In the field of glaucoma, a specific, sensitive, and verifiable definition of disease for clinical care and research remains elusive. Intraobserver and interobserver variations limit the clinical assessment of the optic nerve alone in diagnosing glaucoma, particularly in its early stages, and has led to clinicians advocating for perimetry to aid in evaluating the disease. However, automated perimetry as currently performed is often insensitive to early disease, especially in the central visual field and is also vulnerable to testing error and human inconsistency.
Dr. Jeffrey M. Liebmann
Though the glaucoma community has long accepted spatially consistent structural and functional damage as a reference standard to diagnose glaucoma, there is currently no agreed-upon system to serve as a gold standard for the diagnosis of glaucomatous optic neuropathy or to detect its progression. Jeffrey M. Liebmann, MD, Director of the Glaucoma Service in the Department of Ophthalmology at NewYork-Presbyterian/Columbia University Irving Medical Center, and his Columbia ophthalmology colleagues believe that including additional information from localized optical coherence tomography (OCT) could aid in detecting glaucomatous optic neuropathy and serve as a future reference standard. They base their theory on the following:
- Compared with imaging, the use of perimetry as a diagnostic or screening modality is limited because of its psychophysical nature, learning curve, longer test duration, and poorer reproducibility, as well as poor patient acceptance.
- In addition to high intraobserver and interobserver variability, clinical examination of the optic nerve is limited by normal physiological variability in optic nerve shape, size, insertion, and topography.
- Most importantly, spectral-domain and swept-source OCT technologies and analytic programs are now able to provide information about retinal nerve fiber layer (RNFL) and macular ganglion cell layer (GCL) anatomy that extend well beyond a clinician’s evaluative ability.
Given these reasons, the Columbia team hypothesized that by drawing on the information available in OCT imaging, it is possible to provide a more accurate definition and method for detecting glaucomatous eyes in individuals with vision field loss, especially in those where a diagnosis is unclear.
Developing an OCT-Driven Method for Detecting Glaucoma
To test their assumption, Dr. Liebmann and the researchers devised an iterative, Delphi-like approach to produce a consensus-based, OCT-driven glaucoma definition and diagnostic method by members of the Columbia Glaucoma Service. Panel members, who met virtually, were surveyed to gain a consensus. This led to the creation of a formalized, methodological approach that included a pilot study in which clinicians using this method could separate healthy eyes from those with clear disease.
Dr. Liebmann and the Columbia researchers believe the OCT method offers a highly specific, highly sensitive, and intersubjectively verifiable definition of glaucoma for clinical care and research and provides a solid foundation for disease detection.
The pilot study, the results of which were published in the June 1, 2022, issue of the Journal of Glaucoma, confirmed the consensus opinion of sequentially presenting elements of the OCT report. In particular, they agreed that individual RNFL and GCL probability plots, followed by the combined set of imaging RNFL and GCL thickness maps and circumpapillary B-scan, provide key information, enhance uniformity of approach among graders, and is consistent with clinical practices. Their method resulted in an OCT-based structural definition of glaucoma, a method for OCT evaluation, and an OCT Decision Tree.
Key elements of the study include:
- The algorithmic quality of the approach formalizes the decision-making process and offers a bridge to a future when artificial intelligence can be utilized to aid in decision-making.
- The OCT-driven method makes use of the precise, repeatable, and quantitative information from the OCT scan, including thickness maps and probability plots – a powerful diagnostic tool even without the addition of perimetry data – to support decision-making.
- Reflecting the ambiguity that sometimes exists in diagnosing glaucoma during cross-sectional assessment, the Columbia researchers allowed for uncertainty rather than forcing the grader to choose “Yes” or “No” at each decision point.
- While some may object to the use of semiquantitative evaluation of the scans, as opposed to completely automated summary statistics produced by commercial reports, the researchers maintain that evidence in the literature supports the need for a panel of trained graders when evaluating imaging results and notes the risks of trusting summary statistics.
The Columbia researchers maintain that their goal was not to create the “perfect” method to determine a healthy or glaucomatous eye, but rather to “standardize the approach to these diagnoses, maximize intraobserver and interobserver agreement, and reduce the number of individuals defined as glaucoma suspects, with the goal of providing a rubric for OCT Reading Centers, clinical research, and patient care.” In summary, they believe it is time to embrace the more objective, OCT-based vocabulary that can serve to standardize enrollment criteria for clinical research and improve a clinician’s ability to diagnose and treat the disease.