Standardization of reagents and methods used in cytological and histological practice with emphasis on dyes, stains and chromogenic reagents

Lyon, H.; Leenheer, A.P. De; Horobin, Richard W.; Lambert, W. E.; Schulte, Erik; Liedekerke, B. Van; Wittekind, D

doi:10.1007/bf00158587

Cited by 44 publications

(29 citation statements)

References 53 publications

(21 reference statements)

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“…The DEP force acting on a cell in the vertical direction above a set of parallel electrodes can be approximated as F DEP = 2πɛ m ( r d ) 3 f CM AV 2 e −h /2πd (1) where V is the RMS value of the applied AC voltage, h is the height of the cell above the electrode plane, d is the periodicity of the parallel electrode elements, A is a constant pertaining to the electrode geometry (A=2.76 for a planar parallel electrode array), and ɛ m is the electrical permittivity of the buffer in which the cells are suspended. 18,19 This equation assumes that the cells experience dipolar forces and that higher order terms do not significantly affect cell levitation.…”

Section: Theorymentioning

confidence: 99%

“…It represents the average force seen by cells as they travel through the electric field profile which actually varies with cell position with respect to electrode edges and gaps. Although, in principle, DEP forces arise from either DC or alternating fields, equation (1) assumes that electrode polarization has a negligible impact on the field seen by the cells. This is typically satisfied for AC fields above about 20 kHz in frequency.The parameter f CM is the real part of the so-called Clausius-Mossotti factor, a dielectric parameter that reflects the properties of the cells and the characteristics of their suspending medium.…”

Section: Theorymentioning

confidence: 99%

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Dielectrophoretic Segregation of Different Human Cell Types on Microscope Slides

et al. 2005

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A new method for preparing cells for microscopic examination is presented in which cell mixtures are fractionated by dielectrophoretic forces and simultaneously collected into characteristic zones on slides. The method traps cells directly from the suspending medium onto the slide, reducing cell loss. Furthermore, it exploits differences in the dielectric properties of the cells, which sensitively reflect their morphology. Because different cell types are trapped in characteristic zones on the slide, the technique represents an advance over existing methods for slide preparation, such as centrifugation and smears where cells are randomly distributed. In particular, the new method should aid in the detection of rare and anomalous cell subpopulations that might otherwise go unnoticed against a high background of normal cells. As well as being suitable for traditional microscopic examination and automated slide scanning approaches, it is compatible with histochemical and immunochemical techniques, as well as emerging molecular and proteomic methods. This paper describes the rationale and design of this so-called electrosmear instrumentation and shows experimental results that verify the theory and applicability of the method with model cell lines and normal peripheral blood subpopulations. KeywordsSlide preparation; Dielectrophoresis; Cell separation; Cell discrimination; Microelectrodes Advances in cytological slide preparation techniques have facilitated the identification and characterization of different cell types and have improved the ease and accuracy of disease diagnosis. In particular, numerous staining procedures, including chemical dye-, 1 fluorescent-, 2 enzyme-linked-, 3 immunosensitive-, 4 and specific molecular-methods 5 have been developed. While these techniques allow target cells to be differentiated from other cell types, specimen screening efficiency depends on how well the pathologist discriminates target components such as bacteria, precancerous lesions or cancerous cells from background cells. In diseases characterized by the presence of extremely small numbers of marker cells against a background of large numbers of normal cells, identifying the randomly distributed target cells is tedious, time consuming, and prone to error. Recently, a number of instruments have been introduced that automatically scan slides and attempt to identify putative marker cells for later review by a pathologist. 6 These instruments are based on machine vision through a high quality microscope and they are expensive and relatively slow.

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Section: Theorymentioning

confidence: 99%

Section: Theorymentioning

confidence: 99%

Dielectrophoretic Segregation of Different Human Cell Types on Microscope Slides

et al. 2005

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“…Stain concentration, manufacturer, and batch effects affect the final appearance of a slide. 13 In addition, the specific whole slide scanner used to digitize a slide can affect the appearance of the final digital image. All these preparation-induced image variations can affect the automated analysis of the image and thus the calculated feature values.…”

Section: Introductionmentioning

confidence: 99%

“…[18][19][20][21] While standardization of stains and procedures as suggested in Lyon et al 13 could help reduce variation, logistical and physical limitations mean that digital color correction will always be needed to ensure uniform color. Color normalization (CN) is broadly the process of altering the color channel values of pixels in a source image so that its color distribution matches that of a template image.…”

Section: Introductionmentioning

confidence: 99%

Evaluating stability of histomorphometric features across scanner and staining variations: prostate cancer diagnosis from whole slide images

et al. 2016

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Abstract. Quantitative histomorphometry (QH) is the process of computerized feature extraction from digitized tissue slide images to predict disease presence, behavior, and outcome. Feature stability between sites may be compromised by laboratory-specific variables including dye batch, slice thickness, and the whole slide scanner used. We present two new measures, preparation-induced instability score and latent instability score, to quantify feature instability across and within datasets. In a use case involving prostate cancer, we examined QH features which may detect cancer on whole slide images. Using our method, we found that five feature families (graph, shape, co-occurring gland tensor, sub-graph, and texture) were different between datasets in 19.7% to 48.6% of comparisons while the values expected without site variation were 4.2% to 4.6%. Color normalizing all images to a template did not reduce instability. Scanning the same 34 slides on three scanners demonstrated that Haralick features were most substantively affected by scanner variation, being unstable in 62% of comparisons. We found that unstable feature families performed significantly worse in inter-than intrasite classification. Our results appear to suggest QH features should be evaluated across sites to assess robustness, and class discriminability alone should not represent the benchmark for digital pathology feature selection.

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“…Additionally, commercial dye content will vary from batch to batch and from supplier to supplier. Each batch may contain a different degree of impurities, which can lead to differences in staining intensity and, in some cases, may even be mislabeled with the name of a different solution 21,22 . As it stands, each batch must be tested before it can be used for proper tissue staining (daily quality control).…”

Section: Discussionmentioning

confidence: 99%

Hematoxylin and Eosin Tissue Stain in Mohs Micrographic Surgery: A Review

Larson

Anumolu

et al. 2011

Dermatologic Surgery

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Standardization of reagents and methods used in cytological and histological practice with emphasis on dyes, stains and chromogenic reagents

Cited by 44 publications

References 53 publications

Dielectrophoretic Segregation of Different Human Cell Types on Microscope Slides

Dielectrophoretic Segregation of Different Human Cell Types on Microscope Slides

Evaluating stability of histomorphometric features across scanner and staining variations: prostate cancer diagnosis from whole slide images

Hematoxylin and Eosin Tissue Stain in Mohs Micrographic Surgery: A Review

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