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1 Automated red cell analysis
1 Automated red cell analysis R. T H O M
A hundred years ago the perfection of mechanical and optical techniques had reached a level that allowed the visual enumeration of red cells. The reliability of this estimate outweighed that of the other two relevant parameters, haemoglobin concentration and haematocrit. At that time the estimation of haemoglobin concentration was by simple visual comparison. The haematocrit depended upon suitable centrifuges and anticoagulants which did not influence the volume proportionality between plasma and erythrocytes, and these were not available. As early as 1931, Nageli lamented the absence of a haemoglobin standard 'because it is not possible to judge the results of other investigators... The haematocrit method can hardly be considered reliable'. Today, the situation has changed dramatically and while there are international and national standards for haemoglobin measurements it is the enumeration and characterization of the cell count which has, until recently, been less well-defined. The initial breakthrough in cell counting was made possible by technologies which depended upon the accuracy and speed of electronic components and the cytometry of single cells in a stream of diluent. At the moment, counting and differentiation of blood cells may be effected by either impedance technology or electro-optical methods. The more recent introduction of electronic and flow-cytometric techniques to this area has, however, opened up the possibility of detailed analysis and characterization of the red cell population. This may form the basis for the differential diagnosis of anaemias as well as providing insight into the population kinetics of the erythron pool. The aim of this chapter is to outline the new developments in techniques and to discuss their inherent difficulties and limitations. ELECTRONIC CELL COUNTING The determination of the number of particles in a given fluid is basically very simple. A sample of the cell suspension is carefully diluted in a medium that both preserves the particles' integrity and allows a normal relationship between the diluted and the original sample to be established. The dilution should scatter the particles throughout the fluid in order to eliminate any masking effect which would occur if the concentration was sufficiently high Bailli~re's ClinicalHaematology--
Vol. 3, No. 4, October1990 ISBN0-7020-1475-3
837 Copyright© 1990,byBailli~reTindall All rightsofreproductionin anyformreserved
838
R. THOM
to allow groups or clumps of particles to pass the detecting device. For red cell counting the dilution is usually 1 : 50000 but the use of hydrodynamic focusing methods allows cells to be measured at concentrations two orders greater than this. In these hydrodynamic focused systems cells are placed one at a time in the sensing zone surrounded by diluting medium. The diameter of the axial sample stream is approximately equal to the diameter of the cells under investigation (Figure 1).
Figure 1. Hydrodynamic focusing. The blood sample stream (Jet Flow stained black) is surrounded by particle free sheath fluid. The jet flow in the orifice has the same diameter as a single cell. A back sheath flow (not shown) prevents recirculation of blood cells.
ELECTRICAL DETECTORS The original invention of W. Coulter several decades ago transformed the practice of laboratory haematology. The method which was developed from this used a constricted electrical current path in a fluid medium of different electrical conductivity to that of the suspended particles, and a relative motion between the suspension and the constricted path such that particles passing through that path would modulate the current. In other words, a non-conducting cell passing through an orifice displaced sufficient medium to cause a change in the current which passed through that hole. This created a current pulse which was, in turn, converted into a voltage pulse by a resistor and coupled thereafter to an amplifier circuit. The pulses from the amplifier output were discriminated from noise by setting a voltage threshold and using standard electronic counting techniques. This is still the basis of electrical impedance cell counting.
A U T O M A T E D RED CELL A N A L Y S I S
839
ELECTRO-OPTICAL DETECTORS In transducers based on light scattering, single cells or particles in suspension must pass one at a time through a narrow beam of light. As the cells pass through the microscopic beam, light is scattered from their surface and refracted through the cytoplasm. The light emanating from the cell is then converted into electrical pulses by photomultipliers or photodiodes. This technique lies at the heart of many of the latest automated cell counters. COMPARISON OF ELECTRICAL AND OPTICAL DETECTORS In electrical detectors the resistance impulse is proportional to the volume of the particle passing through the restricted orifice, whereas in electro-optical transducers the light impulse scattered by the cells is proportional to their surface area. Thus, the influence of cell size on electronic resistance is proportional to the third power of the cell diameter, whereas optical signals are proportional to the second power. This endows optical methods with less resolution but a greater range of detection than electrical methods. This capacity to cope with large size differences is especially advantageous in veterinary haematology as the volume of red cells of cattle, rats and mice is half that of human erythrocytes and in goats is only about a quarter. In addition, optical systems have a relatively small sensor volume because they are more easily able to employ hydrodynamic focusing of cells in the sample stream. Light can then be focused at one point and is not dissipated over the whole electrical field of the aperture. This allows the counting chamber in electro-optical systems to be reduced to approach the size of a single blood cell. In optical systems volumes as small as 2-3 pl are commonly obtained, in contrast to the aperture impedance sensing volumes that often exceed 100 pl. Despite the relatively small sensing volume of optical systems it may still be necessary to apply a correction for coincidence counts. In conventional impedance counting systems there is a slow initial rise of the pulse which is caused by the relatively low speed of the particle as it approaches the orifice. The outflow from the stream does not spread and the particle velocity remains high so that it leaves the sensing zone rapidly. The pulse amplitude immediately falls to the base line. This longitudinal acceleration of cells approaching the orifice can be reduced by sheath flow technology. This allows single discreet impulses to be generated which are short enough to permit a high counting rate but nevertheless produce low coincidence loss. In optical systems the asymmetric biconcave shape of the red cell creates a major problem because cells may present either edge-on or in their planar aspect, or at any angle between these two extremes. As a result the size of the pulse depends upon the orientation of the cell in optical systems. In addition, the estimate of cell size in conventional optical systems may be confounded by changes in intracellular haemoglobin concentration. The different characteristics of the two detection methods will result in different perceptions of blood cell parameters. The haematologist should be aware of these differences and appreciate the limitation of the technologies.
