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Review
. 2023 Oct 9;10(6):e200169.
doi: 10.1212/NXI.0000000000200169. Print 2023 Nov.

The OSCAR-MP Consensus Criteria for Quality Assessment of Retinal Optical Coherence Tomography Angiography

Affiliations
Review

The OSCAR-MP Consensus Criteria for Quality Assessment of Retinal Optical Coherence Tomography Angiography

Rebecca Wicklein et al. Neurol Neuroimmunol Neuroinflamm. .

Abstract

Background and objectives: Optical coherence tomography angiography (OCTA) is a noninvasive high-resolution imaging technique for assessing the retinal vasculature and is increasingly used in various ophthalmologic, neuro-ophthalmologic, and neurologic diseases. To date, there are no validated consensus criteria for quality control (QC) of OCTA. Our study aimed to develop criteria for OCTA quality assessment.

Methods: To establish criteria through (1) extensive literature review on OCTA artifacts and image quality to generate standardized and easy-to-apply OCTA QC criteria, (2) application of OCTA QC criteria to evaluate interrater agreement, (3) identification of reasons for interrater disagreement, revision of OCTA QC criteria, development of OCTA QC scoring guide and training set, and (4) validation of QC criteria in an international, interdisciplinary multicenter study.

Results: We identified 7 major aspects that affect OCTA quality: (O) obvious problems, (S) signal strength, (C) centration, (A) algorithm failure, (R) retinal pathology, (M) motion artifacts, and (P) projection artifacts. Seven independent raters applied the OSCAR-MP criteria to a set of 40 OCTA scans from people with MS, Sjogren syndrome, and uveitis and healthy individuals. The interrater kappa was substantial (κ 0.67). Projection artifacts were the main reason for interrater disagreement. Because artifacts can affect only parts of OCTA images, we agreed that prior definition of a specific region of interest (ROI) is crucial for subsequent OCTA quality assessment. To enhance artifact recognition and interrater agreement on reduced image quality, we designed a scoring guide and OCTA training set. Using these educational tools, 23 raters from 14 different centers reached an almost perfect agreement (κ 0.92) for the rejection of poor-quality OCTA images using the OSCAR-MP criteria.

Discussion: We propose a 3-step approach for standardized quality control: (1) To define a specific ROI, (2) to assess the occurrence of OCTA artifacts according to the OSCAR-MP criteria, and (3) to evaluate OCTA quality based on the occurrence of different artifacts within the ROI. OSCAR-MP OCTA QC criteria achieved high interrater agreement in an international multicenter study and is a promising QC protocol for application in the context of future clinical trials and studies.

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Conflict of interest statement

