Masks in imaging flow cytometry.

Data analysis in imaging flow cytometry incorporates elements of flow cytometry together with other aspects of morphological analysis of images. A crucial early step in this analysis is the creation of a mask to distinguish the portion of the image upon which further examination of specified features can be performed. Default masks are provided by the manufacturer of the imaging flow cytometer but additional custom masks can be created by the individual user for specific applications. Flawed or inaccurate masks can have a substantial negative impact on the overall analysis of a sample, thus great care must be taken to ensure the accuracy of masks. Here we discuss various types of masks and cite examples of their use. Furthermore we provide our insight for how to approach selecting and assessing the optimal mask for a specific analysis.

[1]  Andrew Filby,et al.  Reporting imaging flow cytometry data for publication: Why mask the detail? , 2012, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[2]  Jonathan D. Katz,et al.  Nonobese Diabetic Mouse Diabetes Cell Antigens in b Break T Cell Tolerance to Cutting Edge: Merocytic Dendritic Cells , 2010 .

[3]  J. P. McCoy,et al.  Imaging flow cytometry for automated detection of hypoxia‐induced erythrocyte shape change in sickle cell disease , 2014, American journal of hematology.

[4]  J P McNamee,et al.  Analysis of chromosome damage for biodosimetry using imaging flow cytometry. , 2013, Mutation research.

[5]  J. Messer,et al.  The Crohn's disease: associated ATG16L1 variant and Salmonella invasion , 2013, BMJ Open.

[6]  P. Kuo,et al.  Characterization of Uptake and Internalization of Exosomes by Bladder Cancer Cells , 2014, BioMed research international.

[7]  David Basiji,et al.  Quantitative measurement of nuclear translocation events using similarity analysis of multispectral cellular images obtained in flow. , 2006, Journal of immunological methods.

[8]  Hao Fang,et al.  Slp‐76 is a critical determinant of NK‐cell mediated recognition of missing‐self targets , 2015, European journal of immunology.

[9]  Joanne Lannigan,et al.  An improved method for differentiating cell-bound from internalized particles by imaging flow cytometry. , 2015, Journal of immunological methods.

[10]  D. Jenner,et al.  Using multispectral imaging flow cytometry to assess an in vitro intracellular Burkholderia thailandensis infection model , 2016, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[11]  Judy Lieberman,et al.  Numbers matter: quantitative and dynamic analysis of the formation of an immunological synapse using imaging flow cytometry. , 2009, Journal of immunological methods.

[12]  Philip Morrissey,et al.  Quantitative image based apoptotic index measurement using multispectral imaging flow cytometry: a comparison with standard photometric methods , 2008, Apoptosis.

[13]  William E. Ortyn,et al.  Cellular image analysis and imaging by flow cytometry. , 2007, Clinics in laboratory medicine.

[14]  Jan Gursky,et al.  Imaging flow cytometry as a sensitive tool to detect low‐dose‐induced DNA damage by analyzing 53BP1 and γH2AX foci in human lymphocytes , 2015, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[15]  K. McGrath,et al.  Multispectral imaging of hematopoietic cells: where flow meets morphology. , 2008, Journal of immunological methods.

[16]  Matthew L Albert,et al.  Simultaneous assessment of autophagy and apoptosis using multispectral imaging cytometry , 2011, Autophagy.

[17]  Jacques Neefjes,et al.  Selective Infection of Antigen-Specific B Lymphocytes by Salmonella Mediates Bacterial Survival and Systemic Spreading of Infection , 2012, PloS one.