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Flow cytometry


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flowcytometry, introduction, basics, case studies, CLPD, acute leukaemia, markers

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Flow cytometry

  1. 1. FLOW CYTOMETRY MODERATOR: DR. R.M. JAISWAL By: Dr. Megha Gupta & Dr. Tashi Agarwal
  2. 2. FLOW CYTOMETRY  Definition: Measuring properties of cell as they flow in a fluid suspension across an illuminated light path.
  3. 3. Basic mechanism Biological sample Label it with a fluorescent marker Cells move in a linear stream through a focused light source (laser beam) Fluorescent molecule gets activated and emits light that is filtered and detected by sensitive light detectors (usually a photomultiplier tube) Conversion of analog fluorescent signals to digital signals
  4. 4. Flow Cytometry  This method allows the quantitative and qualitative analysis of several properties of cell populations from virtually any type of fresh unfixed tissue or body fluid.  The properties measured include a particle’s related size, relative granularity or internal complexity, and relative fluorescence intensity Most commonly analyzed materials are:  blood,  bone marrow aspirate and  lymph node suspensions.
  5. 5. Principle of Flow Cytometry  Flow cytometer is composed of three main components:  The Flow system (fluidics) Cells in suspension are brought in single file past  The Optical system (light sensing) a focused laser which scatter light and emit fluorescence that is filtered and collected  The Electronic system (signal processing) emitted light is converted to digitized values that are stored in a file for analysis
  6. 6. The Flow System  One of the fundamentals of flow cytometry is the ability to measure the properties of individual particles, which is managed by the fluidics system.  When a sample is injected into a flow cytometer, it is ordered into a stream of single particles.  The fluidic system consists of a FLOW CELL (Quartz Chamber):  Central channel/ core - through which the sample is injected.  Outer sheath - contains faster flowing fluid k/a Sheath fluid (0.9% Saline / PBS) , enclosing the
  7. 7. Hydrodynamic Focusing Once the sample is injected into a stream of sheath fluid within the flow chamber, they are forced into the center of the stream forming a single file by the PRINCIPLE OF HYDRODYNAMIC FOCUSING. 'Only one cell or particle can pass through the laser beam at a given moment.'
  8. 8. • The sample pressure is always higher than the sheath fluid pressure, ensuring a high flow rate allowing more cells to enter the stream at a given moment. • High Flow Rate - Immunophenotyping analysis of cells • Low Flow Rate - DNA Analysis Sheath Tank Waste Tank Line PressureVacuum Sample Pressure (Variable) Sheath Pressure (Constant) Sample Tube
  9. 9. OPTICS  After the cell delivery system, the need is to excite the cells using a light source.  The light source used in a flow cytometer:  Laser (more commonly)  Arc lamp  Why Lasers are more common?  They are highly coherent and uniform. They can be easily focused on a very small area (like a sample stream).  They are monochromatic, emitting single wavelengths of light.  ARGON Lasers - 488nm wavelength (blue to blue green)
  10. 10. When a light intersects a laser beam at the so called 'interogation point' two events occur: a) light scattering b) emission of light (fluorescence ) Fluorescence is light emitted during decay of excited electron to its basal state.
  11. 11. OPTICS a) LIGHT SCATTER  When light from a laser interrogates a cell, that cell scatters light in all directions.  The scattered light can travel from the interrogation point down a path to a detector.
  12. 12. OPTICS - FORWARD SCATTER (FSC) • Light that is scattered in the forward direction (along the same axis the laser is traveling) is detected in the Forward Scatter Channel. • The intensity of this signal has been attributed to cell size, refractive index (membrane permeability).
  13. 13. OPTICS - SIDE SCATTER (SSC)  Laser light that is scattered at 90 degrees to the axis of the laser path is detected in the Side Scatter Channel.  The intensity of this signal is proportional to the amount of cytosolic structure in the cell (eg. granules, cell inclusions, etc.) Side scatter detector Measuring cell granularity
  14. 14. FSC Detector Collection Lens SSC Detector Laser Beam
  15. 15. FSC SSC Lymphocytes Monocytes Granulocytes RBCs, Debris, Dead Cells Study of FSC and SSC allows us to know the differentiation of different types of cells. Why FSC & SSC?
  16. 16.  The light scattered in the forward direction is proportional to the square of the radius of a sphere, and so to the size of the cell or particle.  The cells are labelled with fluorochrome-linked antibodies or stained with fluorescent membrane, cytoplasmic or nuclear dye.
