Label-free imaging and classification of live P. falciparum enables high performance parasitemia quantification without fixation or staining.

Manual microscopic inspection of fixed and stained blood smears has remained the gold standard for Plasmodium parasitemia analysis for over a century. Unfortunately, smear preparation consumes time and reagents, while manual microscopy is skill-dependent and labor-intensive. Here, we demonstrate that deep learning enables both life stage classification and accurate parasitemia quantification of ordinary brightfield microscopy images of live, unstained red blood cells. We tested our method using both a standard light microscope equipped with visible and near-ultraviolet (UV) illumination, and a custom-built microscope employing deep-UV illumination. While using deep-UV light achieved an overall four-category classification of Plasmodium falciparum blood stages of greater than 99% and a recall of 89.8% for ring-stage parasites, imaging with near-UV light on a standard microscope resulted in 96.8% overall accuracy and over 90% recall for ring-stage parasites. Both imaging systems were tested extrinsically by parasitemia titration, revealing superior performance over manually-scored Giemsa-stained smears, and a limit of detection below 0.1%. Our results establish that label-free parasitemia analysis of live cells is possible in a biomedical laboratory setting without the need for complex optical instrumentation. We anticipate future extensions of this work could enable label-free clinical diagnostic measurements, one day eliminating the need for conventional blood smear analysis.

Performance of malaria microscopy external quality assessment and networking among health facilities in west Amhara region, Ethiopia.

BACKGROUND: Microscopic examination of peripheral blood smear produces reliable results both about the malaria infection status and level of parasitemia. However, test results are affected by skill of the laboratory personnel, workload, condition of microscopes and quality of laboratory supplies. Therefore, continuous monitoring of the performance of laboratories is of pivotal importance in order to make timely correction. METHODS: A facility based cross-sectional study was conducted from July 2017 to July 2019 to assess malaria microscopy performance among thirty malaria diagnostic laboratories in west Amhara region. Thirty slides were collected from participating laboratories every quarter. Collected slides were taken to Amhara Public Health Institute reference laboratory and re-checked by malaria microscopists who were blind to the results from health facilities. Percentage of test agreement, rates of false positive, false negative and species misdiagnosis were calculated using Excel 2010. RESULTS: Among a total of 6689 slides re-checked, results of 6146 slides were the same with that of participating laboratories. The test agreement was 97.31 and 94.6% for parasite detection and species identification, respectively. Variations in the overall performance of individual laboratories were seen within a range of 81.55 to 97.27% test agreement. Results of 543 (8.12%) slides were discordant, of which 363 (5.4%), 93 (1.4%) and 87 (1.3%) slides were due to species misdiagnosis, false positive and false negative results, respectively. CONCLUSION: There was good test agreement between participated laboratories and Amhara Public Health Institute. More accurate performance is expected as the country is tracking to malaria elimination. Hence, further strengthening the external quality assurance program is recommended.

A low-cost, automated parasite diagnostic system via a portable, robotic microscope and deep learning.

Manual hand counting of parasites in fecal samples requires costly components and substantial expertise, limiting its use in resource-constrained settings and encouraging overuse of prophylactic medication. To address this issue, a cost-effective, automated parasite diagnostic system that does not require special sample preparation or a trained user was developed. It is composed of an inexpensive (~US$350), portable, robotic microscope that can scan over the size of an entire McMaster chamber (100 mm2 ) and capture high-resolution (~1 µm lateral resolution) bright field images without need for user intervention. Fecal samples prepared using the McMaster flotation method were imaged, with the imaging region comprising the entire McMaster chamber. These images are then automatically segmented and analyzed using a trained convolution neural network (CNN) to robustly separate eggs from background debris. Simple postprocessing of the CNN output yields both egg species and egg counts. The system was validated by comparing accuracy with hand-counts by a trained operator, with excellent performance. As a further demonstration of utility, the system was used to conveniently quantify drug response over time in a single animal, showing residual disease due to Anthelmintic resistance after 2 weeks.

Updating the modified Thompson test by using whole-body bioluminescence imaging to replace traditional efficacy testing in experimental models of murine malaria.

