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Domrazek K, Jurka P. Application of Next-Generation Sequencing (NGS) Techniques for Selected Companion Animals. Animals (Basel) 2024; 14:1578. [PMID: 38891625 PMCID: PMC11171117 DOI: 10.3390/ani14111578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 05/22/2024] [Accepted: 05/24/2024] [Indexed: 06/21/2024] Open
Abstract
Next-Generation Sequencing (NGS) techniques have revolutionized veterinary medicine for cats and dogs, offering insights across various domains. In veterinary parasitology, NGS enables comprehensive profiling of parasite populations, aiding in understanding transmission dynamics and drug resistance mechanisms. In infectious diseases, NGS facilitates rapid pathogen identification, characterization of virulence factors, and tracking of outbreaks. Moreover, NGS sheds light on metabolic processes by elucidating gene expression patterns and metabolic pathways, essential for diagnosing metabolic disorders and designing tailored treatments. In autoimmune diseases, NGS helps identify genetic predispositions and molecular mechanisms underlying immune dysregulation. Veterinary oncology benefits from NGS through personalized tumor profiling, mutation analysis, and identification of therapeutic targets, fostering precision medicine approaches. Additionally, NGS plays a pivotal role in veterinary genetics, unraveling the genetic basis of inherited diseases and facilitating breeding programs for healthier animals. Physiological investigations leverage NGS to explore complex biological systems, unraveling gene-environment interactions and molecular pathways governing health and disease. Application of NGS in treatment planning enhances precision and efficacy by enabling personalized therapeutic strategies tailored to individual animals and their diseases, ultimately advancing veterinary care for companion animals.
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Affiliation(s)
- Kinga Domrazek
- Institute of Veterinary Medicine, Warsaw University of Life Sciences—SGGW, Nowoursynowska 159c, 02-776 Warsaw, Poland;
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2
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Nagamori Y, Scimeca R, Hall-Sedlak R, Blagburn B, Starkey LA, Bowman DD, Lucio-Forster A, Little SE, Cree T, Loenser M, Larson BS, Penn C, Rhodes A, Goldstein R. Multicenter evaluation of the Vetscan Imagyst system using Ocus 40 and EasyScan One scanners to detect gastrointestinal parasites in feces of dogs and cats. J Vet Diagn Invest 2024; 36:32-40. [PMID: 38014739 PMCID: PMC10734580 DOI: 10.1177/10406387231216185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2023] Open
Abstract
The Vetscan Imagyst system (Zoetis) is a novel, artificial intelligence-driven detection tool that can assist veterinarians in the identification of enteric parasites in dogs and cats. This system consists of a sample preparation device, an automated digital microscope scanner, and a deep-learning algorithm. The EasyScan One scanner (Motic) has had good diagnostic performance compared with manual examinations by experts; however, there are drawbacks when used in veterinary practices in which space for equipment is often limited. To improve the usability of this system, we evaluated an additional scanner, the Ocus 40 (Grundium). Our objectives were to 1) qualitatively evaluate the performance of the Vetscan Imagyst system with the Ocus 40 scanner for identifying Ancylostoma, Toxocara, and Trichuris eggs, Cystoisospora oocysts, and Giardia cysts in canine and feline fecal samples, and 2) expand the assessment of the performance of the Vetscan Imagyst system paired with either the Ocus 40 or EasyScan One scanner to include a larger dataset of 2,191 fecal samples obtained from 4 geographic regions of the United States. When tested with 852 canine and feline fecal samples collected from different geographic regions, the performance of the Vetscan Imagyst system combined with the Ocus 40 scanner was correlated closely with manual evaluations by experts. Sensitivities were 80.0‒97.0% and specificities were 93.7‒100.0% across the targeted parasites. When tested with 1,339 fecal samples, the Vetscan Imagyst system paired with the EasyScan One scanner successfully identified the targeted parasite stages; sensitivities were 73.6‒96.4% and specificities were 79.7‒100.0%.
