A Review on the Applications of Crowdsourcing in Human Pathology

The advent of the digital pathology has introduced new avenues of diagnostic medicine. Among them, crowdsourcing has attracted researchers' attention in the recent years, allowing them to engage thousands of untrained individuals in research and diagnosis. While there exist several articles in this regard, prior works have not collectively documented them. We, therefore, aim to review the applications of crowdsourcing in human pathology in a semi-systematic manner. We firstly, introduce a novel method to do a systematic search of the literature. Utilizing this method, we, then, collect hundreds of articles and screen them against a pre-defined set of criteria. Furthermore, we crowdsource part of the screening process, to examine another potential application of crowdsourcing. Finally, we review the selected articles and characterize the prior uses of crowdsourcing in pathology

Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images, including Supplementary Information

Malaria is a life-threatening disease affecting millions. Microscopy-based assessment of thin blood films is a standard method to (i) determine malaria species and (ii) quantitate high-parasitemia infections. Full automation of malaria microscopy by machine learning (ML) is a challenging task because field-prepared slides vary widely in quality and presentation, and artifacts often heavily outnumber relatively rare parasites. In this work, we describe a complete, fully-automated framework for thin film malaria analysis that applies ML methods, including convolutional neural nets (CNNs), trained on a large and diverse dataset of field-prepared thin blood films. Quantitation and species identification results are close to sufficiently accurate for the concrete needs of drug resistance monitoring and clinical use-cases on field-prepared samples. We focus our methods and our performance metrics on the field use-case requirements. We discuss key issues and important metrics for the application of ML methods to malaria microscopy.Comment: 16 pages, 13 figure

Performance of a fully‐automated system on a WHO malaria microscopy evaluation slide set

Background: Manual microscopy remains a widely-used tool for malaria diagnosis and clinical studies, but it has inconsistent quality in the field due to variability in training and field practices. Automated diagnostic systems based on machine learning hold promise to improve quality and reproducibility of field microscopy. The World Health Organization (WHO) has designed a 55-slide set (WHO 55) for their External Competence Assessment of Malaria Microscopists (ECAMM) programme, which can also serve as a valuable benchmark for automated systems. The performance of a fully-automated malaria diagnostic system, EasyScan GO, on a WHO 55 slide set was evaluated. Methods: The WHO 55 slide set is designed to evaluate microscopist competence in three areas of malaria diagnosis using Giemsa-stained blood films, focused on crucial field needs: malaria parasite detection, malaria parasite species identification (ID), and malaria parasite quantitation. The EasyScan GO is a fully-automated system that combines scanning of Giemsa-stained blood films with assessment algorithms to deliver malaria diagnoses. This system was tested on a WHO 55 slide set. Results: The EasyScan GO achieved 94.3 % detection accuracy, 82.9 % species ID accuracy, and 50 % quantitation accuracy, corresponding to WHO microscopy competence Levels 1, 2, and 1, respectively. This is, to our knowledge, the best performance of a fully-automated system on a WHO 55 set. Conclusions: EasyScan GO’s expert ratings in detection and quantitation on the WHO 55 slide set point towards its potential value in drug efficacy use-cases, as well as in some case management situations with less stringent species ID needs. Improved runtime may enable use in general case management settings

Diagnosing Severe Falciparum Malaria in Parasitaemic African Children: A Prospective Evaluation of Plasma PfHRP2 Measurement.

In African children, distinguishing severe falciparum malaria from other severe febrile illnesses with coincidental Plasmodium falciparum parasitaemia is a major challenge. P. falciparum histidine-rich protein 2 (PfHRP2) is released by mature sequestered parasites and can be used to estimate the total parasite burden. We investigated the prognostic significance of plasma PfHRP2 and used it to estimate the malaria-attributable fraction in African children diagnosed with severe malaria. Admission plasma PfHRP2 was measured prospectively in African children (from Mozambique, The Gambia, Kenya, Tanzania, Uganda, Rwanda, and the Democratic Republic of the Congo) aged 1 month to 15 years with severe febrile illness and a positive P. falciparum lactate dehydrogenase (pLDH)-based rapid test in a clinical trial comparing parenteral artesunate versus quinine (the AQUAMAT trial, ISRCTN 50258054). In 3,826 severely ill children, Plasmadium falciparum PfHRP2 was higher in patients with coma (p = 0.0209), acidosis (p<0.0001), and severe anaemia (p<0.0001). Admission geometric mean (95%CI) plasma PfHRP2 was 1,611 (1,350-1,922) ng/mL in fatal cases (n = 381) versus 1,046 (991-1,104) ng/mL in survivors (n = 3,445, p<0.0001), without differences in parasitaemia as assessed by microscopy. There was a U-shaped association between log(10) plasma PfHRP2 and risk of death. Mortality increased 20% per log(10) increase in PfHRP2 above 174 ng/mL (adjusted odds ratio [AOR] 1.21, 95%CI 1.05-1.39, p = 0.009). A mechanistic model assuming a PfHRP2-independent risk of death in non-malaria illness closely fitted the observed data and showed malaria-attributable mortality less than 50% with plasma PfHRP2≤174 ng/mL. The odds ratio (OR) for death in artesunate versus quinine-treated patients was 0.61 (95%CI 0.44-0.83, p = 0.0018) in the highest PfHRP2 tertile, whereas there was no difference in the lowest tertile (OR 1.05; 95%CI 0.69-1.61; p = 0.82). A limitation of the study is that some conclusions are drawn from a mechanistic model, which is inherently dependent on certain assumptions. However, a sensitivity analysis of the model indicated that the results were robust to a plausible range of parameter estimates. Further studies are needed to validate our findings. Plasma PfHRP2 has prognostic significance in African children with severe falciparum malaria and provides a tool to stratify the risk of "true" severe malaria-attributable disease as opposed to other severe illnesses in parasitaemic African children

