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The Power of Focal Loss Volume (FLV%) and Global Loss Volume (GLV%) in the Diagnosis and Management of Glaucoma as Measured by Visual Field Progression

Written by Larry J Alexander OD FAAO Friday, 28 March 2014

The analysis of the Ganglion Cell Complex is a measure of thinning of the inner retinal layers…the neurological representation of the retina. There are a number of ways to assess the Ganglion Cell Complex (GCC) thickness metric available on SD-OCT devices. Overall average thickness may be depressed in a number of conditions including normal tension glaucoma, primary open angle glaucoma, retinal arterial occlusive disease, type 1 diabetic retinopathy, sleep apnea, and the dementias. There may be isolated pockets of thinning in the GCC in other conditions such as normal tension glaucoma and ischemic optic neuropathy. Asymmetry, which is critical to all differential diagnosis, is highlighted by most SDOCT instruments.

More attention is now being directed at other quantifiable aspects of this Ganglion Cell Complex feature including the metrics focal loss volume percentage and global loss volume percentage. The only devices currently approved to calculate Focal Loss Volume Percentage (FLV%) and Global Loss Volume Percentage (GLV%) are those manufactured by Optovue, Inc Fremont CA. The FLV% and GLV% concept is illustrated in the following graphic. FLV% demonstrates “the potholes in the topography of the Ganglion Cell Complex” and GLV% shows an “overall thinning of the topography of the Ganglion Cell Complex.” Both the FLV% and GLV% are now revealing potential in assistance in differential diagnosis and management of ocular disease.

 

Focal Loss Volume (FLV%)

Focal Loss Volume (FLV%) provides a quantitative measure for one aspect of the amount of significant GCC loss.1  FLV% measures the average amount of focal (isolated) loss over the entire GCC map.  This raw number is then related to the normative database and flagged if outside the expected for the patient.  FLV% detects localized thinning using a pattern deviation map to correct for overall absolute changes, much like the Corrected Pattern Standard Deviation feature in visual fields.  The explanation of FLV% can be equated to looking at the significance of “depressions or pot holes” in the overall ganglion cell complex layer.  FLV% equates to the evaluation of the “Potholes in the Hill of Vision.” 

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Global Loss Volume (GLV%)

GLV% measures the average amount of GCC loss over the entire GCC map.  This raw number is then related to the normative database and flagged if outside the expected for the patient.  GLV% is similar to Mean Deviation in visual fields.  GLV% assesses the extent of overall uniform depression of the GCC thickness.  GLV% equates to “Generalized Erosion of the Hill of Vision.” GLV% will best detect diffuse ganglion cell loss and FLV% will best detect localized ganglion cell loss. 

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General Information

Tan et al found that FLV% and GLV% are the most accurate parameters to differentiate normal from glaucomatous eyes, actually being more effective than the average GCC thickness parameter.  In Tan’s study GLV% proved to be of most benefit in differential diagnosis.1  A more recent study demonstrated that average GCC thickness significantly differed between Normotensive Glaucoma and Primary Open Angle Glaucoma patients.  Additionally GLV% was significantly higher in the POAG group while FLV% did not differ between the two groups. 2-3  

As such, the clinician is able to add two more valuable metrics to the armamentarium.  FLV% assesses and quantifies the localized depressions while GLV% assesses and quantifies the general depressions.  Further research on these tools cited in this publication will reveal the benefits of both in early differential diagnosis and management.

A Clinical Example courtesy Dr. Larry Brown

 

Case: Female with a history of variable Blood Pressue complaining of a visual issue in the right eye.

The iWellness reports suggest an asymmetric GCC map.  Also Note that the FLV % and GLV % were flagged (red and yellow) in the right eye.  This indicates an overall depression with specific focal thinning of the Ganglion Cell Complex (GCC).

 

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A comparison of fundus photos from previous exams (2007 v 2014) demonstrated a change in the OD but not the OS.  Note the relative inferior temporal pallor and the wedge defect in the RNFL of OD on the 2014 photo to the right.

