Development of a test grid using Eye Movement Perimetry for screening glaucomatous visual field defects.

BACKGROUND: Eye Movement Perimetry (EMP) uses Saccadic Eye Movement (SEM) responses for visual field evaluation. Previous studies have demonstrated significant delay in initiation of SEMs among glaucoma patients in comparison with healthy subjects. The aim of the current study was to develop an EMP-based screening grid to identify glaucomatous visual field defects. METHODS: An interactive test consisting of 36 locations and two stimulus contrasts (162 cd/m2 and 190 cd/m2 on a background of 140 cd/m2) was evaluated in 54 healthy subjects and 50 primary glaucoma patients. Each subject was presented a central fixation target combined with the random projection of Goldmann size III peripheral targets. Instructions were given to look at each peripheral target on detection and then re-fixate at the central fixation target while the saccades were assessed using an eye tracker. From each seen peripheral target, the Saccadic Reaction Time (SRT) was calculated for contrast level 162 cd/ m2. These values were used to plot Receiver Operating Characteristic (ROC) curves for each test locations and the Area Under the Curve (AUC) values were used to identify the locations with highest susceptibility to glaucomatous damage. Each stimulus location with an AUC less than 0.75 along with its mirrored test location around the horizontal axis were eliminated from the grid. RESULTS: The mean age was 48.1 ± 16.6 years and 50.0 ± 14.5 years for healthy subjects and glaucoma patients respectively. A significant increase of SRT values by 76.5% (p < 0.001) was found in glaucoma patients in comparison with the healthy subjects. From the ROC analysis, ten out of 36 locations meeting the cut-off criteria of AUC were eliminated resulting in a new grid containing 26 test locations. SRT values were significantly different (p < 0.05) between the healthy subjects and glaucoma irrespective of the grids used. CONCLUSIONS: The present study resulted in a screening grid consisting of 26 locations predominantly testing nasal, superior and inferior areas of the visual field. An internal validation of the modified grid showed 90.4% of screening accuracy which makes it a potential approach for population based glaucoma screening.

Modeling the resiliency of energy-efficient retrofits in low-income multifamily housing.

Residential energy efficiency and ventilation retrofits (eg, building weatherization, local exhaust ventilation, HVAC filtration) can influence indoor air quality (IAQ) and occupant health, but these measures' impact varies by occupant activity. In this study, we used the multizone airflow and IAQ analysis program CONTAM to simulate the impacts of energy retrofits on indoor concentrations of PM2.5 and NO2 in a low-income multifamily housing complex in Boston, Massachusetts (USA). We evaluated the differential impact of residential activities, such as low- and high-emission cooking, cigarette smoking, and window opening, on IAQ across two seasons. We found that a comprehensive package of energy and ventilation retrofits was resilient to a range of occupant activities, while less holistic approaches without ventilation improvements led to increases in indoor PM2.5 or NO2 for some populations. In general, homes with simulated concentration increases included those with heavy cooking and no local exhaust ventilation, and smoking homes without HVAC filtration. Our analytical framework can be used to identify energy-efficient home interventions with indoor retrofit resiliency (ie, those that provide IAQ benefits regardless of occupant activity), as well as less resilient retrofits that can be coupled with behavioral interventions (eg, smoking cessation) to provide cost-effective, widespread benefits.

The Effect of Cataract on Eye Movement Perimetry.

Purpose. To determine how different grades of cataract affect sensitivity threshold and saccadic reaction time (SRT) in eye movement perimetry (EMP). Methods. In EMP, the visual field is tested by assessing the saccades that a subject makes towards peripheral stimuli using an eye tracker. Forty-eight cataract patients underwent pre- and postoperative EMP examination in both eyes. The subjects had to fix a central stimulus presented on the eye tracker monitor and to look at any detected peripheral stimulus upon its appearance. A multilevel mixed model was used to determine the factors that affected the sensitivity threshold and the SRT as a function of cataract grade. Results. We found no effect of cataract severity (LOCS III grades I through IV) on SRT and the sensitivity thresholds. In cataract of LOCS III grade V, however, we found an increase by 27% and 21% (p < 0.001), respectively, compared to the SRT and the sensitivity threshold in LOCS III grade I. Eyes that underwent cataract surgery showed no change in mean SRTs and sensitivity thresholds after surgery in LOCS III grade IV and lower. Conclusion. The present study shows that EMP can be readily used in patients with cataract with LOCS III grade IV and below.

