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Visual Field Point-Wise Analyzer

Technology Benefits
Analysis based on exponential regression analysis instead of linearHead-to-head competition: Exponential regression analysis wins! Usually a better fitConsistently proves a better predictor of future changesUses same data input as other software systems
Technology Application
Monitoring of glaucoma progressionCan be used as a complement to existing systems based on linear regression analysisMonitoring progression of macular degeneration
Detailed Technology Description
UCLA researchers have developed a software package that analyzes visual field data of glaucoma patients collected over time. Using exponential regression analysis, this software better predicts the progression of glaucoma in the patient. The software synthesizes data collected from the commonly-used Humphrey Field Analyzer (Zeiss).
Others

State Of Development

Software has been created and validated using patient data


Background

Patients with glaucoma experience optic nerve damage, leading to visual field loss along the periphery. Loss of the visual field is monitored using perimetry, which produces visual field data. Analysis of those fields over time can track the progression of a patient’s disease. Several software suites currently exist to synthesize this pool of data, track visual field loss, and predict future changes. However, all existing analytical methods use various forms of linear regression analysis, and head-to-head comparisons have shown that exponential regression analysis is a better predictor of future progression.


Related Materials

Caprioli, J. et al. (2011). A method to measure and predict rates of regional visual field decay in glaucoma. Invest Ophthalmol Vis Sci, 52(7):4765-73.
Azarbod, P. et al. (2012). Validation of point-wise exponential regression to measure decay rates of glaucomatous visual fields. Invest Ophthalmol Vis Sci, 53(9):5403-9.
Chen, A. et al. (2014). Models of glaucomatous visual field loss. Invest Ophthalmol Vis Sci, 55(12):7881-7.
Lee, J.M. et al. (2014). Comparison of regression models for serial visual field analysis. Jpn J Ophthalmol, 58(6):504-14.
Morales, E. et al. (2016). Enhancement of visual field predictions with pointwise exponential regression (PER) and pointwise linear regression (PLR). Transl Vis Sci Technol, 5(2):12.


Tech ID/UC Case

25908/2016-786-0


Related Cases

2016-786-0

*Abstract
UCLA researchers have developed a novel algorithm to track and predict the progression of patients with glaucoma.
*Principal Investigator

Name: Joseph Caprioli

Department:


Name: Esteban Morales

Department:

Country/Region
USA

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