Article

Brief Communication

Ann Lab Med 2021; 41(2): 221-224

Published online March 1, 2021 https://doi.org/10.3343/alm.2021.41.2.221

Copyright © Korean Journal of Laboratory Medicine.

Utility of an Automatic Vision-Based Examination System (AVE-562) for the Detection of Clonorchis sinensis Eggs in Stool

Yu Jeong Lee, M.T.1 , Eun Jeong Won, M.D., Ph.D.1,2 , Young-Chang Cho, Ph.D.3 , Soo Hyun Kim, M.D., Ph.D.2 , Myung Geun Shin, M.D., Ph.D.2 , and Jong Hee Shin, M.D., Ph.D.2

1Department of Parasitology and Tropical Medicine, Chonnam National University Medical School, Gwangju, Korea; 2Department of Laboratory Medicine, Chonnam National University Medical School, Gwangju, Korea; 3College of Pharmacy, Chonnam National University, Gwangju, Korea

Correspondence to: Eun Jeong Won, M.D., Ph.D.
Department of Parasitology and Tropical Medicine, Chonnam National University Medical School, 42 Jebongro, Dongku, Gwangju 61469, Korea
Tel: +82-61-379-2716
Fax: +82-62-220-5370
E-mail: Parasite.woni@jnu.ac.kr

Received: January 29, 2020; Revised: April 22, 2020; Accepted: September 19, 2020

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Stool examination is the gold standard for the detection of intestinal parasites. We assessed the performance of a newly developed AVE-562 analyzer (AVE Science & Technology Co., Hunan, China) for the vision-based detection of eggs of Clonorchis sinensis—the most common intestinal parasite in Korea—in stool samples. In total, 30 stool samples with a high or low egg count or without eggs (as negative control samples) (N=10 each) were prepared and analyzed. The performance of the AVE-562 analyzer was compared with that of the formalin-ether concentration (FEC) method. The overall correct identification rate of the AVE-562 analyzer based on FEC results was 66.6%. The sensitivity, specificity, positive predictive value, and negative predictive value of the AVE-562 analyzer for detecting C. sinensis eggs were 36.4%, 100.0%, 100.0%, and 73.1%, respectively. The average time required to run five tests simultaneously was 27 min using the AVE-562 analyzer and 58 min using the FEC method. Although the AVE-562 analyzer enables rapid and convenient stool examination, its sensitivity needs to be improved, particularly considering the prevalence of low-burden C. sinensis infection in Korea.

Keywords: AVE-562 analyzer, Performance, Parasite, Clonorchis sinensis, Eggs

Infection with intestinal parasites occurs worldwide and represents a widespread and serious public health concern in developing countries [1]. In Korea, intestinal parasitic infections were highly prevalent [2], but their prevalence has drastically declined [3]. Currently, Clonorchis sinensis infection is the most prevalent intestinal parasitic infection in Korea [3, 4]. With an estimated 932,540 Koreans being infected, the prevalence of clonorchiasis is 1.9% [4], and it remains highly endemic in riverside areas of Korea [5]. For the control of clonorchiasis, accurate and rapid diagnosis is essential. Clonorchiasis can be diagnosed on the basis of stool microscopy, imaging, serology, and molecular methods. Serological analysis using enzyme-linked immunosorbent assay (ELISA) is useful for diagnosing clonorchiasis, but it is insensitive for low-burden infection. Although molecular diagnostic techniques are sensitive, they are associated with issues concerning contamination and high cost, which hindered their application in large-scale field surveys [6-9]. Stool examination for C. sinensis eggs is the gold standard for clonorchiasis diagnosis [10, 11], but it is labor-intensive, requires a high level of technical expertise, and can be insensitive for low-burden infection [12].

