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Evaluation of a lens-free imager to facilitate tuberculosis diagnostics in MODS
- Source :
- Tuberculosis. 97:26-32
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- Tuberculosis (TB) control efforts are hampered by a mismatch in diagnostic technology. Lack of adequate early diagnostics and Multi-drug resistant (MDR) detection is a critical problem in control efforts. Alternate and novel diagnostic approaches are required, especially in low-resources settings where they are needed most. The Microscopic Observation Drug Susceptibility (MODS) assay is a cost-effective, highly sensitive, and specific method based on the detection of characteristic cording growth patterns of Mycobacterium tuberculosis (MTB), in microscopic examination of a liquid culture under an inverted microscope. By adding antimicrobials to the wells, MODS also determines antimicrobial susceptibility in both MDR and Extreme Drug Resistant (XDR) tuberculosis. The interpretation of a MODS culture performed in a 24 well plate, requires an extensive inspection over the entire surface to detect TB cords. This process requires significant time and effort from a trained microscopist. We evaluated a lens-free imager system, able to render microscopic images of live specimens, for the proof of principle to be used for MODS culture interpretation. The lens-free imager system is able to digitalize a 24-mm(2) surface with approximately 40X magnification in a single capture. The evaluation of the lens-free imager found that it produced microscopic images that were adequate for MODS interpretation by a human expert. Compared to the average time that takes a microscopist to completely examine a MODS culture sample, the lens free imager notably reduced the time of inspection. Therefore, lens-free imager variants may constitute promising systems to aid in the diagnostics of tuberculosis, by simplifying and reducing the time of inspection and permitting automatization of MODS interpretation.
- Subjects :
- Mycobacterium tuberculosis/drug effects/growth & development
0301 basic medicine
Time Factors
Computer science
Extensively Drug-Resistant Tuberculosis
Antitubercular Agents
Sputum/microbiology
MODS
Multi drug resistance
Microscopy/instrumentation
Workflow
law.invention
0302 clinical medicine
law
Drug Resistance, Multiple, Bacterial
Tuberculosis, Multidrug-Resistant
MDR
Diagnostic technology
Computer vision
030212 general & internal medicine
Diagnostics
Microscopy
biology
Lens-free imager
Tuberculosis, Multidrug-Resistant/diagnosis/drug therapy/microbiology
Equipment Design
Drug susceptibility
Lens (optics)
Microbial Sensitivity Tests/instrumentation
Infectious Diseases
Tuberculosis, Pulmonary/diagnosis/drug therapy/microbiology
ePetri
Microbiology (medical)
medicine.medical_specialty
Tuberculosis
Extensively Drug-Resistant Tuberculosis/diagnosis/drug therapy/microbiology
Antitubercular Agents/therapeutic use
Immunology
Microbial Sensitivity Tests
Microbiology
Mycobacterium tuberculosis
03 medical and health sciences
Predictive Value of Tests
Tuberculosis diagnostics
medicine
Humans
Microscopist
Tuberculosis, Pulmonary
Lens-free microscopy
business.industry
Sputum
Reproducibility of Results
Extensively drug-resistant tuberculosis
medicine.disease
biology.organism_classification
Surgery
030104 developmental biology
purl.org/pe-repo/ocde/ford#3.02.07 [https]
Artificial intelligence
business
Subjects
Details
- ISSN :
- 14729792
- Volume :
- 97
- Database :
- OpenAIRE
- Journal :
- Tuberculosis
- Accession number :
- edsair.doi.dedup.....86a17cca84903bb038ea89c13515baf7
- Full Text :
- https://doi.org/10.1016/j.tube.2015.12.001