Artificial Intelligence Mapping of Structure to Function in Glaucoma.
Purpose
To develop an artificial intelligence (AI)-based structure-function (SF) map relating retinal nerve fiber layer (RNFL) damage on spectral domain optical coherence tomography (SDOCT) to functional loss on standard automated perimetry (SAP).


Methods
The study included 26,499 pairs of SAP and SDOCT from 15,173 eyes of 8878 patients with glaucoma or suspected of having the disease extracted from the Duke Glaucoma Registry. The data set was randomly divided at the patient level in training and test sets. A convolutional neural network (CNN) was initially trained and validated to predict the 52 sensitivity threshold points of the 24-2 SAP from the 768 RNFL thickness points of the SDOCT peripapillary scan. Simulated localized RNFL defects of varied locations and depths were created by modifying the normal average peripapillary RNFL profile. The simulated profiles were then fed to the previously trained CNN, and the topographic SF relationships between structural defects and SAP functional losses were investigated.


Results
The CNN predictions had an average correlation coefficient of 0.60 (P < 0.001) with the measured values from SAP and a mean absolute error of 4.25 dB. Simulated RNFL defects led to well-defined arcuate or paracentral visual field losses in the opposite hemifield, which varied according to the location and depth of the simulations.


Conclusions
A CNN was capable of predicting SAP sensitivity thresholds from SDOCT RNFL thickness measurements and generate an SF map from simulated defects.


Translational Relevance
AI-based SF map improves the understanding of how SDOCT losses translate into detectable SAP damage.
['Mariottoni|Eduardo B|EB|', 'Datta|Shounak|S|', 'Dov|David|D|', 'Jammal|Alessandro A|AA|', 'Berchuck|Samuel I|SI|', 'Tavares|Ivan M|IM|', 'Carin|Lawrence|L|', 'Medeiros|Felipe A|FA|']
D000368:Aged D001185:Artificial Intelligence D005260:Female D005901:Glaucoma D006801:Humans D008297:Male D008875:Middle Aged D009412:Nerve Fibers D012165:Retinal Ganglion Cells D041623:Tomography, Optical Coherence D014794:Visual Fields
artificial intelligence glaucoma optical coherence tomography deep learning machine learning