Mobile Phone Devices and Handheld Microscopes as Diagnostic Platforms for Malaria and Neglected Tropical Diseases (NTDs) in Low-Resource Settings

Vasiman, Alon; Stothard, J. Russell; Bogoch, Isaac I.

doi:10.1016/bs.apar.2018.09.001

Cited by 19 publications

(23 citation statements)

References 45 publications

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“…Digitizing the samples at the right moment could provide a solution, which allows digital storage of the sample images and further analysis at any moment in time. Different digitalization devices have been tested allowing remote diagnosis and second opinion (10). A further step that could save time, increase performance and remove subjectivity of microscopic techniques is the possibility of implementing artificial intelligence algorithms for the automatic detection and quantification of these parasites on digitized image samples.…”

Section: Introductionmentioning

confidence: 99%

Mobile microscopy and telemedicine platform assisted by deep learning for quantification ofTrichuris trichiurainfection

Dacal¹,

Bermejo-Peláez²,

Lin

et al. 2021

Preprint

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Soil-transmitted helminths (STH) are the most prevalent pathogens among the group of neglected tropical diseases (NTDs). Kato-Katz technique is the diagnosis method recommended by WHO and although is generally more sensitive than other microscopic methods in high transmission settings, it often presents a decreased sensitivity in low transmission settings and it is labour intensive. Digitizing the samples could provide a solution which allows to store the samples in a digital database and perform remote analysis. Artificial intelligence methods based on digitized samples can support diagnostics efforts by support diagnostics efforts by performing an automatic and objective quantification of disease infection.In this work, we propose an end-to-end pipeline for microscopy image digitization and automatic analysis of digitized images of soil-transmitted helminths. Our solution includes (1) a digitalization system based on a mobile app that digitizes the microscope samples using a low-cost 3D-printed microscope adapter, (2) a telemedicine platform for remote analysis and labelling and (3) novel deep learning algorithms for automatic assessment and quantification of parasitological infection of STH.This work has been evaluated by comparing the STH quantification using both a manual remote analysis based on the digitized images and the AI-assisted quantification against the reference method based on conventional microscopy. The deep learning algorithm has been trained and tested on 41 slides of stool samples containing 949 eggs from 6 different subjects using a cross-validation strategy obtaining a mean precision of 98,44% and mean recall of 80,94%. The results also proved the potential of generalization capability of the method at identifying different types of helminth eggs.In conclusion, this work has presented a comprehensive pipeline using smartphone-based microscopy integrated with a telemedicine platform for automatic image analysis and quantification of STH infection using artificial intelligence models.

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Section: Introductionmentioning

confidence: 99%

Mobile microscopy and telemedicine platform assisted by deep learning for quantification ofTrichuris trichiurainfection

Dacal¹,

Bermejo-Peláez²,

Lin

et al. 2021

Preprint

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“…infection compared with standard diagnostic procedures. 30,31 Thus, a type of CellScope (LoaScope) has been proposed by the WHO as a key point-of-care testing tool for NTD elimination in areas with co-endemicity. 10 TREATMENT Treatment of loiasis can be difficult and often requires a strong team collaboration between an expert in infectious diseases or tropical medicine, an ophthalmologist, and a parasitologist.…”

Section: No Risk Low Risk Moderate Risk High Risk No Data Availablementioning

confidence: 99%

“…32 Surgical removement of the live, migratory worm is often needed because one of the most frequent clinical presentations of loiasis is the presence of live worms in the ocular-periocular region. 30 When still visible under the bulbar conjunctiva, the technique used to remove the worm from the eye often does not resolve the situation because capture of the nematode requires immobilization of the worm. 30 Removal of the nematode relieves pain and allows confirmation of diagnosis, although histological exam is not essential.…”

Section: No Risk Low Risk Moderate Risk High Risk No Data Availablementioning

confidence: 99%

Loa loa in the Vitreous Cavity of the Eye: A Case Report and State of Art

Pallara

Cotugno

Guido

et al. 2022

The American Journal of Tropical Medicine and Hygiene

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Loa loa is a filarial nematode responsible for loiasis, endemic to West–Central Africa south of the Sahara and transmitted by flies. This study reports a case of L. loa in the vitreous cavity of the eye of a young patient, along with an in-depth literature review. A 22-year-old woman from Cameroon who migrated from Cameroon to Italy was referred to the Emergency Ophthalmology Department at Policlinico di Bari in July 2021 with the presence of a moving parasite in the subconjunctiva of the left eye. A recent onset of a papular lesion on the dorsal surface of the right wrist and a nodular lesion in the scapular region were detected. L. loa filariasis was diagnosed based on anamnestic data, clinical and paraclinical signs, and a parasitological test confirming the presence of microfilariae in two blood samples collected in the morning of two different days. Because of the unavailability of diethylcarbamazine (DEC), albendazole (ALB) 200 mg twice daily was administered for 21 days. A mild exacerbation of pruritus occurred during treatment, but resolved with the use of an antihistamine. A single dose of 12 mg ivermectin was prescribed at the end of the treatment with albendazole. Unlike other endemic parasite infections, L. loa is not included in the Global Program to Eliminate Lymphatic Filariasis, because it is not mentioned in the WHO and CDC list of neglected tropical diseases. This can result in an overall risk of lack of attention and studies on loiasis, with lack of data on global burden of the disease.

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“…The latest research in this field demonstrates that novel diagnostic tools, such as mobile phone microscopes have rapidly improved diagnostic characteristics and broadened the scope of pathogens tested, and have excellent functionality in neglected tropical disease-endemic settings. 3,4 Such devices are already being field tested and implemented on a limited scale, for example in Côte d'Ivoire. 5 However, careful consideration to several ethical concerns arising from artificial intelligence-driven diagnoses of neglected tropical diseases in low-resource settings is critical for maximizing the benefit of this technology.…”

Section: Perspectivesmentioning

confidence: 99%

Artificial intelligence, diagnostic imaging and neglected tropical diseases: ethical implications

Vaisman

Linder

Lundin

et al. 2020

Bull. World Health Organ.

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Mobile Phone Devices and Handheld Microscopes as Diagnostic Platforms for Malaria and Neglected Tropical Diseases (NTDs) in Low-Resource Settings

Cited by 19 publications

References 45 publications

Mobile microscopy and telemedicine platform assisted by deep learning for quantification ofTrichuris trichiurainfection

Mobile microscopy and telemedicine platform assisted by deep learning for quantification ofTrichuris trichiurainfection

Loa loa in the Vitreous Cavity of the Eye: A Case Report and State of Art

Artificial intelligence, diagnostic imaging and neglected tropical diseases: ethical implications

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