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Affiliation(s)
| | - Ruth Scimeca
- Oklahoma Animal Disease Diagnostic Laboratory, College of Veterinary Medicine, Oklahoma State University, Stillwater, OK, USA
| | | | - Byron Blagburn
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA
| | - Lindsay A. Starkey
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA
| | - Dwight D. Bowman
- Department of Microbiology and Immunology, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA
| | - Araceli Lucio-Forster
- Department of Microbiology and Immunology, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA
| | - Susan E. Little
- Department of Veterinary Pathobiology, College of Veterinary Medicine, Oklahoma State University, Stillwater, OK, USA
| | - Travis Cree
- Zoetis, Global Diagnostics, Parsippany, NJ, USA
| | | | | | - Cory Penn
- Zoetis, Global Diagnostics, Parsippany, NJ, USA
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Charlier J, Bartley DJ, Sotiraki S, Martinez-Valladares M, Claerebout E, von Samson-Himmelstjerna G, Thamsborg SM, Hoste H, Morgan ER, Rinaldi L. Anthelmintic resistance in ruminants: challenges and solutions. ADVANCES IN PARASITOLOGY 2022; 115:171-227. [PMID: 35249662 DOI: 10.1016/bs.apar.2021.12.002] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Anthelmintic resistance (AR) is a growing concern for effective parasite control in farmed ruminants globally. Combatting AR will require intensified and integrated research efforts in the development of innovative diagnostic tests to detect helminth infections and AR, sustainable anthelmintic treatment strategies and the development of complementary control approaches such as vaccination and plant-based control. It will also require a better understanding of socio-economic drivers of anthelmintic treatment decisions, in order to support a behavioural shift and develop targeted communication strategies that promote the uptake of evidence-based sustainable solutions. Here, we review the state-of-the-art in these different fields of research activity related to AR in helminths of livestock ruminants in Europe and beyond. We conclude that in the advent of new challenges and solutions emerging from continuing spread of AR and intensified research efforts, respectively, there is a strong need for transnational multi-actor initiatives. These should involve all key stakeholders to develop indicators of infection and sustainable control, set targets and promote good practices to achieve them.
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Affiliation(s)
| | - D J Bartley
- Disease Control, Moredun Research Institute, Penicuik, United Kingdom
| | - S Sotiraki
- Veterinary Research Institute, Hellenic Agricultural Organisation ELGO-DIMITRA, Thessaloniki, Greece
| | - M Martinez-Valladares
- Instituto de Ganadería de Montaña (CSIC-Universidad de León), Departamento de Sanidad Animal, León, Spain
| | - E Claerebout
- Ghent University, Faculty of Veterinary Medicine, Laboratory of Parasitology, Merelbeke, Belgium
| | - G von Samson-Himmelstjerna
- Institute for Parasitology and Tropical Veterinary Medicine, Veterinary Centre for Resistance Research, Freie Universität Berlin, Berlin, Germany
| | - S M Thamsborg
- Veterinary Parasitology, University of Copenhagen, Frederiksberg C, Denmark
| | - H Hoste
- INRAE, UMR 1225 IHAP INRAE/ENVT, Toulouse University, Toulouse, France
| | - E R Morgan
- Institute for Global Food Security, Queen's University Belfast, Belfast, United Kingdom
| | - L Rinaldi
- University of Naples Federico II, Unit of Parasitology and Parasitic Diseases, Department of Veterinary Medicine and Animal Production, CREMOPAR, Napoli, Italy.
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Nielsen MK, Doran D, Slusarewicz P. Effects of sample homogenizing on the performance of an automated strongylid egg counting system. Vet Parasitol 2021; 300:109623. [PMID: 34837877 DOI: 10.1016/j.vetpar.2021.109623] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 11/15/2021] [Accepted: 11/20/2021] [Indexed: 10/19/2022]
Abstract
Fecal egg counts are essential monitoring tools in veterinary parasite control. In recent years, several groups have developed automated egg counting systems based on image analysis and deep learning algorithms. Work in our laboratory demonstrated that an automated system performed with significantly better precision than traditional egg counting techniques. However, while the counting process is no longer operator dependent, the pre-analytical homogenization steps still are. This study aimed at evaluating the influence of sample homogenization on diagnostic performance on an automated equine strongylid egg counting system. Samples were collected from 12 horses and assigned to three egg count categories (four samples per category): Low (0-500 eggs per gram (EPG)), Moderate (501-1000 EPG), and High (1001-2000 EPG). Within each category, all samples were divided into four portions and each was analyzed with the automated system using the following four homogenizing procedures using a homogenizing device supplied with the system: 1) pressing the plunger five times and pouring directly into the counting chamber, 2) pressing the plunger five times and shaking the bottle prior to pouring, 3) pressing the plunger ten times with direct pouring, and 4) pressing the plunger ten times with shaking the bottle before pouring. There were no differences in precision expressed as coefficient of variation between these four procedures but shaking of the bottle prior to pouring was significantly associated with higher counts (p = 0.0068). These results demonstrate that the homogenization process can affect the diagnostic performance of an automated egg counting system and suggest that more efforts should be invested in standardizing and optimizing homogenization procedures.