840
R. THOM
Not all cell counters are the same, even if they appear to measure the same parameters.
THRESHOLD SETTING When blood cells are counted electronically the signal pulses produced by a specific cell population must be discriminated from other pulses arising within the system. At the extreme, platelet signals can overlap electronic noise caused either by thermal agitation in impedance detection or by light scatter from plasma proteins in optical detectors. In addition, microcytic red cells must be distinguished from platelets and clumped platelets from white cells. For this reason modern instruments use multiple thresholds which may be adiusted by the manufacturers or by the users themselves. The manufacturer will adjust the thresholds on the assumption that the minimum value of the overlap between cell signal impulses and stray pulses is always constant. When the user adjusts the threshold he or she can check whether or not the threshold settings are appropriate for the pulse height distribution produced by each blood sample. This is necessary wherever manufacturers set the various thresholds on the assumption that all blood samples are normal. Automatic threshold adjustment and discrimination has evolved with increasing use of software integrated into the counting system. These adjustments will vary to match the changing nature of the sample. As a result it is now possible to obtain accurate counts of the separate cell populations without operator intervention even in the abnormal range. Where this automated approach cannot reliably discriminate the cell populations the modern counter will alert the operator to the problem. PULSE PROCESSING The high cell counting rate of modern analysers means that each analysis will be based on a count of 50-100000 cells. This reduces the co-efficient of variation of the count to the 1% level. It is, however, fallacious to misinterpret this remarkable conformity as an indication of the instrument's accuracy and the reason for this is related to the way in which the blood cell derived pulses are processed in the counters. There are two basic approaches to particle counting (Figure 2). The first, direct, method measures cell concentration from the fundamental physical dimensions, number and volume; that is, the volume is defined as a liquid column between a start and a stop sensor. The accuracy of the count is therefore limited by the accuracy of this volume definition. The number of particles, corrected for coincidence, counted during the interval between the start and stop signals gives the cell count in that volume. Concentration may then be calculated directly. This is the only principle that may be applicable to reference counters. For the second, indirect count, method, the pulses are counted in relation to time rather than volume. In other words, they measure a count rate rather
841
AUTOMATED RED CELL ANALYSIS
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Figure 2. The principles of direct (left) and indirect (right) cell counting methods. The sample is processed at the top and the analysis sequence is shown below. The pulses are discriminated from background noise and then counted as either the sum of the particles (direct method) or a frequency (indirect method).
than a concentration. The count rate is transformed into a voltage which may be read rather like an automobile speedometer. This voltage may, in turn, be converted to an indirect estimate of the cell count per unit volume by reference to a calibration material during manufacture. The assay value of this material m a y not exactly correspond with the true particle concentration if this material is stabilized. In this respect, it will therefore differ from fresh h u m a n blood. The assay value of stabilized calibrating material for instruments based on indirect counts is therefore related to the specific class of instrument. This value can only be derived from a particular instrument which has been calibrated with fresh blood. The correct results for these fresh blood samples
842
R. THOM
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Figure 3. Errors in electrical detectors. 1: Electrolysis; 2: Air bubbles; 3: Recirculation; 4: Adhesion; 5: Coincidence. Degassing the diluent eliminates 1 and 2, electronic high pass filters obviate 3, hydrophilic coated sample beakers (e.g. TOA-beaker) will prevent 4, a statistical model may be used to eliminate 5.
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Figure 4. Shape factors in impedance based transducers. Particles of the same volume are shown between two electrodes. Increased resistance is registered as the ionic pathway between the electrodes is impeded. The resultant shape factor is shown on the left.
AUTOMATED RED CELL ANALYSIS
843
must in turn have been derived from an instrument using the direct method. This tenous link means that the assay value of the calibrator is only valid for those fresh blood samples measured by a specific instrument and that the relationship is likely to be different for pathological samples. Herein lies the root of the problem of calibrating such instruments. COINCIDENCE CORRECTION An apparent loss in cell counts due to pulse coincidence is the main reason why enumeration of erythrocytes with electronic pulse processing counters has not been established as a reference method (Figure 3). While it is generally assumed that the probability distribution of the data conform to the Poisson equation, other forms of coincidence correction have been proposed. Most of them differ only in the degree of approximation. Thus, the coincidence loss probability depends on the product of the number of cells which flow through the sensing zone of the detector per unit time and of the electronic dead-time which is related to the pulse duration. This pulse is influenced, in turn, by the volume, shape and flexibility (Figure 4) of the particles, by the incidence of noise pulses of long duration, especially those caused by erythrocytes recirculating at the aperture exit, as well as the amplification and aperture current itself. These last two parameters, together with the counting volume, can be compensated by setting appropriate thresholds. Hydrodynamically focused detectors significantly reduce coincidence probability because the cells approach the aperture in single file in the centre of the sensing zone (Figure 5). In addition, the high flow rate means that there is only a short pulse duration. This gives a low sensing dead time and allows a large number of cells to be counted discretely. In conventional impedance detectors this is not the case and the properties of the cells will determine the part of the stream in which they travel. For example, small flexible red cells will travel close to the aperture wall and may occlude the detection of cells in the central stream (Figure 5). This is particularly true when there is an element of abnormal deformability in the erythrocytes. The ability of counters with hydrodynamic focusing to reduce coincidence also allows a greater number of cells to be counted and thereby requires a lesser dilution. This is important because the tendency of cells to attach to container walls is greatly increased as the cell suspension becomes more dilute. Once again, this illustrates how the fundamentals of the technology of automated cell counters may affect the results. FACTORS INFLUENCING RED CELL PARAMETERS
Although cell volume, haemoglobin content and haemoglobin concentration are potentially powerful parameters in the classification of anaemia, they are subject to a number of artefactual factors. The most important of these is the manner in which blood is taken and anti-coagulated. To avoid
844
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systematic bias, careful specimen processing is essential. In general, EDTA is the anti-coagulant of choice because heparin does not prevent platelet aggregation and will thereby produce significant errors in the platelet count. In order to avoid osmotic and pH artefacts it is necessary to maintain the EDTA concentration as low as possible (1 mg anhydrous acid per millilitre
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Figure 5. Systematic errors caused by inhomogeneity of the electrical field in impedance based detectors. Cells may take different pathways through the orifice. (a) In the central flow (A and B) or peripheral flow (C and D) they pass through different electrical potentials (equipotentials shown as dashed lines). (b) Electrical pulses produced by monosized latex particles (diameter, 3 p,m). Particles in the central flow (A and B) produce short duration pulses. Particles in the peripheral flow (C and D) produce a higher apparent volume than A and B. The prolonged pulses produced by C and D will occlude the short pulses of A and B.
