Investigation of a novel approach to scoring Giemsa-stained malaria-infected thin blood films
© Proudfoot et al; licensee BioMed Central Ltd. 2008
Received: 08 July 2007
Accepted: 21 April 2008
Published: 21 April 2008
Daily assessment of the percentage of erythrocytes that are infected ('percent-parasitaemia') across a time-course is a necessary step in many experimental studies of malaria, but represents a time-consuming and unpopular task among researchers. The most common method is extensive microscopic examination of Giemsa-stained thin blood-films. This study explored a method for the assessment of percent-parasitaemia that does not require extended periods of microscopy and results in a descriptive and permanent record of parasitaemia data that is highly amenable to subsequent 'data-mining'. Digital photography was utilized in conjunction with a basic purpose-written computer programme to test the viability of the concept. Partial automation of the determination of percent parasitaemia was then explored, resulting in the successful customization of commercially available broad-spectrum image analysis software towards this aim. Lastly, automated discrimination between infected and uninfected RBCs based on analysis of digital parameters of individual cell images was explored in an effort to completely automate the calculation of an accurate percent-parasitaemia.
When conducting blood-stage malaria trials involving live malaria challenges in mice, frequent assessment of their 'percent parasitaemia' is necessary throughout the duration of the experiment. Similarly, the in vitro expansion of the human malaria parasite Plasmodium falciparum requires frequent monitoring of the percent parasitaemia of cultures . While FACS-based experimental methods have been reported [2, 3], the most common method used to assess percent parasitaemia remains extensive microscopic scrutiny of Giemsa-stained thin blood-films. Lengthy sessions of microscopy are tedious and uncomfortable though, thus this is not a popular task among researchers. Particularly where new models are being explored by a laboratory or future data scrutiny or mining may be required, retention of all thin-blood-films is desirable. The slides can become a storage burden and degrade over time however. Additionally, they do not represent a record of the exact microscopic-field from which the data was derived at the time of recording.
Initially, this study sought to improve the qualitative substance of 'percent parasitaemia' data utilizing a combination of microscopy, digital photography and computer software. A simple programme was written towards this aim in the 'Visual-Basic ' computer language. Once a digital image of the Giemsa-stained blood-film is captured, the programme enables the researcher to 'score' each cell from a comfortable distance on a monitor via mouse clicks, rather than while looking down a microscope. Every decision at the cell level is recorded via a small colour-coded addition to the on-screen image. This approach negates long microscopy sessions and the possibility of cells inadvertently being included twice ('double-counts') in the assessment of percent-parasitaemia.
Optional parameters include scoring a lymphocyte count per microscopic-field, subdivision of uninfected RBCs based on maturity, and subdivision of malaria-infected RBCs based on parasite-stage. Regardless of the parameters chosen, overall percent-parasitaemia is calculated as scoring data are entered. Via this approach, the microscopy and scoring need not be performed by the same researcher, and the data-base created represents a legitimate substitute for actual blood-film-slides, which is more amenable to long term storage and future scrutiny. The programme ('Plasmoscore') is freely available for download  as a stand alone programme.
After development of a simple programme affording a permanent digital record of the precise derivation of parasitaemia data, partial automation of the process via customizing commercially available digital-image analysis software (Image-Pro® ) was attempted. A 'macro' combining an automated total cell count for each microscopic field with manual user determination of each infected cell was developed. Lastly, automated discrimination between infected and uninfected cells was attempted in an effort to completely automate the determination of the percent-parasitaemia depicted in digital thin-blood-film images.
Manual scoring of a digital image (Plasmoscore)
Semi-automated scoring of a digital image (Image-pro®)
Completely automated scoring of a digital image
Discussion and conclusion
There are several advantages conferred by using digital image based methods of scoring thin-blood-films for percent-parasitaemia over the traditional method. Foremost, large numbers of films can be scored without extended hours of microscopy. Automating the total cell count via the above-described method substantially reduces the time taken to score each film; if parasitaemia appears low (<50%) then the user need only score infected cells, and if it appears high the user need only score uninfected cells, to derive the over-all percent-parasitaemia. The graphic nature of the permanent records generated enable data of interest to be perused by multiple researchers simultaneously, emailed to distant researchers or retrospectively 'mined' for additional details such as differential parasite-stage analysis and lymphocyte counts. Unlike an actual blood-film, the digital image does not degrade over time and is not an incumbrance to store or transport.
Monetary considerations limit the utilisation of this approach. The most obvious is the requirement of a high-resolution, wide lens, microscope-mounted digital camera. At the operational level if the camera used cannot capture at least 400 cells per image, multiple images per blood-film will be required and the programme will need to combine user input appropriately to derive a valid percent parasitaemia per sample. Commercial software was used to enable an automatic cell-count, which would represent a financial limitation for many laboratories. Notably, there are various free 'open-source' software projects in a constant state of development such as NIH-image  and Image-J , which may prove useful to this end in the future.
While it was found that accurate automated determination of the total-cell-count of Giemsa-stained thin-blood-film images was ultimately achievable via commercial software , the success of this was affected by the uniformity with which thin blood-films were generated, processed and photographed. Particularly, thickly spread, over-fixed or over-stained blood films were not accurately processed by automated cell-counting software.
The ultimate aim of completely automated scoring of malaria infected thin-blood film images was explored by the authors, but remains elusive. Attempts were made to utilize parameters such as background flattening, internal-contrast and brightness of isolated objects (in this case 'cells') to discriminate infecteds from uninfecteds. Various factors including the presence of lymphocytes and the increased incidence of reticulocytes hampered these efforts however, resulting in a requirement for extensive 'user-correction'. The automated generation of a graphic grid 'ranking and grouping' cells based on a combination of criteria (predicting the likelihood that cells were infected) was achieved, which could substantially reduce the user-time required to score cells as infected or uninfected. It is anticipated that digital imaging processes will be widely utilized to determine the percent parasitaemia of malaria infected thin blood-films in the future. The extent to which this can be automated will rely on the adaptability of the software utilized. Given the complexity of the task, completely accurate yet entirely automated (no user correction required) determination of the process seems distant.
Because the Vaccine and Infectious Diseases (VID) Laboratory headed by Magdalena Plebanski was already a well-equipped malaria research facility at the time of the projects inception, it was able to be conducted with minimal funding. Notably, the project would also not have been possible without the computing advisor/programmer (Nathan Drew) contributing his services entirely gratis, apparently due to the humanitarian aims of the project. The costs of publication were covered by Monash University's ongoing subscription to the BMC journal network.
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