| The above-described situations indicate the necessity of a comprehensive approach to FCM data analysis and interpretation. In the authors’ experience, the optimal method is for the laboratory medical staff to apply a visual approach to FCM data analysis rather than relying on percentages. In other words, data interpretation is based on a visual appraisal of the FCM graphics, assessing the complex patterns formed by the shape and relative position of the cell clusters observed on various dot plots such as FSC versus fluorescence, side scatter (SSC) versus CD45, and correlated fluorescence dot plots. Any other approach to FCM data interpretation, using a scoring system or percent positive per antibody, underutilizes the full potential of FCM. Laboratory professionals, as well as clinicians, should realize that visual FCM data analysis is a process reminiscent of the microscopic examination of morphologic material (e.g., bone marrow aspirate smears, lymph node sections) in which the data form a pattern and are reported in a qualitative and quantitative (where appropriate) format. Although microscopic examination encompasses all elements in the sample, reporting the data focuses only on the abnormal component. Similarly, the FCM interpretative report should be based on the cells of interest, even though the list mode data should be collected unselected (i.e., it includes all cells in the sample). Collecting list mode data ungated ensures that no abnormal cells are lost, because in many instances, the nature of the abnormal population is not yet known at the time the specimen is run. Restricting the initial data collection to certain preset criteria (i.e., a “live gating” approach such as the use of a live light scatter gate) may easily result in “throwing the critical cells away.” A specific example is missing a small number of circulating hairy cells when the analysis is live-gated on cells with the light scatter characteristics of normal lymphocytes. An additional advantage of the ungated approach is that the presence of other cells serves as internal positive and negative controls. After the data have been acquired ungated, certain gating procedures can be applied during the analysis step. Some of the most useful gating strategies include (1) gating on B-cells, to determine clonality (Figure 1.1) and the coexpression of other critical antigens, and (2) gating on CD45 to characterize leukemic blasts (Figure 1.2). These strategies require the use of multicolor (two-color, at the very least) antibody combinations. Following the recommendations by the U.S.–Canadian Consensus on the Use of Flow Cytometry Immunophenotyping in Leukemia and Lymphoma in 1997, the multiparameter approach to FCM testing has become a standard routine in clinical laboratories, taking advantage of more sophisticated instrumentation and a larger repertoire of fluorochromes. Since the publication of the consensus recommendations, there has been an increase in the awareness of the visual approach to FCM data analysis. The literature contains very little information on this approach, however. The purpose of the first edition of this book was to fill this void. More recent developments in the field are added in this second edition. The FCM dot plots and histograms displayed in this book, using FCS Express software, are derived from clinical samples analyzed primarily on Becton-Dickinson instruments, using commercially available antibody reagents (see Chapter 2). Other current state-of-the-art instruments are equipped with a similar capability for multicolor FCM testing and mechanisms for color compensation. The principles of FCM data analysis presented in this book are applicable to all brands of flow cytometers. Interpretation of the FCM immunophenotyping results is one step in the diagnosis of malignant lymphoma and leukemia. Although, in many cases the diagnosis is apparent after a visual inspection of the FCM immunophenotyping data together with the DNA cell cycle histogram, in other instances the antigenic profile and the pattern of the cell clusters suggest only a differential diagnosis instead of a specific disorder. In such cases, it is critical that the diagnostic interpretation takes into account the other clinical and laboratory data, such as the hemogram findings and the cytologic/morphologic features. The synthesis of the pertinent results requires the responsible medical staff in the laboratory to be well versed in the different subdisciplines of hematopathology. Irrespective of whether a case is straightforward or complex, the authors advocate a routine systematic approach to FCM diagnostic interpretation. This will ensure that no relevant information is omitted. A correlation between the FCM findings and the available morphologic data should be performed in all cases. Wright-Giemsa-stained cytospins made from the cell suspension of the tissue or fluid submitted for FCM study must be reviewed, to correlate the findings with those derived from the FCM plots. This is especially helpful when abnormal (neoplastic) cells are few or the FCM data cannot be clearly interpreted. For peripheral blood specimens, the FCM data are correlated with the hemogram and cytologic features from a fresh blood film. Similarly, FCM interpretation on bone marrow specimens should include a review of the hemogram, peripheral blood film, bone marrow aspirate smear or imprint, and cytochemistries, where appropriate. It cannot be emphasized enough that hemogram findings, along with fresh peripheral blood and bone marrow smears, must accompany the specimen when bone marrow is sent to a referral laboratory for immunophenotyping, so that a proper, thorough diagnostic evaluation of the case can be conducted. For interpretation on solid tissue (e.g., lymph nodes), the FCM data are correlated with the morphologic features on the imprints and hematoxylin and eosin (H&E) sections (where available). In addition to the above-mentioned minimum correlation with the morphologic findings, it is also important to review immunoelectrophoresis results in suspected lymphoplasmacytoid neoplasms or plasma cell dyscrasias. Knowledge of the pertinent clinical history, especially the type of therapy (e.g., immunotherapy, growth factors), is also useful to further refine FCM diagnostic interpretation. This necessitates a dialogue between the medical staff caring for the patient and the FCM laboratory. Because of the time delay associated with molecular genotyping and cytogenetics, these techniques play a minimal role at the time of rendering the diagnosis. Correlation of those results with the FCM data is useful, however, for confirming the diagnosis or providing additional information. |
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