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    Using OCT to assess anterior chamber inflammation

    Seeing clearly even when corneal clarity is reduced

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    The clinical assessment of an anterior chamber inflammatory reaction may be difficult to determine in eyes where corneal clarity is reduced by corneal oedema. Slit lamp examination is currently the gold standard method to assess inflammation1-3 but in conditions such as poor corneal clarity, the clinician routinely encounters difficulties.

    In this study, we used high-speed anterior segment optical coherence tomography (OCT) to quantify changes in the morphology of anterior chamber inflammation.

    OCT is an imaging modality that allows high-resolution, cross-sectional imaging of the eye,4-7 and has thus been shown to have roles in various clinical situations.8-14 Although anterior chamber cell grading has been reported with high-speed OCT in uveitis patients,6 to our knowledge this is the first study to assess all parameters of inflammation, namely anterior chamber cells, keratic precipitates, fibrinous membrane and endothelial infiltrate in eyes with a clear and oedematous cornea.

    The assessment begins

    Sixty-two eyes of 45 patients from the outpatient clinic of Dr Agarwal's Eye Hospital and Eye Research Centre in Chennai, India were studied between August and November 2007.

    Eyes with acute and chronic idiopathic anterior uveitis, postoperative uveitis, panuveitis, herpetic keratouveitis, interstitial keratitis, corneal ulcer, posterior corneal abscess and endophthalmitis were included in the study group. All patients had non-granulomatous uveitis.

    All eyes underwent comprehensive slit lamp examination and the anterior chamber reaction was graded from 0 to 4+ using Standardization of Uveitis Nomenclature (SUN).15 Topical 1% homatropine was used for pupillary dilatation.


    Figure 1: Anterior segment OCT image showing hyper reflective spots in the anterior chamber.
    All patients underwent cross sectional imaging of the anterior chamber with the high-resolution (1,310 nm) anterior segment Visante OCT (Carl Zeiss Meditec), using single scan mode. The single capture image of the anterior chamber from the central cornea to the anterior lens surface was included. The hyper-reflective spots detected in the anterior chamber were counted both manually and with an automated computer algorithm.


    Figure 2: Automated method of counting hyper reflective spots in pixel based candidate object extraction algorithm and connected component labelling technique using custom MATLAB software.
    Using the manual method, the hyper-reflective spots were counted directly from the OCT images. In contrast, when using the automated method, hyper-reflective spots were segmented from the OCT image by a pixel-based candidate object extraction algorithm, and counted with a connected component labelling technique (Figures 1 & 2) using custom MATLAB software (version 7.1). SPSS version 15.1 was used to obtain the mean and standard deviation.

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    Dhivya Ashok Kumar, MD
    Dhivya Ashok Kumar, MD works at the Eye Research Centre & Dr Agarwal's Group of Eye Hospitals in Chennai, India.

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