Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma

Abstract

Using VF features may predict the GHT results reversal to WNL after 2 consecutive ONL results.

Development of a Visual Field Simulation Model of Longitudinal Point-Wise Sensitivity Changes From a Clinical Glaucoma Cohort

“… 33 However, there are future opportunities to perform such analyses in even larger longitudinal datasets collated from multiple clinical centers (using the concept of “big data”), which can include up to tens of thousands of patients. 39 , 40 Nonetheless, we believe the study's sample size was sufficient and that including a large sample would only strengthen the conclusions reached. Another limitation to consider when interpreting the variability estimates shown in this study is that they were obtained from participants seen at approximately biannual intervals, and such estimates may be slightly higher for patients seen at annual intervals.…”

Deep learning in ophthalmology: The technical and clinical considerations

“…77 This algorithm has been validated 78 and has proven useful in augmenting the GHT for the detection of early functional glaucomatous loss. 79 Using an entirely different strategy, Li et al trained a CNN to learn the Pattern Deviation probability plots of normal and glaucomatous eyes and was able to detect glaucoma with 93.2% sensitivity and 82.6 sensitivity. 80 Yousefi et al used an alternative Gaussian mixture and expectation maximization method to decompose VFs along different axes to detect VF progression.…”

Inter-Eye Association of Visual Field Defects in Glaucoma and Its Clinical Utility

“…The reliability criteria were fixation loss ≤ 33%, false-negative rates ≤ 20%, and false-positive rates ≤ 20%. 39 The cutoffs for fixation loss and falsepositive rates are based on published recommendations, 40,41 and the cutoff for false-negative rates is based on the criterion used to develop archetype analysis 42 and has been adapted for glaucoma identification in population-based studies. 43,44 We selected the most recent VF pairs of both eyes from each subject.…”

“…Each total deviation (TD) plot was decomposed into 16 archetypal patterns including one normal VF pattern and 15 defect patterns determined in our prior work, 42 which were clinically validated in a subsequent study 45 and further applied to improve glaucoma diagnosis and progression detection. 39,[46][47][48] An illustration of the 16 archetype (AT) patterns and corre-sponding nomenclature can be found in Figure 1A. An example of VF decomposition into ATs is shown in Figure 1B.…”