Evaluation of automated malaria diagnosis using the Sysmex XN-30 analyser in a clinical setting

Abstract

Background: Early and accurate diagnosis of malaria is a critical aspect of efforts to control the disease, and several diagnostic tools are available. Microscopic assessment of a peripheral blood smear enables direct visualization of parasites in infected red blood cells and is the clinical diagnostic gold standard. However, it is subjective and requires a high level of skill. Numerous indirect detection methods are in use, but are not ideal since surrogate markers of infection are measured. This study describes the first clinical performance evaluation of the automated Sysmex XN-30 analyser, which utilizes fluorescence flow cytometry to directly detect and quantitate parasite-infected red blood cells.

Results: Residual EDTA blood samples from suspected malaria cases referred for routine diagnosis were analysed on the XN-30. Parasitaemia was reported as a percentage, as well as absolute numbers of infected red blood cells, and scattergrams provided a visual image of the parasitized red blood cell clusters. The results reported by the XN-30 correlated with microscopy and the analyser demonstrated 100% sensitivity and specificity. Measurements were reproducible and storage of samples at room temperature did not affect the parameters. Several Plasmodium species were detected, including Plasmodium falciparum, Plasmodium vivax and Plasmodium ovale. The XN-30 also identified the transmissible gametocytes as a separate cluster on the scattergrams. Abnormal red blood cell indices (low haemoglobin and raised reticulocyte counts), haemoglobinopathies and thrombocytopenia did not interfere with the detection of parasites. The XN-30 also generated a concurrent full blood count for each sample.

Conclusions: The novel technology of the Sysmex XN-30 provides a robust, rapid, automated and accurate platform for diagnosing malaria in a clinical setting. The objective enumeration of red blood cells infected with Plasmodium species makes it suitable for global use and allows monitoring of the parasite load once therapy has been initiated, thereby providing an early marker of drug resistance. The automated generation of a full blood count for each sample provides an opportunity for detecting unsuspected cases. Asymptomatic carriers can also be identified, which will be useful in blood transfusion centres, and will enable treatment of these individuals to prevent the spread of the disease.

Keywords: Automated diagnosis; Plasmodium falciparum; Sysmex XN-30 analyser.

Fig. 1

M scattergrams illustrating the principle of detection of red blood cells infected with malaria parasites. SFL: side fluorescence light; FSC: forward scattered light. Samples were analysed in WB mode. a Malaria-negative blood sample. Blue dots: non-infected RBCs, platelets and debris; red dots: background noise below the limit of quantitation. b RBCs infected with P. falciparum (MI-RBCs) showing R1: RBCs infected with 1 ring form, and R2: RBCs infected with 2 ring forms. c RBCs infected with P. vivax showing different parasite developmental stages. T: trophozoites; G: gametocytes; S: schizonts; W: white blood cells

Fig. 2

XN-30 M scattergrams illustrating the detection of red blood cells infected with P. falciparum malaria parasites (MI-RBCs) using WB mode. The corresponding FBC and quantitative MI-RBC parameters (MI-RBC# and MI-RBC%) are shown to the right of the scattergrams. SFL: side fluorescence light; FSC: forward scattered light; blue dots: non-infected RBCs, platelets and debris; red dots: MI-RBCs; turquoise dots: white blood cells; “+”: value exceeds upper limit; “−”: value exceeds the lower limit; *value has low reliability. a Sample with a low parasitaemia of 0.3019%. b Sample with a higher parasitaemia of 1.6286%

Fig. 3

Correlation between P. falciparum parasitaemia obtained from the XN-30 (MI-RBC%) and expert microscopy. Samples were analysed in WB mode. R² indicates the coefficient of determination. The diagonal line represents the regression line

Fig. 4

Lack of interference by Howell-Jolly bodies with the quantitative MI-RBC parameters. a Peripheral blood smear of the sample with numerous Howell-Jolly body-containing RBCs. b The sample was analysed on the XN-30 in WB mode and the M scattergram shows a large blue cluster with a grey area, reflecting the region where MI-RBCs scatter. Turquoise dots: white blood cells. c The MI-RBC parameters (MI-RBC# and MI-RBC%) were suppressed and the software triggered an “abnormal MI-RBC scattergram” flag in response to the large blue cluster and the result was reported as indeterminate

Fig. 5

Stability of MI-RBC parameters (MI-RBC#) measured in WB mode on the XN-30. Seven samples with P. falciparum parasitaemia ranging from low to high (4–136 × 10³/µL), were stored at room temperature and analysed at various time intervals. The first measurement was performed within 24 h of sample collection from the patient and thus the initial point is different for each sample

Fig. 6

XN-30 M scattergrams illustrating the detection of P. falciparum gametocytes. Malaria-negative whole blood (1 mL) spiked with 200 µL (a) and 800 µL (b) of purified P. falciparum gametocytes. SFL: side fluorescence light; FSC: forward scattered light; circled green dots: gametocytes. These samples were analysed in WB mode