Detecting Dementia in the Retina: a Big Data Machine Learning Approach

The Moorfields Eye Hospital NHS Foundation Trust (MEH) and University College London (UCL) require access to NHS England data to investigate the association between changes of the retina, as measured using retinal photography and scans, with the onset of dementia for the following research 'Detection of Dementia in the Retina: a Big Data Machine Learning Approach'

The primary objective is to quantify the changes in the Retinal Nerve Fibre Layer (RNFL), ganglion cell layer and macular volume, as measured by Optical Coherence Tomography (OCT), that are consistently associated with Alzheimer’s Disease and other forms of neurodegenerative disease

The secondary objectives are to explore other features in the retina which can be identified in patients with neurodegenerative disease. In addition, we will use machine learning techniques on OCT scans to explore novel structural biomarkers indicative of diagnosis and progression of dementia.

AI modelling techniques, developed by UCL are used to enhance the accuracy of measuring eye tissues and identifying potential dementia indicators. These AI algorithms rely solely on imaging data from Moorfields Eye Hospital NHS Foundation Trust (MEH) and do not involve any NHS England data at any stage.

The following NHS England Data will be accessed:

• Hospital Episode Statistics Admitted Patient Care, Critical Care, Accident & Emergency, Outpatients and Emergency Care Dataset– necessary as this project is investigating the relationship between retinal structure, as measured on eye scans, and neurodegenerative disease. The overarching aim is to develop early detection tools for dementia and other forms of neurodegeneration. These datasets provide information on systemic disease diagnoses and procedures which allow us to define our cohorts for analysis and prediction tool development.

It should be noted that the changes seen on retinal imaging are not all specific to dementia - for example, some changes may reflect cardiovascular disease (and its relationship with vascular dementia), metabolic dysfunction (e.g. diabetes) and other chronic health conditions. To develop tools and understanding of the specific relationship between dementia and retinal structure, information on other health states is required in these individuals. The majority of dementia coding will be within HES APC. However, the Outpatients datasets provide an additional source of dementia codes, which though low in coverage, can have high predictive value for certain neurodegenerative states and also crucially, demonstrate which specialty services an individual may have attended (e.g. Neurology and Old Age Psychiatry in this case). HES A&E and ECDS also provide further information which is invaluable in cohort selection - for example, whether individuals have had brain imaging, whether they have suffered a fall.

• Civil Registration of Deaths – necessary because dementia is a leading cause of death in the UK and without knowledge of those individuals, there may be bias imparted into prediction tools where those who pass away during the study period are excluded from the training data.

The level of the Data will be:

• Pseudonymised

The Data will be minimised as follows:

• Limited to a study cohort identified by MEH as meeting the following criteria: Patients that have attended Moorfields Eye Hospital, aged over 40 at the time of their scan and had a retinal scan between 01/04/1997 and 01/04/2024 (approximately 550,000 individuals)

• Limited to data between 1997 and Latest Available

Data between 1997 and latest available (with no additional filtering applied) is necessary to;

- Enable appropriate identification of control individuals (e.g. those diagnosed with all-cause dementia in 2005 but no admission from 2008 onwards would have been falsely misclassified as an unaffected individual previously)

- Enable appropriate selection of control individuals. Filtering carried out on data previously shared under this DSA included only individuals with certain ICD-10 codes which created an unrepresentative selection of controls for a project which seeks to support public health for the general population

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Dementia affects more than 800,000 people in the UK alone and with the progressive shift in the age of the population, these numbers are likely to increase over the next decade. As deemed by the Confidential Advisory Group, there is strong public interest in the activity proceeding as ‘any advancement in detecting the onset of dementia had the potential for significant wider benefit’.

The funding is provided by Fight for Sight UK and Alzheimer's Research UK. The funding is specifically for the project described.

The funder(s) will have no ability to suppress or otherwise limit the publication of findings.

UCL is a processor acting under the instructions of MEH. UCL’s role is limited to storing the data on their servers at the UCL Safe Haven and processing the data on behalf of MEH.

Amazon Web Services (AWS) is a processor acting under the instructions of UCL. AWS’ role is limited to secure back-up of data stored in UCL’s Data Safe Haven. UCL uses offsite data centre services provided by VIRTUS data centre. VIRTUS does not have access to the data.

Public and Patient Involvement and Engagement (PPIE) support for the project is provided by the PPIE team at the NIHR Biomedical Research Centre at Moorfields Eye Hospital and UCL Institute of Ophthalmology. The group help refine the purpose of the research. The group supports the collection of the data for the purposes described above.

The initial outcome of this project has been the establishment of a substantial research image database, containing NHS England data, with relevant neurodegenerative disease labels. The database was completed by March 2021 and access to this database is limited to UCL Trusted Research Environment (UCL Data Safe Haven) by designated members.