AUTOMATED RED CELL ANALYSIS
845
of blood). As far as the choice of appropriate salts is concerned the high solubility of the tripotassium salt (1600g per litre) gives it considerable advantage over the less soluble disodium salt. An appropriate concentration is 1.4 mg per millilitre of blood. Although the tripotassium salt is widely used in North America, it does have an affect on red cell volume. It causes shrinkage due to increased plasma osmotic pressure and pH. As a result tripotassium salts produce discordant MCV and haematocrit values between electronic and manual measurements. This artefact will be randomized if the tube production process does not strictly control the correct amount of anticoagulant; it will also be more pronounced if the tubes are incompletely filled. Time and temperature will also affect the perceived results in different counters in different ways. In general, electrical impedance methods show an apparent linear swelling of red cells with time which is more marked at 22°C than at 4°C. In contrast, optical systems show a lesser degree of swelling at 22°C and at 4°C red cell size remains largely constant over the same period of time. Once blood samples have been taken they should be analysed within a few hours or kept at approximately 4°C. If samples are left so that CO2 can escape, the pH will increase and this will in turn produce cell volume changes.
M E T H O D S FOR M E A S U R I N G CELL SIZE
The pulses produced in an electrical impedance method result in a cell size distribution which is actually the distribution of the pulse height amplitudes. To a first approximation the electrical pulse height generated by cells passing the aperture is proportional to the volume of the particle, so that particlesize distribution can be obtained by linear amplification of the pulses. From this size distribution the mean size can be calculated. However, the nonuniform current density at different locations within the cylindrical orifice makes the pulse height dependent on the path that an individual cell takes through the physical gap (Figure 5). Thus, in order to correlate pulse amplitude with cell size, or more precisely cell volume, it is necessary to fulfil three requirements. (1) The pulse shape and amplitude must not be distorted by uneven current density. This problem can be avoided by employing a hydrodynamic focusing system. (2) The shape and flexibility of the cells must not influence the cell volume measurement. The pulse height distribution cannot be converted into cell size distribution without a knowledge of the morphology of the cell in the aperture. The shape factor which describes the relationship between cell volume and the electrical response is a constant derived by comparing the pulse height of real cells to a theoretical cylindrical particle of the same volume. Such theoretical cells do not alter the flow direction of ions in the diluent and the shape factor for such a cell is given as 1.0 (Figure 4). For a spherical cell the shape factor would be exactly 1.5. Photomicrographs of cells in the aperture show that leukocytes remain spherical while erythro-
846
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cytes stretch considerably into a cigar shape. Young erythrocytes may have a shape factor less than 1.1 while old, harder and more rigid erthrocytes will have a shape factor between 1.1 and 1.2. Platelets in EDTA, like leukocytes, remain spherical in the aperture and adopt a shape with a factor of 1.5. The interaction of shape factor and perceived count is an unavoidable complication when calibrating the instrument with latex particles or when attempting to express cell volume as an absolute size. In pathological samples where the MCHC is raised, such as hereditary spherocytosis, the rigidity of the cell gives a relatively high shape factor in the impedance method. As a result, the MCV is overestimated and the M C H C is underestimated. Similarly, stabilized cell preparations for control materials will behave differently to fresh bloods and this must limit their usefulness for calibration purposes. This will be exacerbated if these cells are exposed to different diluents for different times. (3) For change in resistance to be proportional to cell volume it is necessary for the cell membrane to be intact. If it is not, the insulating property of the membrane will be lost and there will be ionic flow through the cell. This will make the cell appear 'transparent' in the impedance system and its volume will be underestimated. Haematologists should not assume that all modern automated blood counters are equal in these respects.