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A complete SDOCT medical work-up based on the iWellness and Fundus photos revealed compromise of the RNFL OU with special emphasis on the inferior rim OD and marked GCC Compromise in the inferior area of the right eye.  Of special note is the flagging of both the FLV% and the GLV% in the right eye.

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Further testing of the visual fields corroborates functional loss associated with the structural loss in OD and a hint of loss OS. 

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In this case iWellness highlighted the issue even before the patient was seen and alerted the clinician.  The flagged FLV% and GLV% on both iWellness and the OHN evaluation demonstrated results outside of the expected.

Recent Information Addressing Remarkable Additional Value to the FLV% and GLV%

At a recent American Glaucoma Society Meeting on February 28, 2014 Huang et al presented results of a study using SDOCT information to guide in the initial treatment of patients at risk for losing visual field from primary open-angle glaucoma.  On March 1, 2014 at the same meeting Zhang et al looked at the same variables to assess the predictive ability of the variables of SDOZCT on the further progression of visual field defects on known glaucoma patients.  The essence of both groups was to assess progression of either pre-perimetric glaucoma or perimetric proven glaucoma.  The groups looked at variables that might have some predictive value to assess patient’s risk for progression.  The statistical analysis highlighted the AROC evaluation of each of the variables.  But first I will present a very brief primer on AROC to facilitate the ability to analyze the studies.

Statistical Analysis and AROC

AROC refers to the Area Under the Curve (AUC) of a Receiver Operating Characteristic (ROC) .  AROC is a predictor of the efficacy of a diagnostic test or a management plan.  The higher the positive AROC, the better the predictive value of the efficacy of the event. 

In all diagnosis and management of disease, the physician is attempting to perform testing that pushes the likelihood of the diagnosis in a positive direction.  The entire process relies on statistical probability using both Sensitivity which applies to the ability of a test to give a positive result when the test is applied to a patient known to have the disease and Specificity which applies to the ability of a test to give a negative result when given to a person known to not have the disease (a normal).  To simplify even further, when the doctor orders a test to determine an answer, the doctor is trying to improve the likelihood of the diagnosis.  In so doing a number of things happen including false positives (specificity or what is there is not really there) and true positives (sensitivity or what is there is there).  All of this comes together under the application of Baye’s Theorum.  A test that does not push strongly toward a posterior probability improvement of 1.0 is of limited value.

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An AROC curve plots the true positives (sensitivity) vs. false positives (1 − specificity) to assess the efficacy of any applied test.  The highest positive AROC is 1 and an AROC of 0.5 simply means that you could achieve the same result by flipping a coin.  Accuracy is measured by the area under the ROC curve as shown in the accompanying figure.

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As such, when assessing the two highlighted presentations, the clinician should pay close attention to higher AROC numbers, which are better predictors than tests with lower AROC numbers.

The phrase Receiver Operating Characteristic came from the use of ROC analysis as part of a concept called Signal Detection Theory developed during World War II. During the war radar operators had to decide whether a blip on the screen represented an enemy target, a friendly ship, or just noise. Signal detection theory measured the ability of radar receiver operators to make these important distinctions. Their ability to do so was called the Receiver Operating Characteristics of that individual. It was not until the 1970's that signal detection theory was recognized as useful for interpreting medical test results.

American Glaucoma Society Meeting February 28, 2014 Huang et al Presentation

Baseline FD-OCT Risk Factors for Glaucomatous Visual Field Conversion in the Advanced Imaging for Glaucoma Study. Huang D, Zhang X, Tan O, Varma R, Francis BA, Greenfield DS, Schuman JS, Loewen N.  Advanced Imaging for Glaucoma Study Group. Presentation Feb 28,2014.  American Glaucoma Society.

Huang presented the results of the ability of Fourier-domain OCT (RTVue from Optovue, Inc.) to predict field loss in patients at risk with glaucoma suspicion and pre-perimetric glaucoma.  The characteristics of the group ( 305 participants and 513 eyes ) are demonstrated below.

