Classification of optic disc shape in glaucoma using machine learning based on quantified ocular parameters

<div><p>Purpose</p><p>This study aimed to develop a machine learning-based algorithm for objective classification of the optic disc in patients with open-angle glaucoma (OAG), using quantitative parameters obtained from ophthalmic examination instruments.</p><p>Methods</p><p>This study enrolled 163 eyes of 105 OAG patients (age: 62.3 ± 12.6, mean deviation of Humphrey field analyzer: -8.9 ± 7.5 dB). The eyes were classified into Nicolela’s 4 optic disc types by 3 glaucoma specialists. Randomly, 114 eyes were selected for training data and 49 for test data. A neural network (NN) was trained with the training data and evaluated with the test data. We used 91 types of quantitative data, including 7 patient background characteristics, 48 quantified OCT (swept-source OCT; DRI OCT Atlantis, Topcon) values, including optic disc topography and circumpapillary retinal nerve fiber layer thickness (cpRNFLT), and 36 blood flow parameters from laser speckle flowgraphy, to build the machine learning classification model. To extract the important features among 91 parameters, minimum redundancy maximum relevance and a genetic feature selection were used.</p><p>Results</p><p>The validated accuracy against test data for the NN was 87.8% (Cohen’s Kappa = 0.83). The important features in the NN were horizontal disc angle, spherical equivalent, cup area, age, 6-sector superotemporal cpRNFLT, average cup depth, average nasal rim disc ratio, maximum cup depth, and superior-quadrant cpRNFLT.</p><p>Conclusion</p><p>The proposed machine learning system has proved to be good identifiers for different disc types with high accuracy. Additionally, the calculated confidence levels reported here should be very helpful for OAG care.</p></div

Comparison of the ratio between the reliably measurable area and the Bruch’s membrane opening area in normal, preperimetric glaucoma, and normal tension glaucoma patients.

<p>BMO: Bruch’s membrane opening. PPG: preperimetric glaucoma. NTG: normal-tension glaucoma. P values were determined with the Kruskal-Wallis test.</p><p>Comparison of the ratio between the reliably measurable area and the Bruch’s membrane opening area in normal, preperimetric glaucoma, and normal tension glaucoma patients.</p

Representative B-scan images of normal eyes, preperimetric glaucoma eyes, and eyes with normal-tension glaucoma.

<p>(A-C) B-scan images. (D-F) <i>en-face</i> images. (G-I) Grayscale Humphrey field analyzer image. (J-L) 12 clock-wise sectors of OCT-measured circumpapillary retinal nerve fiber layer thickness. (M-O) Representative lamina cribrosa (LC) thickness map showing the reliably measurable area. (A, D, G, J, M) Normal. (B, E, H, K, N) PPG. (C, F, I, L, O) Normal-tension glaucoma. Note: LC thickness gradually declined with glaucoma severity.</p

Correlation between average lamina cribrosa (LC) thickness and circumpapillary retinal nerve fiber layer thickness (cpRNFLT).

<p>(A) Bar graph indicating LC thickness in different stages. Note: there were significant differences between these groups (Kruskal-Wallis test followed by Steel-Dwass test). *: P<0.05, **: P<0.01. (B) ROC curve. The area under the ROC curve was 0.9, with a cutoff value of 260.4 μm (sensitivity: 0.83; specificity: 0.89). (C) Scatter plot of cpRNFLT against average LC thickness (avgLCT) in the entire group (N = 54). (D) Scatter plot of MD against avgLCT in the entire group (N = 54). Note: the correlation coefficient of avgLCT and cpRNFLT was 0.64 (p < 0.01) and the correlation coefficient of avgLCT and HFA MD was 0.56 (p < 0.001).</p

Usefulness of axonal tract-dependent OCT macular sectors for evaluating structural change in normal-tension glaucoma