DUAL PARAMETER OPTICAL DETECTOR In optical systems a cell in the light path will show either fluorescence, absorbance or surface scatter. Basic haematology analysers use only the scattering properties of the cells. This produces a less sophisticated and less informative measure of cell size and characteristics than the impedance methods. As indicated previously, orientation of the cells in the light path is a major factor in the appreciation of their size. In addition, the optical density of the cells will affect the amount and direction of the scattered light. Light scatter will also be generated from the internal structures of the circulating blood cells. More recently, optical detectors have been devised which overcome these limitations. Such counters are also able to measure the haemoglobin concentration of individual red cells. However, they depend on the isovolumetric spheric transformation of the native red cells. This is achieved by surface active substances which shrink the membrane until a sphere is formed without altering the total volume of the cell (Figure 6); the sphere shape is then fixed before it is presented to the detector. The light scattered from these cells is measured at two separate angles to give simultaneous measures of volume and haemoglobin concentration. The interaction between these two parameters may be deconvoluted by a non-linear multidimensional analysis using relatively sophisticated software. Results obtained by this method have pointed to errors in haemoglobinometry and derived red cell parameters. Lipaemic samples and those with high white cell counts will give falsely high readings with simple haemoglobinometry. The
AUTOMATED RED CELL ANALYSIS
847
same is true of samples with cold agglutinins. In these samples, haemoglobin concentration can be calculated from measurement of cellular haemoglobin and volume.
(a)
(b) Figure 6. Human red cells (a) undergo isovolumetric spheric transformation (b) in the presence of lysolecthin. This transformation is a necessary prelude to the measurement of red cell volume and haemoglobin concentration in two angle optical detectors.
848
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METHODS TO CHECK MORPHOLOGICAL AND NUMERICAL ANALYSIS
The detection of anisocytosis should be a useful and important step in haematological diagnosis. Heretofore methods for measuring it have not been entirely successful. This is in part because the red cell distribution histogram reflects both single and coincident cells which causes asymmetry in the distribution at the upper end. To achieve an adequate definition of the red cell histogram it is necessary to count a large number of cells which requires a relatively high cell concentration in the sample at analysis. The disadvantage of this is that the high concentration will increase the possibility of coincidence and thereby increase the coefficient of variation of the red cell distribution width. This effect can be demonstrated by concentrating red cells by centrifugation and using the plasma that is removed to dilute another aliquot of the same sample. It is then possible to compare the red cell distribution of the diluted and the concentrated suspension of the same cells. In many instruments the left-hand side of the distribution will remain unchanged but the right-hand side will show a significantly wider distribution in the concentrated sample. Unless the coincidence counts are removed electronically this effect will result in an increased MCV and haematocrit. However, this editing might disbar cells that should be counted. Before haematologists can make use of the valuable information in the red cell distribution data, the interdependance of the distribution width and the derived MCV and haematocrit must be resolved. At the moment none of the routine blood cell counters cope with all these problems, although most of them could be made to do so. Because of the absence of any reference counting method it is not possible to make quantative estimates of the inaccuracy of the various cell-counting systems. Comparison between instruments using different principles of analysis will give an indication of the validity of the estimate if they both give the same result (Figure 7). If they do not agree, the question as to which is right can only be answered by resort to another independent process. At the moment the best way to check accuracy is by comparing the observed and expected counts over a range of values established by diluting fresh blood samples using autologous plasma. Saline or other diluents will alter the counting characteristics and confound the results; they must not be used. As far as red cells are concerned, the MCH should stay constant whatever the dilution. The routine laboratory should not be expected to have to solve the fundamental problems of calibration. However, in some reference laboratories it will be necessary to establish a sound basis for the calibration of automated cell counters. This will require the use of gravimetric methods to achieve accurate dilution of blood samples. They are an order of magnitude more accurate than methods which depend on volumetric measurement but are tedious and time-consuming and certainly not to be undertaken in the routine laboratory. However, we all need there to be laboratories which are able to establish the accuracy of blood counting methods and to compare equipment against absolute standards. Without these, haematology would be adrift without a compass.
849
AUTOMATED RED CELL ANALYSIS 110-
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y = 0 . 9 6 4 x + 3.309
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Acknowledgements I wish to acknowledge the considerable assistance given by Toa Medical Electronics (Europe) GMBH, and in particular the sterling efforts of M. Kutzner in the preparation of this chapter.
BIBLIOGRAPHY Thorn R (1979) Rationalisierung h~imatologischer Untersuchungen (Rationalization of hematological tests). In: Haeckel R (ed,) Rationalisierung des Medizinischen Laboratoriums. Darmstadt: GIT Giebeler. Thom R (1981) Calibration in haematology. In: Rosalki SB (ed.) New Approaches to Laboratory Medicine, pp 3-15. Darmstadt: GIT Giebeler. Thorn R (1985) Einflug von reagenzien und materialien auf hfimatologische mefSergebnisse und probleme der standardisierung mit kalibriermaterial (Influence of reagents and materials on hematological results and problems to standardize with calibration material). Laboratory Medicine 9: 98.
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Thom R & Kachel V (1970) Fortschritte fiir die elektronische gr6ssenbestimmung von blutk6rperchen (Progress on the electronic size measurement of blood particles). Blut 21: 48. Thorn R, Hampe A & Sauerbrey G (1969) Die elektronisehe volumenbestimmung von blutk6rperchen und ihre fehlerquellen (The electronic volumetric measurement of blood particles and related source of errors). Zeitschriftfiir die Gesamte Experirnentelle Medizin 151: 331-349.