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Affiliation(s)
- Martin K Nielsen
- M.H. Gluck Equine Research Center, Department of Veterinary Science, University of Kentucky, Lexington, KY, USA.
| | - Daniel Doran
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN, USA
| | - Paul Slusarewicz
- MEP Equine Solutions, 3905 English Oak Circle, Lexington, KY, USA
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Inácio SV, Gomes JF, Falcão AX, Martins dos Santos B, Soares FA, Nery Loiola SH, Rosa SL, Nagase Suzuki CT, Bresciani KDS. Automated Diagnostics: Advances in the Diagnosis of Intestinal Parasitic Infections in Humans and Animals. Front Vet Sci 2021; 8:715406. [PMID: 34888371 PMCID: PMC8650151 DOI: 10.3389/fvets.2021.715406] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 10/19/2021] [Indexed: 11/25/2022] Open
Abstract
The increasingly close proximity between people and animals is of great concern for public health, given the risk of exposure to infectious diseases transmitted through animals, which are carriers of more than 60 zoonotic agents. These diseases, which are included in the list of Neglected Tropical Diseases, cause losses in countries with tropical and subtropical climates, and in regions with temperate climates. Indeed, they affect more than a billion people around the world, a large proportion of which are infected by one or more parasitic helminths, causing annual losses of billions of dollars. Several studies are being conducted in search for differentiated, more sensitive diagnostics with fewer errors. These studies, which involve the automated examination of intestinal parasites, still face challenges that must be overcome in order to ensure the proper identification of parasites. This includes a protocol that allows for elimination of most of the debris in samples, satisfactory staining of parasite structures, and a robust image database. Our objective here is therefore to offer a critical description of the techniques currently in use for the automated diagnosis of intestinal parasites in fecal samples, as well as advances in these techniques.
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Affiliation(s)
- Sandra Valéria Inácio
- São Paulo State University (Unesp), School of Veterinary Medicine, Araçatuba, Brazil
| | - Jancarlo Ferreira Gomes
- School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
- Institute of Computing (IC), University of Campinas (UNICAMP), Campinas, Brazil
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Nielsen MK. What makes a good fecal egg count technique? Vet Parasitol 2021; 296:109509. [PMID: 34218175 DOI: 10.1016/j.vetpar.2021.109509] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 06/19/2021] [Accepted: 06/23/2021] [Indexed: 11/28/2022]
Abstract
The first parasite fecal egg counting techniques were described over 100 years ago, and fecal egg counting remains essential in parasitology research as well as in clinical practice today. Several novel techniques have been introduced and validated in recent years, but this work has also highlighted several current issues in this research field. There is a lack of consensus on which diagnostic parameters to evaluate and how to properly design studies doing so. Furthermore, there is a confusing and sometimes incorrect use of terminology describing performance of fecal egg counting techniques, and it would be helpful to address these. This manuscript reviews qualitative and quantitative diagnostic performance parameters, discusses their relevance for fecal egg counting techniques, and highlights some of the challenges with determining them. Qualitative parameters such as diagnostic sensitivity and specificity may be considered classic diagnostic performance metrics, but they generally only have implications at low egg count levels. The detection limit of a given technique is often referred to as the "analytical sensitivity", but this is misleading as the detection limit is a theoretically derived number, whereas analytical sensitivity is determined experimentally. Thus, the detection limit is not a diagnostic performance parameter and does not inform on the diagnostic sensitivity of a technique. Quantitative performance parameters such as accuracy and precision are highly relevant for describing the performance of fecal egg counting techniques, and precision is arguably the more important of the two. An absolute determination of accuracy can only be achieved by use of samples spiked with known quantities of parasite ova, but spiking does not necessarily mimic the true distribution of eggs within a sample, and accuracy estimates are difficult to reproduce between laboratories. Instead, analysis of samples from naturally infected animals can be used to achieve a relative ranking of techniques according to egg count magnitude. Precision can be estimated in a number of different approaches, but it is important to ensure a relevant representation of egg count levels in the study sample set, as low egg counts tend to associate with lower precision estimates. Coefficients of variation generally provide meaningful measures of precision that are independent of the multiplication factor of the techniques evaluated. Taken together, there is a need for clear guidelines for studies validating fecal egg counting techniques in veterinary parasitology with emphasis on what should be evaluated, how studies could be designed, and how to appropriately analyze the data. Furthermore, there is a clear need for better consensus regarding use of terminology describing the diagnostic performance of fecal egg count techniques.
