Guided Progression Analysis™ (GPA)for GDx

GPATM

Progression tools can help

Helps address key clinical needs:

Identifying RNFL progression Determining rate of progression Assessing treatment effectiveness

Why GPATM Progression Analysis for GDx

GDx is ideal for measuring Progression. Excellent reproducibility 1

Operator independence 1 Large images allow precise scan alignment

Why GPATM Progression Analysis for GDx

1Frenkel, Slonim, et al. Operator learning effect and interoperator reproducibility of the scanning laser polarimeter with variable corneal compensation. Ophthalmology. 2005 Feb;112(2):257-61

= Possible Progression

= Likely Progression

(design specificity 95%)

with clear, concise summary of Progression.

Identify progressing patients

Simulated data.

Identify progressing patients

using three approaches for varying defect shapes

Diffuse defects

TSNIT Progression Graph

Image Progression Map

Summary Parameter Chart

Simulated data.

Deep, narrow focal defects

Shallower, broader focal defects

to identify patients at risk.

Determine the rate of progression

Simulated data.

by comparing rates before and after treatment.

Assess treatment effectiveness

Before:

-3.9 microns/yr ± 1.1

After:

-1.8 microns/yr ± 1.1

Simulated data.

Minimum cluster size is 150 pixels (2% of image area)

95% design specificity

Image Progression Map: For deep, narrow focal defects

Simulated data.

Divides ring around optic nerve into 64 segments

3 adjacent segments must show change.

95% design specificity

TSNIT Progression Graph: For broader, shallow focal defects

Simulated data.

Regression line drawn for Likely Progression and p<5%

95% design specificity

Parameter Progression Charts: For diffuse defects

TSNIT Average, Superior Average, and Inferior Average

Simulated data.

Courtesy of Robert N. Weinreb, MDFelipe A. Medeiros, MD, PhDHamilton Glaucoma Center

University of California at San Diego

GDx Progression: Case Examples

Example 1: deep, narrow focal defect

Deep, narrow wedge defect (~10 degrees)

Only identified by Image Progression Map

Data presented using research format.

Example 2: shallow, broad focal defect

Shallow inferior defect

Only identified by TSNIT Progression Graph

Data presented using research format.

Example 3: larger defect identified by all

Inferior defect

Sufficient area and depth to be identified by all three approaches

Data presented using research format.

Extending GPATM across structure and function

GPATM

tools integrate your structure and function analysis by using consistent terms and rules.

GPATM

Progression for GDx

GPA™ Progression Analysis for GDx is a comprehensive, simple tool to help you:

Make more confident treatment decisions Effectively educate patients

Summary