MOESM1 of Evaluation of automated malaria diagnosis using the Sysmex XN-30 analyser in a clinical setting

Additional file 1: Fig. S1. XN-30 software improvements. a. In the prototype software, the M scattergram plot area was divided into 3 regions classifying signals as WBCs (cluster a), non-infected RBCs, platelets and debris (cluster b) and MI-RBCs (cluster c). In brief, the gating strategy sequence was to first identify cluster a and then cluster b. In the prototype, all remaining signals were then assigned to cluster c. Upon further investigation, it was identified that the specified MI-RBC area (cluster c) was too broad, giving rise to false positive MI-RBC results. b. The software was subsequently improved for the XN-30 by narrowing the MI-RBC area (cluster c) and incorporating the recognition of one or more distinct clusters (ring forms, gametocytes, trophozoites/schizonts) within an appropriate shape and position as a prerequisite for generating an MI-RBC result. Fig. S2. XN-30 malaria classification algorithm. The left side illustrates the algorithm flow if a malaria cluster is not recognized. In such cases, if the MI-RBC# is < LoQ, the sample is reported as malaria negative (MI-RBC green box). However, if the MI-RBC# is ≥ LoQ but signals are detected in the absence of appropriate clustering, or an incorrect cluster shape is generated within the MI-RBC area, then the result is suppressed and an MI-RBC abnormal scattergram flag is generated. An indeterminate result is reported (MI-RBC grey box). An example is presented in M scattergram (a). The right side illustrates the algorithm flow if a malaria cluster is recognized. In such cases, if the MI-RBC# is < LoQ, the sample is reported as malaria negative (MI-RBC green box). However, if the MI-RBC# is ≥ LoQ the sample is reported as malaria positive (MI-RBC red box). An example is presented in M scattergram (b). Fig. S3. XN-30 M scattergrams, MI-RBC values and the species RBC flags for patient samples infected with a P. falciparum (P. f) and b P. ovale (others). Measurements were performed in WB mode. P. ovale parasites were confirmed microscopically. SFL: side fluorescence light; FSC: forward scattered light; blue dots: non-infected RBCs, platelets and debris; red dots: MI-RBCs; green and orange dots: different P. ovale life cycle forms; turquoise dots: white blood cells. Fig. S4. Correlation between P. falciparum parasitaemia obtained from the XN-30 (MI-RBC%) and expert microscopy. Samples were analysed in a LM mode and b PD mode. R2 indicates the coefficient of determination. The diagonal lines represent the regression lines. Fig. S5. XN-30 M scattergrams of malaria-negative patient samples with a thalassaemia, b sickle cell disease and c reticulocytosis of 13.86%. The grey area within the large blue cluster reflects the region where MI-RBCs scatter, but the software correctly triggered an “abnormal MI-RBC scattergram”. Measurements were performed in WB mode. SFL: side fluorescence light; FSC: forward scattered light; blue dots: non-infected RBCs, platelets and debris; turquoise dots: white blood cells. Fig. S6. Stability of MI-RBC parameters (MI-RBC#) at 4–8 °C measured in WB mode on the XN-30. Four samples with P. falciparum parasitaemia ranging from a high (21–107 × 103/µL), to b low (3–4.5 × 103/µL), were stored at 4–8 °C 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.