<div><p>Purpose</p><p>To identify sectors of the optical coherence tomography (OCT) macular map that could be used to effectively assess structural progression in patients with normal-tension glaucoma (NTG).</p><p>Methods</p><p>This study examined 117 eyes of 117 NTG patients to establish axonal tract-dependent macular sectors, and also examined a separate group of 122 eyes of 81 NTG patients to evaluate the ability of these sectors to reveal glaucoma progression. Longitudinal data, including macular maps from at least 5 OCT examinations performed over at least 2 years, was available for all patients in this group. Circumpapillary retinal nerve fiber layer thickness (cpRNFLT), temporal clockwise sector scans (from 7 to 11 o’clock), macular retinal nerve fiber layer thickness (mRNFLT), and macular ganglion cell layer plus inner plexiform layer thickness (mGCIPLT) were measured with spectral-domain OCT (3D OCT-2000, TOPCON). The axonal tract-dependent macular sectors were identified by calculating Spearman’s rank correlation coefficient for each point on a grid overlaid on the macular map and cpRNFLT in each clockwise scan sector. Trend and event analyses for the slope of progression in each sector and macular map were performed. Visual field progression in the macula was defined by the presence of more than 2 progressive test points in the 16 central test points of the Humphrey field analyzer SITA standard 24–2 program, evaluated with Progressor software.</p><p>Results</p><p>The slope of progression in the entire macular area was -0.22 ± 0.58 μm/year for mRNFLT and -0.35 ± 0.52 μm/year for mGCIPLT. The fastest-progressing mRNFLT sector (-1.00 ± 0.84 μm/year, p < 0.001) and mGCIPLT sector (-1.16 ± 0.63 μm/year, p < 0.001) progressed significantly faster than the overall macula. Classifying patients according to visual field progression showed that baseline mRNFLT in the inferior hemifield, 7 and 8 o’clock sectors, as well as baseline mGCIPLT in the overall macular map, inferior hemifield, and 8 o’clock sector, were significantly lower in progressors (22 eyes) than non-progressors (100 eyes). There were significant differences in mRNFLT slope in 8 o’clock sector and in the fastest progressing sector in progressors and non-progressors, but mGCIPLT did not differ, even in the fastest-progressing sector. Event analysis showed that progression occurred most frequently in inferior mRNFLT and superior mGCIPLT in this study.</p><p>Conclusion</p><p>Axonal tract-dependent OCT macular sectors could effectively reveal structural change in patients with NTG. Furthermore, mRNFLT slope was consistent with visual field progression. This method promises to open new avenues for the OCT-based evaluation of glaucoma progression.</p></div

OCT-Based Quantification and Classification of Optic Disc Structure in Glaucoma Patients

<div><p>Purpose</p><p>To objectively classify the optic discs of open-angle glaucoma (OAG) patients into Nicolela's four disc types, i.e., focal ischemic (FI), myopic (MY), senile sclerotic (SS), and generalized enlargement (GE), with swept-source optical coherence tomography (SS-OCT).</p><p>Methods</p><p>This study enrolled 113 eyes of 113 OAG patients (mean age: 62.5 ± 12.6; Humphrey field analyzer-measured mean deviation: -9.4 ± 7.3 dB). Newly developed software was used to quantify a total of 20 optic disc parameters in SS-OCT (DRI OCT-1, TOPCON) images of the optic disc. The most suitable reference plane (RP) above the plane of Bruch’s membrane opening was determined by comparing, at various RP heights, the SS-OCT-measured rim parameters and spectral-domain OCT-measured circumpapillary retinal nerve fiber layer thickness (cpRNFLT), with Pearson's correlation analysis. To obtain a discriminant formula for disc type classification, a training group of 72 eyes of 72 OAG patients and a validation group of 60 eyes of 60 OAG patients were set up.</p><p>Results</p><p>Correlation with cpRNFLT differed with disc type and RP height, but overall, a height of 120 μm minimized the influence of disc type. Six parameters were most significant for disc type discrimination: disc angle (horizontal), average cup depth, cup/disc ratio, rim-decentering ratio, average rim/disc ratio (upper and lower nasal). Classifying the validation group with these parameters returned an identification rate of 80.0% and a Cohen’s Kappa of 0.73.</p><p>Conclusion</p><p>Our new, objective SS-OCT-based method enabled us to classify glaucomatous optic discs with high reproducibility and accuracy.</p></div

Correlation between B-scan and <i>en-face</i> images.

<p>(A) B-scan image with dotted lines showing the position of the <i>en-face</i> images below. (B) Upper area of the lamina cribrosa (LC). (C) Upper border of the LC. (D) Centerline of the LC. (E) Lower border of the LC. (F) Lower area of the LC.</p

Assignment data.

<p>Assignment data.</p

Demographic data.

<p>Demographic data.</p

Feature contribution to Nicolela’s classification.

<p>The nine most important discriminative characteristics selected by the NN were listed as high contribution order. Overall, horizontal disc angle was the most contributed characteristics of Nicolela’s classification. Contribution to each optic disc type, was also calculated. The value was the relative value of deviation from the mean of each feature. For example, in aspect of age, SS that only has the positive value means SS tends to have older age, compared to other types.</p