Assessment of Keratitis Severity Using Quantitative Image Analysis in an In Vivo Murine Model of Staphylococcus aureus Bacterial Keratitis.


Journal

Translational vision science & technology
ISSN: 2164-2591
Titre abrégé: Transl Vis Sci Technol
Pays: United States
ID NLM: 101595919

Informations de publication

Date de publication:
01 11 2022
Historique:
entrez: 16 11 2022
pubmed: 17 11 2022
medline: 19 11 2022
Statut: ppublish

Résumé

Bacterial keratitis (BK) severity in murine models has traditionally been measured by subjective clinical grading or quantification of ocular bacterial burden. This investigation explores an objective and repeatable quantification of slit lamp photography (SLP) images to measure BK severity. BALB/c strain mice underwent three parallel scratches of the right cornea with subsequent inoculation of 107Staphylococcus aureus cells. SLP imaging and clinical severity grading were performed at 48 hours post-infection. Stromal infiltrate (SI) area on SLP images were quantified. Bacterial burden was determined after enucleation and homogenization. Spearman rank correlations (rs) were used to estimate associations between SI area, clinical severity grades, and bacterial burden. BALB/c strain mice (n = 14) were evaluated with an average SI area of 0.92 mm2 (standard deviation, SD = 0.65) and average bacterial burden of 3.16 × 105 colony forming units per milliliter (CFU/mL) (SD = 8.3 × 105). Clinical severity grade positively correlated with SI area (rs = 0.59, p = 0.0276) and bacterial burden (rs = 0.66, p = 0.0106). There was a trend towards positive association between SI area and bacterial burden (rs = 0.51, p = 0.0543). SLP annotation of SI area is correlated with clinical severity and may provide an objective, quantitative, and repeatable assessment of BK disease severity. SLP annotation of SI area is a novel quantitative method to evaluate bacterial keratitis severity longitudinally in mouse models which may be a powerful tool to better understand BK pathogenesis and response to treatments.

Identifiants

pubmed: 36383392
pii: 2783865
doi: 10.1167/tvst.11.11.12
pmc: PMC9680585
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

12

Subventions

Organisme : NEI NIH HHS
ID : R01 EY031033
Pays : United States
Organisme : NEI NIH HHS
ID : K08 EY029012
Pays : United States

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Auteurs

Tomas E Meijome (TE)

Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, USA.

Rachel Wozniak (R)

Department of Ophthalmology, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.

Linda Kang (L)

Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, USA.

Lyna Azzouz (L)

Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, USA.

Leslie M Niziol (LM)

Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, USA.

William L Johnson (WL)

Department of Ophthalmology, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.

Matthias Kriegel (M)

Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, USA.
Augenzentrum am St. Franziskus Hospital, Muenster, Germany.

Maria A Woodward (MA)

Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, USA.

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Classifications MeSH