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The definition of visual field conversion was based on HFA II SITA 24-2 threshold perimetry.  The baseline variables that predicted visual field conversion are presented below in the table.  The AROC for each variable is presented with the FLV% being highlighted as the best predictor.  FLV% scored a 0.753 AROC while the metric of C/D Ratio was low at 0.623.

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Statistical analysis shown below further demonstrated that the FLV% being borderline or abnormal was an excellent predictor of conversion.

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The group also found that the AROC improved to 0.783 when combining GCC FLV% with Inferior RNFL thinning, Visual Field and Age.  A basic premise that the more specific and sensitive tests applied, the further the positive predictive value will move toward the goal of 1.0.  

Their group concluded that Fourier Domain OCT measurements of FLV% at baseline are statistically significant predictors of future visual field conversion in the AIGS group.

American Glaucoma Society Meeting March 1, 2014 Zhang et al Presentation

Baseline Risk Factors for Event and TrendBased Visual Field Glaucoma Progression Using FourierDomain Optical Coherence Tomography in the Advance Imaging for Glaucoma Study. Zhang X, Huang D, Tan O, Varma R, Francis BA, Greenfield DS, Sehi M, Schuman JS, Loewen N.  Advanced Imaging for Glaucoma Study Group. Presentation Mar 1,2014 American Glaucoma Society.

Zhang presented the results of the ability of Fourier-domain OCT (RTVue from Optovue, Inc.) to predict field loss progression in patients with glaucoma and perimetric defects.  The characteristics of the group ( 188 participants and 277 eyes ) are demonstrated below.  Of the 277 eyes, 194 or 70% did not progress, while 83 eyes or 30% did progress based on the study criteriae.

The baseline variables that predicted visual field progression are presented below in the table.  The AROC for each variable is presented with the FLV% being highlighted as the best predictor.

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Their results also indicated that if the FLV% was borderline or abnormal the likelihood of progression of the visual field defects doubled over a 6-year period.  This is shown below.

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The group also found that the AROC improved to 0.653 when combining GCC FLV% with Central Corneal Thickness, and Age.  A basic premise that the more specific and sensitive tests applied, the further the positive predictive value will move toward the goal of 1.0. 

Their group concluded that Fourier Domain OCT measurements of FLV% are statistically significant predictors of future visual field progression in the AIGS group.

Conclusion

Recent reports point to the importance of the FLV% and GLV% metric in the prediction of a pre-perimetric glaucoma suspect converting to a perimetric defect.  Likewise in perimetrically proven glaucoma patients the FLV% is an excellent predictor of progression of the visual field defect.  Utilization of high AROC associated factors further improved predictive values.

  1. 1.      Tan O, Chopra V, Lu AT, Schuman JS, Ishikawa H, Wollstein G, Varma R, Huang D.  Detection of macular ganglion cell loss in glaucoma by Fourier-domain optical coherence tomography. Ophthalmology 2009;116:2305-14.
  2. 2.      Rao HL, Zangwill LM, Weinreb RN, Sample PA, Alencar LM, Medeiros FA. Comparison of different spectral domain optical coherence tomography scanning areas for glaucoma diagnosis. Ophthalmology 2010;117:1629-1699.
  3. 3.      Kim NR, Hong S, Kim JH, Rho SS, Seong GJ, Kim CY. Comparison of Macular Ganglion Cell Complex Thickness by Fourier-Domain OCT in Normal Tension Glaucoma and Primary Open-Angle Glaucoma. J Glaucoma. 2011 Jun 22. [Epub ahead of print]

 

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About the Author(s)

Larry J Alexander OD FAAO

Larry J Alexander OD FAAO

Dr. Alexander (1948-2016) was a 1971 graduate of Indiana University School of Optometry. He served in the US Navy then served as a Professor at the University of Alabama Birmingham School of Optometry. Larry contributed to a number of chapters in textbooks and has published three editions of Primary Care of the Posterior Segment, as well as contributed to the professional literature. He also lectured extensively in the area of ocular and systemic disease. His areas of special interest included dysfunctional tear syndrome, glaucoma and macular degeneration.  His lessons are the basis for this site and he will be dearly missed. 

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