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Development of an automated MODS plate reader to detect early growth of Mycobacterium tuberculosis

  • G. Comina
  • , D. Mendoza
  • , A. Velazco
  • , J. Coronel
  • , P. Sheen
  • , R. H. Gilman
  • , D. A.J. Moore
  • , Mirko Zimic
  • Universidad Nacional de Ingeniería
  • Universidad Peruana Cayetano Heredia
  • Johns Hopkins Bloomberg School of Public Health
  • Imperial College Faculty of Medicine
  • London School of Hygiene and Tropical Medicine

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

In this work, an automated microscopic observation drug susceptibility (MODS) plate reader has been developed. The reader automatically handles MODS plates and after autofocussing digital images are acquired of the characteristic microscopic cording structures ofMycobacterium tuberculosis, which are the identification method utilized in the MODS technique to detect tuberculosis and multidrug resistant tuberculosis. In conventional MODS, trained technicians manually move the MODS plate on the stage of an inverted microscope while trying to locate and focus upon the characteristic microscopic cording colonies. In centres with high tuberculosis diagnostic demand, sufficient time may not be available to adequately examine all cultures. An automated reader would reduce labour time and the handling ofM. tuberculosiscultures by laboratory personnel. Two hundred MODS culture images (100 from tuberculosis positive and 100 from tuberculosis negative sputum samples confirmed by a standard MODS reading using a commercial microscope) were acquired randomly using the automated MODS plate reader. A specialist analysed these digital images with the help of a personal computer and designated them asM. tuberculosispresent or absent. The specialist considered four images insufficiently clear to permit a definitive reading. The readings from the 196 valid images resulted in a 100% agreement with the conventional nonautomated standard reading. The automated MODS plate reader combined with open-source MODS pattern recognition software provides a novel platform for high throughput automated tuberculosis diagnosis.

Original languageEnglish
Pages (from-to)325-330
Number of pages6
JournalJournal of Microscopy
Volume242
Issue number3
DOIs
StatePublished - Jun 2011

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Autofocussing algorithm
  • Automated MODS
  • MODS
  • MODS plate reader

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