There is an increasing demand for low-complexity, highthroughput, and cost-effective tools to replace labor-intensive microscopic examinations. Accordingly, digital imaging diagnosis based on the morphometric characteristics of parasite eggs has been proposed [13-15]. The first study to use an automated stool examination system suggested that an adjusted algorithm should be created for the correct classification of helminth eggs [13]. Recently, a cuvette-based automated microscopy analyzer, sediMAX 1 (77 Elektronika, Budapest, Hungary), was evaluated for the detection of intestinal parasites, helminths, and protozoa [14]. The sediMAX 1 analyzer showed perfect performance for the detection of Dibothriocephalus nihonkaiensis, Taenia species, Hymenolepis nana, Trichuris trichiura, Ascaris lumbricoides, and Paragonimus westermani [14, 15]. However, C. sinensis and other intestinal parasites prevalent in Korea were not evaluated in these studies. Similarly to sediMAX 1, the newly developed AVE-562 analyzer (AVE Science & Technology Co., Hunan, China) allows vision-based detection of eggs. Here, we evaluated the utility of the AVE-562 analyzer for detecting C. sinensis eggs in low-burden infections. Additionally, we assessed the performance of this system compared with that of conventional examination for the detection of C. sinensis eggs in stool samples.

In total, 30 stool samples with a high or low egg count or without eggs (as negative control samples; N= 10 each) were prepared and analyzed. Then, the amount of eggs in high-count formalinized stool samples collected for laboratory quality-control purposes at Chonnam National University Hospital, Gwangju, Korea, from January 2018 to December 2019 was adjusted to 150 eggs/mL. Stool samples were collected with the approval provided by the Institutional Review Board of Chonnam National University Hospital (IRB CNUH-2015-052). All data obtained were anonymized, and no information was used that could lead to patient identification. The need for written consent was waived due to minimal risk to the subjects.

Formalized stool samples within a month from subjects not infected with C. sinensis served as negative controls. The low-count samples (< 10 eggs/mL) were prepared by mixing 10 µL of high-count samples with 1 mL of negative control samples. Automated vision-based stool examination for egg detection was performed using the AVE-562 analyzer. On adding the formalinized stool samples to the sampling cup, cuvette slides were automatically generated. The internal charge-coupled device camera captured 20 images, which were analyzed using the system software (AVE Science & Technology Co.). The images were reviewed on-screen for the presence of parasites by two experts, each blinded to the other’s findings. After one run of the analyzer, the cuvette contents were re-examined under a Nikon Eclipse Ni-U microscope (Nikon Co., Tokyo, Japan). Conventional stool examination was performed using the formalin-ether concentration (FEC) method [10]; three slides per sample were observed independently by two experts. The procedure time for conducting one, five, and 10 tests simultaneously was evaluated for both methods. The chi-squared or Fisher’s exact test was used to compare the overall correct identification rates. Student’s t-test was used to compare the procedure times. The performance (sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]) of the AVE-562 analyzer was evaluated and compared with that of FEC as a gold standard. All statistical analyses were performed using the GraphPad Prism 5 software (GraphPad Software Inc., La Jolla, CA, USA), and significance was determined at P < 0.05.

Of the 10 high-egg-count samples, only four tested positive using the AVE-562 analyzer, whereas all 10 tested positive by the FEC method (Table 1). Of the 10 low-egg-count samples, none tested positive using the AVE-562 analyzer, and only one tested positive using the FEC method. All negative control samples tested negative using both methods. The overall correct identification rate of the AVE-562 analyzer based on the FEC results was 66.6% (14/21) (P < 0.001). The sensitivity, specificity PPV, and NPV of the AVE-562 analyzer were 36.4%, 100.0%, 100.0%, and 73.1%, respectively. When we analyzed the seven samples, eggs in which were detected using the FEC method but not using the AVE-562 analyzer, two tested positive on cuvette reexamination, four tested positive by retrospective image observation, and the remaining one was a test failure. Such falsenegatives may be overcome through the acquisition of more images (> 20) or the development of an image-processing software based on neural networks [16]. The AVE-562 analyzer had a shorter total procedure time than the FEC method (P = 0.01 for a test, P = 0.0131 for five tests, P = 0.0275 for ten tests, respectively) (Fig. 1). Thus, the AVE-562 analyzer allows rapid testing and is easy to use; however, its diagnostic sensitivity requires improvement.