R. Wicklein received a poster grant from Novartis; C. Yam reports no conflict of interest; C. Noll reports no disclosures relevant to the manuscript; L. Aly received travel and research support by Novartis; N. Banze reports no disclosures relevant to the manuscript; E.F. Romahn reports no disclosures relevant to the manuscript; E. Wolf reports no disclosures relevant to the manuscript; B. Hemmer has served on scientific advisory boards for Novartis; he has served as DMSC member for AllergyCare, Sandoz, Polpharma, Biocon, and TG therapeutics; his institution received research grants from Roche for multiple sclerosis research. He has received honoraria for counseling (Gerson Lehrmann Group). He holds part of 2 patents; one for the detection of antibodies against KIR4.1 in a subpopulation of patients with multiple sclerosis and one for genetic determinants of neutralizing antibodies to interferon. All conflicts are not relevant to the topic of the study. He is associated with DIFUTURE (Data Integration for Future Medicine) [BMBF 01ZZ1804[A-I]]; F.C. Oertel reports no disclosures relevant to the manuscript; H.G. Zimmermann received research grants and speaking honoraria from Novartis; P. Albrecht received, with approval of the Rector of Heinrich-Heine University and the CEO of University of Düsseldorf Hospital, personal fees, research grants, and nonfinancial support from Allergan, Biogen, Celgene, Janssen Cilag, Ipsen, Merck Serono, Merz Pharmaceuticals, Novartis, and Roche, personal fees and nonfinancial support from Bayer Healthcare, Teva, and Sanofi-Aventis/Genzyme, grants from the German Research Foundation (DFG) all outside the submitted work; M. Ringelstein received speaker honoraria from Novartis, Bayer Vital GmbH, Roche, Alexion, Horizon, and Ipsen and travel reimbursement from Bayer Schering, Biogen Idec, Merz, Genzyme, Teva, Roche, Horizon, and Merck, none related to this study; C. Baumann reports no disclosures relevant to the manuscript; N. Feucht reports no disclosures relevant to the manuscript; J. Penkava reports no disclosures relevant to the manuscript; J. Havla reports personal fees and nonfinancial support from Alexion, Horizon, Roche, Merck, Novartis, Biogen, BMS, and Janssen and nonfinancial support from the Guthy-Jackson Charitable Foundation and the Sumaira Foundation; J.A. Gernert received travel expenses and nonfinancial support from Merck; C. Mardin is a medical advisor to Heidelberg Engineering, Heidelberg, Germany, receives lecture honorarium by Heidelberg Engineering, Bayer AG, Leverkusen, Germany, and is partially funded by Federal Ministry of Education and Research and Bavarian Ministry of Health; E. Vasileiou reports no disclosures relevant to the manuscript; A. van der Walt served on advisory boards for Novartis, Biogen, Merck, Roche, and NervGen. She received unrestricted research grants from Novartis, Biogen, Merck, and Roche. She is currently a coprincipal investigator on a cosponsored observational study with Roche, evaluating a Roche-developed smartphone app, Floodlight-MS. She has received speaker's honoraria and travel support from Novartis, Roche, Biogen, and Merck. She serves as the Chief operating Officer of the MSBase Foundation (not for profit). Her primary research support is from the National Health and Medical Research Council of Australia and MS Research Australia; O. Al-Louzi has received grant support from the National Multiple Sclerosis Society and American Brain Foundation (FAN-1807-32163) unrelated to the current project; S. Cabello reports no disclosures relevant to the manuscript; A. Vidal-Jordana has engaged in consulting and/or participated as speaker in events organized by Roche, Novartis, Merck, and Sanofi, none of them related to this work; J. Krämer received honoraria for lecturing from Biogen, Novartis, Sanofi Genzyme, Roche, Mylan, and Teva and financial research support from Sanofi Genzyme, Novartis, Roche, and Amicus Therapeutics; H. Wiendl received compensation for serving on Scientific Advisory Boards/Steering Committees for Bayer Healthcare, Biogen Idec, Sanofi Genzyme, Merck Serono, and Novartis. He has received speaker honoraria and travel support from Bayer Vital GmbH, Bayer Schering AG, Biogen, CSL Behring, EMD Serono, Fresenius Medical Care, Genzyme, Merck Serono, Omniamed, Novartis, and Sanofi Aventis. He has received compensation as a consultant from Biogen Idec, Merck Serono, Novartis, Roche, and Sanofi Genzyme. H. Wiendl also received research support from Bayer Healthcare, Bayer Vital, Biogen Idec, Merck Serono, Novartis, Sanofi Genzyme, Sanofi US, and Teva; J. Lizrova Preiningerova received travel support and speaking honoraria from Roche, Genzyme, Novartis, and Biogen and received a research grant from Biogen; O. Ciccarelli is a member of independent DSMB for Novartis, gave a teaching talk on McDonald criteria in a Merck local symposium, and contributed to an Advisory Board for Biogen; she is Deputy Editor of Neurology, for which she receives an honorarium; E. Garcia-Martin has nothing to disclose; V. Kana received travel support from Biogen and speaking honoraria from Merck; P.A. Calabresi is PI on a grant to Johns Hopkins University from Genentech and has received consulting honoraria from Idorsia and Lilly; F. Paul has nothing to disclose; S. Saidha has received consulting fees from Medical Logix for the development of CME programs in neurology and has served on scientific advisory boards for Biogen, Novartis, Genentech Corporation, TG therapeutics, Horizon therapeutics, Rewind therapeutics, and Bristol Myers Squibb. He has performed consulting for Novartis, Genentech Corporation, JuneBrain LLC, and Lapix therapeutics. He is the PI of investigator-initiated studies funded by Genentech Corporation, Novartis, and Biogen. He previously received support from the Race to Erase MS foundation. He has received equity compensation for consulting from JuneBrain LLC and Lapix therapeutics. He was also the site investigator of trials sponsored by MedDay Pharmaceuticals and Clene Pharmaceuticals and is the site investigator of a trial sponsored by Novartis; A. Petzold received grant support for remyelination trials in multiple sclerosis to the Amsterdam University Medicam Centre, Department of Neurology, MS Centre (RESTORE trial) and UCL, London RECOVER trial; fight for Sight (nimodipine in optic neuritis trial); royalties or licenses from Up-to-Date (Wolters Kluver) on a book chapter; speaker fees for the Heidelberg Academy; participation on Advisory Board SC Zeiss OCTA Angi-Network, SC Novartis OCTiMS study; leadership roles for Governing Board IMSVISUAL (until DEC 2022), Chairman ERN-EYE Neuro-ophthalmology (until OCT 2020), board member of National Dutch Neuro-ophthalmology Association; equipment: OCTA from Zeiss (Plex Elite); medical writing: support from Novartis for manuscript doi: 10.1002/acn3.51473; A. Toosy has received speaker honoraria from Biomedia and Merck and meeting expenses from Biogen Idec and Merck. He was the UK PI for 2 clinical trials sponsored by MEDDAY pharmaceutical company (MD1003 in optic neuropathy [MS-ON - NCT02220244] and progressive MS [MS-SPI2 - NCT02220244]; B. Knier received travel support and speaking honoraria from Novartis and Teva and served at the advisory board of Merck. He received a research grant from Novartis. Go to Neurology.org/NN for full disclosures.

