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Improving quantitation of malaria parasite burden with digital image analysis
Transactions of the Royal Society of Tropical Medicine and Hygiene (2008) 102, 1062—1063
available at www.sciencedirect.com
journal homepage: www.elsevierhealth.com/journals/trst
MINI-REVIEW
Improving quantitation of malaria parasite burden with digital image analysis John Frean Parasitology Reference Unit, National Institute for Communicable Diseases and University of the Witwatersrand, Johannesburg, South Africa Available online 2 June 2008
KEYWORDS Malaria; Parasites; Parasite burden; Quantitation; Technology; Digital image analysis
Summary Quantitation of malaria parasite burden has prognostic value as well as providing objective evidence of response to treatment or, potentially, to vaccination against malaria. Estimation of parasite load by microscopy is prone to inaccuracy and inconsistency. Digital image analysis is well suited to this application rather than to the more difficult task of malaria diagnosis and species identification. Preliminary work has shown the feasibility of using off-theshelf hardware and software. Standardised banks of slides for comparing human and machine counts, cheaper imaging methods for laboratories with limited resources, and customisation of readily available image analysis software are proposed as priority needs. © 2008 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved.
Digital image analysis has been applied to the detection and identification of malaria species with variable success (Ross et al., 2006). It is clearly difficult to reproduce artificially in full the ability of a trained and experienced microscopist to identify and discriminate between malaria parasite species and stages. However, a closely related topic that has not received much attention is the practical application of image analysis techniques to malaria parasite quantitation in field studies, as opposed to experimental in vitro-cultured parasites (Sio et al., 2007). Estimation of haematozoan parasitaemia in birds and other non-mammalian vertebrates (Gering and Atkinson, 2004) is more amenable to digital image analysis techniques because their nucleated erythrocytes are readily recognised and counted by the software. Unlike other human malaria species, Plasmodium falciparum has the capacity for nearly unlimited replication in the human host, and very high parasitaemias (>50% of erythrocytes infected) are possible in falciparum infections.
E-mail address: [email protected]
Assessment of the parasite burden provides a useful indicator of the severity of infection, particularly in non-immune patients, and the level of parasitaemia correlates generally with clinical features and prognosis. Thus, although there is no uniformly agreed definition of hyperparasitaemia, >4% (or >5%) parasitaemia or >100 000 parasites/l are commonly regarded as indicators of risk of severe malaria in a lowtransmission setting (WHO, 2006). Parasite load monitoring is an objective way of monitoring response to treatment, especially in the presence of possible drug-resistant P. falciparum, as well as (potentially) assessing vaccine efficacy. However, there are some caveats: peripheral blood parasitaemia may well not accurately reflect the total body burden of parasites because of sequestration of parasitised erythrocytes in the capillaries and venules of the deep circulation. As an alternative, the proportion of malaria pigment-containing neutrophils has been used as an indirect measure of recent parasite replication. There are several methods of expressing the parasite load, most commonly as the percentage of infected erythrocytes counted on a stained thin blood film (e.g. 1%
0035-9203/$ — see front matter © 2008 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.trstmh.2008.04.017
Digital image analysis for quantitation of malaria parasite burden parasitaemia) or the number of parasites per unit volume of blood (e.g. 5000 parasites/l). The latter is usually assessed on a thick film by counting parasites against leukocytes (100, 200 or more), then multiplying by either the patient’s own leukocyte count, if available, or an assumed count of 8000/l. When the parasite count is either very high or very low, these thick film and thin film counts, respectively, are inaccurate. Another method is to count parasites in an assumed volume of blood per high power field on the thick film (Greenwood and Armstrong, 1991), but this is not widely used. Semiquantitation (parasite density graded as + through ++++), although often used in laboratories in developing countries, is inherently imprecise and therefore less satisfactory than the other methods. Rapid immunochromatographic (dipstick) or centrifuged capillary tube (QBC) tests are not suitable for measuring and tracking parasite density. Recent national programmatic proficiency testing of qualitative malaria laboratory diagnosis in South African medical laboratories has yielded disappointing results (Dini and Frean, 2003). As assessed in the same proficiency testing programme, the ability of laboratories to measure parasite loads is generally poor. In a recent quantitation exercise using a specimen with 14.3% parasitaemia, only 49% of 134 responding laboratories achieved acceptable results. Of special concern was the wide range of counts reported (0.08—68%). Whilst trained technologists readily recognise and count parasitised erythrocytes (the numerator) in an adequately stained thin film, estimating the denominator (total number of erythrocytes) of the required fraction is the source of most error (Gering and Atkinson, 2004). Use of a simple microscope eyepiece graticule (Miller squares; Graticules Ltd., Tonbridge, UK) markedly improves the accuracy and reproducibility of parasitaemia estimates. This technique was originally used for reticulocyte counts, where it was shown to produce smaller standard errors than the conventional method. The technique cannot be applied to parasite load quantitation on most thick films because of the typical locally uneven dispersion of parasites. It is also rather slow and therefore not suitable for busy laboratories. I suggest that modern digital techniques have the potential to improve the accuracy of quantitation both on thick and thin films. A pilot study using a standard laboratory microscope (Olympus BX40) plus phototube, a digital microscope camera (Nikon DS-U1), Eclipse Net imaging software (Nikon Instruments Europe BV, Badhoevedorp, The Netherlands) and image analysis software (ImageJ, an NIHdeveloped program) produced promising results and a larger comparison of digital and conventional microscopic quantitation is in progress. Potential advantages over conventional methods are improved accuracy and precision, reproducibility and objectivity of the counts. An obvious disadvantage of the method as experimented with so far is the time required both to capture a sufficient number of fields and to perform
1063
the digital manipulations on each, which includes resolving the problem of touching or overlapping erythrocytes. A more general issue is the cost of equipment and software that is needed. To optimise this approach to quantitation there are three requirements to be addressed: first, a bank of well standardised specimens that can be used confidently to assess and compare various approaches to digital counting; second, an alternative to the standard microscope—camera combination, for example a camera that fits in the eyepiece of any standard laboratory microscope, attaches to a standard personal computer and uses free software to capture and save images; and finally, adaptation and optimisation of readily available image analysis software to make this technology usable in routine practice. Ultimately, in malaria-endemic areas, laboratories, clinicians and patients could benefit from this technology. Acknowledgements: Thanks go to Leigh Dini, Rita van Deventer and Bhavani Poonsamy for producing, staining and manually counting blood films. Funding: National Institute for Communicable Diseases, Johannesburg, South Africa. Conflicts of interest: None declared. Ethical approval: Specimens for blood film production were collected under ethical clearance from the Human Research Ethics Committee (Medical), University of the Witwatersrand, Johannesburg, South Africa.
References Dini, L., Frean, J., 2003. Quality assessment of malaria laboratory diagnosis in South Africa. Trans. R. Soc. Trop. Med. Hyg. 97, 675—677. Gering, E., Atkinson, C.T., 2004. A rapid method for counting nucleated erythrocytes on stained blood smears by digital image analysis. J. Parasitol. 90, 879—881. Greenwood, B.M., Armstrong, J.R.M., 1991. Comparison of two simple methods for determining malaria parasite density. Trans. R. Soc. Trop. Med. Hyg. 85, 186—188. Ross, N.E., Pritchard, C.J., Rubin, D.M., Dus´ e, A., 2006. Automated image processing method for the diagnosis and classification of malaria on thin blood smears. Med. Biol. Eng. Comput. 44, 427—436. Sio, S.W., Sun, W., Kumar, S., Bin, W.Z., Tan, S.S., Ong, S.H., Kikuchi, H., Oshima, Y., Tan, K.S.W., 2007. MalariaCount: an image analysis-based program for the accurate determination of parasitemia. J. Microbiol. Methods 68, 11—18. WHO, 2006. Guidelines for the Treatment of Malaria. WHO/HTM/MAL/2006.1108. World Health Organization, Geneva. http://whqlibdoc.who.int/publications/2006/9241546948 eng. pdf [accessed 28 March 2007].