  17. 17. Commonly used Fluorochromes FLUOROCHROMES EMISSION MAXIMUM Fluorescein Isothiocynate (FITC) 530nm Phycoerythrin (PE) 576nm Peridin-chlorophyll alpha complex (PerCP) 680nm Allophycocyanin (APC) 660nm Texas red 620nm ECD( PE - Texas Red Tandem) 615nm PC5 (PE - cyanin 5 dye tandem) 667nm
  18. 18. Optics B) EMISSION OF FLUORESCENT LIGHT (FLUORESCENCE)  As the fluorescent molecule present in or on the particle is interrogated by the laser light, it will absorb energy from the laser light and release the absorbed energy at longer wave length.  Emitted photons pass through the collection lens and are split and steered down specific channels with the use of filters.  Emitted fluorescence intensity is proportional to the
  19. 19. Optics- Filters  Different wavelengths of light are scattered simultaneously from a cell  Need to split the light into its specific wavelengths in order to measure and quantify them independently. This is done with filters.  The system of filters ensures that each photodetector receives light bands of various wavelengths.  Optical filters are designed such that they absorb or reflect some wavelengths of light, while transmitting others.  Types of filters 1. Long Pass 2. Short Pass 3. Band Pass 4. Dichroic
  20. 20. Optics- Long Pass Filters  Transmit all wavelengths greater than specified wavelength  Example: 500LP will transmit all wavelengths greater than 500nm 400nm 500nm 600nm 700nm Transmittance Original from Cytomation Training Manual
  21. 21. Optics- Short Pass Filter  Transmits all wavelengths less than specified wavelength  Example: 600SP will transmit all wavelengths less than 600nm. 400nm 500nm 600nm 700nm Transmittance Original from Cytomation Training Manual
  22. 22. Optics- Band Pass Filter  Transmits a specific band of wavelengths  Example: 550/20BP Filter will transmit wavelengths of light between 540nm and 560nm (550/20 = 550+/- 10, not 550+/-20) 400nm 500nm 600nm 700nm Transmittance Original from Cytomation Training Manual
  23. 23. Optics- Dichroic Filters  Long pass or short pass filters  Placed at a 45º angle of incidence  Part of the light is reflected at 90º , and part of the light is transmitted and continues. Dichroic Filter Detector 1 Detector 2
  24. 24. OPTICS - DETECTORS  The photodetectors convert the photons to electrical impulses.  Two common types of detectors used in flow cytometry:  Photodiode used for strong signals, when saturation is a potential problem (eg, forward scatter detector).  Photomultiplier tube (PMT) more sensitive than photodiode but can be destroyed by exposure to too much light. used for side scatter and fluorescent signols.
  25. 25. ELECTRONICS  The electronic subsystem converts photons to photoelectrons.  Measures amplitude, area and width of photoelectron pulse.  It amplifies pulse either linearly or logarithmically and then digitalizing the amplified pulse.
  26. 26. Time Electronics- Creation of a Voltage Pulse
  27. 27. Data Analysis- Plot Types  There are several plot choices:  Single Color Histogram  Fluorescence intensity (FI) versus the number of cells counted.  Two Color Dot Plot  FI of parameter 1 versus FI of Parameter 2  Two Color Contour Plot  Concentric rings form around populations. The more dense the population, the closer the rings are to each other  Two Color Density Plot  Areas of higher density will have a different color than
  28. 28. Plot Types Contour Plot Density Plot Greyscale Density Dot Plot Histogram
  29. 29. DATA ANALYSIS - GATING  Gating is in essence electronic window that sets upper and lower limits on the type and amount of material that passes through.  Selection of only a certain population of cells for analysis on a plot.  Allows the ability to look at parameters specific to only that subset.
  30. 30. Interpretation of Graphs  An important tool for evaluating data is the dot plot.  The instrument detects each cell as a point on an X-Y graph. This form of data presentation looks at two parameters of the sample at the same time.
  31. 31. Three common modes for dot plots are:  Forward scatter (FSC) vs. side scatter (SSC) To look at the distribution of cells based upon size & granularity  Single color vs. side scatter To visualize the expression of the fluorescence of the cells  Two-color fluorescence plot. To differentiate between those cells that express only one of the particular fluorescent markers, those that express neither, and those that express both. used to discriminate dead cells from the live ones that are expressing the desired fluorescence.
  32. 32. When to say an antigen is positive or negative?  A sample that has some cells single positives for CD8 along the x-axis (green arrow)  some single positives for CD4 along the y-axis (red arrow).  Upper right quadrant of the plot - cells positive for both fluorescent markers (purple arrow).  Lower left quadrant - cells negative for both markers (orange arrow).