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Affiliation(s)
- Martin K Nielsen
- M.H. Gluck Equine Research Center, Department of Veterinary Science, University of Kentucky, Lexington, KY, USA.
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Nagamori Y, Sedlak RH, DeRosa A, Pullins A, Cree T, Loenser M, Larson BS, Smith RB, Penn C, Goldstein R. Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm. Parasit Vectors 2021; 14:89. [PMID: 33514412 PMCID: PMC7844936 DOI: 10.1186/s13071-021-04591-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 01/11/2021] [Indexed: 11/12/2022] Open
Abstract
Background Fecal examinations in pet cats and dogs are key components of routine veterinary practice; however, their accuracy is influenced by diagnostic methodologies and the experience level of personnel performing the tests. The VETSCAN IMAGYST system was developed to provide simpler and easier fecal examinations which are less influenced by examiners’ skills. This system consists of three components: a sample preparation device, an automated microscope scanner, and analysis software. The objectives of this study were to qualitatively evaluate the performance of the VETSCAN IMAGYST system on feline parasites (Ancylostoma and Toxocara cati) and protozoan parasites (Cystoisospora and Giardia) and to assess and compare the performance of the VETSCAN IMAGYST centrifugal flotation method to reference centrifugal and passive flotation methods. Methods To evaluate the diagnostic performance of the scanning and algorithmic components of the VETSCAN IMAGYST system, fecal slides were prepared by the VETSCAN IMAGYST centrifugal flotation technique with pre-screened fecal samples collected from dogs and cats and examined by both an algorithm and parasitologists. To assess the performance of the VETSCAN IMAGYST centrifugal flotation technique, diagnostic sensitivity and specificity were calculated and compared to those of conventional flotation techniques. Results The performance of the VETSCAN IMAGYST algorithm closely correlated with evaluations by parasitologists, with sensitivity of 75.8–100% and specificity of 93.1-100% across the targeted parasites. For samples with 50 eggs or less per slide, Lin’s concordance correlation coefficients ranged from 0.70 to 0.95 across the targeted parasites. The results of the VETSCAN IMAGYST centrifugal flotation method correlated well with those of the conventional centrifugal flotation method across the targeted parasites: sensitivity of 65.7–100% and specificity of 97.6–100%. Similar results were observed for the conventional passive flotation method compared to the conventional centrifugal flotation method: sensitivity of 56.4–91.7% and specificity of 99.4–100%. Conclusions The VETSCAN IMAGYST scanning and algorithmic systems with the VETSCAN IMAGYST fecal preparation technique demonstrated a similar qualitative performance to the parasitologists’ examinations with conventional fecal flotation techniques. Given the deep learning nature of the VETSCAN IMAGYST system, its performance is expected to improve over time, enabling it to be utilized in veterinary clinics to perform fecal examinations accurately and efficiently.![]()
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Affiliation(s)
- Yoko Nagamori
- Department of Veterinary Pathobiology, College of Veterinary Medicine, Oklahoma State University, Stillwater, OK, 74078, USA. .,Petcare, Zoetis, 10 Sylvan Way, Parsippany, NJ, 07054, USA.
