Flow Cytometry in Hematopathology: A Visual Approach to Data Analysis and Interpretation 2nd ed. 2007 [Minkštas viršelis]

Table of ContentsPreface to second editionPreface to first editionAcknowledgementsList of AbbreviationsList of Case StudiesColor PlatesChapter 1 Approach to Flow Cytometry - General Considerations1.1 Reasons for the necessity of proper data analysis1.1.1 The pitfalls of the FCM data format of 'percent positive' perantibody tested1.2 General aspects of FCM data analysis and interpretation1.3 Other applications of FCM in hematopathology1.4 Maturation and differentiation of hematopoietic elements, anoverview based on the immunologic markers currently in use in the FCMlaboratoryChapter 2 FCM immunophenotyping and DNA analysis - Practical aspectsthat can affect data analysis and interpretation 2.1 Sample selection2.1.1 Liquid specimens2.1.2 Solid tissue specimens2.2 Preparing nucleated cell suspensions2.3 Cell yield and viability2.4 Sample staining.2.4.1 Surface antigens2.4.2 Intracellular antigens2.4.3 DNA content2.5 Data acquisition2.5.1 Calibration2.5.2 Color compensation2.5.3 List mode data collection 2.5.4 Exclusion of nonviable cells2.6 Antibody panel design2.6.1 Antibody selection2.6.1.1 Anti-light chain antibodies2.6.2 Fluorochrome conjugation2.7 Comprehensive antibody panels2.7.1 Disease-oriented antibody panels2.7.2 Antibody panels oriented by specimen type2.8 Tailored panels and add-on testing2.8.1 Minimal residual disease2.9 FCM immunophenotyping data representation2.9.1 Analysis panels2.9.2 Color display2.10 Approach to DNA data analysis2.10.1 DNA ploidy2.10.2 S-phaseChapter 3 FCM data analysis on nearly homogeneous samples3.1 FCM parameters3.1.1 Forward scatter3.1.2 Side scatter3.1.3 Fluorescence3.1.3.1 Heterogeneous fluorescence intensity (bimodal, variable)3.2 Fluorescence dynamic range3.3 Strategy to the visual review of FCM immunophenotyping data3.4 Common SSC/CD45 patterns3.4.1 Assessment of the blast population3.4.2 Immature neoplastic cells with downregulated CD453.4.3 SSC/CD45 in mature lymphoid disorders3.5 Other dot plot patterns useful in acute leukemia diagnosis3.5.1 Useful antigenic features in AML3.5.1.1 Myeloid phenotypic abnormalities and MRD detection 3.5.2 Precursor B-ALL vs bone marrow B-cell progenitors3.5.3 Useful antigenic features in precursor T-lymphoma/leukemia3.6 Evaluation of mature lymphoid malignancies3.6.1 Assessment of surface light chain expression3.6.2 Assessment of pan B-cell antigens3.6.3 Useful antigenic features in mature B-cell malignancies3.6.3.1 CD10 expression: Follicular center cell lymphomas3.6.3.2 Pattern of CD20 and CD11c coexpression3.6.3.3 CD5 expression3.6.3.4 Aberrant B-cell profile3.6.4 Identification of abnormal mature T-cells3.6.5 Useful antigenic features in mature T-cell malignancies3.7 Assessing the biological behavior of mature lymphoid neoplasms3.8 Dot plot patterns in histiocytic proliferations andnonhematopoietic malignanciesChapter 4 FCM data analysis on heterogeneous specimens4.1 Identifying normal FCM samples4.1.1 Benign/reactive solid lymphoid tissue (e.g., lymph nodes,tonsils)4.1.1.1 Pattern of CD10/CD20 coexpression. Distinction between FRFHand FCC lymphoma4.1.2 Normal peripheral blood and normal bone marrow4.1.2.1 Blast region4.1.2.2 Bone marrow B-cell precursors4.1.2.3 Lymphocytes4.1.2.4 Monocytes4.1.2.5 Plasma cells4.1.2.6 Erythroid precursors4.1.2.7 Maturing myeloid cells4.2 Abnormal heterogeneous samples with a detectable immatureneoplastic population4.2.1 Blasts of lymphoid lineage4.2.2 Blasts of myeloid lineage4.2.2.1 AML4.2.2.2 High-grade MDS and MPD with increased blasts4.3 Minimal residual disease4.4 Abnormal heterogeneou