  33. 33. How to differentiate dim & bright expression of an antigen?  Dim : cells are present more towards the origin(0) on x(red) - y axis (pink)  Bright : cells are present away from the origin(0) on x(green) & y(yellow) axis. DIM BRIGHT Y-axis CD4 X-axis CD8
  36. 36. APPLICATIONS  ANALYSIS  Immunophenotyping  Dyes that bind to nucleic acids (DNA, RNA)  Functional assays  CELL COUNTING  CELL SORTING
  37. 37. CLINICAL APPLICATIONS • Absolute CD4 counts HIV/AIDS • HLA B27 assay Joint Pain • Diagnosis and Classification • Detection of MRD Hematological Malignancies • DNA Ploidy • S Phase fractionSolid Tumours • TBNK • Phagocytic function defect Primary Immunodeficiency disorders
  38. 38. Cont.. • Reticulocyte count • PNH • Osmotic fragility assay Hemolytic anaemia • Feto- maternal Hemorrhage • treatment response in Sickle Cell AnemiaFetal Hb detection • Platelet receptor assays (Platelet count, GT, BSS) • Platelet function assay (CD62P, PAC-1) Bleeding Disorders • CD34 STEM CELL COUNTS • Residual WBC count in leukodepleted blood packs • Flow cytometry Crossmatch Transfusion and Transplant • Surface markers in PMN, Monocytes • Cytokine response Host Immune response in Sepsis
  40. 40. Objectives  Diagnosis of lymphoma  Classification of lymphoma  Ploidy analysis
  41. 41. Flow cytometric approach to the diagnosis and classification of B- cell lymphoid neoplasms. B Cell Lymphoma
  43. 43. How to differentiate between Normal and Neoplastic B cells 1) Imunoglobulin light chain class restriction. 2) Aberrant antigen expression. MONOCLONALITY CD 13, CD 33, CD 5 ON B CELLS
  44. 44. Normal, polyclonal B-cells are a mixture of kappa-B-cells and lambda-B-cells. A B-cell carries either kappa- or lambda-light chain on its surface. And normal polyclonal B-cells are a mixture of kappa-B-cells and lambda B-cells as can be seen in the left-hand figure. Monoclonal mature B-cells are either kappa or lambda. If a malignant B-cell clone proliferates this will result in a B-cell population consisting of either only kappa- or only lambda-B-cells. The latter case (i.e. lambda-monoclonal B-cells) is symbolized in the left-hand figure.
  45. 45. Expression of CD5 The arrow in the right panel points to the abnormal, strong expression of CD5 by B-cells. CD5 expression as strong as this can usually only be found on T-cells. Normal B-cells show no or only a weak expression of CD5 (left-hand panel) Weak expression of CD20 The B-cells in the right panel show only a weak expression of CD20 (arrow). For comparison: normal CD20 expression in the left- hand panel.
  47. 47. Chronic lymphocytic leukemia  Typical phenotype: CD20 (d), CD22 (d), sIg (d), CD23+  FMC-7-  Characteristic morphology  Testing for the prognostic markers CD38 and ZAP-70 can be considered
  48. 48. Mantle cell lymphoma  Variable phenotype not typical for CLL;  often CD20 (i), sIg (i), CD23-, FMC-7 +  IHC : Cyclin-D1  FISH : t(11;14)/CCND1 rearrangement
  49. 49. Hairy cell lekaemia  Typical pheotype: CD20 (b), CD22 (b), CD11c (b),  CD25+, CD103+, sIg (i)  Confirm characteristic morphology of a hairy cell and TRAP +  A small subset of HCL are CD10+ but are morphologically similar to CD10- HCL.
  50. 50. Follicular lymphoma  Usually bcl-2, CD43.  Some follicular growth.  t(14;18)/BCL-2 rearrangement.  D/D 1. DLBCL : diffuse growth pattern against the nodular growth pattern in FL 2. BL : morphologial (vacuoles), High S phase fraction.
  51. 51.  80/F  c/o cervical adenopathy  On CBC : an absolute lymphocytosis ≥5 × 109/L;  PBF is flooded with small mature lymphocytes with condensed chromatin and scant cytoplasm along with numerous smudge cells. CASE
  52. 52. On flow A diagnosis of CLL can be made. CD5+ CD23+
  53. 53. Not that simple  A certain immunophenotype may be typical but is by no means obligatory.  The significance of one marker depends on the expression of other markers.  The strength of antigen expression is important.