Automated detection and staging of malaria parasites from cytological smears using convolutional neural networks

Microscopic examination of blood smears remains the gold standard for laboratory inspection and diagnosis of malaria. Smear inspection is, however, time-consuming and dependent on trained microscopists with results varying in accuracy. We sought to develop an automated image analysis method to improve accuracy and standardization of smear inspection that retains capacity for expert confirmation and image archiving. Here, we present a machine learning method that achieves red blood cell (RBC) detection, differentiation between infected/uninfected cells, and parasite life stage categorization from unprocessed, heterogeneous smear images. Based on a pretrained Faster Region-Based Convolutional Neural Networks (R-CNN) model for RBC detection, our model performs accurately, with an average precision of 0.99 at an intersection-over-union threshold of 0.5. Application of a residual neural network-50 model to infected cells also performs accurately, with an area under the receiver operating characteristic curve of 0.98. Finally, combining our method with a regression model successfully recapitulates intraerythrocytic developmental cycle with accurate lifecycle stage categorization. Combined with a mobile-friendly web-based interface, called PlasmoCount, our method permits rapid navigation through and review of results for quality assurance. By standardizing assessment of Giemsa smears, our method markedly improves inspection reproducibility and presents a realistic route to both routine lab and future field-based automated malaria diagnosis

Development of Phenotypic Drug Discovery Models for Tropical Parasitic Diseases

Malaria and visceral leishmaniasis are major killer parasitic diseases. These diseases though occur primarily in tropical countries; economic burden and overall health impacts of malaria and leishmaniasis are global. The emergence of drug-resistant and more-virulent strains of the pathogens has further amplified the problems. New drug discovery approaches primarily rely on in vitro and in vivo models of the disease. The pathogens causing leishmaniasis and malaria are intracellular. Leishmania parasite grows as amastigotes in macrophages cells, and malaria parasite grows within the hepatocytes or erythrocytes. The intracellular forms of the pathogens are responsible for the pathophysiology of the diseases. New phenotypic cell-based models have been developed for leishmaniasis and malaria, those have been employed for in vitro/in vivo screening for new drug discovery. A parasite-rescue and transformation assay was developed for macrophage-internalized Leishmania donovani amastigotes. The assay has been applied for high-throughput screening of a library of plants’ fractions. Two fluorescent transgenic cell lines of L. donovani were developed with mCherry and Citrine reporter genes by stable transfection approach. The transgenic cell lines have shown stable and constitutive expression of the fluorescent reporter proteins. The in vitro screening methods were developed with the transgenic leishmania cells employing flow-cytometric and fluorescent microscopy analyses. Analysis of parasitemia and intra-erythrocytic growth of the parasite are hallmarks of malaria research. A flow-cytometric assay, based on staining of the malaria parasites with LDS-751, a fluorescent cell-permeant nucleic acid stain, was developed for parasitemia analysis. Staining of malaria-infected RBCs may be performed directly without additional processing. Selective staining of malaria-infected erythrocytes by LDS-751 was confirmed with fluorescent microscopy. The method has been applied for flow-cytometric analysis of parasitemia in mice blood infected with Plasmodium berghei and human blood infected with P. falciparum. The utility of this developed method was established for both in vitro and in vivo antimalarial drug screenings. Establishment of the new phenotypic assay will expedite the process of new drug discovery against the tropical parasitic diseases. These assays would also have utility for understanding biology, virulence, and pathogenesis of malaria and leishmania pathogens

