State-of-the-Art Techniques for Diagnosis of Medical Parasites and Arthropods

Conventional methods such as microscopy have been used to diagnose parasitic diseases and medical conditions related to arthropods for many years. Some techniques are considered gold standard methods. However, their limited sensitivity, specificity, and accuracy, and the need for costly reagents and...

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Bibliographic Details
Published inDiagnostics (Basel) Vol. 11; no. 9; p. 1545
Main Author Ruenchit, Pichet
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 26.08.2021
MDPI
Subjects
Antigens
arthropod
Arthropods
artificial intelligence
Biosensors
diagnosis
DNA barcoding
Enzymes
Epidemics
geometric morphometrics
Immunology
Infections
Laboratories
Mass spectrometry
Methods
Molecular biology
parasite
Parasites
Parasitic diseases
Polymerase chain reaction
Polymorphism
R&D
Research & development
Review
Scientific imaging
Tropical diseases
Thailand
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Summary:Conventional methods such as microscopy have been used to diagnose parasitic diseases and medical conditions related to arthropods for many years. Some techniques are considered gold standard methods. However, their limited sensitivity, specificity, and accuracy, and the need for costly reagents and high-skilled technicians are critical problems. New tools are therefore continually being developed to reduce pitfalls. Recently, three state-of-the-art techniques have emerged: DNA barcoding, geometric morphometrics, and artificial intelligence. Here, data related to the three approaches are reviewed. DNA barcoding involves an analysis of a barcode sequence. It was used to diagnose medical parasites and arthropods with 95.0% accuracy. However, this technique still requires costly reagents and equipment. Geometric morphometric analysis is the statistical analysis of the patterns of shape change of an anatomical structure. Its accuracy is approximately 94.0–100.0%, and unlike DNA barcoding, costly reagents and equipment are not required. Artificial intelligence technology involves the analysis of pictures using well-trained algorithms. It showed 98.8–99.0% precision. All three approaches use computer programs instead of human interpretation. They also have the potential to be high-throughput technologies since many samples can be analyzed at once. However, the limitation of using these techniques in real settings is species coverage.
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ISSN:2075-4418
2075-4418
DOI:10.3390/diagnostics11091545