A hundred years ago the perfection of mechanical and optical techniques had reached a level that allowed the visual enumeration of red cells. The reliability of this estimate outweighed that of the other two relevant parameters, haemoglobin concentration and haematocrit. At that time the estimation of haemoglobin concentration was by simple visual comparison. The haematocrit depended upon suitable centrifuges and anticoagulants which did not influence the volume proportionality between plasma and erythrocytes, and these were not available. As early as 1931, Nageli lamented the absence of a haemoglobin standard 'because it is not possible to judge the results of other investigators... The haematocrit method can hardly be considered reliable'. Today, the situation has changed dramatically and while there are international and national standards for haemoglobin measurements it is the enumeration and characterization of the cell count which has, until recently, been less well-defined. The initial breakthrough in cell counting was made possible by technologies which depended upon the accuracy and speed of electronic components and the cytometry of single cells in a stream of diluent. At the moment, counting and differentiation of blood cells may be effected by either impedance technology or electro-optical methods. The more recent introduction of electronic and flow-cytometric techniques to this area has, however, opened up the possibility of detailed analysis and characterization of the red cell population. This may form the basis for the differential diagnosis of anaemias as well as providing insight into the population kinetics of the erythron pool. The aim of this chapter is to outline the new developments in techniques and to discuss their inherent difficulties and limitations. ELECTRONIC CELL COUNTING The determination of the number of particles in a given fluid is basically very simple. A sample of the cell suspension is carefully diluted in a medium that both preserves the particles' integrity and allows a normal relationship between the diluted and the original sample to be established. The dilution should scatter the particles throughout the fluid in order to eliminate any masking effect which would occur if the concentration was sufficiently high Bailli~re's ClinicalHaematology--
Vol. 3, No. 4, October1990 ISBN0-7020-1475-3
837 Copyright© 1990,byBailli~reTindall All rightsofreproductionin anyformreserved
838
R. THOM
to allow groups or clumps of particles to pass the detecting device. For red cell counting the dilution is usually 1 : 50000 but the use of hydrodynamic focusing methods allows cells to be measured at concentrations two orders greater than this. In these hydrodynamic focused systems cells are placed one at a time in the sensing zone surrounded by diluting medium. The diameter of the axial sample stream is approximately equal to the diameter of the cells under investigation (Figure 1).
Figure 1. Hydrodynamic focusing. The blood sample stream (Jet Flow stained black) is surrounded by particle free sheath fluid. The jet flow in the orifice has the same diameter as a single cell. A back sheath flow (not shown) prevents recirculation of blood cells.
ELECTRICAL DETECTORS The original invention of W. Coulter several decades ago transformed the practice of laboratory haematology. The method which was developed from this used a constricted electrical current path in a fluid medium of different electrical conductivity to that of the suspended particles, and a relative motion between the suspension and the constricted path such that particles passing through that path would modulate the current. In other words, a non-conducting cell passing through an orifice displaced sufficient medium to cause a change in the current which passed through that hole. This created a current pulse which was, in turn, converted into a voltage pulse by a resistor and coupled thereafter to an amplifier circuit. The pulses from the amplifier output were discriminated from noise by setting a voltage threshold and using standard electronic counting techniques. This is still the basis of electrical impedance cell counting.
A U T O M A T E D RED CELL A N A L Y S I S
839
ELECTRO-OPTICAL DETECTORS In transducers based on light scattering, single cells or particles in suspension must pass one at a time through a narrow beam of light. As the cells pass through the microscopic beam, light is scattered from their surface and refracted through the cytoplasm. The light emanating from the cell is then converted into electrical pulses by photomultipliers or photodiodes. This technique lies at the heart of many of the latest automated cell counters. COMPARISON OF ELECTRICAL AND OPTICAL DETECTORS In electrical detectors the resistance impulse is proportional to the volume of the particle passing through the restricted orifice, whereas in electro-optical transducers the light impulse scattered by the cells is proportional to their surface area. Thus, the influence of cell size on electronic resistance is proportional to the third power of the cell diameter, whereas optical signals are proportional to the second power. This endows optical methods with less resolution but a greater range of detection than electrical methods. This capacity to cope with large size differences is especially advantageous in veterinary haematology as the volume of red cells of cattle, rats and mice is half that of human erythrocytes and in goats is only about a quarter. In addition, optical systems have a relatively small sensor volume because they are more easily able to employ hydrodynamic focusing of cells in the sample stream. Light can then be focused at one point and is not dissipated over the whole electrical field of the aperture. This allows the counting chamber in electro-optical systems to be reduced to approach the size of a single blood cell. In optical systems volumes as small as 2-3 pl are commonly obtained, in contrast to the aperture impedance sensing volumes that often exceed 100 pl. Despite the relatively small sensing volume of optical systems it may still be necessary to apply a correction for coincidence counts. In conventional impedance counting systems there is a slow initial rise of the pulse which is caused by the relatively low speed of the particle as it approaches the orifice. The outflow from the stream does not spread and the particle velocity remains high so that it leaves the sensing zone rapidly. The pulse amplitude immediately falls to the base line. This longitudinal acceleration of cells approaching the orifice can be reduced by sheath flow technology. This allows single discreet impulses to be generated which are short enough to permit a high counting rate but nevertheless produce low coincidence loss. In optical systems the asymmetric biconcave shape of the red cell creates a major problem because cells may present either edge-on or in their planar aspect, or at any angle between these two extremes. As a result the size of the pulse depends upon the orientation of the cell in optical systems. In addition, the estimate of cell size in conventional optical systems may be confounded by changes in intracellular haemoglobin concentration. The different characteristics of the two detection methods will result in different perceptions of blood cell parameters. The haematologist should be aware of these differences and appreciate the limitation of the technologies.
840
R. THOM
Not all cell counters are the same, even if they appear to measure the same parameters.