  54. 54. Flow cytometric approach to the diagnosis and classification of T- cell lymphoid neoplasms. T CELL LYMPHOMA
  55. 55. Finding abnormal T/ NK cells. 1) Search for monoclonal T cells 2) T cells with aberrant antigen expression. CD4/CD8 Ratio Loss of CD3 Overexpression of CD5
  56. 56. Normally, the CD4/CD8-T- Cell ratio in peripheral blood is about 2:1. In a T-lymphocytic leukemia this ratio can shift dramatically. Unfortunately, this ratio may also be altered by many non-malignant diseases. eg viral infections. Therefore, only extreme alterations of this ratio can be regarded as a sign for T- lymphocytic malignancy.
  57. 57. CD4/CD8 coexpression In the right-hand dot-plot you can see cells that express both the CD4 and the CD8-antigen (arrow) which is highly irregular. In addition both antigens are expressed weakly (compared to normal T-cells). Left- hand panel shows a normal situation. Loss of CD3 Overexpression of CD5 In the right-hand dot-plot you can see T-cells which overexpress CD5 while they lack CD3 (arrow). Only a few normal T-cells are present. (blue oval). Left-hand panel shows a normal situation.
  58. 58. PROBLEMS IN DIAGNOSIS OF T- CLPD  Relatively low incidence.  5-25% of all lympoid neoplasms.  Clinico-biological heterogeneity.  Lack of distinctive genetic markers.
  61. 61. CTCL/Sézary syndrome  Often CD7-, CD26-, CD4+, CD25+/- (with heterogeneous staining intensity).  Confirm characteristic morphology and clinical presentation.  HTLV-1-
  63. 63. Cell cycle analysis  The percentage of the cells in each region is analyzed. In normal tissues –  95% cells - G0/G1 phase  2.5% cells - S phase  2.5% cells - G2/M phase  In neoplasm, percentage of cells in S and G2/M phase increases which is expressed as S phase fraction or the proliferation index
  64. 64. S Phase, synthesis phase. It is the part of cell cycle in which DNA is replicated occurring between G1phase and G2 phase.
  65. 65. S phase has strong correlation with grading. DNA ploidy has no correlation with grading. ADVANTAGES OVER IHC
  66. 66. Highest proliferative activity: mean SPF, 35.3% 6.6% 6.5% 20.4%
  68. 68. STEPS  Finding the blast population  Defining the immunophenotype  Diagnosis
  69. 69. A malignant blast population may be detected because of Increase of immature cells Abnormal marker expression of immature cells CD38 / CD45 AGAINST SSC CD19, 7 on non lymphoid cell
  70. 70. Finding immature cells using CD45- CD34 dot-plots The arrows points at the blast populations, which is very conspicuous in case AL 1 (upper right) and AL 3 (lower right). In case AL 2 (lower left), the difference between the normal picture is more subtle and the blasts may be missed because in this case the blasts are CD34 negative.
  71. 71. Intermediate CD45 and low side scatter BLAST WINDOW NEUTROPHI LS LYMPHOCYT ES MONOCYTE S RBC’S AND DEBRIS B CELLS CD45/SSC gating strategy is more sensitive than FSC/SSC gating and it dilineates the blasts well.
  72. 72. Finding immature cells using CD45- Side Scatter dot-plots The three cases of acute leukemia: The arrows point to the blast populations which are clearly visible in all three cases. Even the blasts of case AL 2 can easily be spotted.
  73. 73. BLAST WINDOW B CELLS MONOCYTES RBC’S AND DEBRIS LYMPHOCYT ES NEUTROPHIL S CD45/SSC gating strategy is more sensitive than FSC/SSC gating and it dilineates the blasts well.
  74. 74. Example of an abnormal antigen expression on myeloid blasts Compare the normal blasts (upper dot-plot, blue oval) with those of an acute myeloid leukemia (lower dot- plot, red oval)): the malignant blasts abnormally express CD15 and they show an increased expression of CD34. Note: CD34-negative cells have been removed for reason of clarity.
