K R Castleman, R Eils, L Morrison, J Piper, K Saracoglu, M A Schulze, M R Speicher
{"title":"Classification accuracy in multiple color fluorescence imaging microscopy.","authors":"K R Castleman, R Eils, L Morrison, J Piper, K Saracoglu, M A Schulze, M R Speicher","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":10947,"journal":{"name":"Cytometry","volume":"41 2","pages":"139-47"},"PeriodicalIF":0.0000,"publicationDate":"2000-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cytometry","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.