Figures

Figure 1
Figure 1. Obvious Problems (O) and Centration Artifacts (C)
Different examples for obvious problems: (A) A poorly centered beam placement during OCTA acquisition may cause tilting artifacts. Tilting causes a symmetric decrease of vessel densities in the affected area as marked in red. (B) Defocus (lower panel) of the retinal area of interest severely affects image quality and analysis of vessel densities in comparison with the images with good focus (upper panel). (C) OCTA images are mostly centered on the region of interest, which mostly reflects the fovea or optic disc (not shown). Correct centering, by making use of defined landmarks, is important for comparison of different measures. Dividing the image into 4 vertical and horizontal sections might be helpful for evaluation of correct (left panel) and incorrect (right panel) centration. OCTA = optical coherence tomography angiography.
Figure 2
Figure 2. Algorithm Failure (A) and Retinal Pathology (R)
(A) The superficial vascular complex (left) is located and defined between the inner limiting membrane (ILM) and the inner plexiform layer (IPL) and the deep vascular complex (right) between the IPL and the outer plexiform layer (OPL). Segmentation errors due to incorrect identification of the respective layer borders within the B-scan may result in distorted vessel density measures (upper row). Manual correction of segmentation errors restores attribution of vessel signals to the different vascular complexes (lower row). (B) Retinal pathology (central macular edema) as detected in the OCT B-scan may affect retinal layer segmentation accuracy with wrong assignment of the ILM, IPL, and OPL resulting in incorrect and skewed visualization of the retinal vasculature.
Figure 3
Figure 3. Motion Artifacts (M) and Projection Artifacts (P)
Motion artifacts due to eye movement (A–B) and motion artifacts due to eye movement and software correction (C–E): (A) Blink lines are caused by missing imaging information due to blinking as marked by white arrows; (B) Vessel displacement (asterisk) results from a shift in fixation and eye movements. (C) Vessels appear stretched and flattened particularly at the edge of OCTA image (right) as stretch artifacts (white arrows); (D) vessel doubling (asterisk); (E) Artifacts with adjacent horizontal stripes or bands of different brightness are called banding (white squares); quilting can be described as a rectangular, checkerboard, or crisscross pattern of black and/or white horizontal and vertical lines (white circle). Motion artifacts may appear in smaller areas (≤25% of the image area, left) and larger areas (>25% of the image are, right). (F) Projection artifacts mostly affect deeper layers due to projection of superficial and bigger vessels. The vessel in the lower half of the SVC (left image) can be observed in the DVC when no projection artifact removal (PAR) software is used (PAR off, middle panel). Software-based removal of the superficial vessel exclude information about the DVC vessels in this area and are called negative projections (PAR on, right panel). DVC = deep vascular complex; OCTA = optical coherence tomography angiography; SVC = superficial vascular complex.
Figure 4
Figure 4. OSCAR-MP Based on Region of Interest
In the image on the left, major motion artifacts and severe decentration are evident; if the whole image is defined as region of interest (ROI), the image should be excluded (middle), and if the parafoveal area is defined as ROI (right), the image might be accepted for further analysis.

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