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Biomedical subjects

K R Castleman

Publications and source records attributed to K R Castleman.

At least 19 recordsLinked to original sources
PubMed2000

Classification accuracy in multiple color fluorescence imaging microscopy.

BACKGROUND: The discriminatory power and imaging efficiency of different multicolor FISH (M-FISH) analysis systems are key factors in obtaining accurate and reproducible classification results. In a recent paper, Garini et al. put forth an analytical technique to quantify the discriminatory power ("S/N ratio") and imaging efficiency ('excitation efficiency') of multicolor fluorescent karyotyping systems. METHODS: A parametric model of multicolor fluorescence microscopy, based on the Beer-Lambert law, is analyzed and reduced to a simple expression for S/N ratio. Parameters for individual system configurations are then plugged into the model for comparison purposes. RESULTS: We found that several invalid assumptions, which are used to reduce the complex mathematics of the Beer-Lambert law to a simple S/N ratio, result in some completely misleading conclusions about classification accuracy. The authors omit the most significant noise source, and consider only one highly abstract and unrepresentative situation. Unwisely chosen parameters used in the examples lead to predictions that are not consistent with actual results. CONCLUSIONS: The earlier paper presents an inaccurate view of the M-FISH situation. In this short communication, we point out several inaccurate assumptions in the mathematical development of Garini et al. and the poor choices of parameters in their examples. We show results obtained with different imaging systems that indicate that reliable and comparable results are obtained if the metaphase samples are well-hybridized. We also conclude that so-called biochemical noise, not photon noise, is the primary factor that limits pixel classification accuracy, given reasonable exposure times.

Chromosomes↗
PubMed1998

Image enhancement improves reading performance in age-related macular degeneration patients.

We wanted to determine whether the 2- to 4-fold increases in reading speed found for patients with age-related macular degeneration (ARMD) when reading filtered text, presented one word at a time in the middle of the display would also be found when filtered text was scrolled across the screen. Reading speeds for filtered text that compensates for an observer's reduced contrast sensitivity function (CSF) were compared with the reading speeds for unfiltered text, when continuous, non-repeating text was scrolled across the display. The reading speeds of the ARMD observers tested were 1.7-4.5-times faster when reading filtered text, than when reading unfiltered text that was scrolled across the screen. The largest increments, over a 4-fold increase, were obtained in those subjects with the lowest unfiltered reading rates and the greatest loss of central vision. This study illustrates the usefulness of individualized text filtering for image enhancement in digitally based viewing devices to provide low vision remediation.

Aged↗
PubMed1998

Concepts in imaging and microscopy: color image processing for microscopy.

Digital image analysis has long been applied to monochrome images from the light microscope. Using these techniques one can locate, measure, identify, and count the objects of interest in a microscope field of view. Since microscope images often contain color information of interest, it is now becoming more common to analyze the spectral content of images as well. Although most of the digital imaging techniques developed for monochrome microscopy work well with color images, there are a few considerations specific to the analysis of multispectral imagery. These include obtaining a properly balanced multicolor digital image, specifying the color components of the image, and compensating for imperfect separation among the color channels.

Color↗
PubMed1997

Automated biodosimetry using digital image analysis of fluorescence in situ hybridization specimens.

Fluorescence in situ hybridization (FISH) of metaphase chromosome spreads is valuable for monitoring the radiation dose to circulating lymphocytes. At low dose levels, the number of cells that must be examined to estimate aberration frequencies is quite large. An automated microscope that can perform this analysis autonomously on suitably prepared specimens promises to make practical the large-scale studies that will be required for biodosimetry in the future. This paper describes such an instrument that is currently under development. We use metaphase specimens in which the five largest chromosomes have been hybridized with different-colored whole-chromosome painting probes. An automated multiband fluorescence microscope locates the spreads and counts the number of chromosome components of each color. Digital image analysis is used to locate and isolate the cells, count chromosome components, and estimate the proportions of abnormal cells. Cells exhibiting more than two chromosomal fragments in any color correspond to a clastogenic event. These automatically derived counts are corrected for statistical bias and used to estimate the overall rate of chromosome breakage. Overlap of fluorophore emission spectra prohibits isolation of the different chromosomes into separate color channels. Image processing effectively isolates each fluorophore to a single monochrome image, simplifying the task of counting chromosome fragments and reducing the error in the algorithm. Using proportion estimation, we remove the bias introduced by counting errors, leaving accuracy restricted by sample size considerations alone.

Automation↗
PubMed1993

Effect of random abnormal cell proportion on specimen classifier performance.