THRESHOLD SETTING When blood cells are counted electronically the signal pulses produced by a specific cell population must be discriminated from other pulses arising within the system. At the extreme, platelet signals can overlap electronic noise caused either by thermal agitation in impedance detection or by light scatter from plasma proteins in optical detectors. In addition, microcytic red cells must be distinguished from platelets and clumped platelets from white cells. For this reason modern instruments use multiple thresholds which may be adiusted by the manufacturers or by the users themselves. The manufacturer will adjust the thresholds on the assumption that the minimum value of the overlap between cell signal impulses and stray pulses is always constant. When the user adjusts the threshold he or she can check whether or not the threshold settings are appropriate for the pulse height distribution produced by each blood sample. This is necessary wherever manufacturers set the various thresholds on the assumption that all blood samples are normal. Automatic threshold adjustment and discrimination has evolved with increasing use of software integrated into the counting system. These adjustments will vary to match the changing nature of the sample. As a result it is now possible to obtain accurate counts of the separate cell populations without operator intervention even in the abnormal range. Where this automated approach cannot reliably discriminate the cell populations the modern counter will alert the operator to the problem. PULSE PROCESSING The high cell counting rate of modern analysers means that each analysis will be based on a count of 50-100000 cells. This reduces the co-efficient of variation of the count to the 1% level. It is, however, fallacious to misinterpret this remarkable conformity as an indication of the instrument's accuracy and the reason for this is related to the way in which the blood cell derived pulses are processed in the counters. There are two basic approaches to particle counting (Figure 2). The first, direct, method measures cell concentration from the fundamental physical dimensions, number and volume; that is, the volume is defined as a liquid column between a start and a stop sensor. The accuracy of the count is therefore limited by the accuracy of this volume definition. The number of particles, corrected for coincidence, counted during the interval between the start and stop signals gives the cell count in that volume. Concentration may then be calculated directly. This is the only principle that may be applicable to reference counters. For the second, indirect count, method, the pulses are counted in relation to time rather than volume. In other words, they measure a count rate rather
841
AUTOMATED RED CELL ANALYSIS
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n volt
a~ t :
voltage
label
analog-digital converter (voltage number) display = 5000//zl DIRECT
INDIRECT
Figure 2. The principles of direct (left) and indirect (right) cell counting methods. The sample is processed at the top and the analysis sequence is shown below. The pulses are discriminated from background noise and then counted as either the sum of the particles (direct method) or a frequency (indirect method).
than a concentration. The count rate is transformed into a voltage which may be read rather like an automobile speedometer. This voltage may, in turn, be converted to an indirect estimate of the cell count per unit volume by reference to a calibration material during manufacture. The assay value of this material m a y not exactly correspond with the true particle concentration if this material is stabilized. In this respect, it will therefore differ from fresh h u m a n blood. The assay value of stabilized calibrating material for instruments based on indirect counts is therefore related to the specific class of instrument. This value can only be derived from a particular instrument which has been calibrated with fresh blood. The correct results for these fresh blood samples
842
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Counter
I 90 °C
iiiii I 1111111I
Iiiiiii I' I'1"1'1"1 Illl i Il lI lIlI
'IIII~ Iii /~, la- I b <. J
L,
Figure 3. Errors in electrical detectors. 1: Electrolysis; 2: Air bubbles; 3: Recirculation; 4: Adhesion; 5: Coincidence. Degassing the diluent eliminates 1 and 2, electronic high pass filters obviate 3, hydrophilic coated sample beakers (e.g. TOA-beaker) will prevent 4, a statistical model may be used to eliminate 5.
~2
Factor 1
Cylinder
1.5
Sphere
1.05
Reticulocyte Erythrocyte
~1.1
Spherocyte
1.25
Fixed
~1.2
Erythrocyte SCHEMATICELECTROLYTICCELL
Figure 4. Shape factors in impedance based transducers. Particles of the same volume are shown between two electrodes. Increased resistance is registered as the ionic pathway between the electrodes is impeded. The resultant shape factor is shown on the left.
AUTOMATED RED CELL ANALYSIS
843
must in turn have been derived from an instrument using the direct method. This tenous link means that the assay value of the calibrator is only valid for those fresh blood samples measured by a specific instrument and that the relationship is likely to be different for pathological samples. Herein lies the root of the problem of calibrating such instruments. COINCIDENCE CORRECTION An apparent loss in cell counts due to pulse coincidence is the main reason why enumeration of erythrocytes with electronic pulse processing counters has not been established as a reference method (Figure 3). While it is generally assumed that the probability distribution of the data conform to the Poisson equation, other forms of coincidence correction have been proposed. Most of them differ only in the degree of approximation. Thus, the coincidence loss probability depends on the product of the number of cells which flow through the sensing zone of the detector per unit time and of the electronic dead-time which is related to the pulse duration. This pulse is influenced, in turn, by the volume, shape and flexibility (Figure 4) of the particles, by the incidence of noise pulses of long duration, especially those caused by erythrocytes recirculating at the aperture exit, as well as the amplification and aperture current itself. These last two parameters, together with the counting volume, can be compensated by setting appropriate thresholds. Hydrodynamically focused detectors significantly reduce coincidence probability because the cells approach the aperture in single file in the centre of the sensing zone (Figure 5). In addition, the high flow rate means that there is only a short pulse duration. This gives a low sensing dead time and allows a large number of cells to be counted discretely. In conventional impedance detectors this is not the case and the properties of the cells will determine the part of the stream in which they travel. For example, small flexible red cells will travel close to the aperture wall and may occlude the detection of cells in the central stream (Figure 5). This is particularly true when there is an element of abnormal deformability in the erythrocytes. The ability of counters with hydrodynamic focusing to reduce coincidence also allows a greater number of cells to be counted and thereby requires a lesser dilution. This is important because the tendency of cells to attach to container walls is greatly increased as the cell suspension becomes more dilute. Once again, this illustrates how the fundamentals of the technology of automated cell counters may affect the results. FACTORS INFLUENCING RED CELL PARAMETERS
Although cell volume, haemoglobin content and haemoglobin concentration are potentially powerful parameters in the classification of anaemia, they are subject to a number of artefactual factors. The most important of these is the manner in which blood is taken and anti-coagulated. To avoid
844
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systematic bias, careful specimen processing is essential. In general, EDTA is the anti-coagulant of choice because heparin does not prevent platelet aggregation and will thereby produce significant errors in the platelet count. In order to avoid osmotic and pH artefacts it is necessary to maintain the EDTA concentration as low as possible (1 mg anhydrous acid per millilitre
(a)
/....,£.
