Advancing Glaucoma Diagnostics with Functional and Structural OCT Imaging
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- Functional and Structural OCT (FSOCT) offers a comprehensive view by combining structural integrity with microvascular function, enabling earlier and more accurate glaucoma detection.
- Novel retinal nerve fiber layer (NFL) reflectance metrics, such as NFL/Post-NFL-Bright, and the summation of attenuation coefficients (NFL/AC), significantly enhance diagnostic precision and reliability.
- The research demonstrates improved repeatability and reproducibility of these measurements, crucial for robust longitudinal monitoring of disease progression.
- FSOCT facilitates the critical identification of pre-perimetric glaucoma (PPG), allowing for timely therapeutic intervention before noticeable visual field loss occurs.
- Advanced analytical methodologies, including careful adjustment for confounding factors like age, are vital for extracting diagnostically meaningful information from FSOCT data and improving its clinical utility.
- Advancing Glaucoma Diagnostics with Functional and Structural OCT Imaging
- The Promise of Functional and Structural OCT (FSOCT)
- Unpacking the Research: A Deeper Dive into Methodologies
- The Impact: Enhanced Precision for Early Glaucoma Detection
- Actionable Steps for Clinicians and Researchers
- Conclusion
- Take Action Against Glaucoma
- Frequently Asked Questions (FAQ)
Advancing Glaucoma Diagnostics with Functional and Structural OCT Imaging
Glaucoma, often dubbed the “silent thief of sight,” is a leading cause of irreversible blindness worldwide. Its insidious progression, typically without noticeable symptoms in its early stages, makes timely and accurate diagnosis paramount. Traditional diagnostic methods, primarily visual field testing and optic nerve head examination, have limitations, especially in detecting the disease before significant, irreversible damage has occurred.
In this context, Optical Coherence Tomography (OCT) has emerged as a revolutionary tool, offering unprecedented detail of retinal structures. However, the quest for even earlier and more precise detection continues. This article delves into the exciting advancements in Functional and Structural OCT (FSOCT) imaging and novel analytical approaches that are poised to redefine glaucoma diagnostics, ensuring patients receive intervention before their vision is compromised.
The Promise of Functional and Structural OCT (FSOCT)
FSOCT represents a significant leap forward by combining the strengths of structural imaging with functional insights. While conventional OCT primarily measures retinal nerve fiber layer (RNFL) thickness – a key indicator of glaucomatous damage – FSOCT integrates additional dimensions. It allows for the assessment of crucial elements such as blood flow within the optic nerve head and retina (via OCT angiography) and changes in the optical scattering properties of the nerve fibers. This holistic view provides a much richer dataset for clinicians.
The ability of FSOCT to capture both structural integrity and microvascular function offers a more comprehensive understanding of the disease’s pathophysiology. Glaucoma involves not just nerve cell death but also microvascular changes that can precede or accompany structural thinning. By detecting these subtle functional alterations, FSOCT holds the potential to identify glaucoma even in its earliest, pre-perimetric stages, long before changes appear on a standard visual field test.
However, extracting reliable and diagnostically meaningful information from FSOCT data requires sophisticated analytical techniques. One critical area of focus is the accurate measurement of retinal nerve fiber layer (NFL) reflectance. Reflectance patterns can reveal important information about the health and organization of nerve fibers, but they are susceptible to artifacts and confounding factors that can obscure true disease signals. This is where advanced research, like the study discussed here, plays a pivotal role.
Unpacking the Research: A Deeper Dive into Methodologies
A recent study, conducted by a team of experts at the Casey Eye Institute, Oregon Health & Science University (OHSU), has meticulously explored novel methods for enhancing NFL reflectance analysis using FSOCT. Their work focuses on improving the repeatability, reproducibility, and ultimately, the diagnostic accuracy of these measurements. The detailed methodology provides the backbone for their advancements:
Abstract and 1. Introduction
Methods
2.1 Participants
2.2 Data Acquisition
2.3 NFL Reflectance Analysis
Results
3.1 Neutral Density Filter Experiment
3.2 FSOCT Clinic Data Analysis
Discussion
Conclusions and References
2 Methods
2.1 Participants
This study utilized two cohorts of datasets, Neutral Density Filter (NDF) experimental data and Functional and Structural OCT (FSOCT) data. This prospective observational study was performed from January 06, 2017, to May 30, 2019, for FSOCT and 3/8/2022 to 5/12/2022 for NDF experiment at the Casey Eye Institute, Oregon Health & Science University (OHSU), Portland, OR, USA. The Institutional Review Board at OHSU approved the research protocol to carry the research accordingly with the tenets of the Declaration of Helsinki. Each of the participant given their written informed consent. This research was performed according to the Health Insurance Portability and Accountability Act of 1996 (HIPAA) privacy and security regulations.