Table 1 . Performance of the AVE-562 analyzer for the detection of Clonorchis sinensis eggs

N (%) of correct resultsPerformance (95% confidence interval)*


Positive samples (N=20)Negative samples (N=10)SubtotalSensitivitySpecificityPositive predictive valueNegative predictive value

High count (N=10)Low count (N=10)
AVE-5624 (40%)0 (0%)10 (100%)14/21 (66.6%)36.40% (10.9%-69.2%)100% (82.3%-100.0%)100%73.10% (63.4%-80.9%)
FEC10 (100%)1 (10%)10 (100%)21/21 (100%)NA

*Stool examination based on FEC was considered as a gold standard diagnostic test for evaluating the performance of the AVE-562 analyzer; Significant differences were found between AVE-562 and FEC in the overall correct identification, in addition to the correct identification for the high-count positive samples (P value <0.001).

Abbreviations: FEC, formalin-ether concentration; NA, not applicable.


Figure 1. Average procedure times for the two methods as a function of the number of samples analyzed simultaneously. The average times required to run one, five, and 10 tests at a time were 8, 27, and 51 minutes, respectively, for the AVE-562 analyzer and 43, 58, and 66 minutes, respectively, for the FEC method. The AVE-562 analyzer showed a significantly shorter total procedure time than the FEC method (P = 0.01 for one test, P = 0.0131 for five tests, P = 0.0275 for ten tests, respectively). Abbreviation: FEC, formalin-ether concentration.

Our study had several limitations. First, eggs of intestinal parasites prevalent in Korea other than C. sinensis were not evaluated; this is required to ensure the specificity of the AVE-562 analyzer. Second, we analyzed a relatively small number of samples. However, the AVE-562 analyzer has enough potential to detect C. sinensis eggs in routine screening of stool samples. In addition, images stored by the AVE-562 analyzer can be also useful for educational and quality-control purposes. Overall, our findings indicate that the AVE-562 analyzer enables rapid and convenient stool examination in clinical laboratories, where multiple samples are tested in real-time. However, further improvement is required for the more sensitive and accurate diagnosis of intestinal parasite infections on the basis of vision-based egg detection using the AVE-562 analyzer.

This work was partly supported by the AVE Science & Technology Co. The opinions expressed in this paper are those of the authors and do not necessarily represent those of AVE Science & Technology Co.

Eun Jeong Won conceived the study, participated in study design and data analysis and was responsible for the writing and submission of the final manuscript. Yu Jeong Lee carried out the experimental study and participated in writing the manuscript. Young-Chang Cho, Soo Hyun Kim, Myung Geun Shin, and Jong Hee Shin analyzed and interpreted data. All authors were involved in revising the manuscript critically for important intellectual content, and all authors approved the final version to be published.

No potential conflicts of interest relevant to this article were reported.

This study was financially supported by Chonnam National University (grant number: 2018-3309), Chonnam National University Hwasun Hospital Institute for Biomedical Science (HCRI 19026), and the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2019R1C1C1004605 and NRF2019M3E5D1A02067953).