r
', I I
D c
' ' I l i a
Figure 5. Systematic errors caused by inhomogeneity of the electrical field in impedance based detectors. Cells may take different pathways through the orifice. (a) In the central flow (A and B) or peripheral flow (C and D) they pass through different electrical potentials (equipotentials shown as dashed lines). (b) Electrical pulses produced by monosized latex particles (diameter, 3 p,m). Particles in the central flow (A and B) produce short duration pulses. Particles in the peripheral flow (C and D) produce a higher apparent volume than A and B. The prolonged pulses produced by C and D will occlude the short pulses of A and B.
AUTOMATED RED CELL ANALYSIS
845
of blood). As far as the choice of appropriate salts is concerned the high solubility of the tripotassium salt (1600g per litre) gives it considerable advantage over the less soluble disodium salt. An appropriate concentration is 1.4 mg per millilitre of blood. Although the tripotassium salt is widely used in North America, it does have an affect on red cell volume. It causes shrinkage due to increased plasma osmotic pressure and pH. As a result tripotassium salts produce discordant MCV and haematocrit values between electronic and manual measurements. This artefact will be randomized if the tube production process does not strictly control the correct amount of anticoagulant; it will also be more pronounced if the tubes are incompletely filled. Time and temperature will also affect the perceived results in different counters in different ways. In general, electrical impedance methods show an apparent linear swelling of red cells with time which is more marked at 22°C than at 4°C. In contrast, optical systems show a lesser degree of swelling at 22°C and at 4°C red cell size remains largely constant over the same period of time. Once blood samples have been taken they should be analysed within a few hours or kept at approximately 4°C. If samples are left so that CO2 can escape, the pH will increase and this will in turn produce cell volume changes.
M E T H O D S FOR M E A S U R I N G CELL SIZE
The pulses produced in an electrical impedance method result in a cell size distribution which is actually the distribution of the pulse height amplitudes. To a first approximation the electrical pulse height generated by cells passing the aperture is proportional to the volume of the particle, so that particlesize distribution can be obtained by linear amplification of the pulses. From this size distribution the mean size can be calculated. However, the nonuniform current density at different locations within the cylindrical orifice makes the pulse height dependent on the path that an individual cell takes through the physical gap (Figure 5). Thus, in order to correlate pulse amplitude with cell size, or more precisely cell volume, it is necessary to fulfil three requirements. (1) The pulse shape and amplitude must not be distorted by uneven current density. This problem can be avoided by employing a hydrodynamic focusing system. (2) The shape and flexibility of the cells must not influence the cell volume measurement. The pulse height distribution cannot be converted into cell size distribution without a knowledge of the morphology of the cell in the aperture. The shape factor which describes the relationship between cell volume and the electrical response is a constant derived by comparing the pulse height of real cells to a theoretical cylindrical particle of the same volume. Such theoretical cells do not alter the flow direction of ions in the diluent and the shape factor for such a cell is given as 1.0 (Figure 4). For a spherical cell the shape factor would be exactly 1.5. Photomicrographs of cells in the aperture show that leukocytes remain spherical while erythro-
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R. THOM
cytes stretch considerably into a cigar shape. Young erythrocytes may have a shape factor less than 1.1 while old, harder and more rigid erthrocytes will have a shape factor between 1.1 and 1.2. Platelets in EDTA, like leukocytes, remain spherical in the aperture and adopt a shape with a factor of 1.5. The interaction of shape factor and perceived count is an unavoidable complication when calibrating the instrument with latex particles or when attempting to express cell volume as an absolute size. In pathological samples where the MCHC is raised, such as hereditary spherocytosis, the rigidity of the cell gives a relatively high shape factor in the impedance method. As a result, the MCV is overestimated and the M C H C is underestimated. Similarly, stabilized cell preparations for control materials will behave differently to fresh bloods and this must limit their usefulness for calibration purposes. This will be exacerbated if these cells are exposed to different diluents for different times. (3) For change in resistance to be proportional to cell volume it is necessary for the cell membrane to be intact. If it is not, the insulating property of the membrane will be lost and there will be ionic flow through the cell. This will make the cell appear 'transparent' in the impedance system and its volume will be underestimated. Haematologists should not assume that all modern automated blood counters are equal in these respects.