  75. 75. DIAGNOSIS  WHICH ONES TO IMMUNOPHENOTYPE? 1. Equivocal morphology 2. Cytochemistry is noncontributory 3. Specific subtypes  LEUKAEMIA VS NON LEUKAEMIA 1. Overlapping morphology. Eg: hematogones, viral infections. 2. Partially treated acute leukaemia
  76. 76. PROGNOSTIFICATION  CYTOGENIC AND MOLECULAR ABNORMALITIES • Association with specific cytogenic abnormalities • DNA ploidy  RESIDUAL DISEASE MONITORING
  77. 77. CLASSIFICATION Acute leukaemia is classified on the basis of immunological markers into  B lineage ALL  T lineage ALL  Acute myeloid leukaemia  Acute leukaemia of ambiguous lineage
  78. 78. How to define the lineage of leukaemia THE FLOW CYTOMETRIC EVALUATION OF HEMATOPOIETIC NEOPLASIA Brent L. Wood, Michael J. Borowitz. Henry’s, 22nd edition, Chapter 34
  79. 79. Flow cytometric approach to the diagnosis and classification of ALL. ACUTE LYMPHOID LEUKAEMIA
  80. 80. How to diff ALL from NHL  CD 34  TdT  Bcl2  CD99  NHL cases with spillover demonstrate bright CD45 expression while it is moderate in B ALL.
  81. 81. Subtypes of ALL  Flow cytometric immunophenotyping does not provide a suitable surrogate tool for detection of these subtypes of ALL. Subtype ALL HLA- DR TdT CD 10 CD 19 SmIg CyCD79 a Pro- B ALL +/- + - + - + Common ALL + + + + - + Pre B ALL + - - + - + Mature B ALL - - - + +K/L +
  82. 82. Precursor B cell lymphoblastic leukemia/lymphoma
  83. 83. Flow cytometric approach to the diagnosis and classification of AML. ACUTE MYELOID LEUKAEMIA
  84. 84. Diagnosis of AML Morphology Auer rod Cytochemistry >3% MPO positive Immunophenotyping CD33, CD13, CD117, anti- MPO Cytogenetics t(8;21), t(15;17), inv16, MLL, t(9;11), t(6;9), t(3;3), t(1;22)
  85. 85. CD markers used for hematolymphoid neoplasms All white cells CD 45 (LCA) Myeloid cells Anti-MPO, CD13, CD33, CD14, CD117 Monocytic Markers CD14, CD64 Megakaryocytic Marker CD41, CD61 B-cells cyCD22, CD22, CD19, CD20, FMC7, CD23, CD79a, CD79b, SmIg, IgM T-cells cyCD3, CD3, CD2, CD5, CD7, CD8, TCR-α/β, TCR-γ/δ NK cells CD16, CD56, CD57 Plasma cells CD38, CD138, Kappa & Lambda chains Blasts CD34, TdT Others HLA-DR, CD55, CD59, cyclin D1, glycophorin A
  86. 86. Myeloblast characterization 13+, 15+, 33+, anti-MPO+ Clinical, Genetic, Morphologic Erythroi d Megakaryocyti c Myeloid Monocytic 41+ 61+ 71++ GlyA+ 36+, 64+, 14+, 33++ 36+
  87. 87. Classification - FAB  M0 : AML-minimal differentiation  M1 : AML-without maturation  M2 : AML-with maturation (blast<80%)  M3 : AML-promyelocytic  M4 : AML-myelomonocytic (>20% monocytes)  M5 : AML-monocytic  M6 : AML-erythroid  M7 : AML-megakaryocytic
  88. 88. AML- minimal differentiation (M0)  Myeloblasts - < 3% positivity with SBB, MPO & PAS-, NSE-  Myeloid antigens - CD13+, CD33+, CD117+, and/or MPO+  CD34, CD38, HLA-DR, and TdT - often expressed
  89. 89. AML- Promyelocytic Leukemia (M3)  Phenotype - CD13h+, CD33++, CD34-, HLA- DR-  Diagnostic molecular alteration - PML/RARA t(15;17) translocation  Strongly positive - MPO, SBB, PAS cytoplasmic positivity.  Characteristic morphology  D/D : AML-monocytic leukemia (M5) -  HLA-DR+, CD11c+, CD14+ & CD64+
  90. 90. AML - Myelomonocytic Leukemia (M4)  Phenotype:  myeloid antigens - CD13+ & CD33+, HLA-DR+  monocytic markers: CD14+, CD4+, CD11b+, CD11c+, CD64+, CD36+, CD68+  Blasts >20% of marrow NEC  Monocytic component >20% of NEC & monocytes in blood >5 x 109/L
  91. 91. AML - Monocytic Leukemia (M5)  Phenotype: CD33 (b), CD13+, HLA-DR+  Characteristic CD14+, CD11b+, CD11c+, CD64+, CD68+  Cytochemistry : NSE +  M5a : Acute monoblastic leukemia  M5b : Acute monocytic leukemia