A series of papers had analyzed a simplified model of an automated cytology prescreening configuration consisting of a two-class cell classifier followed by a two-class specimen classifier. This has shown, among other things, that the proportion (p) of abnormal cells on an abnormal specimen dictates the number (N) of cells that must be classified before the specimen can be classified with specified accuracy (Anal Quant Cytol, 2:117-122, 1980). It has also shown that if a system designed assuming one fixed value, po, encounters a specimen with a different fixed value, p, then the specimen classifier false negative rate will deviate significantly from the design value, increasing for p < po and vice versa (Cytometry, 2: 155-158, 1981). Using a Gaussian approximation, Timmers and Gelsema (Cytometry, 6:22-25, 1985) extended this to the case where p is a Beta-distributed random variable. They showed that N increases dramatically with the width (coefficient of variation) of the distribution of p. They also concluded that the randomness of p imposes a fundamental lower limit on the specimen false negative rate below which it is impossible to go, even with an error-free cell classifier. In this paper we also extend the basic model to cover the case of random p, but by using an asymptotic expansion (rather than the Gaussian approximation), to develop an expression for N. We show that the limit cited by Timmers and Gelsema is not real, but is actually an artifact of the breakdown of the Gaussian approximation.(ABSTRACT TRUNCATED AT 250 WORDS)

Cell Size↗
PubMed1992

The PSI automatic metaphase finder.

The Genetiscanner automatic metaphase finder (AMF) instrument manufactured by Perceptive Scientific Instruments, Inc. is capable of searching a microscope slide and generating a list of the stage coordinates of the metaphases within the 20 mm x 40 mm search area in ten minutes. It can process a cassette load of sixty slides in approximately ten hours, ranking the metaphases according to six categories of quality. It uses a robot arm to load and unload slides from a 60-slide cassette onto an automated microscope stage. It searches at approximately 1.5 sq. mm per second and uses automatic focus to keep the image sharp during the search. On good quality blood slides it detects greater than 80% of the metaphases with greater than 80% ranking accuracy and less than 20% false positives. It can also search amniotic fluid, bone marrow and mammalian cell culture metaphase preparations. The pattern recognition algorithms use classifiers specifically trained for each specimen type, and for the rejection of non-metaphase material. Such units have been in continuous operation for up to two years with good performance and reliability.

Cytogenetics↗
PubMed1988

Canonical analysis of cells in normal and abnormal cervical smears.

Over 4,000 cells from 105 normal and 96 abnormal uterine cervical scrapes were prepared according to the UCLA monolayer procedure, stained by a routine Papanicolaou method and visually classified by two cytopathologists and a technologist into seven classes: parabasal, metaplastic, mild dysplasia, moderate dysplasia, severe dysplasia, carcinoma in situ and invasive carcinoma. Canonical analysis was used to correlate effects-coded class membership variables with 23 cell features derived from digital image analysis. In general, nuclear texture measures derived from linear combinations of run-length correlations along with features derived from a Markov transitional probability matrix provided the best predictors of cell class. After cells were divided into benign (moderate dysplasia or less) and malignant (severe dysplasia or worse) groups, discriminant analysis correctly classified 84% of the benign cells and 91% of the malignant cells.

Cell Nucleus↗
PubMed1985

Quantitative histochemical determination of muscle enzymes: biochemical verification.

We established quantitative histochemical assays for the enzymatic activity of succinate dehydrogenase and alpha-glycerol phosphate dehydrogenase for cat skeletal muscle. A computer-enhanced image analysis system was used to quantitate the histochemical enzyme-activity reaction products. We describe a series of experiments that verify the reliability and validity of the assays. Histochemically determined enzyme activities were linear with respect to tissue thickness and reaction time. Biochemically determined enzyme activities were also linear with respect to tissue thickness and incubation time. Consecutive tissue sections, assayed either histochemically or biochemically, were used to establish a linear regression equation that allowed quantitative histochemically determined reaction rates, measured in optical density per minute, to be calibrated as nanomoles per minute.

Animals↗
PubMed1984

Cytomorphometric differences among individual "moderate dysplasia" cells derived from cervical intraepithelial neoplasia.

Individual abnormal cervical epithelial cells can be categorized either by the lesion from which they are derived or by their unique cytologic characteristics. In building a data base for image analysis of cervical epithelial cells, categories of cells were defined according to distinct cytomorphologic characteristics, without knowledge of the lesion of origin. The three individual scorers, two cytopathologists and one senior cytotechnologist, most frequently agreed upon the cells classified as "moderate dysplasia." The measurements of digitized cells in this category had the smallest confidence intervals of any of the abnormal cell categories. For these two reasons, as well as the ubiquitous nature of "moderate dysplasia" cells in smears obtained from all patients with cervical epithelial neoplasia, cells in this category were studied in greater detail. Significant differences were noted in cell measurements among cells in this class when the cells came from patients with different grades of cervical neoplasia. The findings indicate that visually similar "moderate dysplasia" cells can be separated by digitized measurements into clusters dependent upon the parent lesion. The biologic implications are not yet clear, but such findings suggest that each disease is perhaps a committed lesion from inception. Therefore, predictability of ultimate outcome could be based on image analysis of cells derived from early cervical lesions, which would allow therapy to be performed on a more logical basis.

Carcinoma in Situ↗
PubMed1983

The effect of filtration on the loss of abnormal cervical cells in specimen preparation for automated cytology.