The participants in the NDF study were part of the “Pilot Studies for New Scan Protocols Using UltrahighSpeed Optical Coherence Tomography” study. The NDF data contains only a normal group, while the FSOCT data consists of both a normal and a glaucoma group.
The inclusion and exclusion criteria for both the NDF experimental data and the FSOCT normal group are as follows: (1) No evidence of retinal pathology or glaucoma, (2) a normal Humphrey 24-2 VF, (3) intraocular pressure < 21 mmHg, (4) central corneal thickness > 500 µm, (5) no chronic ocular or systemic corticosteroid use, (6) an open angle on gonioscopy, (7) a normal appearing optic nerve head (ONH) and NFL, and (8) a symmetric ONH between left and right eyes.
It could be noted that the participants were excluded from this study if any of the following situations were observed: (1) best-corrected visual acuity less than 20/40, (2) age < 21 or age > 80 years for FSOCT and age>21 for NDF, (3) spherical equivalent refractive error of > +3.00D or < -7.00 diopters, (4) previous intraocular surgery except for an uncomplicated cataract extraction with posterior chamber intraocular lens implantation, (5) any other diseases that might cause VF loss or optic disc abnormalities, or (6) inability to perform reliably on automated VF testing.
The FSOCT glaucoma group further divided into two groups, Preperimetric glaucoma (PPG) and Perimetric glaucoma (PG). The inclusion criteria for each of the group were different. The PG group’s inclusion criteria were (1) an optic disc rim defect (thinning or notching) or retinal NFL defect visible on slit-lamp bio-microscopy, and (2) a consistent glaucomatous pattern on both qualifying Humphrey SITA 24-2 VFs. A glaucoma specialist assed the pattern of glaucoma defect based on the VF total deviation map. It could be noted that either pattern standard deviation (PSD) outside normal limits (p < 0.05) or glaucoma hemifield test outside normal limits were defined as the abnormality criteria for glaucomatous VF. The PPG group only meet the biomicroscopic criteria (1), but not the VF criteria (2).
It should be noted that FSOCT normal data were followed up every year, while the glaucoma data were followed up every six months.
2.2 Data Acquisition
A spectral-domain OCT system (Solix, Optovue, Inc., Fremont, CA, USA) was used for scanning participants with a 130 kHz scanning rate, 840 nm wavelength. The study utilized the optic disc volumetric high-definition OCT angiography (HD OCTA) scan.
The area covered by the optic disc volumetric HD OCTA scan was 6.0×6.0 mm that centered on the disc. The cross-sectional B-frames consisted of 512 A-lines. Each cross-sectional B-frames were repeated twice at each location to allow the computation of the angiographic flow signal, and each volume composed of 512 B-frames. An orthogonal registration algorithm was used to merge two volumetric scans, i.e., a vertical-priority raster and a horizontal-priority raster, to reduce motion artifacts and improved image quality. The resultant merge algorithm provided both angiographic (flow signal) and structural (reflectance signal) images. In the study, we used good quality images with a signal strength index (SSI) of 50 (out of 100) or more and a quality index (QI) of 5 (out of 10) for FSOCT dataset. For NDF, we didn’t use SSI or QI, since want to study NDF experimental data with no quality control.
Standard automated perimetry on the Humphrey Field Analyzer (HFA II; Carl Zeiss Meditec, Inc., Dublin, CA, USA) used to assess the VF, which is using the Swedish Interactive Thresholding Algorithm 24-2.
2.3 NFL Reflectance Analysis
2.3.1 Nerve Fibre layer (NFL) Reflectance Metrics
We have evaluated several reference bands in this study (See Figure. 1), such as pigment epithelium complex (PPEC), the band between NFL and Bruch’s membrane (Post-NFL), and created a new reference called Post-NFL-Bright by selecting the top 50% of pixels with higher values from the Post-NFL band. Additionally, summation of attenuation coefficient in NFL layers, NFL/AC also evaluated for reliability test. A custom MATLAB program has been used to analyzed the NFL reflectance, the OCT data were transferred into linear scale first and then then converted in to dB scale later. It could be noted the blood vessels were excluded from the OCT data for estimation. The NFL reflectance were summed to create NFL reflection map, then the ratio for each of the metrics (NFL/PPEC Max, NFL/PPEC mean, NFL/PostNFL-Mean and NFL/Post-NFL-Bright) were estimated. Detailed description of the references can be found here [2].
2.3.2 Summation of Attenuation Coefficients (AC)
A study suggested that the glaucomatous damage is not only reflected by the thickness and reflectance of the RNFL [6] but also by changes in its optical scattering properties. Therefore, quantitative scattering property from the OCT images is needed to measure. To measure the summation of the attenuation coefficient, we estimate the ratio of OCT intensity by the summation of intensity multiply by pixel size. We have implemented the Depth-resolved model-based reconstruction [7] method to estimate the summation of the attenuation coefficient. It could be noted that the author [7] used average attenuation coefficients whereas we used the summation for AC estimation because we want to compared the AC with references.
