Hydrophilic-treated plastic plates for wide-range analysis of Giemsa-stained red blood cells and automated Plasmodium infection rate counting

A review on innovative optical devices for the diagnosis of human soil-transmitted helminthiasis and schistosomiasis: from research and development to commercialization

Diagnosis of soil-transmitted helminth (STH) and schistosome infections relies largely on conventional microscopy which has limited sensitivity, requires highly trained personnel and is error-prone. Rapid advances in miniaturization of optical systems, sensors and processors have enhanced research and development of digital and automated microscopes suitable for the detection of these diseases in resource-limited settings. While some studies have reported proof-of-principle results, others have evaluated the performance of working prototypes in field settings. The extensive commercialization of these innovative devices has, however, not yet been achieved. This review provides an overview of recent publications (2010–2022) on innovative field applicable optical devices which can be used for the diagnosis of STH and schistosome infections. Using an adapted technology readiness level (TRL) scale taking into account the WHO target product profile (TPP) for these diseases, the developmental stages of the devices were ranked to determine the readiness for practical applications in field settings. From the reviewed 18 articles, 19 innovative optical devices were identified and ranked. Almost all of the devices (85%) were ranked with a TRL score below 8 indicating that, most of the devices are not ready for commercialization and field use. The potential limitations of these innovative devices were discussed. We believe that the outcome of this review can guide the end-to-end development of automated digital microscopes aligned with the WHO TPP for the diagnosis of STH and schistosome infections in resource-limited settings.

Recent technical advances in whole slide imaging instrumentation

Microscopic observation of biological specimen smears is the mainstay of diagnostic pathology, as defined by the Digital Pathology Association. Though automated systems for this are commercially available, their bulky size and high cost renders them unusable for remote areas. The research community is investing much effort towards building equivalent but portable, low-cost systems. An overview of such research is presented here, including a comparative analysis of recent reports. This paper also reviews recently reported systems for automated staining and smear formation, including microfluidic devices; and optical and computational automated microscopy systems including smartphone-based devices. Image pre-processing and analysis methods for automated diagnosis are also briefly discussed. It concludes with a set of foreseeable research directions that could lead to affordable, integrated and accurate whole slide imaging systems.

Image Analysis Using Machine Learning for Automated Detection of Hemoglobin H Inclusions in Blood Smears - A Method for Morphologic Detection of Rare Cells

Background

Morphologic rare cell detection is a laborious, operator-dependent process which has the potential to be improved by the use of image analysis using artificial intelligence. Detection of rare hemoglobin H (HbH) inclusions in red cells in the peripheral blood is a common screening method for alpha-thalassemia. This study aims to develop a convolutional neural network-based algorithm for the detection of HbH inclusions.

Methods

Digital images of HbH-positive and HbH-negative blood smears were used to train and test the software. The software performance was tested on images obtained at various magnifications and on different scanning platforms. Another model was developed for total red cell counting and was used to confirm HbH cell frequency in alpha-thalassemia trait. The threshold minimum red cells to image for analysis was determined by Poisson modeling and validated on image sets.

Results

The sensitivity and specificity of the software for HbH+ cells on images obtained at ×100, ×60, and ×40 objectives were close to 91% and 99%, respectively. When an AI-aided diagnostic model was tested on a pilot of 40 whole slide images (WSIs), good inter-rater reliability and high sensitivity and specificity of slide-level classification were obtained. Using the lowest frequency of HbH+ cells (1 in 100,000) observed in our study, we estimated that a minimum of 2.4 × 10⁶ red cells would need to be analyzed to reduce misclassification at the slide level. The minimum required smear size was validated on 78 image sets which confirmed its validity.

Conclusions

WSI image analysis can be utilized effectively for morphologic rare cell detection. The software can be further developed on WISs and evaluated in future clinical validation studies comparing AI-aided diagnosis with the routine diagnostic method.

Quantitative Detection of Plasmodium falciparum Using, LUNA-FL, A Fluorescent Cell Counter

The microscopic examination of Giemsa-stained thin and/or thick blood films (Giemsa microscopy) is the standard method of malaria diagnosis. However, the results of the diagnosis significantly depend on the skills of clinical technicians. Furthermore, sample preparation and analysis are laborious and time-consuming. Therefore, in this study, we investigated if a commercially available fluorescent cell counter, LUNA-FL, was useful for the detection of Plasmodium parasite and the estimation of parasitemia. Whole blood samples from uninfected persons, spiked with P. falciparum-infected erythrocytes, were analysed. Most of the leucocytes and platelets were removed from whole blood samples with SiO₂-nanofiber filters set on spin columns. The filtered samples were stained with acridine orange, and automatic detection, as well as counting of erythrocytes and parasites, were performed using LUNA-FL. Whole blood, with various levels of parasites, was analysed by Giemsa microscopy or with LUNA-FL to estimate parasitemia, and a comparative analysis was performed. The coefficient determination value of the regression line was high (R² = 0.98), indicating that accurate quantitative parasite detection could be performed using LUNA-FL. LUNA-FL has a low running cost; it is compact, fast, and easy to operate, and may therefore be useful for point-of-care testing in the endemic areas.

