Literature DB >> 33733938

Detection of circulating microfilariae in canine EDTA blood using lens-free technology: preliminary results.

Typhaine Lavabre1,2, Zoe S Polizopoulou3, Damien Isèbe4, Olivier Cioni5, Véronique Rebuffel5, Pierre Blandin5, Nathalie Bourgès-Abella2, Catherine Trumel1,2.   

Abstract

Dirofilaria immitis causes life-threatening heart disease in dogs, thus screening of dog populations is important. Lens-free technology (LFT) is a low-cost imaging technique based on light diffraction that allows computerized recognition of small objects in holographic images. We evaluated an algorithm capable of recognizing microfilariae in canine whole blood using the LFT. We examined 3 groups of 10 EDTA blood specimens, from dogs with microfilaremia (group A), healthy dogs (B), and dogs with hematologic modifications other than microfilaremia (C). The LFT analyzer photographed repeated series of 5 images of all samples. The algorithm declared a sample positive if a microfilaria was detected on ≥1, ≥2, or ≥3 of the 5 images of a series. Microfilariae were detected visually in the images in 9 of 10 cases in group A; no microfilariae were seen in the images from groups B and C. Of the 30 cases, there were 14, 4, and only 3 false-positives with the 1 of 5, 2 of 5, and 3 of 5 image cutoffs, respectively. There were no false-negatives, regardless of cutoff. LFT seems useful for detecting microfilaria and could have application in clinical pathology.

Entities:  

Keywords:  Dirofilaria immitis; dogs; lens-free imaging; microfilaria

Mesh:

Substances:

Year:  2021        PMID: 33733938      PMCID: PMC8120067          DOI: 10.1177/10406387211001092

Source DB:  PubMed          Journal:  J Vet Diagn Invest        ISSN: 1040-6387            Impact factor:   1.279


  4 in total

Review 1.  A review of recent progress in lens-free imaging and sensing.

Authors:  Mohendra Roy; Dongmin Seo; Sangwoo Oh; Ji-Woon Yang; Sungkyu Seo
Journal:  Biosens Bioelectron       Date:  2016-08-01       Impact factor: 10.618

Review 2.  Lens-free imaging for biological applications.

Authors:  Sang Bok Kim; Hojae Bae; Kyo-In Koo; Mehmet R Dokmeci; Aydogan Ozcan; Ali Khademhosseini
Journal:  J Lab Autom       Date:  2012-02

3.  Motility-based label-free detection of parasites in bodily fluids using holographic speckle analysis and deep learning.

Authors:  Yibo Zhang; Hatice Ceylan Koydemir; Michelle M Shimogawa; Sener Yalcin; Alexander Guziak; Tairan Liu; Ilker Oguz; Yujia Huang; Bijie Bai; Yilin Luo; Yi Luo; Zhensong Wei; Hongda Wang; Vittorio Bianco; Bohan Zhang; Rohan Nadkarni; Kent Hill; Aydogan Ozcan
Journal:  Light Sci Appl       Date:  2018-12-12       Impact factor: 17.782

4.  Evaluation of a lens-free imager to facilitate tuberculosis diagnostics in MODS.

Authors:  Leonardo Solis; Jorge Coronel; Daniel Rueda; Robert H Gilman; Patricia Sheen; Mirko Zimic
Journal:  Tuberculosis (Edinb)       Date:  2015-12-21       Impact factor: 3.131

  4 in total

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