2.3.3 NDF Experiment
A series of scans for neutral density filter (NDF) were conducted for each scan pattern. Baseline scans were taken without any NDF. The NDF scans were taken by placing an absorptive NDF of increasing optical density (NEK01; Thorlab, Newton, NJ, USA) in front of the eye. The optical densities ranged from 0.1 to 0.6, as well as NDF with no filter. This resulted in the collection of 7 scans for each participant.
Later, the NDF data were used to normalize the NDF reflectance with the references. We applied a linear mixed model to estimate the slope for each metric at each NDF level. Lower slope values for the metrics indicate effective compensation in removing artifacts, whereas higher slope values indicate less effective compensation. Moreover, to assess the difference in slope between two segments, we utilized a broken stick model that had a breakpoint at NDF level = 0.4 optical density.
2.3.4 Adjustment of confounding factor
Our prime objective is to analysis repeatability among reference metrics with FSOCT dataset. Therefore, before doing that we want to reduce dependent on dataset with confounding factors, e.g., SSI, age, axial length and gender. We performed unpaired T-test for age, SSI and axial length, and Fisher’s exact test for gender to find association. The age and SSI have significantly associated (P<0.05) with the NFL reflectance metrics. However, in the subsequent stages of the analysis, we refrained from adjusting NFL reflectance using SSI as it had diagnostic information related to NFL intensity. Instead, we adjusted the normalized NFL reflectance metrics using age only.
2.3.5 FSOCT for repeatability, reproducibility and diagnostics
In the FSOCT dataset, multiple scans were performed for each eye. To evaluate within-visit repeatability and between-visit reproducibility, we divided the FSOCT data into two groups based on scan and visit. Two scans were selected for each participant on the same day for within-visit analysis. The duration between two visits was 5 to 14 months for between-visit analysis. The eye and scan were excluded if doesn’t meet the within-visit and between-visit criteria.
The pooled standard deviation (pooled SD) has been estimated among all the participant for repeatability and reproducibility analysis. Moreover, the intra-class correlation coefficient (ICC) is also measured to assess the consistency or agreement among all of the subjects. The ICC has been implemented using linear mixed model to consider random effect. We estimated pooled SD and ICC for each of the references (NFL/PPEC Max, NFL/PPEC Mean, NFL/Post-NFL-Mean, NFL/Post-NFL-Bright, NFL/AC) for evaluation.
It could be noted lower pooled SD and higher ICC provide better repeatability and reproducibility that ultimately means higher diagnostic accuracy. Therefore, we have estimated AROC in R for diagnostic accuracy for each of the references.
This paper is available on arxiv under ATTRIBUTION-NONCOMMERCIAL-NODERIVS 4.0 INTERNATIONAL license.
This rigorous study involved two distinct cohorts: a Neutral Density Filter (NDF) experimental group and a Functional and Structural OCT (FSOCT) clinical data group. Participants, including both healthy individuals and those with glaucoma (divided into pre-perimetric and perimetric stages), underwent detailed ophthalmic examinations. Data acquisition utilized a high-speed spectral-domain OCT system, providing both angiographic (flow signal) and structural (reflectance signal) images of the optic disc. To ensure robust analysis, an orthogonal registration algorithm was employed to minimize motion artifacts and enhance image quality.
A central tenet of the research was the development and evaluation of novel NFL reflectance metrics. These included ratios such as NFL/PPEC Max, NFL/PPEC Mean, NFL/Post-NFL-Mean, NFL/Post-NFL-Bright, and the summation of attenuation coefficients (NFL/AC). By comparing these metrics against various reference bands, the researchers aimed to find the most stable and diagnostically valuable indicators. The NDF experiment played a crucial role in calibrating and normalizing reflectance measurements, effectively compensating for potential light attenuation artifacts that could skew results.
Recognizing the influence of confounding factors, the study meticulously adjusted for variables like age, which was found to be significantly associated with NFL reflectance metrics. While signal strength index (SSI) also showed association, it was intentionally not adjusted for, given its inherent diagnostic relevance to NFL intensity. The ultimate goal was to assess the within-visit repeatability and between-visit reproducibility of these new metrics, using statistical measures like pooled standard deviation (pooled SD) and intra-class correlation coefficient (ICC), alongside evaluating their diagnostic accuracy via Area Under the Receiver Operating Characteristic (AROC) curves.