available at www.sciencedirect.com
journal homepage: www.elsevierhealth.com/journals/trst
MINI-REVIEW
Improving quantitation of malaria parasite burden with digital image analysis John Frean Parasitology Reference Unit, National Institute for Communicable Diseases and University of the Witwatersrand, Johannesburg, South Africa Available online 2 June 2008
KEYWORDS Malaria; Parasites; Parasite burden; Quantitation; Technology; Digital image analysis
Summary Quantitation of malaria parasite burden has prognostic value as well as providing objective evidence of response to treatment or, potentially, to vaccination against malaria. Estimation of parasite load by microscopy is prone to inaccuracy and inconsistency. Digital image analysis is well suited to this application rather than to the more difficult task of malaria diagnosis and species identification. Preliminary work has shown the feasibility of using off-theshelf hardware and software. Standardised banks of slides for comparing human and machine counts, cheaper imaging methods for laboratories with limited resources, and customisation of readily available image analysis software are proposed as priority needs. © 2008 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved.
Digital image analysis has been applied to the detection and identification of malaria species with variable success (Ross et al., 2006). It is clearly difficult to reproduce artificially in full the ability of a trained and experienced microscopist to identify and discriminate between malaria parasite species and stages. However, a closely related topic that has not received much attention is the practical application of image analysis techniques to malaria parasite quantitation in field studies, as opposed to experimental in vitro-cultured parasites (Sio et al., 2007). Estimation of haematozoan parasitaemia in birds and other non-mammalian vertebrates (Gering and Atkinson, 2004) is more amenable to digital image analysis techniques because their nucleated erythrocytes are readily recognised and counted by the software. Unlike other human malaria species, Plasmodium falciparum has the capacity for nearly unlimited replication in the human host, and very high parasitaemias (>50% of erythrocytes infected) are possible in falciparum infections.
E-mail address: [email protected]
Assessment of the parasite burden provides a useful indicator of the severity of infection, particularly in non-immune patients, and the level of parasitaemia correlates generally with clinical features and prognosis. Thus, although there is no uniformly agreed definition of hyperparasitaemia, >4% (or >5%) parasitaemia or >100 000 parasites/l are commonly regarded as indicators of risk of severe malaria in a lowtransmission setting (WHO, 2006). Parasite load monitoring is an objective way of monitoring response to treatment, especially in the presence of possible drug-resistant P. falciparum, as well as (potentially) assessing vaccine efficacy. However, there are some caveats: peripheral blood parasitaemia may well not accurately reflect the total body burden of parasites because of sequestration of parasitised erythrocytes in the capillaries and venules of the deep circulation. As an alternative, the proportion of malaria pigment-containing neutrophils has been used as an indirect measure of recent parasite replication. There are several methods of expressing the parasite load, most commonly as the percentage of infected erythrocytes counted on a stained thin blood film (e.g. 1%
0035-9203/$ — see front matter © 2008 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.trstmh.2008.04.017
Digital image analysis for quantitation of malaria parasite burden parasitaemia) or the number of parasites per unit volume of blood (e.g. 5000 parasites/l). The latter is usually assessed on a thick film by counting parasites against leukocytes (100, 200 or more), then multiplying by either the patient’s own leukocyte count, if available, or an assumed count of 8000/l. When the parasite count is either very high or very low, these thick film and thin film counts, respectively, are inaccurate. Another method is to count parasites in an assumed volume of blood per high power field on the thick film (Greenwood and Armstrong, 1991), but this is not widely used. Semiquantitation (parasite density graded as + through ++++), although often used in laboratories in developing countries, is inherently imprecise and therefore less satisfactory than the other methods. Rapid immunochromatographic (dipstick) or centrifuged capillary tube (QBC) tests are not suitable for measuring and tracking parasite