BACKGROUND: Rodent malaria models are extensively used to predict treatment outcomes in human infections. There is a constant need to improve and refine these models by innovating ways to apply new scientific findings and cutting edge technologies. In addition, and in accordance with the three R's of animal use in research, in vivo studies should be constantly refined to avoid unnecessary pain and distress to the experimental animals by using preemptive euthanasia as soon as the main scientific study objective has been accomplished. METHODS: The new methodology described in this manuscript uses the whole-body bioluminescence signal emitted by transgenic, luciferase-expressing Plasmodium berghei parasites to assess the parasite load predicted parasitaemia (PLPP) in drug and control treated female ICR-CD1 mice infected with 1 × 105 luciferase-expressing P. berghei (ANKA strain) infected erythrocytes. This methodology can replace other time-consuming and expensive methods that are routinely used to measure parasitaemia in infected animals, such as Giemsa-stained thin blood smears and flow cytometry. RESULTS: There is a good correlation between whole-body bioluminescence signal and parasitaemia measured using Giemsa-stained thin blood smears and flow cytometry respectively in donor and study mice in the modified Thompson test. The algebraic formulas which represent these correlations can be successfully used to assess PLPP in donor and study mice. In addition, the new methodology can pinpoint sick animals 2-8 days before they would have been otherwise diagnosed based on behavioural or any other signs of malaria disease. CONCLUSIONS: The new method for predicting parasitaemia in the modified Thompson test is simple, precise, objective, and minimizes false positive results that can lead to the premature removal of animals from study. Furthermore, from the animal welfare perspective of replace, reduce, and refine, this new method facilitates early removal of sick animals from study as soon as the study objective has been achieved, in many cases well before the clinical signs of disease are present.

ARAM: an automated image analysis software to determine rosetting parameters and parasitaemia in Plasmodium samples.

BACKGROUND: Rosetting is associated with severe malaria and a primary cause of death in Plasmodium falciparum infections. Detailed understanding of this adhesive phenomenon may enable the development of new therapies interfering with rosette formation. For this, it is crucial to determine parameters such as rosetting and parasitaemia of laboratory strains or patient isolates, a bottleneck in malaria research due to the time consuming and error prone manual analysis of specimens. Here, the automated, free, stand-alone analysis software automated rosetting analyzer for micrographs (ARAM) to determine rosetting rate, rosette size distribution as well as parasitaemia with a convenient graphical user interface is presented. METHODS: Automated rosetting analyzer for micrographs is an executable with two operation modes for automated identification of objects on images. The default mode detects red blood cells and fluorescently labelled parasitized red blood cells by combining an intensity-gradient with a threshold filter. The second mode determines object location and size distribution from a single contrast method. The obtained results are compared with standardized manual analysis. Automated rosetting analyzer for micrographs calculates statistical confidence probabilities for rosetting rate and parasitaemia. RESULTS: Automated rosetting analyzer for micrographs analyses 25 cell objects per second reliably delivering identical results compared to manual analysis. For the first time rosette size distribution is determined in a precise and quantitative manner employing ARAM in combination with established inhibition tests. Additionally ARAM measures the essential observables parasitaemia, rosetting rate and size as well as location of all detected objects and provides confidence intervals for the determined observables. No other existing software solution offers this range of function. The second, non-malaria specific, analysis mode of ARAM offers the functionality to detect arbitrary objects. CONCLUSIONS: Automated rosetting analyzer for micrographs has the capability to push malaria research to a more quantitative and statistically significant level with increased reliability due to operator independence. As an installation file for Windows © 7, 8.1 and 10 is available for free, ARAM offers a novel open and easy-to-use platform for the malaria community to elucidate resetting.

Early dystrophin disruption in the pathogenesis of experimental chronic Chagas cardiomyopathy.

Chronic Chagas cardiomyopathy evolves over a long period of time after initial infection by Trypanosoma cruzi. Similarly, a cardiomyopathy appears later in life in muscular dystrophies. This study tested the hypothesis that dystrophin levels are decreased in the early stage of T. cruzi-infected mice that precedes the later development of a cardiomyopathy. CD1 mice were infected with T. cruzi (Brazil strain), killed at 30 and 100 days post infection (dpi), and the intensity of inflammation, percentage of interstitial fibrosis, and dystrophin levels evaluated. Echocardiography and magnetic resonance imaging data were evaluated from 15 to 100 dpi. At 30 dpi an intense acute myocarditis with ruptured or intact intracellular parasite nests was observed. At 100 dpi a mild chronic fibrosing myocarditis was detected without parasites in the myocardium. Dystrophin was focally reduced or completely lost in cardiomyocytes at 30 dpi, with the reduction maintained up to 100 dpi. Concurrently, ejection fraction was reduced and the right ventricle was dilated. These findings support the hypothesis that the initial parasitic infection-induced myocardial dystrophin reduction/loss, maintained over time, might be essential to the late development of a cardiomyopathy in mice.

