Convolutional neural network-based classification of glaucoma using optic radiation tissue properties
Authors: Kruper John , Richie-Halford Adam , Benson Noah C. , Caffarra Sendy , Owen Julia , Wu Yue , Egan Catherine , Lee Aaron Y. , Lee Cecilia S. , Yeatman Jason D. , Rokem Ariel ,   UK Biobank Eye and Vision Consortium, Allen Naomi , Aslam Tariq , Atan Denize , Balaskas Konstantinos , Barman Sarah , Barrett Jenny , Bishop Paul , Black Graeme , Braithwaite Tasanee , Carare Roxana , Chakravarthy Usha , Chan Michelle , Chua Sharon , Day Alexander , Desai Parul , Dhillon Bal , Dick Andrew , Doney Alexander , Egan Catherine , Ennis Sarah , Foster Paul , Fruttiger Marcus , Gallacher John , Garway-Heath David , Gibson Jane , Guggenheim Jeremy , Hammond Chris , Hardcastle Alison , Harding Simon , Hogg Ruth , Hysi Pirro , Keane Pearse , Khaw Peng Tee , Khawaja Anthony , Lascaratos Gerassimos , Littlejohns Thomas , Lotery Andrew , Luben Robert , Luthert Phil , MacGillivray Tom , Mackie Sarah , Madhusudhan Savita , McGuinness Bernadette , McKay Gareth , McKibbin Martin , Moore Tony , Morgan James , O’Sullivan Eoin , Oram Richard , Owen Chris , Patel Praveen , Paterson Euan , Peto Tunde , Petzold Axel , Pontikos Nikolas , Rahi Jugnoo , Rudnicka Alicja , Sattar Naveed , Self Jay , Sergouniotis Panagiotis , Sivaprasad Sobha , Steel David , Stratton Irene , Strouthidis Nicholas , Sudlow Cathie , Sun Zihan , Tapp Robyn , Thomas Dhanes , Thomas Mervyn , Trucco Emanuele , Tufail Adnan , Viswanathan Ananth , Vitart Veronique , Weedon Mike , Williams Katie , Williams Cathy , Woodside Jayne , Yates Max , Zheng Yalin 
Published: April 2024

AbstractBackgroundSensory changes due to aging or disease can impact brain tissue. This study aims to investigate the link between glaucoma, a leading cause of blindness, and alterations in brain connections.MethodsWe analyzed diffusion MRI measurements of white matter tissue in a large group, consisting of 905 glaucoma patients (aged 49-80) and 5292 healthy individuals (aged 45-80) from the UK Biobank. Confounds due to group differences were mitigated by matching a sub-sample of controls to glaucoma subjects. We compared classification of glaucoma using convolutional neural networks (CNNs) focusing on the optic radiations, which are the primary visual connection to the cortex, against those analyzing non-visual brain connections. As a control, we evaluated the performance of regularized linear regression models.ResultsWe showed that CNNs using information from the optic radiations exhibited higher accuracy in classifying subjects with glaucoma when contrasted with CNNs relying on information from non-visual brain connections. Regularized linear regression models were also tested, and showed significantly weaker classification performance. Additionally, the CNN was unable to generalize to the classification of age-group or of age-related macular degeneration.ConclusionsOur findings indicate a distinct and potentially non-linear signature of glaucoma in the tissue properties of optic radiations. This study enhances our understanding of how glaucoma affects brain tissue and opens avenues for further research into how diseases that affect sensory input may also affect brain aging.