DUAL PARAMETER OPTICAL DETECTOR In optical systems a cell in the light path will show either fluorescence, absorbance or surface scatter. Basic haematology analysers use only the scattering properties of the cells. This produces a less sophisticated and less informative measure of cell size and characteristics than the impedance methods. As indicated previously, orientation of the cells in the light path is a major factor in the appreciation of their size. In addition, the optical density of the cells will affect the amount and direction of the scattered light. Light scatter will also be generated from the internal structures of the circulating blood cells. More recently, optical detectors have been devised which overcome these limitations. Such counters are also able to measure the haemoglobin concentration of individual red cells. However, they depend on the isovolumetric spheric transformation of the native red cells. This is achieved by surface active substances which shrink the membrane until a sphere is formed without altering the total volume of the cell (Figure 6); the sphere shape is then fixed before it is presented to the detector. The light scattered from these cells is measured at two separate angles to give simultaneous measures of volume and haemoglobin concentration. The interaction between these two parameters may be deconvoluted by a non-linear multidimensional analysis using relatively sophisticated software. Results obtained by this method have pointed to errors in haemoglobinometry and derived red cell parameters. Lipaemic samples and those with high white cell counts will give falsely high readings with simple haemoglobinometry. The
AUTOMATED RED CELL ANALYSIS
847
same is true of samples with cold agglutinins. In these samples, haemoglobin concentration can be calculated from measurement of cellular haemoglobin and volume.
(a)
(b) Figure 6. Human red cells (a) undergo isovolumetric spheric transformation (b) in the presence of lysolecthin. This transformation is a necessary prelude to the measurement of red cell volume and haemoglobin concentration in two angle optical detectors.
848
R. THOM
METHODS TO CHECK MORPHOLOGICAL AND NUMERICAL ANALYSIS
The detection of anisocytosis should be a useful and important step in haematological diagnosis. Heretofore methods for measuring it have not been entirely successful. This is in part because the red cell distribution histogram reflects both single and coincident cells which causes asymmetry in the distribution at the upper end. To achieve an adequate definition of the red cell histogram it is necessary to count a large number of cells which requires a relatively high cell concentration in the sample at analysis. The disadvantage of this is that the high concentration will increase the possibility of coincidence and thereby increase the coefficient of variation of the red cell distribution width. This effect can be demonstrated by concentrating red cells by centrifugation and using the plasma that is removed to dilute another aliquot of the same sample. It is then possible to compare the red cell distribution of the diluted and the concentrated suspension of the same cells. In many instruments the left-hand side of the distribution will remain unchanged but the right-hand side will show a significantly wider distribution in the concentrated sample. Unless the coincidence counts are removed electronically this effect will result in an increased MCV and haematocrit. However, this editing might disbar cells that should be counted. Before haematologists can make use of the valuable information in the red cell distribution data, the interdependance of the distribution width and the derived MCV and haematocrit must be resolved. At the moment none of the routine blood cell counters cope with all these problems, although most of them could be made to do so. Because of the absence of any reference counting method it is not possible to make quantative estimates of the inaccuracy of the various cell-counting systems. Comparison between instruments using different principles of analysis will give an indication of the validity of the estimate if they both give the same result (Figure 7). If they do not agree, the question as to which is right can only be answered by resort to another independent process. At the moment the best way to check accuracy is by comparing the observed and expected counts over a range of values established by diluting fresh blood samples using autologous plasma. Saline or other diluents will alter the counting characteristics and confound the results; they must not be used. As far as red cells are concerned, the MCH should stay constant whatever the dilution. The routine laboratory should not be expected to have to solve the fundamental problems of calibration. However, in some reference laboratories it will be necessary to establish a sound basis for the calibration of automated cell counters. This will require the use of gravimetric methods to achieve accurate dilution of blood samples. They are an order of magnitude more accurate than methods which depend on volumetric measurement but are tedious and time-consuming and certainly not to be undertaken in the routine laboratory. However, we all need there to be laboratories which are able to establish the accuracy of blood counting methods and to compare equipment against absolute standards. Without these, haematology would be adrift without a compass.
849
AUTOMATED RED CELL ANALYSIS 110-
105
y = 0 . 9 6 4 x + 3.309
-
r = 0.987 n = 85
100-
95-
8 0
+ a-~+
90-
=, UJ
z
85-
>(J
80-
757065-
/ /+
60 60
70 '
8'0
9'0
100 '
'
110 '
MCV,fl (Technicon H 1 )
Figure 7. Comparison of red cell volume measured by an electro-optical detector (Technicon HI) and an electrical detector with hydrodynamic focusing (Sysmex NE-8000). There is close correspondence over a wide range of normal and abnormal samples.
Acknowledgements I wish to acknowledge the considerable assistance given by Toa Medical Electronics (Europe) GMBH, and in particular the sterling efforts of M. Kutzner in the preparation of this chapter.
BIBLIOGRAPHY Thorn R (1979) Rationalisierung h~imatologischer Untersuchungen (Rationalization of hematological tests). In: Haeckel R (ed,) Rationalisierung des Medizinischen Laboratoriums. Darmstadt: GIT Giebeler. Thom R (1981) Calibration in haematology. In: Rosalki SB (ed.) New Approaches to Laboratory Medicine, pp 3-15. Darmstadt: GIT Giebeler. Thorn R (1985) Einflug von reagenzien und materialien auf hfimatologische mefSergebnisse und probleme der standardisierung mit kalibriermaterial (Influence of reagents and materials on hematological results and problems to standardize with calibration material). Laboratory Medicine 9: 98.
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Thom R & Kachel V (1970) Fortschritte fiir die elektronische gr6ssenbestimmung von blutk6rperchen (Progress on the electronic size measurement of blood particles). Blut 21: 48. Thorn R, Hampe A & Sauerbrey G (1969) Die elektronisehe volumenbestimmung von blutk6rperchen und ihre fehlerquellen (The electronic volumetric measurement of blood particles and related source of errors). Zeitschriftfiir die Gesamte Experirnentelle Medizin 151: 331-349.