Literature DB >> 3300687

Application of morphometry in tumor pathology.

Y Collan, T Torkkeli, E Pesonen, E Jantunen, V M Kosma.   

Abstract

The application of morphometry in tumor pathology is discussed, e.g., its use in studying the biology of tumors, in creating tumor classification(s), in creating methods for the identification of a tumor in the diagnostic context, and in characterizing diagnostic histopathology in absolute terms. In traditional subjective diagnostic histopathology, reproducibility can be defined satisfactorily, but the definition of accuracy is ambiguous; in morphometric histopathology, a satisfactory definition is found for both concepts but it may be difficult to separate them in practice. Morphometric histopathology can study parameters measured from sections or parameters derived from the primary measurements through calculations. In the histopathology of tumors, the following parameters have turned out to be specially valuable: densitometric measurements of nuclei, nuclear area, perimeter and form factors, nucleolar parameters, the number of mitotic cells per area, the cellularity, the volume fraction of the epithelium, and parameters associated with the fraction of tumor tissue in the sample. The standard deviation or other moments of the distribution of these measurements can be more relevant than the mean values of the results. This indicates that more attention should be given to sampling rules, which are important in defining the efficiency of the methods. For rational application of morphometric methods, it is very important to make a distinction between group morphometry and diagnostic morphometry. The latter engenders numerous sources of variation (variation in section thickness, variation in tissue processing, variation in the techniques of measurement, interobserver variation, interlaboratory variation, variation due to subjective interpretation, etc.), which are usually better controlled in group morphometry. The influence on morphometric parameters of variation in section thickness and tissue shrinkage during processing are discussed.

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Mesh:

Year:  1987        PMID: 3300687

Source DB:  PubMed          Journal:  Anal Quant Cytol Histol        ISSN: 0884-6812            Impact factor:   0.302


  4 in total

Review 1.  The study of endocrine tumors by flow and image cytometry.

Authors:  Ingrid Zbieranowski; David Murray
Journal:  Endocr Pathol       Date:  1992-06       Impact factor: 3.943

2.  Osteoclast cytomorphometry demonstrates an abnormal population in B cell malignancies but not in multiple myeloma.

Authors:  D Chappard; J F Rossi; R Bataille; C Alexandre
Journal:  Calcif Tissue Int       Date:  1991-01       Impact factor: 4.333

3.  Analyzing huge pathology images with open source software.

Authors:  Christophe Deroulers; David Ameisen; Mathilde Badoual; Chloé Gerin; Alexandre Granier; Marc Lartaud
Journal:  Diagn Pathol       Date:  2013-06-06       Impact factor: 2.644

4.  Morphometric Cell Classification for Single-Cell MALDI-Mass Spectrometry Imaging.

Authors:  Klára Ščupáková; Frédéric Dewez; Axel K Walch; Ron M A Heeren; Benjamin Balluff
Journal:  Angew Chem Int Ed Engl       Date:  2020-08-17       Impact factor: 16.823

  4 in total

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