density. Recent national programmatic proficiency testing of qualitative malaria laboratory diagnosis in South African medical laboratories has yielded disappointing results (Dini and Frean, 2003). As assessed in the same proficiency testing programme, the ability of laboratories to measure parasite loads is generally poor. In a recent quantitation exercise using a specimen with 14.3% parasitaemia, only 49% of 134 responding laboratories achieved acceptable results. Of special concern was the wide range of counts reported (0.08—68%). Whilst trained technologists readily recognise and count parasitised erythrocytes (the numerator) in an adequately stained thin film, estimating the denominator (total number of erythrocytes) of the required fraction is the source of most error (Gering and Atkinson, 2004). Use of a simple microscope eyepiece graticule (Miller squares; Graticules Ltd., Tonbridge, UK) markedly improves the accuracy and reproducibility of parasitaemia estimates. This technique was originally used for reticulocyte counts, where it was shown to produce smaller standard errors than the conventional method. The technique cannot be applied to parasite load quantitation on most thick films because of the typical locally uneven dispersion of parasites. It is also rather slow and therefore not suitable for busy laboratories. I suggest that modern digital techniques have the potential to improve the accuracy of quantitation both on thick and thin films. A pilot study using a standard laboratory microscope (Olympus BX40) plus phototube, a digital microscope camera (Nikon DS-U1), Eclipse Net imaging software (Nikon Instruments Europe BV, Badhoevedorp, The Netherlands) and image analysis software (ImageJ, an NIHdeveloped program) produced promising results and a larger comparison of digital and conventional microscopic quantitation is in progress. Potential advantages over conventional methods are improved accuracy and precision, reproducibility and objectivity of the counts. An obvious disadvantage of the method as experimented with so far is the time required both to capture a sufficient number of fields and to perform
1063
the digital manipulations on each, which includes resolving the problem of touching or overlapping erythrocytes. A more general issue is the cost of equipment and software that is needed. To optimise this approach to quantitation there are three requirements to be addressed: first, a bank of well standardised specimens that can be used confidently to assess and compare various approaches to digital counting; second, an alternative to the standard microscope—camera combination, for example a camera that fits in the eyepiece of any standard laboratory microscope, attaches to a standard personal computer and uses free software to capture and save images; and finally, adaptation and optimisation of readily available image analysis software to make this technology usable in routine practice. Ultimately, in malaria-endemic areas, laboratories, clinicians and patients could benefit from this technology. Acknowledgements: Thanks go to Leigh Dini, Rita van Deventer and Bhavani Poonsamy for producing, staining and manually counting blood films. Funding: National Institute for Communicable Diseases, Johannesburg, South Africa. Conflicts of interest: None declared. Ethical approval: Specimens for blood film production were collected under ethical clearance from the Human Research Ethics Committee (Medical), University of the Witwatersrand, Johannesburg, South Africa.
References Dini, L., Frean, J., 2003. Quality assessment of malaria laboratory diagnosis in South Africa. Trans. R. Soc. Trop. Med. Hyg. 97, 675—677. Gering, E., Atkinson, C.T., 2004. A rapid method for counting nucleated erythrocytes on stained blood smears by digital image analysis. J. Parasitol. 90, 879—881. Greenwood, B.M., Armstrong, J.R.M., 1991. Comparison of two simple methods for determining malaria parasite density. Trans. R. Soc. Trop. Med. Hyg. 85, 186—188. Ross, N.E., Pritchard, C.J., Rubin, D.M., Dus´ e, A., 2006. Automated image processing method for the diagnosis and classification of malaria on thin blood smears. Med. Biol. Eng. Comput. 44, 427—436. Sio, S.W., Sun, W., Kumar, S., Bin, W.Z., Tan, S.S., Ong, S.H., Kikuchi, H., Oshima, Y., Tan, K.S.W., 2007. MalariaCount: an image analysis-based program for the accurate determination of parasitemia. J. Microbiol. Methods 68, 11—18. WHO, 2006. Guidelines for the Treatment of Malaria. WHO/HTM/MAL/2006.1108. World Health Organization, Geneva. http://whqlibdoc.who.int/publications/2006/9241546948 eng. pdf [accessed 28 March 2007].