Depth-resolved model-based reconstruction of attenuation coefficients in optical coherence tomography.

We present a method, based on a single scattering model, to calculate the attenuation coefficient of each pixel in optical coherence tomography (OCT) depth profiles. Numerical simulations were used to determine the model's response to different depths and attenuation coefficients. Experiments were performed on uniform and layered phantoms with varying attenuation coefficients. They were measured by a 1300 nm OCT system and their attenuation coefficients were evaluated by our proposed method and by fitting the OCT slope as the gold standard. Both methods showed largely consistent results for the uniform phantoms. On the layered phantom, only our proposed method accurately estimated the attenuation coefficients. For all phantoms, the proposed method largely reduced the variability of the estimated attenuation coefficients. The method was illustrated on an in-vivo retinal OCT scan, effectively removing common imaging artifacts such as shadowing. By providing localized, per-pixel attenuation coefficients, this method enables tissue characterization based on attenuation coefficient estimates from OCT data.

Event-based progression detection strategies using scanning laser polarimetry images of the human retina.

Monitoring glaucoma patients and ensuring optimal treatment requires accurate and precise detection of progression. Many glaucomatous progression detection strategies may be formulated for Scanning Laser Polarimetry (SLP) data of the local nerve fiber thickness. In this paper, several strategies, all based on repeated GDx VCC SLP measurements, are tested to identify the optimal one for clinical use. The parameters of the methods were adapted to yield a set specificity of 97.5% on real image series. For a fixed sensitivity of 90%, the minimally detectable loss was subsequently determined for both localized and diffuse loss. Due to the large size of the required data set, a previously described simulation method was used for assessing the minimally detectable loss. The optimal strategy was identified and was based on two baseline visits and two follow-up visits, requiring two-out-of-four positive tests. Its associated minimally detectable loss was 5-12 µm, depending on the reproducibility of the measurements.

Automated segmentation by pixel classification of retinal layers in ophthalmic OCT images.

Current OCT devices provide three-dimensional (3D) in-vivo images of the human retina. The resulting very large data sets are difficult to manually assess. Automated segmentation is required to automatically process the data and produce images that are clinically useful and easy to interpret. In this paper, we present a method to segment the retinal layers in these images. Instead of using complex heuristics to define each layer, simple features are defined and machine learning classifiers are trained based on manually labeled examples. When applied to new data, these classifiers produce labels for every pixel. After regularization of the 3D labeled volume to produce a surface, this results in consistent, three-dimensionally segmented layers that match known retinal morphology. Six labels were defined, corresponding to the following layers: Vitreous, retinal nerve fiber layer (RNFL), ganglion cell layer & inner plexiform layer, inner nuclear layer & outer plexiform layer, photoreceptors & retinal pigment epithelium and choroid. For both normal and glaucomatous eyes that were imaged with a Spectralis (Heidelberg Engineering) OCT system, the five resulting interfaces were compared between automatic and manual segmentation. RMS errors for the top and bottom of the retina were between 4 and 6 µm, while the errors for intra-retinal interfaces were between 6 and 15 µm. The resulting total retinal thickness maps corresponded with known retinal morphology. RNFL thickness maps were compared to GDx (Carl Zeiss Meditec) thickness maps. Both maps were mostly consistent but local defects were better visualized in OCT-derived thickness maps.

Split bundle detection in polarimetric images of the human retinal nerve fiber layer.

