Determination of the unit size of the corneal endothelial cell mosaic from Fourier component image analysis.

Scanning electron micrographs were taken of the central region of the corneal endothelium of cows (Holstein). The cells were outlined and an image overlay generated of approximately 100 cells. Via a Windows-based scanning system, the overlay was subjected to a two-dimensional Fourier transform on a Unix-based system. A custom algorithm was developed (IRIS) to sequentially analyse the Fourier transform pattern. The transform and resultant harmonics spectrum were compared to those obtained from artificial cell mosaics generated from uniform sized symmetrical hexagons. The position, width, and height of the 1st harmonic component of the frequency distribution appears to be derived from average cell-cell border distances across the image. The radial position of the 1st harmonic is inversely related to the unit cell size in the mosaic, i.e. the dominant cell size. The application of such techniques to cell mosaic analyses is discussed.

A program for analyzing the morphological organization of tessellated cellular mosaics.

We have constructed a computer program that allows sequential sets of data from tessellated cellular mosaics to be evaluated such that the presence and position of abnormal cells in the mosaic can be easily, quickly, and quantitatively identified. Conventional parametric analysis of the global morphological organization of large tessellated cellular mosaics does not provide the necessary granularity of analysis to allow for rapid identification of such atypical cellular structures. Our program, written in C using structured programming techniques, provides the needed analytical granularity for detailed studies of subsections of large cellular mosaics, while also providing conventional statistical evaluation of the data set. The architecture of the program is modular and designed as a set of procedures and subprocessess that can either analyze the entire mosaic or discrete sets of cells within the larger sample. The types of morphological heterogeneity (or dishomogeneity) that the program can investigate occur in a variety of biological mosaics where there is a continuum of the structural features, including fairly regular linear stacked arrays of cells or tissue partitions, to less regular mosaics of epithelial or endothelial cell layers, to heterogeneous patterns found on tissue surfaces, such as fluorescein dye-highlighted features on the human conjunctiva. The program has been used to successfully evaluate several different types of mosaics.

Impact of using weighted versus unweighted measures to assess optometry faculty productivity in research.

BACKGROUND: Activities in scholarship and research are commonly self-reported in terms of the number of publications per calendar year or grant-tenure period; individuals might show widely different productivities at different times but specific data on this do not appear to be available for optometry school faculty. METHODS: Using a data base generated from a 20-year activity period at an optometry school, the impact of calculating publication rate by self-reporting or weighted scaling (linear or exponential) according to co-authorship on such publications was assessed for each individual faculty member. RESULTS: Results are presented from a faculty productivity perspective on a calendar year basis or with the faculty members matched for seniority on a year-by-year basis. CONCLUSIONS: The use of weighted scaling to productivity assessment substantially reduced the net output from the faculty in most of the 20 years assessed. The average weighted productivity was generally close to two published articles (excluding book chapters) per year, per faculty member compared to close to three articles per year per faculty member, using self-reported unweighted data.

Identification of topographical variations in the sizes of cells in a monolayer--application to corneal endothelium.

The cells in the corneal endothelium, do not have a constant geometric arrangement but rather can be organized into widely different patterns or arrays. Conventional statistical analyses of variance in cell size can be used to report that the endothelial mosaic is homogeneous (homomegethous) or heterogeneous (polymegethous) but do not identify the source of the homogeneity or its loss. We present methods that allow for both identification and graphical presentation of regional homogeneity or heterogeneity in the endothelial cell monolayer. Single electron micrographs (containing 180 cells) were taken at the central region of the rabbit corneal endothelium and cell areas measured by planimetry. Special computer programs allow progressive evaluation of variance in all cell areas across the set of cells. Several examples are presented in detail to illustrate different degrees and types of variance for sets of endothelial cells that have small to extremely large ranges of areas (i.e. coefficient of variation values ranging from 0.12 to over 1.0). There also appears to be a mathematically predictable relationship between cell surface area and the number of cell sides. The methods developed should be applicable to quantitative comparisons of cells in monolayers or tissue sections.

Clinical low vision resource usage prediction.

In an era of increased demands and constrained budgets, it is necessary to make the best use of all available resources. This is difficult when specialized vision care, such as low vision clinical assessment, is involved because of the heterogeneity of the patient populations seen by such clinics. PURPOSE. This research attempts to discover if these diverse patient populations can be identified and clustered into groups based upon similarity of clinical resources use. Specifically, the inquiry examines the potential for a low vision patient resource utilization classification scheme at the Low Vision Clinic (LVC) in the Centre for Sight Enhancement (CSE), University of Waterloo. METHODS. From a sample of 99 patients consulting the LVC in a 3-month period, retrospective data collection involved abstracting and coding medical records containing information detailing each patient's demographic, diagnostic, therapeutic, and resource utilization characteristics. Cluster analysis using Hartigan's block clustering algorithm was then applied to the data. A replication study was completed using a sample of 99 patients visiting the LVC 1 year later. RESULTS. Patients can be classified into five iso-resource groups, hereby termed low vision patient resource groups (LVPRGs). The clusters represent a resource consistent and clinically coherent scheme for classifying low vision patients based upon resource requirements. As a measure of repeatability, the groups reemerged in the replication study. CONCLUSIONS. If the groupings demonstrate robustness in a field test, clustering algorithms in general, and LVPRGs in specific, may offer useful tools to enhance resource utilization in the LVC setting.