Computer vision for microscopy diagnosis of malaria

This paper reviews computer vision and image analysis studies aiming at automated diagnosis or screening of malaria infection in microscope images of thin blood film smears. Existing works interpret the diagnosis problem differently or propose partial solutions to the problem. A critique of these works is furnished. In addition, a general pattern recognition framework to perform diagnosis, which includes image acquisition, pre-processing, segmentation, and pattern classification components, is described. The open problems are addressed and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided

Full blood count and haemozoin-containing leukocytes in children with malaria: diagnostic value and association with disease severity

<p>Abstract</p> <p>Background</p> <p>Diligent and correct laboratory diagnosis and up-front identification of risk factors for progression to severe disease are the basis for optimal management of malaria.</p> <p>Methods</p> <p>Febrile children presenting to the Medical Research Unit at the Albert Schweitzer Hospital (HAS) in Lambaréné, Gabon, were assessed for malaria. Giemsa-stained thick films for qualitative and quantitative diagnosis and enumeration of malaria pigment, or haemozoin (Hz)-containing leukocytes (PCL) were performed, and full blood counts (FBC) were generated with a Cell Dyn 3000^®instrument.</p> <p>Results</p> <p>Compared to standard light microscopy of Giemsa-stained thick films, diagnosis by platelet count only, by malaria pigment-containing monocytes (PCM) only, or by pigment-containing granulocytes (PCN) only yielded sensitivities/specificities of 92%/93%; 96%/96%; and 85%/96%, respectively. The platelet count was significantly lower in children with malaria compared to those without (p < 0.001), and values showed little overlap between groups. Compared to microscopy, scatter flow cytometry as applied in the Cell-Dyn 3000^®instrument detected significantly more patients with PCL (p < 0.01). Both PCM and PCN numbers were higher in severe versus non-severe malaria yet reached statistical significance only for PCN (p < 0.0001; PCM: p = 0.14). Of note was the presence of another, so far ill-defined pigment-containing group of phagocytic cells, identified by laser-flow cytometry as lymphocyte-like gated events, and predominantly found in children with malaria-associated anaemia.</p> <p>Conclusion</p> <p>In the age group examined in the Lambaréné area, platelets are an excellent adjuvant tool to diagnose malaria. Pigment-containing leukocytes (PCL) are more readily detected by automated scatter flow cytometry than by microscopy. Automated Hz detection by an instrument as used here is a reliable diagnostic tool and correlates with disease severity. However, clinical usefulness as a prognostic tool is limited due to an overlap of PCL numbers recorded in severe versus non-severe malaria. However, this is possibly because of the instrument detection algorithm was not geared towards this task, and data lost during processing; and thus adjusting the instrument's algorithm may allow to establish a meaningful cut-off value.</p

An Optofluidic Lens Biochip and an x-ray Readable Blood Pressure Microsensor: Versatile Tools for in vitro and in vivo Diagnostics.

Three different microfabricated devices were presented for use in vivo and in vitro diagnostic biomedical applications: an optofluidic-lens biochip, a hand held digital imaging system and an x-ray readable blood pressure sensor for monitoring restenosis. An optofluidic biochip–termed the ‘Microfluidic-based Oil-Immersion Lens’ (mOIL) biochip were designed, fabricated and test for high-resolution imaging of various biological samples. The biochip consists of an array of high refractive index (n = 1.77) sapphire ball lenses sitting on top of an oil-filled microfluidic network of microchambers. The combination of the high optical quality lenses with the immersion oil results in a numerical aperture (NA) of 1.2 which is comparable to the high NA of oil immersion microscope objectives. The biochip can be used as an add-on-module to a stereoscope to improve the resolution from 10 microns down to 0.7 microns. It also has a scalable field of view (FOV) as the total FOV increases linearly with the number of lenses in the biochip (each lens has ~200 microns FOV). By combining the mOIL biochip with a CMOS sensor, a LED light source in 3D printed housing, a compact (40 grams, 4cmx4cmx4cm) high resolution (~0.4 microns) hand held imaging system was developed. The applicability of this system was demonstrated by counting red and white blood cells and imaging fluorescently labelled cells. In blood smear samples, blood cells, sickle cells, and malaria-infected cells were easily identified. To monitor restenosis, an x-ray readable implantable blood pressure sensor was developed. The sensor is based on the use of an x-ray absorbing liquid contained in a microchamber. The microchamber has a flexible membrane that is exposed to blood pressure. When the membrane deflects, the liquid moves into the microfluidic-gauge. The length of the microfluidic-gauge can be measured and consequently the applied pressure exerted on the diaphragm can be calculated. The prototype sensor has dimensions of 1x0.6x10mm and adequate resolution (19mmHg) to detect restenosis in coronary artery stents from a standard chest x-ray. Further improvements of our prototype will open up the possibility of measuring pressure drop in a coronary artery stent in a non-invasively manner.PhDMacromolecular Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111384/1/toning_1.pd