughness of retinal layers, assessed by the fractal dimension (FD) of their thickness maps, is an early biomarker of AD. Ten retinal layers have been studied in macular volumes of optical coherence tomography from 24 healthy volunteers and 19 patients with mild AD (Mini-Mental State Examination 23.42 ± 3.11). Results show that FD of retinal layers is greater in the AD group, the differences being statistically significant (p < 0.05). Correlation of layer FD with cognitive score, visual acuity and age reach statistical significance at 7 layers. Nearly all (44 out of 45) FD correlations among layers are positive and half of them reached statistical significance (p < 0.05). Factor analysis unveiled two independent factors identified as the dysregulation of the choroidal vascular network and the retinal inflammatory process. Conclusions: surface roughness is a holistic feature of retinal layers that can be assessed by the FD of their thickness maps and it is an early biomarker of AD.

Spatial analysis of thickness changes in ten retinal layers of Alzheimer's disease patients based on optical coherence tomography.

The retina is an attractive source of biomarkers since it shares many features with the brain. Thickness differences in 10 retinal layers between 19 patients with mild Alzheimer's disease (AD) and a control group of 24 volunteers were investigated. Retinal layers were automatically segmented and their thickness at each scanned point was measured, corrected for tilt and spatially normalized. When the mean thickness of entire layers was compared between patients and controls, only the outer segment layer of patients showed statistically significant thinning. However, when the layers were compared point-by point, patients showed statistically significant thinning in irregular regions of total retina and nerve fiber, ganglion cell, inner plexiform, inner nuclear and outer segment layers. Our method, based on random field theory, provides a precise delimitation of regions where total retina and each of its layers show a statistically significant thinning in AD patients. All layers, except inner nuclear and outer segments, showed thickened regions. New analytic methods have shown that thinned regions are interspersed with thickened ones in all layers, except inner nuclear and outer segments. Across different layers we found a statistically significant trend of the thinned regions to overlap and of the thickened ones to avoid overlapping.

Occult Orbital Injury with Dagger Fragment with Resulting Pneumocephalus.

Penetrating injuries of the cranium are relatively uncommon, only 0.4% of all head injuries. In patients with disturbed conscious level, an extensive examination should be performed in the emergency unit to rule out transorbital penetrating brain injury. A 25-year-old male was attacked with a dagger. He presented with ethylic intoxication and the physical examination demonstrated a small skin injury on the lateral canthus of the left eye with a large periocular hematoma which prevented eyelid opening. Cranial CT scan showed a metallic intraorbital foreign body consisting of a fragment of a dagger which perforated the eyeball, and penetrated through the superomedial wall of the orbit into the anterior cranial fossa. Reconstruction of the eyeball was performed and the fragment was removed. Orbital injuries with a knife in situ are very unusual. Early identification and removal of retained foreign bodies are essential.

Three-Dimensional Reconstruction of the Bony Nasolacrimal Canal by Automated Segmentation of Computed Tomography Images.

OBJECTIVE: To apply a fully automated method to quantify the 3D structure of the bony nasolacrimal canal (NLC) from CT scans whereby the size and main morphometric characteristics of the canal can be determined. DESIGN: Cross-sectional study. SUBJECTS: 36 eyes of 18 healthy individuals. METHODS: Using software designed to detect the boundaries of the NLC on CT images, 36 NLC reconstructions were prepared. These reconstructions were then used to calculate NLC volume. The NLC axis in each case was determined according to a polygonal model and to 2nd, 3rd and 4th degree polynomials. From these models, NLC sectional areas and length were determined. For each variable, descriptive statistics and normality tests (Kolmogorov-Smirnov and Shapiro-Wilk) were established. MAIN OUTCOME MEASURES: Time for segmentation, NLC volume, axis, sectional areas and length. RESULTS: Mean processing time was around 30 seconds for segmenting each canal. All the variables generated were normally distributed. Measurements obtained using the four models polygonal, 2nd, 3rd and 4th degree polynomial, respectively, were: mean canal length 14.74, 14.3, 14.80, and 15.03 mm; mean sectional area 15.15, 11.77, 11.43, and 11.56 mm2; minimum sectional area 8.69, 7.62, 7.40, and 7.19 mm2; and mean depth of minimum sectional area (craniocaudal) 7.85, 7.71, 8.19, and 8.08 mm. CONCLUSION: The method proposed automatically reconstructs the NLC on CT scans. Using these reconstructions, morphometric measurements can be calculated from NLC axis estimates based on polygonal and 2nd, 3rd and 4th polynomial models.