The primary outcome will be a comprehensive description of the morphological features of dementia in the retina, including details on how retinal morphology evolves throughout the disease course. These will form the basis for a series of submission to peer reviewed journals. Scientific findings from this project will be communicated through presentations at both national and international conferences, which extend beyond ophthalmology into cardiology and neurology. Results will be submitted to peer-reviewed journals across a range of fields including ophthalmology, neuroscience, epidemiology and cardiology. As the study has been peer-reviewed and received funding from Fight for Sight UK and Alzheimers Research UK, results may also be presented at forums supported by these charities. Presentations will be by members of the research team but may also come from two members of the public, who will sit on the Working Group of the study.

Engagement with a wide range of stakeholders will be sought. These goals are facilitated by the Chief Investigator, who has extensive experience in communicating research findings with the public across a range of settings as well as the Patient and Public Involvement and Engagement (PPIE) team at the NIHR Biomedical Research Centre at Moorfields Eye Hospital-University College London. Significant PPIE has already contributed to the establishment of the AlzEye database and been complimented by the UK Confidential Advisory Group (CAG) of the NHS Health Research Authority (HRA). In addition to surveying nearly 500 interested lay members at Moorfields Eye Hospital into the methodology of AlzEye, two members of the public will sit on the working group and dissemination of results is planned through both medical and public forums.

The conclusions of this study will also be of interest to non-medical research groups exploring linked health research, predictive modelling and implications of real-world studies on shaping public policy. The group also plans to present study findings at pertinent meetings for public health researchers. To engage with members of the public, results of the study will be presented at research open days at Moorfields Eye Hospital, seminars and symposia within University College London and public meetings. To further promote public interest and communication, two lay members from the AlzEye working group will also be offered the opportunity to present study results at meetings, such as those hosted by Fight for Sight UK. Digital settings will also be explored with lay summaries uploaded to websites - details of the study are already available on the Moorfields Eye Hospital and Fight for Sight UK websites as well as the public database, clinicaltrials.gov. These organisations additionally have well-established social media departments frequently used for dissemination of results.

Initial results from this study were published in BMJ Open in 2022. UCL and MEH have also described retinal differences in neurodegeneration in Parkinson disease, published in the journal Neurology in 2024. The ultimate outcome of this project will be a prediction tool capable of diagnosing pre-symptomatic dementia on the basis of retinal scans of the patients retina. Details of this data analysis tool will be publicly published in peer-reviewed journals.

Learnings from this project thus far have been communicated through presentations as well as discussions with Health Data Research UK and NHSx. International presentations resulting from this dataset have been presented at the following:

Scientific events

• Annual Research in Vision and Ophthalmology Conference, the largest global conference dedicated to eye research, in May 2021.

• Swiss Retina awards October 2020

• Lisbon Ophthalmology Congress January 2020

Public events/coverage

• A TEDx Talk titled “Tackling Dementia with AI powered Eye Care” in March 2021

• Article in The Economist titled “A system based on AI will scan the retina for signs of Alzheimer’s” in December 2019

• Café Scientifique February 2019

Results will continue to be submitted to peer-reviewed journals across a range of fields including ophthalmology, neuroscience, epidemiology and cardiology. As the study has been peer-reviewed and received funding from Fight for Sight UK and Alzheimer’s Research UK, results may also be presented at forums supported by these charities. Presentations will be by members of the research team but may also come from two members of the public, who will sit on the Working Group of the study.

All published data will be in an aggregated form with small numbers suppressed in line with HES analysis guide.

Work on this project was initially delayed by the COVID-19 pandemic. Although NHS England HES admitted patient care data arrived in December 2019, the infrastructure needed for the export of the retinal images was in the process of being built when the pandemic started. Institutional priorities at Moorfields Eye Hospital towards the pandemic meant that the engineering/information technology team were tasked towards other priorities relating to potential vision loss and the development of digital infrastructure to combat the limitation on face-to-face clinics. Moreover, several of the research team (academic clinicians) were redeployed to intensive care units to support pandemic efforts.

Nonetheless, the AlzEye dataset was linked in 2021 and consists of approximately six million retinal images linked with neurodegenerative and cardiovascular disease outcome data providing an exciting, scientifically powerful, substrate for research. The initial publication for this project was published in BMJ Open in 2022.

This project has led to several scientific advances in this field. For example, work from this project identified that there are not only detectable retinal features in people with Parkinson disease (the fastest growing neurodegenerative disease globally), but that these retinal changes can be seen, on average seven years prior to clinical presentation. The work was highlighted as a case example of the importance of health data research in the NHS (https://digital.nhs.uk/data-and-information/keeping-data-safe-and-benefitting- the-public/powerful-moments/how-were-using-data-to-help-find-early-signs-of-parkinsons- disease) and received considerable public interest and support.