  92. 92. CD34 APC CD15 FITC CD56 A488 CD45 CD4
  93. 93. AML - Megakaryocytic leukemia (M7)  CD41+, CD61+, CD13+, CD33+  CD34, HLA-DR - Negative
  94. 94. CASE  29yrs/ F  O/E : Fever, Pallor, Gum hyperplasia, Hepatosplenomegaly.  CBC : Hb-5.2 g%, Plt- 19,000/  PBF : shows blasts and dual differentiation to granulocytes and monocytoid cells (large cells, abundant pale blue cytoplasm, lobulated or indented nucleus with variable nucleoli). DLC Blasts40 P8 L10 Monocytoid41 E1
  95. 95. red - dim CD45and low side scatter. Positive for - CD13, cyMPO, CD34, HLA- DR, CD33, CD11c Negative for - CD10, CD19, CD3, CD79a. Blue - bright CD45 & moderate side scatter. Positive for - CD14, CD11c, CD13. Negative for - CD34, cyMPO, CD3, CD10, CD19 ACUTE MYELOMONOCYTIC LEUKEM
  96. 96. Hematogones  Physiologic precursors of maturing B-cells.  Confused with neoplastic immature lymphoid cells of B lymphoblastic leukemia/ lymphoma or B-ALL.  Increased in:  Autoimmune or congenital cytopenias  Solid organ tumors e.g. neuroblastoma  AIDS  NHL  Post-chemotherapy and after BMT  Copper deficiency
  97. 97.  Morphologically, hematogones resemble lymphoblasts.  Hematogones can be differentiated from lymphoblasts by  Unique Immunophenotypic pattern :  CD34 < TdT < CD20 < PAX5  Variable CD10 & CD20  "J shaped trail pattern" : on CD10/20 Dot plot
  98. 98. Lymphocytes Hematogone Immunophenotypic analysis of hematogones in 662 consecutive bone marrow specimens by 4-color flow cytometry. Mckenna et al, BLOOD, 15 OCTOBER 2001
  99. 99. Acute leukaemia of ambiguous lineage  Mixed phenotype acute leukaemia  Acute undifferentiated leukaemia  NK/plasmacytoid dendritic cell leukaemia
  100. 100. MPAL – WHO 2008 Myeloid lineage MPO FC, IHC, Cytochemistry Monocytic diferentiation Atleast 2: NSE, CD11c, CD14, CD64, lyzozyme T lineage Cytoplasmic CD3 Surface CD3 B lineage Strong CD19 with atleast 1 : CD79a, cytoplasmic CD22, CD10 Weak CD19 with atleast 2 strongly expressed CD79a, cytoplasmic CD22, CD10 Or Or Or
  101. 101. EGIL scoring system The European group for the Immunological Classification of Leukaemias (EGIL) scoring system
  102. 102. Flowcytometry analysis in MRD detection Minimal Residual Disease detection
  103. 103.  At diagnosis the tumour burden is approximately 10^12 leukaemic cells.  Induction chemothereapy achieves a 3 log cell kill bringing it down to 10^9 leukaemic cells.  Light microscopy of BMA can detect leukaemia only when there are more than 5 blasts/ 100 nucleated cells. Anything less than that is termed remission. Introduction
  104. 104. Introduction  What is Minimal residual disease or MRD? It is that submicroscopic disease that cannot be detected by conventional light microscopic examination of the BMA.  It could be as high as 1 billion leukaemic cells.  It can be performed by two techniques: FCM & PCR.
  105. 105. Used mainly in - 1. Acute leukaemia for guiding thereapy as well as prognostic purposes. 2. Patients with low grade B cell malignancies undergoing high dose chemotherapy. 3. Post stem cell transplant and immunothereapy. 4. Lymphoma spillover.
  106. 106. REFERENCES  THE FLOW CYTOMETRIC EVALUATION OF HEMATOPOIETIC NEOPLASIA Brent L. Wood, Michael J. Borowitz. Henry’s, 22nd edition, Chapter 34  ATLAS AND TEXT OF HEMATOLOGY. Dr Tejinder singh  Manual: 6th Advanced TCS Flowcytometry workshop on hematological malignancies.  Flow Cytometry in Hematopathology. A visual approach to data analysis and interpretation. Doyen, Lawrence and Raul.  Flow Cytometric Analysis of Leukemia and Lymphoma - The Basics Wolfgang Hübl