Trypanosoma cruzi: biodistribution of technetium-99m pertechnetate in infected rats.

With the aim of investigating the biodistribution of technetium-99m pertechnetate ((99m)TcO4-) in rats infected with Y strain of Tripanosoma Cruzi, at the peak of parasitemia, (14th day of infection), we injected Wistar rats with 0.1 ml of (99m)TcO4- (3.7MBq). After 60 min, the percentage of radioactivity per gram was counted in several isolated organs and blood, using a gamma counter (1470 Wizard, PerkinElmer Finland). The uptake of (99m)TcO4- increased significantly in blood and decreased in the colon of infected animals (p<0.05). A significant reduction in serum iron and red blood cells and a significant increase in total proteins, leukocytes and lymphocytes in the infected rats were observed, compared with controls (p<0.05). A reduction in muscle layer thickness of the colon and mononuclear inflammation were observed. These results conclusively demonstrate that T. cruzi infection would be associated with changes in the biodistribution of (99m)TcO4- and in colon morphology, with potential clinical implications.

Enhancement of splenic glucose metabolism during acute malarial infection: correlation of findings of FDG-PET imaging with pathological changes in a primate model of severe human malaria.

In the current study, to elucidate the clinical features of severe malaria, we performed whole-body positron emission tomography (PET) with (18)F-fluorodeoxyglucose (FDG) of Plasmodium coatneyi-infected acute-phase Japanese macaques. The infected monkeys clearly exhibited increase in splenic FDG uptake indicating marked enhancement of glucose metabolism. The standardized uptake values (SUVs) of the spleen in the infected monkeys were significantly higher than those in the uninfected monkey. At autopsy, splenomegaly was clearly present in all infected monkeys, and histopathologic findings included hyperplasia of lymphoid follicles in white pulp, a large number of activated macrophage, and congestion of parasitized red blood cells (PRBCs) and malaria pigments in red pulp. We suggest that increase in splenic glucose uptake may thus be closely related to activation of splenic clearance system against blood-stage malarial parasites.

Reliable and frequent detection of adult Wuchereria bancrofti in Ghanaian women by ultrasonography.

Detection of adult Wuchereria bancrofti by ultrasonography of the scrotal region in men is a suitable diagnostic tool for lymphatic filariasis, whereas there are only a few case reports of adult filariae observed by ultrasonography in women. We examined 35 microfilaraemic women ultrasonographically in sites of the body suspected as locations for worm nests. In 15 women the 'filaria dance sign' (FDS) was detected in various locations, some being novel, such as adult worms within lymphatic vessels between muscular fibres of the thighs. The surprisingly high number of worm nests detectable in microfilaraemic women recommends ultrasonography for diagnosis and treatment efficacy monitoring of female patients infected with W. bancrofti.

Clinical overlap between malaria and severe pneumonia in Africa children in hospital.

Data collected from 200 children admitted to a hospital on the Kenyan coast who met a broad definition of severe acute respiratory infection (ARI) indicated that simple clinical signs alone are unable absolutely to distinguish severe ARI and severe malaria. However, laboratory data showed that marked differences exist in the pathophysiology of unequivocal malaria and unequivocal ARI. Children in the former group had a higher mean oxygen saturation (97 vs. 94, P < 0.001), mean blood urea level (5.3 vs. 1.9 mmol/L, P < 0.001) and geometric mean lactate level (4.5 vs. 2.1 mmol/L, P < 0.001), and lower mean haemoglobin level (5.3 vs. 9.0 g/dL, P < 0.001) and base excess (-9.4 vs. -2.6, P < 0.001) than those in the latter group. Using these discriminatory variables it was estimated that up to 45% of children admitted with respiratory signs indicative of severe ARI probably had malaria as the primary diagnosis. Radiological examination supported this conclusion, indicating that pneumonia characterized by consolidation was uncommon in children with respiratory signs and a high malarial parasitaemia (> or = 10,000/microliters). There is no specific radiological sign of severe malaria. In practice, all children with respiratory signs warranting hospital admission in a malaria endemic area should be treated for both malaria and ARI unless blood film examination excludes malaria. In those with malaria and clinical evidence of acidosis, but no crackles, antibodies may be withheld while appropriate treatment for dehydration and anaemia is given. However, if clinical improvement is not rapid, antibiotics should be started.