OBJECTIVES: One method for assessing pathological retinal nerve fiber layer (NFL) appearance is by comparing the NFL to normative values, derived from healthy subjects. These normative values will be more specific when normal physiological differences are taken into account. One common variation is a split bundle. This paper describes a method to automatically detect these split bundles. METHODS: The thickness profile along the NFL bundle is described by a non-split and a split bundle model. Based on these two fits, statistics are derived and used as features for two non-parametric classifiers (Parzen density based and k nearest neighbor). Features were selected by forward feature selection. Three hundred and nine superior and 324 inferior bundles were used to train and test this method. RESULTS: The prevalence of split superior bundles was 68% and the split inferior bundles' prevalence was 13%. The resulting estimated error of the Parzen density- based classifier was 12.5% for the superior bundle and 10.2% for the inferior bundle. The k nearest neighbor classifier errors were 11.7% and 9.2%. CONCLUSIONS: The classification error of automated detection of split inferior bundles is not much smaller than its prevalence, thereby limiting the usefulness of separate cut-off values for split and non-split inferior bundles. For superior bundles, however, the classification error was low compared to the prevalence. Application of specific cut-off values, selected by the proposed classification system, may therefore increase the specificity and sensitivity of pathological NFL detection.

Shaving diffusion tensor images in discriminant analysis: a study into schizophrenia.

A technique called 'shaving' is introduced to automatically extract the combination of relevant image regions in a comparative study. No hypothesis is needed, as in conventional pre-defined or expert selected region of interest (ROI)-analysis. In contrast to traditional voxel based analysis (VBA), correlations within the data can be modeled using principal component analysis (PCA) and linear discriminant analysis (LDA). A study into schizophrenia using diffusion tensor imaging (DTI) serves as an application. Conventional VBA found a decreased fractional anisotropy (FA) in a part of the genu of the corpus callosum and an increased FA in larger parts of white matter. The proposed method reproduced the decrease in FA in the corpus callosum and found an increase in the posterior limb of the internal capsule and uncinate fasciculus. A correlation between the decrease in the corpus callosum and the increase in the uncinate fasciculus was demonstrated.

Automated detection of wedge-shaped defects in polarimetric images of the retinal nerve fibre layer.

PURPOSE: Automated glaucoma detection in images obtained by scanning laser polarimetry is currently insensitive to local abnormalities, impairing its performance. The purpose of this investigation was to test and validate a recently proposed algorithm for detecting wedge-shaped defects. METHODS: In all, 31 eyes of healthy subjects and 37 eyes of glaucoma patients were imaged with a GDx. Each image was classified by two experts in one of four classes, depending on how clear any wedge could be identified. The detection algorithm itself aimed at detecting and combining the edges of the wedge. The performance of both the experts and the algorithm were evaluated. RESULTS: The interobserver correlation, expressed as ICC(3,1), was 0.77. For the clearest cases, the algorithm yielded a sensitivity of 80% at a specificity of 93%, with an area under the ROC of 0.95. Including less obvious cases by the experts resulted in a sensitivity of 55% at a specificity of 95%, with an area under the ROC of 0.89. CONCLUSIONS: It is possible to automatically detect many wedge-shaped defects at a fairly low rate of false-positives. Any detected wedge defect is presented in a user-friendly way, which may assist the clinician in making a diagnosis.

A model based method for retinal blood vessel detection.

Retinal blood vessels are important structures in ophthalmological images. Many detection methods are available, but the results are not always satisfactory. In this paper, we present a novel model based method for blood vessel detection in retinal images. It is based on a Laplace and thresholding segmentation step, followed by a classification step to improve performance. The last step assures incorporation of the inner part of large vessels with specular reflection. The method gives a sensitivity of 92% with a specificity of 91%. The method can be optimized for the specific properties of the blood vessels in the image and it allows for detection of vessels that appear to be split due to specular reflection.

Detecting glaucomatous wedge shaped defects in polarimetric images.

Wedge shaped defects of the retinal nerve fiber layer (RNFL) may occur in glaucoma. Currently, automatic detection of wedge shaped defects in Scanning Laser Polarimetry (SLP) images of the RNFL is not available. An automatic classification is currently based only on global parameters, thereby ignoring important local information. Our method works by a modified dynamic programming technique that searches for locally strong edges with a preference for straight edges. These edges are initially classified based on their strength and next combined into wedge shaped defects. Our method yields a sensitivity of 73% and a specificity of 90% on a limited set of 65 images.

Effect of bacterial filters on spirometry measurements.

Lung function measurements with and without a disposable bacterial filter were compared in 60 children. Although statistically significant, the reduction of lung function measurements caused by using bacterial filters was small and clinically irrelevant (2-4% of predicted for forced expiratory volume in one second and vital capacity).