Deep Learning Estimation of 10-2 Visual Field Map Based on Circumpapillary Retinal Nerve Fiber Layer Thickness Measurements.

PURPOSE: To estimate central 10-degree visual field (VF) map from spectral-domain optical coherence tomography (SD-OCT) retinal nerve fiber layer thickness (RNFL) measurements in glaucoma with artificial intelligence. DESIGN: Artificial intelligence (convolutional neural networks) study. METHODS: This study included 5352 SD-OCT scans and 10-2 VF pairs from 1365 eyes of 724 healthy patients, patients with suspected glaucoma, and patients with glaucoma. Convolutional neural networks (CNNs) were developed to estimate the 68 individual sensitivity thresholds of 10-2 VF map using all-sectors (CNNA) and temporal-sectors (CNNT) RNFL thickness information of the SD-OCT circle scan (768 thickness points). 10-2 indices including pointwise total deviation (TD) values, mean deviation (MD), and pattern standard deviation (PSD) were generated using the CNN-estimated sensitivity thresholds at individual test locations. Linear regression (LR) models with the same input were used for comparison. RESULTS: The CNNA model achieved an average pointwise mean absolute error of 4.04 dB (95% confidence interval [CI] 3.76-4.35) and correlation coefficient (r) of 0.59 (95% CI 0.52-0.64) over 10-2 map and the mean absolute error and r of 2.88 dB (95% CI 2.63-3.15) and 0.74 (95% CI 0.67-0.80) for MD, and 2.31 dB (95% CI 2.03-2.61) and 0.59 (95% CI 0.51-0.65) for PSD estimations, respectively, significantly outperforming the LRA model. CONCLUSIONS: The proposed CNNA model improved the estimation of 10-2 VF map based on circumpapillary SD-OCT RNFL thickness measurements. These artificial intelligence methods using SD-OCT structural data show promise to individualize the frequency of central VF assessment in patients with glaucoma and would enable the reallocation of resources from patients at lowest risk to those at highest risk of central VF damage.

Combining Optical Coherence Tomography and Optical Coherence Tomography Angiography Longitudinal Data for the Detection of Visual Field Progression in Glaucoma.

PURPOSE: To use longitudinal optical coherence tomography (OCT) and OCT angiography (OCTA) data to detect glaucomatous visual field (VF) progression with a supervised machine learning approach. DESIGN: Prospective cohort study. METHODS: One hundred ten eyes of patients with suspected glaucoma (33.6%) and patients with glaucoma (66.4%) with a minimum of 5 24-2 VF tests and 3 optic nerve head and macula images over an average follow-up duration of 4.1 years were included. VF progression was defined using a composite measure including either a "likely progression event" on Guided Progression Analysis, a statistically significant negative slope of VF mean deviation or VF index, or a positive pointwise linear regression event. Feature-based gradient boosting classifiers were developed using different subsets of baseline and longitudinal OCT and OCTA summary parameters. The area under the receiver operating characteristic curve (AUROC) was used to compare the classification performance of different models. RESULTS: VF progression was detected in 28 eyes (25.5%). The model with combined baseline and longitudinal OCT and OCTA parameters at the global and hemifield levels had the best classification accuracy to detect VF progression (AUROC = 0.89). Models including combined OCT and OCTA parameters had higher classification accuracy compared with those with individual subsets of OCT or OCTA features alone. Including hemifield measurements significantly improved the models' classification accuracy compared with using global measurements alone. Including longitudinal rates of change of OCT and OCTA parameters (AUROCs = 0.80-0.89) considerably increased the classification accuracy of the models with baseline measurements alone (AUROCs = 0.60-0.63). CONCLUSIONS: Longitudinal OCTA measurements complement OCT-derived structural metrics for the evaluation of functional VF loss in patients with glaucoma.

Inositol Polyphosphate-5-Phosphatase K (Inpp5k) Enhances Sprouting of Corticospinal Tract Axons after CNS Trauma.

Failure of CNS neurons to mount a significant growth response after trauma contributes to chronic functional deficits after spinal cord injury. Activator and repressor screening of embryonic cortical neurons and retinal ganglion cells in vitro and transcriptional profiling of developing CNS neurons harvested in vivo have identified several candidates that stimulate robust axon growth in vitro and in vivo Building on these studies, we sought to identify novel axon growth activators induced in the complex adult CNS environment in vivo We transcriptionally profiled intact sprouting adult corticospinal neurons (CSNs) after contralateral pyramidotomy (PyX) in nogo receptor-1 knock-out mice and found that intact CSNs were enriched in genes in the 3-phosphoinositide degradation pathway, including six 5-phosphatases. We explored whether inositol polyphosphate-5-phosphatase K (Inpp5k) could enhance corticospinal tract (CST) axon growth in preclinical models of acute and chronic CNS trauma. Overexpression of Inpp5k in intact adult CSNs in male and female mice enhanced the sprouting of intact CST terminals after PyX and cortical stroke and sprouting of CST axons after acute and chronic severe thoracic spinal contusion. We show that Inpp5k stimulates axon growth in part by elevating the density of active cofilin in labile growth cones, thus stimulating actin polymerization and enhancing microtubule protrusion into distal filopodia. We identify Inpp5k as a novel CST growth activator capable of driving compensatory axon growth in multiple complex CNS injury environments and underscores the veracity of using in vivo transcriptional screening to identify the next generation of cell-autonomous factors capable of repairing the damaged CNS.SIGNIFICANCE STATEMENT Neurologic recovery is limited after spinal cord injury as CNS neurons are incapable of self-repair post-trauma. In vitro screening strategies exploit the intrinsically high growth capacity of embryonic CNS neurons to identify novel axon growth activators. While promising candidates have been shown to stimulate axon growth in vivo, concomitant functional recovery remains incomplete. We identified Inpp5k as a novel axon growth activator using transcriptional profiling of intact adult corticospinal tract (CST) neurons that had initiated a growth response after pyramidotomy in plasticity sensitized nogo receptor-1-null mice. Here, we show that Inpp5k overexpression can stimulate CST axon growth after pyramidotomy, stroke, and acute and chronic contusion injuries. These data support in vivo screening approaches to identify novel axon growth activators.