| | - Ruth Hall Sedlak
- Veterinary Medicine Research and Development, Zoetis, 333 Portage Street, Kalamazoo, MI, 49007, USA
| | - Andrew DeRosa
- Veterinary Medicine Research and Development, Zoetis, 333 Portage Street, Kalamazoo, MI, 49007, USA
| | - Aleah Pullins
- Veterinary Medicine Research and Development, Zoetis, 333 Portage Street, Kalamazoo, MI, 49007, USA
| | - Travis Cree
- Veterinary Medicine Research and Development, Zoetis, 333 Portage Street, Kalamazoo, MI, 49007, USA
| | - Michael Loenser
- Global Diagnostics, Zoetis, 10 Sylvan Way, Parsippany, NJ, 07054, USA
| | | | | | - Cory Penn
- Global Diagnostics, Zoetis, 10 Sylvan Way, Parsippany, NJ, 07054, USA
| | - Richard Goldstein
- Global Diagnostics, Zoetis, 10 Sylvan Way, Parsippany, NJ, 07054, USA
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Abstract
The Kubic FLOTAC microscope (KFM) is a compact, low-cost, versatile and portable digital microscope designed to analyse fecal specimens prepared with Mini-FLOTAC or FLOTAC, in both field and laboratory settings. In this paper, we present the characteristics of the KFM along with its first validation for fecal egg count (FEC) of gastrointestinal nematodes (GINs) in cattle. For this latter purpose, a study was performed on 30 fecal samples from cattle experimentally infected by GINs to compare the performance of Mini-FLOTAC either using a traditional optical microscope (OM) or the KFM. The results of the comparison showed a substantial agreement (concordance correlation coefficient = 0.999), with a very low discrepancy (−0.425 ± 7.370) between the two microscopes. Moreover, the KFM captured images comparable with the view provided by the traditional OM. Therefore, the combination of sensitive, accurate, precise and standardized FEC techniques, as the Mini-FLOTAC, with a reliable automated system, will permit the real-time observation and quantification of parasitic structures, thanks also to artificial intelligence software, that is under development. For these reasons, the KFM is a promising tool for an accurate and efficient FEC to improve parasite diagnosis and to assist new generations of operators in veterinary and public health.
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Nagamori Y, Hall Sedlak R, DeRosa A, Pullins A, Cree T, Loenser M, Larson BS, Smith RB, Goldstein R. Evaluation of the VETSCAN IMAGYST: an in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm. Parasit Vectors 2020; 13:346. [PMID: 32653042 PMCID: PMC7353785 DOI: 10.1186/s13071-020-04215-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 07/02/2020] [Indexed: 11/26/2022] Open
Abstract
Background Fecal examination is an important component of routine companion animal wellness exams. Sensitivity and specificity of fecal examinations, however, are influenced by sample preparation methodologies and the level of training and experience of personnel who read fecal slides. The VETSCAN IMAGYST system consists of three components: a sample preparation device, a commercially available scanner, and an analysis software. The VETSCAN IMAGYST automated scanner and cloud-based, deep learning algorithm, locates, classifies, and identifies parasite eggs found on fecal microscopic slides. The main study objectives were (i) to qualitatively evaluate the capabilities of the VETSCAN IMAGYST screening system and (ii) to assess and compare the performance of the VETSCAN IMAGYST fecal preparation methods to conventional fecal flotation techniques. Methods To assess the capabilities of VETSCAN IMAGYST screening components, fecal slides were prepared by the VETSCAN IMAGYST centrifugal and passive flotation techniques with 100 pre-screened fecal samples collected from dogs and cats and examined by both the algorithm and parasitologists. To determine the diagnostic sensitivity and specificity of the VETSCAN IMAGYST sample preparation techniques, fecal flotation slides were prepared by four different techniques (VETSCAN IMAGYST centrifugal and passive flotations, conventional centrifugal flotation, and passive flotation using OVASSAY® Plus) and examined by parasitologists. Additionally, required sample preparation and scanning times were estimated on a subset of samples to evaluate VETSCAN IMAGYST ease-of-use. Results The algorithm performance of the VETSCAN IMAGYST closely matched that of the parasitologists, with Pearsonʼs correlation coefficient (r) ranging from 0.83–0.99 across four taxa of parasites, Ancylostoma, Toxocara, Trichuris and Taeniidae. Both VETSCAN IMAGYST centrifugal and passive flotation methods correlated well with conventional preparation methods on all targeted parasites (diagnostic sensitivity of 75.8–100%, specificity of 91.8–100%, qualitative agreement between methods of 93.8–94.5%). Sample preparation, slide scan and image analysis were completed within 10–14 min by VETSCAN IMAGYST centrifugal and passive flotations, respectively. Conclusions The VETSCAN IMAGYST scanning system with the VETSCAN IMAGYST sample preparation methods demonstrated a qualitative match in comparison to the results of parasitologists’ examinations with conventional fecal flotation techniques. The VETSCAN IMAGYST is an easy-to-use, next generation qualitative and possibly quantitative diagnostic platform that brings expert clinical results into the hands of veterinary clinics.![]()
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Affiliation(s)
- Yoko Nagamori
- Department of Veterinary Pathobiology, College of Veterinary Medicine, Oklahoma State University, Stillwater, OK, 74078, USA
| | - Ruth Hall Sedlak
- Zoetis, Veterinary Medicine Research and Development, 333 Portage St, Kalamazoo, MI, 49007, USA.