The Impact: Enhanced Precision for Early Glaucoma Detection
The findings from this groundbreaking research have significant implications for how glaucoma is diagnosed and monitored. By developing and validating more stable and precise NFL reflectance metrics, the study provides clinicians with superior tools to detect subtle changes indicative of early glaucoma. Improved repeatability and reproducibility mean that longitudinal monitoring becomes more reliable, allowing for the detection of disease progression with greater confidence.
This enhanced precision is particularly vital for identifying pre-perimetric glaucoma (PPG), where structural damage is present but visual field loss has not yet manifested. Early detection in these cases is critical, as it opens the window for timely intervention that can preserve vision. The ability to quantify optical scattering properties through metrics like NFL/AC further adds to the diagnostic arsenal, offering insights beyond simple thickness measurements.
Real-World Example: Mrs. Chen’s Diagnosis
Consider Mrs. Chen, a 55-year-old with a family history of glaucoma. Her initial visual field tests are normal, and her standard OCT shows borderline RNFL thickness. However, using these advanced FSOCT analysis methods, her ophthalmologist detects subtle but consistent abnormalities in her NFL/Post-NFL-Bright and NFL/AC metrics. These findings, which would have been missed by less sophisticated analyses, prompt earlier treatment. Mrs. Chen is able to begin therapy before any noticeable visual impairment occurs, drastically improving her long-term prognosis and quality of life.
Actionable Steps for Clinicians and Researchers
Integrating these advancements into practice requires a proactive approach:
- Embrace Advanced FSOCT Analysis: Move beyond basic RNFL thickness measurements and explore the capabilities of FSOCT systems that offer detailed NFL reflectance and scattering property analysis. Familiarize yourself with these novel metrics and their diagnostic potential.
- Understand Confounding Factors: Be aware of how factors like age and potential imaging artifacts can influence FSOCT results. Prioritize high-quality image acquisition and consider age-adjusted normative databases where available to interpret findings accurately.
- Support Research and Adoption: Stay updated with ongoing research in FSOCT and advocate for the standardization and integration of these validated advanced metrics into clinical software and guidelines. Collaboration between researchers and clinicians is key to translating these discoveries into widespread clinical benefits.
Conclusion
The journey to eradicate preventable blindness from glaucoma relies heavily on our ability to diagnose it as early and accurately as possible. The advancements in Functional and Structural OCT imaging, coupled with sophisticated analytical techniques for NFL reflectance and optical scattering properties, mark a significant milestone in this endeavor. By providing a more reliable and comprehensive picture of optic nerve health, these innovations empower ophthalmologists to detect glaucoma earlier, monitor its progression with greater precision, and ultimately, preserve precious vision for countless individuals.
Take Action Against Glaucoma
As we continue to push the boundaries of ophthalmic diagnostics, it’s crucial for both healthcare providers and patients to remain informed. If you or a loved one are at risk for glaucoma, talk to your eye care professional about the latest diagnostic technologies available. For clinicians, consider how these advancements can enhance your diagnostic toolkit and improve patient outcomes. Together, we can shed light on the “silent thief” and protect sight for generations to come.
Frequently Asked Questions (FAQ)
Here are some common questions about advancing glaucoma diagnostics:
- Q1: What is Functional and Structural OCT (FSOCT) and how does it differ from traditional OCT?
A1: FSOCT combines structural imaging (like RNFL thickness) with functional insights such as blood flow and optical scattering properties, offering a more comprehensive view of optic nerve health than traditional OCT, which primarily focuses on structural thickness. This allows for detection of subtle changes before traditional methods.
- Q2: Why are novel NFL reflectance metrics important in glaucoma diagnosis?
A2: Novel NFL reflectance metrics provide more stable and precise indicators of early glaucomatous damage. They can detect subtle changes in nerve fiber health and organization that might be missed by conventional methods, particularly crucial for early, pre-perimetric stages of the disease.
- Q3: What is pre-perimetric glaucoma (PPG) and why is early detection critical?
A3: Pre-perimetric glaucoma (PPG) is a stage where structural damage to the optic nerve is present, but visual field loss has not yet become evident. Early detection is critical because it allows for timely intervention, such as medication or other therapies, to preserve vision before irreversible damage to sight occurs.
- Q4: How does the research account for confounding factors in FSOCT analysis?
A4: The research meticulously adjusted for confounding factors like age, which was found to be significantly associated with NFL reflectance metrics. While signal strength index (SSI) was also associated, it was intentionally not adjusted for due to its inherent diagnostic information, ensuring that measurements accurately reflect disease progression.
- Q5: What are the actionable steps for clinicians regarding these FSOCT advancements?
A5: Clinicians should embrace advanced FSOCT analysis beyond basic RNFL thickness, understand and account for confounding factors in their interpretations, and actively support ongoing research for the standardization and integration of these validated metrics into clinical practice and software to improve patient outcomes.