Loop-Mediated Isothermal Amplification In Microchambers On A Cell Microarray Chip For Identification of Plasmodium Species

Malaria is caused by Plasmodium spp., a parasitic protist that infects erythrocytes. A method that can detect the parasite with high sensitivity and that can identify the parasite species is urgently required for the control of malaria. The cell microarray chip was made using polystyrene with 200 cone-shaped frustum microchambers (800-μm top diameter, 636-μm bottom diameter, and 225 μm deep). Approximately 3,000 erythrocytes could be accommodated in each microchamber with monolayer formation, there being 60,000 erythrocytes in total microchambers on a cell microarray. Plasmodium could be quantitatively detected with high sensitivity with the use of cell microarray chips. Plasmodium parasitizing in erythrocytes was labeled with a cell-permeant fluorescent nucleic acid stain (SYTO 21), which could be detected in erythrocytes in the microchambers. Next, we used loop-mediated isothermal amplification (LAMP) in the microchambers (on-chip LAMP) to identify the parasite species detected in the microchambers. LAMP was performed in the microchambers (in a reaction volume of 0.09 μl) using Plasmodium falciparum-infected erythrocytes as the template and specific primers targeting 18S rRNA. To avoid evaporation of the reaction buffer during heat treatment, mineral oil was overlaid on each microchamber and the cell microarray chips were heated at 63 C for 1 hr. The results of on-chip LAMP were assessed using a portable ultraviolet transilluminator. We showed that this method has the potential for detection of parasites in 600,000 erythrocytes and for identification of the parasite species on a cell microarray chip. In conclusion, the parasites can be detected quantitatively with high sensitivity, and the species can be identified with the use of cell microarray chips.

Small-scale culture of Plasmodium falciparum using μ-Slide Angiogenesis followed by automatic infection rate counting to assess drug effects

It is very important to reduce the costs involved in malarial drug development by small-scale culture of Plasmodium falciparum, and automation of the assay system for drug efficacy against the parasites for high-throughput screening. In this study, we report that P. falciparum-infected erythrocytes can be stably cultured on μ-Slide Angiogenesis, which is used to investigate angiogenesis in tube formation assays, followed by automatic counting of the infection rate (parasitaemia). After 10 μL of parasite-infected erythrocytes were added to the inner well of μ-Slide Angiogenesis to prevent a multilayer of erythrocytes, 30 μL of silicon oil was overlaid on the culture medium to avoid evaporation of the medium, leading to stable small-scale parasite cultivation. The parasites were stained with a cell-permeant fluorescent nucleic acid stain (SYTO21) followed by cultivation. After taking bright field and fluorescent images using an inverted microscope, the infection rate could be calculated automatically by counting the number of erythrocytes and parasites using MetaMorph Offline software. The effect of anti-malarial drugs on parasite growth could be investigated on μ-Slide Angiogenesis, in which the parasite culture was added to the inner wells containing the drugs followed by their cultivation. Taken together, this method may be useful for image-based screening for anti-malarial drug candidates with automatic counting of parasite infection rates.

In situ loop-mediated isothermal amplification (LAMP) for identification of Plasmodium species in wide-range thin blood smears

BACKGROUND

Five species of Plasmodium are known to infect humans. For proper treatment of malaria, accurate identification of the parasite species is crucial. The current gold standard for malaria diagnosis is microscopic examination of Giemsa-stained blood smears. Since the parasite species are identified by microscopists who manually search for the parasite-infected red blood cells (RBCs), misdiagnosis due to human error tends to occur in case of low parasitaemia or mixed infection. Then, molecular methods, such as polymerase chain reaction or loop-mediated isothermal amplification (LAMP), are required for conclusive identification of the parasite species. However, since molecular methods are highly sensitive, false-positive results tend to occur due to contamination (carry over) or the target gene products may be detected even after clearance of the parasites from the patient's blood. Therefore, accurate detection of parasites themselves by microscopic examination is essential for the definitive diagnosis. Thus, the method of in situ LAMP for the parasites was developed.

RESULTS

Red blood cell suspensions, including cultured Plasmodium falciparum, strain 3D7, infected-RBCs, were dispersed on cyclic olefin copolymer (COC) plate surfaces rendered hydrophilic by reactive ion-etching treatment using a SAMCO RIE system (hydrophilic-treated), followed by standing for 10 min to allow the RBCs to settle down on the plate surface. By rinsing the plate with RPMI 1640 medium, monolayers of RBCs formed on almost the entire plate surface. The plate was then dried with a hair drier. The RBCs were fixed with formalin, followed by permeabilization with Triton X-100. Then, amplification of the P. falciparum 18S rRNA gene by the LAMP reaction with digoxigenin (DIG)-labelled dUTP and a specific primer set was performed. Infected RBCs as fluorescence-positive cells with anti-DIG antibodies conjugated with fluorescein using fluorescent microscopy could be detected.

CONCLUSIONS

The present work shows that the potential of in situ LAMP for the identification of Plasmodium species at the single cell level on hydrophilic-treated COC palates, allowing highly sensitive and accurate malaria diagnosis. The findings will improve the efficacy of the gold standard method for malaria diagnosis.