Advantages and limitations of microscopy and molecular detections for diagnosis of soil-transmitted helminths: An overview

Miswan, Noorizan; Singham, G Veera; Othman, Nurulhasanah

doi:10.2478/helm-2022-0034

Cited by 9 publications

(3 citation statements)

References 104 publications

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“…Currently, the recommended method of diagnostics of STHs is manual microscopy of stool samples to visualize and manually quantify parasites or parasite eggs [ 7 , 8 ]. However, there is a shortage of experts and access to microscopy equipment and laboratory infrastructure in regions with the highest STH prevalence [ 9 , 10 ]. Access to diagnostic tests is vital for efficient infection control and elimination of STHs as a public health problem, as well as and STH management, and there is a need for improved diagnostic tests that are accurate, feasible to use and deployable in regional laboratories, at the point-of-care (POC) and point-of-sampling in low-resource settings [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of soil-transmitted helminth infections with digital mobile microscopy and artificial intelligence in a resource-limited setting

Lundin,

Suutala,

Holmström

et al. 2024

PLoS Negl Trop Dis

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Background Infections caused by soil-transmitted helminths (STHs) are the most prevalent neglected tropical diseases and result in a major disease burden in low- and middle-income countries, especially in school-aged children. Improved diagnostic methods, especially for light intensity infections, are needed for efficient, control and elimination of STHs as a public health problem, as well as STH management. Image-based artificial intelligence (AI) has shown promise for STH detection in digitized stool samples. However, the diagnostic accuracy of AI-based analysis of entire microscope slides, so called whole-slide images (WSI), has previously not been evaluated on a sample-level in primary healthcare settings in STH endemic countries. Methodology/Principal findings Stool samples (n = 1,335) were collected during 2020 from children attending primary schools in Kwale County, Kenya, prepared according to the Kato-Katz method at a local primary healthcare laboratory and digitized with a portable whole-slide microscopy scanner and uploaded via mobile networks to a cloud environment. The digital samples of adequate quality (n = 1,180) were split into a training (n = 388) and test set (n = 792) and a deep-learning system (DLS) developed for detection of STHs. The DLS findings were compared with expert manual microscopy and additional visual assessment of the digital samples in slides with discordant results between the methods. Manual microscopy detected 15 (1.9%) Ascaris lumbricoides, 172 (21.7%) Tricuris trichiura and 140 (17.7%) hookworm (Ancylostoma duodenale or Necator americanus) infections in the test set. Importantly, more than 90% of all STH positive cases represented light intensity infections. With manual microscopy as the reference standard, the sensitivity of the DLS as the index test for detection of A. lumbricoides, T. trichiura and hookworm was 80%, 92% and 76%, respectively. The corresponding specificity was 98%, 90% and 95%. Notably, in 79 samples (10%) classified as negative by manual microscopy for a specific species, STH eggs were detected by the DLS and confirmed correct by visual inspection of the digital samples. Conclusions/Significance Analysis of digitally scanned stool samples with the DLS provided high diagnostic accuracy for detection of STHs. Importantly, a substantial number of light intensity infections were missed by manual microscopy but detected by the DLS. Thus, analysis of WSIs with image-based AI may provide a future tool for improved detection of STHs in a primary healthcare setting, which in turn could facilitate monitoring and evaluation of control programs.

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Section: Introductionmentioning

confidence: 99%

Diagnosis of soil-transmitted helminth infections with digital mobile microscopy and artificial intelligence in a resource-limited setting

Lundin,

Suutala,

Holmström

et al. 2024

PLoS Negl Trop Dis

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“…Helminths are complex organisms that comprise approximately three hundred thousand species that can be either free-living or parasitic. [1] Soil-transmitted helminth (STH) infections are worms that can be facilitated by one or more intestinal parasitic worms such as [2] roundworm (Ascaris lumbricoides [AL]), hookworm (HW; Ancylostoma duodenale and Necator americanus), [3] threadworm (Strongyloides stercoralis), and whipworm (Trichuris trichiura [TT]). [4] Soil is a good medium for egg development and can affect human health, although it rarely causes death.…”

Section: Introductionmentioning

confidence: 99%

Effect of Azadirachta indica on Pheretima posthuma

Quaiyoom,

Kumari,

Aditya

et al. 2023

Pharmaspire

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Soil-transmitted helminth (STH) infections are worm infections that can be facilitated by one or more intestinal parasitic worms such as roundworm (Ascaris lumbricoides), hookworm (HW; Ancylostoma duodenale and Necator americanus), threadworm (Strongyloides stercoralis), and whipworm (Trichuris trichiura). More than two billion people are thought to be affected by STH infections globally. Eggs in human feces, which are commonly seen in low-resource countries, spread STH by contaminating the soil and water in unhygienic places. The transmission is by human exposures to the infective stages, either by direct skin penetration or through ingestion that could result in a serious illness, though infections remain asymptomatic in the majority of cases with light-intensity infections. Azadirachta indica, usually called Indian neem, has been extensively used in ayurveda, unani, and homoeopathic medicine since time immemorial. A. inidica has been used ethnopharmacologically to treat diseases such as cancer, diarrhea, gastric ulcers, wound infections, trypanosomiasis, malaria, and tuberculosis. A. indica leaf extracts in methanol were tested for their ability to treat Pheretima posthuma worms. From the experimental outcome, we find that the leaf extracts of A. indica, when compared to the usual medication, the plant was found to exhibit substantial anthelmintic activity. The present research concludes that neem has a variety of bioactive compou

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“…According to projections, approximately 1.5 billion individuals, or 24% of the global population, are infected with illnesses set on by soil-transmitted helminths (STHs), making them a number of the most prominent infections in the world [7][8] [13][14] [15][5] [16]. Due to the strong correlations between socioeconomic situations, individual cleanliness, and environmental factors in Indonesia, STH infections tend to be an ongoing issue [5] [14][17] [18][19] [20][21] [22]. In certain provinces, children aged between the ages of 1 and 12 have a worm-related spread rate that oscillates between 30% to 90% [13] [14] [17] [23][24] [25].…”

Section: Introductionmentioning

confidence: 99%

Enhancing Soil-Transmitted Helminth Detection in Microscopic Images Using the Chain Code for Object Feature Extraction

Malik,

Frimadani,

Putra

2023

International Journal of Advances in Data and Information Syste

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Soil-Transmitted Helminth (STH) infections are a grave global health issue, which involves particularly in countries that are developing with insufficient sanitation and limited access to healthcare. With better intestinal helminth egg detection technology, health facilities in areas with limited resources can identify and treat these infections more promptly. It is necessary to create a strong framework and an effective method to solve this challenge. The outcomes of this study could assist in parasite infection discovery and public health. Chain code-based feature extraction strategy can also be the foundation for the development of comparable approaches for diagnosing various parasitic diseases. Overall, the neural network design used in this study makes the model that is produced a good model that assigns well to never-before-seen data. The significance of image processing technologies in the medical field is shown by this study.

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Advantages and limitations of microscopy and molecular detections for diagnosis of soil-transmitted helminths: An overview

Cited by 9 publications

References 104 publications

Diagnosis of soil-transmitted helminth infections with digital mobile microscopy and artificial intelligence in a resource-limited setting

Diagnosis of soil-transmitted helminth infections with digital mobile microscopy and artificial intelligence in a resource-limited setting

Effect of Azadirachta indica on Pheretima posthuma

Enhancing Soil-Transmitted Helminth Detection in Microscopic Images Using the Chain Code for Object Feature Extraction

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