July 2019
Volume 60, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2019
Central and paracentral anterior chamber depth for diagnosis of angle closure spectrum disease
Author Affiliations & Notes
  • Jack Phu
    Optometry and Vision Science, Centre for Eye Health, Kensington, New South Wales, Australia
  • Janelle Tong
    Optometry and Vision Science, Centre for Eye Health, Kensington, New South Wales, Australia
  • Barbara Zangerl
    Optometry and Vision Science, Centre for Eye Health, Kensington, New South Wales, Australia
  • Michael Hennessy
    Optometry and Vision Science, Centre for Eye Health, Kensington, New South Wales, Australia
    Ophthalmology, Prince of Wales Hospital, New South Wales, Australia
  • Janet Ly Le
    Optometry and Vision Science, Centre for Eye Health, Kensington, New South Wales, Australia
  • Michael Kalloniatis
    Optometry and Vision Science, Centre for Eye Health, Kensington, New South Wales, Australia
  • Footnotes
    Commercial Relationships   Jack Phu, None; Janelle Tong, None; Barbara Zangerl, None; Michael Hennessy, None; Janet Le, None; Michael Kalloniatis, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 5565. doi:
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      Jack Phu, Janelle Tong, Barbara Zangerl, Michael Hennessy, Janet Ly Le, Michael Kalloniatis; Central and paracentral anterior chamber depth for diagnosis of angle closure spectrum disease. Invest. Ophthalmol. Vis. Sci. 2019;60(9):5565.

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

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Abstract

Purpose : Automated metrics derived using techniques such as Scheimpflug photography assist in diagnosing angle closure spectrum disease. Anterior chamber depth and anterior chamber volume are commonly used with mixed success. However, there may be significant overlap between patients with angle closure disease and normal subjects. We investigated the potential utility of paracentral anterior chamber depth measurements in the diagnostic process.

Methods : Scheimpflug photography was used to obtain anterior chamber depth measurements in one eye each of 84 healthy subjects and 94 patients referred to a secondary ophthalmic facility for suspected angle closure spectrum disease. Measurements were obtained from up to 57 points across the 8mm central corneal diameter. The results from the 84 healthy subjects were used to generate age-correction factors using three models: linear, quadratic and cubic fits. These were then used to correct all subjects’ and patients’ data into a 50 year-old equivalent. Using these, patient data were compared with the normal distribution to determine the number of statistically significantly shallow (p<0.05) locations at each of the 57 points.

Results : Of the 94 patients referred for suspected angle closure disease, 18 had occludable angles or worse on gonioscopy (2+ quadrants of non-visible posterior trabecular meshwork), 38 had narrow and non-occludable angles, and 38 had wide open angles (at least scleral spur in all quadrants). The cubic fit method of age-correction provided smaller anterior chamber depths compared to linear and quadratic fit methods (p<0.0001). Central anterior chamber depth and locations 1mm from fixation identified the most cases of disease (mean >79%) compared to 2+mm from fixation (56-62%) (p=0.02). All locations also tended to identify more patients who had non-occludable angles (>65%) and open angles (>53%) as having angle closure disease.

Conclusions : Paracentral anterior chamber depth, similar to central anterior chamber depth, identifies a significant proportion of patients with angle closure disease, but also erroneously flags patients not needing intervention or those who are completely normal. These parameters should not be used in isolation as a means for distinguishing patients with angle closure spectrum disease.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

 

Fig 1: Proportion of times locations flagged as statistically shallow (p<0.05) when using a quadratic fit for age-correction factors.

Fig 1: Proportion of times locations flagged as statistically shallow (p<0.05) when using a quadratic fit for age-correction factors.

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