  1. Ojha SC, Jaide C, Jinawath N, Rotjanapan P, Baral P. Geohelminths: public health significance. J Infect Dev Ctries 2014;8:5-16.
    Pubmed CrossRef
  2. Hong ST, Chai JY, Choi MH, Huh S, Rim HJ, Lee SH. A successful experience of soil-transmitted helminth control in the Republic of Korea. Korean J Parasitol 2006;44:177-85.
    Pubmed KoreaMed CrossRef
  3. Kim TS, Cho SH, Huh S, Kong Y, Sohn WM, Hwang SS, et al. A nationwide survey on the prevalence of intestinal parasitic infections in the Republic of Korea, 2004. Korean J Parasitol 2009;47:37-47.
    Pubmed KoreaMed CrossRef
  4. Korea Centers for Disease Control and Prevention; Korea National Institute of Health. National survey of the prevalence of intestinal parasitic infections in Korea, 2012. The 8th Report. Osong. Chungcheongbuk-do, Korea. 2013.
  5. Jeong YI, Shin HE, Lee SE, Cheun HI, Ju JW, Kim JY, et al. Prevalence of Clonorchis sinensis infection among residents along 5 major rivers in the Republic of Korea. Korean J Parasitol 2016;54:215-9.
    Pubmed KoreaMed CrossRef
  6. Li HM, Qian MB, Yang YC, Jiang ZH, Wei K, Chen JX, et al. Performance evaluation of existing immunoassays for Clonorchis sinensis infection in China. Parasit Vectors 2018;11:35.
    Pubmed KoreaMed CrossRef
  7. Pacheco FTF, de Carvalho SS, Santos SA, das Chagas GMT, Santos MC, Santos JGS, et al. Specific IgG and IgA antibody reactivities in sera of children by Enzyme-Linked Immunoassay and comparison with Giardia duodenalis diagnosis in feces. Ann Lab Med 2020;40:382-9.
    Pubmed KoreaMed CrossRef
  8. Rahman SMM, Song HB, Jin Y, Oh JK, Lim MK, Hong ST, et al. Application of a loop-mediated isothermal amplification (LAMP) assay targeting cox1 gene for the detection of Clonorchis sinensis in human fecal samples. PLoS Negl Trop Dis 2017;11:e0005995.
    Pubmed KoreaMed CrossRef
  9. Won EJ, Kim SH, Kee SJ, Shin JH, Suh SP, Chai JY, et al. Multiplex real-time PCR assay targeting eight parasites customized to the Korean population: potential use for detection in diarrheal stool samples from gastroenteritis patients. PLoS One 2016;11:e0166957.
    Pubmed KoreaMed CrossRef
  10. Won EJ, Kim J, Ryang DW. Evaluation of modified formalin-ether concentration method using Para tube in clinical settings. Ann Lab Med 2015;35:445-8.
    Pubmed KoreaMed CrossRef
  11. McHardy IH, Wu M, Shimizu-Cohen R, Couturier MR, Humphries RM. Detection of intestinal protozoa in the clinical laboratory. J Clin Microbiol 2014;52:712-20.
    Pubmed KoreaMed CrossRef
  12. Han S, Zhang X, Wen J, Li Y, Shu J, Ling H, et al. A combination of the Kato-Katz methods and ELISA to improve the diagnosis of clonorchiasis in an endemic area, China. PLoS One 2012;7:e46977.
    Pubmed KoreaMed CrossRef
  13. Yang YS, Park DK, Kim HC, Choi MH, Chai JY. Automatic identification of human helminth eggs on microscopic fecal specimens using digital image processing and an artificial neural network. IEEE Trans Biomed Eng 2001;48:718-30.
    Pubmed CrossRef
  14. Intra J, Taverna E, Sala MR, Falbo R, Cappellini F, Brambilla P. Detection of intestinal parasites by use of the cuvette-based automated microscopy analyser sedi MAX®. Clin Microbiol Infect 2016;22:279-84.
    Pubmed CrossRef
  15. Intra J, Sala MR, Falbo R, Cappellini F, Brambilla P. Improvement in the detection of enteric protozoa from clinical stool samples using the automated urine sediment analyzer sediMAX® 2 compared to sediMAX® 1. Eur J Clin Microbiol Infect Dis 2017;36:147-51.
    Pubmed CrossRef
  16. Anwar SM, Majid M, Qayyum A, Awais M, Alnowami M, Khan MK. Medical image analysis using convolutional neural networks: a review. J Med Syst 2018;42:226.
    Pubmed CrossRef