Time-resolved dynamic optical coherence tomography for retinal blood flow analysis

Abstract

AbstractPurposeOptical coherence tomography (OCT) representations in clinical practice are static and do not allow for a dynamic visualisation and quantification of blood flow. This study aims to present a method to analyse retinal blood flow dynamics using time-resolved structural optical coherence tomography (OCT).MethodsWe developed novel imaging protocols to acquire video-rate time-resolved OCT B-scans (1024 x 496 pixels, 10° field of view) at four different sensor integration times (integration time of 44.8 μs at a nominal A-scan rate of 20 kHz, 22.4 μs at 40 kHz, 11.2 μs at 85 kHz, 7.24 μs at 125 kHz). The vessel centres were manually annotated for each B-scan and surrounding subvolumes were extracted. We used a velocity model based on signal-to-noise ratio (SNR) drops due to fringe washout to calculate blood flow velocity profiles in vessels within five optic disc diameters of the optic disc rim.ResultsTime-resolved dynamic structural OCT revealed pulsatile SNR changes in the analysed vessels and allowed the calculation of potential blood flow velocities at all integration times. Fringe washout was stronger in acquisitions with longer integration times; however, the ratio of the average SNR to the peak SNR inside the vessel was similar across all integration times.ConclusionsWe demonstrated the feasibility of estimating blood flow profiles based on fringe washout analysis, showing pulsatile dynamics in vessels close to the optic nerve head using structural OCT. Time-resolved dynamic OCT has the potential to uncover valuable blood flow information in clinical settings.Commercial relationshipsPV received funding from the Swiss National Science Foundation (Grant 323530_199395), the Janggen-Pöhn Stiftung and AlumniMedizin Basel and discloses personal compensation from Heidelberg Engineering GmbH. TPO, SA and MMT are salaried employees of Heidelberg Engineering GmbH, 69115 Heidelberg, Germany. RFS discloses personal compensation from Topcon Medical Systems, Roche, Bayer, Heidelberg Engineering and Genentech. HPNS is supported by the Swiss National Science Foundation (Project funding: “Developing novel outcomes for clinical trials in Stargardt disease using structure/function relationship and deep learning” #310030_201165, and National Center of Competence in Research Molecular Systems Engineering: “NCCR MSE: Molecular Systems Engineering (phase II)” #51NF40-182895), the Wellcome Trust (PINNACLE study), and the Foundation Fighting Blindness Clinical Research Institute (ProgStar study). HPNS is a member of the Scientific Advisory Board of Boehringer Ingelheim Pharma GmbH & Co; Claris Biotherapeutics Inc.; Eluminex Biosciences; Gyroscope Therapeutics Ltd.; Janssen Research & Development, LLC (Johnson & Johnson); Novartis Pharma AG (CORE); Okuvision GmbH; ReVision Therapeutics Inc.; and Saliogen Therapeutics Inc. HPNS is a consultant of: Alnylam Pharmaceuticals Inc.; Gerson Lehrman Group Inc.; Guidepoint Global, LLC; and Intergalactic Therapeutics Inc. HPNS is member of the Data Monitoring and Safety Board/Committee of Belite Bio (CT2019-CTN-04690-1), F. Hoffmann-La Roche Ltd (VELODROME trial,NCT04657289; DIAGRID trial,NCT05126966; HUTONG trial) and member of the Steering Committee of Novo Nordisk (FOCUS trial;NCT03811561). All arrangements have been reviewed and approved by the University of Basel (Universitätsspital Basel, USB) and the Board of Directors of the Institute of Molecular and Clinical Ophthalmology Basel (IOB), in accordance with their conflict-of-interest policies. Compensation is being negotiated and administered as grants by USB, which receives them on its proper accounts. HPNS is co-director of the Institute of Molecular and Clinical Ophthalmology Basel (IOB), which is constituted as a non-profit foundation and receives funding from the University of Basel, the University Hospital Basel, Novartis and the government of Basel-Stadt. PMM is a consultant of Roche and holds intellectual properties for machine learning at MIMO AG and VisionAI, Switzerland. Funding organisations had no influence on the design, performance or evaluation of the current study. The other authors declare no conflict.