June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Automated Analysis of Anterior Chamber Inflammation by Spectral Domain Optical Coherence Tomography
Author Affiliations & Notes
  • Sumit Sharma
    Cleveland Clinic, Cleveland, OH
  • Kimberly Baynes
    Cleveland Clinic, Cleveland, OH
  • Amit Vasanji
    ImageIQ, Cleveland, OH
  • Peter K Kaiser
    Cleveland Clinic, Cleveland, OH
  • Careen Y Lowder
    Cleveland Clinic, Cleveland, OH
  • Sunil K Srivastava
    Cleveland Clinic, Cleveland, OH
  • Footnotes
    Commercial Relationships Sumit Sharma, None; Kimberly Baynes, None; Amit Vasanji, None; Peter Kaiser, None; Careen Lowder, None; Sunil Srivastava, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 6187. doi:
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      Sumit Sharma, Kimberly Baynes, Amit Vasanji, Peter K Kaiser, Careen Y Lowder, Sunil K Srivastava; Automated Analysis of Anterior Chamber Inflammation by Spectral Domain Optical Coherence Tomography. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):6187.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 
Purpose
 

We previously reported the results of a study to automatically analyze the degree of anterior chamber inflammation in eyes with uveitis. That study found a high degree of correlation between clinical grading of inflammation in the anterior chamber with an algorithm to automatically grade the number of inflammatory cells in the anterior chamber based on optical coherence tomography. The purpose of this study is to report the ability to detect inflammatory cells in a larger population of patients and to determine if the size of inflammatory cells is correlated to increasing degrees of inflammatory cell density.

 
Methods
 

Observational, prospective case series of patients presenting to uveitis clinic with active uveitis. AS-OCT images were taken on the RTVue-100 (Optuvue Inc, Fremont, CA) or the Avanti RTVue-XR (Optuvue Inc, Fremont, CA). The number of cells was determined by an automated algorithm (described previously) and reported as the cellular density/mm^3. The size of the cells was determined by the algorithm and reported as the cellular area. The cell area was correlated to the inflammatory cell density.

 
Results
 

290 eyes were imaged with a variety of types of uveitis and a variable degree of anterior chamber inflammation. The average cellular density was 3.54 cells/mm^3 (range 1.19 - 39.24 cells/mm^3). The average cell area was 3.95 pixels (range 2.86 pixels to 6.03 pixels). When comparing the inflammatory cell density to the cell area the r^2 value was 0.37 with the ANOVA showing a F-ration of 167.5 (P<0.0001). The spearman correlation coefficient was 0.748 (P<0.0001) comparing inflammatory cell density to cell area. Figure one shows the relationship of inflammatory cell size to inflammatory cell density.

 
Conclusions
 

The average cell area was found to increase with increasing activity of anterior chamber inflammation. This may be representative of inflammatory cellular clumps with increasing activity of inflammation. Additional study is necessary to determine the etiology of the increase in cell size with increasing degree of anterior chamber inflammation. We plan to take samples of aqueous fluid in patients with increasing degrees of clinical inflammation to microscopically determine the etiology of the increase in cellular size and to determine if the hyper-reflective spots seen on AS-OCT are indicative of individual cells or cellular clumps.  

 
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