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- Baldetorp, Bo, et al.
(författare)
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Improved DNA flow cytometric, DNA ploidy, and S-phase reproducibility between 15 laboratories in analysis of breast cancer using generalized guidelines
- 2003
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Ingår i: Cytometry. - : Wiley. - 0196-4763 .- 1097-0320. ; 56A:1, s. 1-7
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundLack of generalized guidelines for DNA flow cytometric analysis (FCM) may be the main reason for its limited use in the clinical management of breast cancer.MethodsAfter an initial interlaboratory reproducibility study (Round I), we concluded that it was the evaluation of the DNA histograms rather than the technical performance of the analysis that was the main reason for discordant results between laboratories. Guidelines for the interpretation of DNA histograms were therefore drawn up. We present here data from a new reproducibility study (Round II) using these guidelines.ResultsFor 10 laboratories also participating in Round I, use of the guidelines increased the concordance in DNA ploidy status from 89% to 100% for the 46 samples used in both rounds. The concordance rate for SPF also increased; mean rs-value increased from 0.81 to 0.88, and mean kappa value (lower two-thirds versus upper third versus not reported) increased from 0.55 to 0.71. Five new laboratories, participating only in Round II, also agreed with the 10 original laboratories regarding DNA ploidy status. With the inclusion of all 15 laboratories, we obtained a mean rs-value of 0.81 and a mean kappa value of 0.72 for SPF.ConclusionsGeneralized guidelines for DNA FCM increase interlaboratory agreement, which is highly important in clinical routines and in multicenter studies. Furthermore, inexperienced FCM laboratories using generalized guidelines can produce and interpret DNA FCM data equally as well as experienced laboratories.
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| 2. |
- Lindblad, Joakim, et al.
(författare)
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Image Analysis for Automatic Segmentation of Cytoplasms and Classification of Rac1 Activation
- 2004
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Ingår i: Cytometry. - : Wiley. - 0196-4763 .- 1097-0320. ; 57A:1, s. 22-23
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND:Rac1 is a GTP-binding molecule involved in a wide range of cellular processes. Using digital image analysis, agonist-induced translocation of green fluorescent protein (GFP) Rac1 to the cellular membrane can be estimated quantitatively for individual cells.METHODS:A fully automatic image analysis method for cell segmentation, feature extraction, and classification of cells according to their activation, i.e., GFP-Rac1 translocation and ruffle formation at stimuli, is described. Based on training data produced by visual annotation of four image series, a statistical classifier was created.RESULTS:The results of the automatic classification were compared with results from visual inspection of the same time sequences. The automatic classification differed from the visual classification at about the same level as visual classifications performed by two different skilled professionals differed from each other. Classification of a second image set, consisting of seven image series with different concentrations of agonist, showed that the classifier could detect an increased proportion of activated cells at increased agonist concentration.CONCLUSIONS:Intracellular activities, such as ruffle formation, can be quantified by fully automatic image analysis, with an accuracy comparable to that achieved by visual inspection. This analysis can be done at a speed of hundreds of cells per second and without the subjectivity introduced by manual judgments.
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