Literature DB >> 9451557

Flow cytometry in diagnostic cytology.

T J O'Leary1.   

Abstract

Flow cytometry (FCM) is a useful adjunct to cytologic examination, because the quantitative biochemical information it provides complements the morphologic information gained during visual examination. It aids in the interpretation of bladder washings, and is particularly useful for the assessment of lymphoid lesions, whether they originate from fine-needle aspiration, cerebrospinal fluid, or effusions. Optimal use of FCM frequently requires assessment of more than one parameter; simultaneous use of cell differentiation markers and nuclear DNA quantitation is often significantly more useful than either alone. Despite the utility of FCM, however, the potential for future development appears to be limited. Improvements in image cytometry allow reasonable assessment of ploidy and S-fraction to be made from specimens prepared on glass slides. Multiparameter measurements may also be accomplished with imaging techniques, which allow the further advantage of visual identification of cells with equivocal morphologic changes. The development of artificial intelligence methods for use with imaging technology has also significantly exceeded that of FCM. Finally, image cytometry is often more useful for samples with few cells. Other challenges are posed by immunocytochemical methods which compete with flow cytometry as tools for assessment of proliferation. Given the relatively high cost of FCM instrumentation, survival of FCM as an ancillary technique in cytopathology will require further technical refinements to offset the advantages currently associated with image cytometry and immunocytochemistry.

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Year:  1998        PMID: 9451557     DOI: 10.1002/(sici)1097-0339(199801)18:1<41::aid-dc7>3.0.co;2-x

Source DB:  PubMed          Journal:  Diagn Cytopathol        ISSN: 1097-0339            Impact factor:   1.582


  2 in total

Review 1.  Serous effusions: diagnosis of malignancy beyond cytomorphology. An analytic review.

Authors:  S K Mohanty; P Dey
Journal:  Postgrad Med J       Date:  2003-10       Impact factor: 2.401

Review 2.  Artificial Neural Networks as Decision Support Tools in Cytopathology: Past, Present, and Future.

Authors:  Abraham Pouliakis; Efrossyni Karakitsou; Niki Margari; Panagiotis Bountris; Maria Haritou; John Panayiotides; Dimitrios Koutsouris; Petros Karakitsos
Journal:  Biomed Eng Comput Biol       Date:  2016-02-18
  2 in total

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