| | - Andrew DeRosa
- Zoetis, Veterinary Medicine Research and Development, 333 Portage St, Kalamazoo, MI, 49007, USA
| | - Aleah Pullins
- Zoetis, Veterinary Medicine Research and Development, 333 Portage St, Kalamazoo, MI, 49007, USA
| | - Travis Cree
- Zoetis, Veterinary Medicine Research and Development, 333 Portage St, Kalamazoo, MI, 49007, USA
| | - Michael Loenser
- Zoetis, Global Diagnostics, 10 Sylvan Way, Parsippany, NJ, 07054, USA
| | | | | | - Richard Goldstein
- Zoetis, Global Diagnostics, 10 Sylvan Way, Parsippany, NJ, 07054, USA
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Soares FA, Benitez ADN, dos Santos BM, Loiola SHN, Rosa SL, Nagata WB, Inácio SV, Suzuki CTN, Bresciani KDS, Falcão AX, Gomes JF. A historical review of the techniques of recovery of parasites for their detection in human stools. Rev Soc Bras Med Trop 2020; 53:e20190535. [PMID: 32491097 PMCID: PMC7269538 DOI: 10.1590/0037-8682-0535-2019] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 04/30/2020] [Indexed: 11/22/2022] Open
Abstract
Since the early 20th century, the detection of intestinal parasites has improved with the development of several techniques for parasitic structures recovery and identification, which differ in sensitivity, specificity, practicality, cost, and infrastructure demand. This study aims to review, in chronological order, the stool examination techniques and discuss their advantages, limitations, and perspectives, and to provide professionals and specialists in this field with data that lays a foundation for critical analysis on the use of such procedures. The concentration procedures that constitute the main techniques applied in routine research and in parasitological kits are a) spontaneous sedimentation; b) centrifugation-sedimentation with formalin-ethyl acetate; and c) flotation with zinc sulfate solution. While selecting a technique, one should consider the purpose of its application and the technical-operational, biological, and physicochemical factors inherent in the procedures used in stool processing, which may restrict its use. These intrinsic limitations may have undergone procedural changes driven by scientific and technological development and by development of alternative methods, which now contribute to the improvement of diagnostic accuracy.
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Affiliation(s)
- Felipe Augusto Soares
- Universidade Estadual de Campinas, Faculdade de Ciências Médicas, Campinas, SP, Brasil
| | | | | | | | - Stefany Laryssa Rosa
- Universidade Estadual de Campinas, Faculdade de Ciências Médicas, Campinas, SP, Brasil
| | - Walter Bertequini Nagata
- Universidade Estadual Paulista, Faculdade de Medicina Veterinária, Departamento de Apoio, Produção e Saúde Animal, Araçatuba, SP, Brasil
| | - Sandra Valéria Inácio
- Universidade Estadual Paulista, Faculdade de Medicina Veterinária, Departamento de Apoio, Produção e Saúde Animal, Araçatuba, SP, Brasil
| | | | - Katia Denise Saraiva Bresciani
- Universidade Estadual Paulista, Faculdade de Medicina Veterinária, Departamento de Apoio, Produção e Saúde Animal, Araçatuba, SP, Brasil
| | | | - Jancarlo Ferreira Gomes
- Universidade Estadual de Campinas, Faculdade de Ciências Médicas, Campinas, SP, Brasil
- Universidade Estadual de Campinas, Instituto de Computação, Campinas, SP, Brasil
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