The UCLA monolayer procedure is used to produce a preparation of cervical epithelial cells for automated cytology. We investigated the nylon mesh filtration step of the procedure to determine if it altered the proportion of abnormal epithelial cells in the specimen. The proportion of such cells was found to be significantly lower (P less than 0.05) in the final specimen retained by a 10 micron nylon mesh filter than in the filtrate, which has been routinely discarded in our studies. The filtrate specimen is contaminated by large numbers of polymorphonuclear leukocytes, however, making it unusable for automated cytology at present. The implications of our findings for the cost effectiveness of classifier performance are considered, and the implications of the results for further improvements in specimen preparation are discussed.

Cell Separation↗
PubMed1982

An expanded cervical cell classification system validated by automated measurements.

The commonly used nomenclature for classifying cervical cells was expanded to include more classes, reflecting finer gradations of disease-related morphologic changes. Using a set of subjective visual criteria developed for this purpose, we visually classified 7,000 randomly selected cells and then subjected them to morphologic measurement by digital image analysis. Several of the measurements showed statistically significant differences among all the cell classes, indicating that it is possible to distinguish the finer morphologic gradations incorporated in the new system of cell classes. These same measurements showed a continuous trend of change from class to class along the scale from borderline dysplasia to carcinoma. This is consistent with the notion of a continuous progression of disease development. Finally, we found that those measurements that reflect the visual criteria used in the manual classification were significantly different between classes, indicating that the computer system can successfully quantify many of the important visual criteria.

Cell Nucleus↗
PubMed1981

The effect of abnormal cell proportion on specimen classifier performance.

In two previous papers we developed formulas relating the performance (error rates) of a two-class specimen classifier to the performance of a preceding two-class classifier and the number of cells examined (K. R. Castleman and B. S. White, Analytical and Quantitative Cytology 2:117, 1980 and K. R. Castleman and B. S. White, Cytometry 1:156, 1980.). This analysis assumed a certain proportion (p) of abnormal cells on an abnormal specimen. In this paper we examine what happens when a system designed assuming one value of p is presented with a positive specimen having a different abnormal cell proportion. We show that the specimen false negative error rate increases dramatically as p decreases below the design value, and conversely. This suggests that the specimen classification performance of a particular system should be quoted only with reference to the abnormal cell proportion of the specimens used for testing.

Cell Separation↗
PubMed1981

Skeletal muscle properties and performance in elite female track athletes.

Selected biochemical and physiological properties of skeletal muscle were studied in light of performance capabilities in 24 elite female track athletes. The feasibility of quantifying end point histochemistry and relating oxidative staining density (reduced nicotinomide adenine dinucleotide diaphorase: NADH-D) to whole body maximal oxygen consumption (VO2 max) was also investigated, while muscle fiber types, classified according to alkaline APTase stains, were studied and related to muscle oxidative capacity (succinate dehydrogenase: SDH), VO2 max and "in vivo" torque-velocity properties. Muscle biopsies were taken from the vastus lateralis of each subject and maximal knee extensor torques were recorded at 30 degrees from full extension at four selected velocities. While results confirm earlier reports on skeletal muscle properties and performance it was concluded that end point histochemistry could be reliably quantified and that an "oxidative" stain such as NADH-D correlates extremely well with VO2 max (r = 0.86, p less than 0.001) whereas correlations between % slow twitch fibres (Alkaline ATPase stain) and VO2 max were lower (r = 0.44, p less than 0.05). Additionally, as knee extension velocity increased from 0-1.7 rad x s-1 angle specific extensor torque production did not decline as observed in vitro and pentathletes displayed significantly larger torques at all velocities when compared to the other athletes. These data confirm that while myofibrillar ATPase staining correlates with force-velocity properties of muscle, VO2 max is better correlated with quantified oxidative staining.

Adenosine Triphosphatases↗
PubMed1980

The tradeoff of cell classifier error rates.

In gynecologic cytodiagnosis it is generally agreed that specimen false negative errors are more serious than false positives. When classifying individual cells, however, it is not obvious how one should adjust the parameters that control the two cell error rates. In the case where a specimen classifier follows a cell classifier, one can calculate the sample size required to achieve specified overall performance. This analysis shows that for the small abnormal cell proportions encountered in cervical cytology, cell false positives should be kept so low that a substantial portion of the abnormal cells are missed.

Cervix Uteri↗
PubMed1980

Optimizing cervical cell classifiers.

In an automated prescreening system where a cell classifier and a specimen classifier operate in cascade, the false-positive and false-negative error rates of each classifier can be traded off to obtain the best overall performance. It is usually desirable to keep the specimen false-negative rate below the false-positive rate. An analysis of the classifier cascade shows that, in contrast, the cell classifier should have its false-positive rate much lower than its false-negative rate. A procedure is presented for selecting the best operating point on the ROC curve of the cell classifier. This minimizes the sample size required to achieve prescribed specimen error rates.

Cells↗