The project has also led to the development of a prediction model for all-cause dementia using retinal imaging data (https://iovs.arvojournals.org/article.aspx?articleid=2789614).

The Moorfields Eye Hospital NHS Foundation Trust (MEH) and University College London (UCL) require continued access to HES data to investigate the association between changes of the retina, as measured using retinal photography and scans, with the onset of dementia. UCL already have access to HES Accident and Emergency, Admitted Patient Care and Outpatient data, disseminated under previous iterations of this Agreement

Moorfields Eye Hospital NHS Foundation Trust and The University College London (UCL) are joint Data Controllers. The University College London is the only organisation which will process the data for the purpose of this research. Data processing will be undertaken within the School of Life and Medical Sciences within University College London.

A study working group, termed the AlzEye working group, consisting of the Chief Investigator, co-investigators, the Trust Caldicott Guardian and representatives from information technology and information governance convene quarterly to evaluate the management and ongoing progress of the trial. The study working group will not control the purpose for or manner in which the data are processed. The role of the working group is for study monitoring and advising on interpretation of the results.

The data processing is in line with Article 6(1)(e) ‘processing is necessary for the performance of a task carried out in the public interest’. Dementia affects more than 800,000 people in the UK alone and with the progressive shift in the age of the population, these numbers are likely to increase over the next decade. As deemed by the Confidential Advisory Group, there is strong public interest in the activity proceeding as ‘any advancement in detecting the onset of dementia had the potential for significant wider benefit’.

Public interest is in line with Article 9(2)(j) ‘processing is necessary for scientific or historical research purposes’.

Risks to participants' confidentiality arise through the transfer of identifying data to NHS England. This has been mitigated by closely consulting with NHS England and adhering to all data privacy standard operating procedures. In the worst case scenario, this would identify an individual as having had a retinal scan at some point in the last 10 years at Moorfields Eye Hospital. Subsequent data processing will take place on pseudonymised records and it is not envisaged that this would pose a risk to the individual participants.

The focus of this project is the development of a screening tool for the early detection of dementia. The most common form of dementia, Alzheimer’s Disease (AD), affects 26 million people globally, a figure expected to quadruple by 2050.

The most significant features of AD are the accumulation of plaques and tangled proteins in the central nervous system. The optic nerve and retina develop from the same embryonic tissue as the brain, and are thus a sensory extension of the central nervous system. As the only structure of the central nervous system not covered by bone, the retina provides unique access to direct imaging, which can be achieved using optical coherence tomography (OCT).

A number of small studies have identified morphological changes in the retinas of patients who have developed AD. However, plaque deposits in the brain can occur 15 years before the onset of clinical symptoms, and there is evidence to suggest that these plaques can be seen to form in the internal layers of the retina even before this.

The project objective is to characterise the changes in retinal parameters associated with the diagnosis and development of dementia, particularly Alzheimer’s Disease. The data includes HES labels of neurodegenerative disease from the HES outpatients and A&E database and covariate labels of diabetes mellitus and cardiovascular disease were requested for cohort matching as these other conditions can affect retinal structure.

Coding of diagnosis in HES outpatient data is less than 5% and therefore not practically useful for conducting this degree of large scale research. HES A&E data does not include ICD codes and dementia is not included in the A&E coding system. Strong agreement between HES APC and primary care data has already been demonstrated in multiple previous studies evaluating dementia coding.

Retention of HES outpatient data is helpful as it still does provide some patient data on diagnostic codes of dementia, in particular for the less common forms of dementia. In regards to A&E, it does not have ICD codes however HES A&E does still contain diagnostic information on other morbidities, such as cardiovascular disease and diabetes, which are required for covariate analysis and when comparing populations.

Pseudonymised patient record level HES data is required over a 10 year period in the London area to allow longitudinal analysis of scans in individuals developing neurodegenerative disease.

Due to the large number of patients included, the historical nature of the data, advanced age, risk of selection bias and difficulty in contacting patients, it would not be feasible to obtain consent from individuals. As a result, approval has been obtained from the Health Research Authority Confidential Advisory Group to process confidential information without consent under section 251 of the NHS Act 2006.

The purpose for processing the data pertains to a stand-alone project and the data will allow the largest and most in-depth analysis of retinal changes in dementia to be carried out. Cases have been defined as those with a HES label of Alzheimer’s disease (AD) and have been compared with controls. In addition, longitudinal analysis of cases will be analysed to identify retinal changes associated with an eventual diagnosis of AD.

Information is requested on individuals over the age of 40, who have attended Moorfields Eye Hospital and had a retinal scan between 01/01/2008 and 01/06/2018. In collaboration with machine learning partners within UCL, the Moorfields Eye Hospital propose to analyse their repository of more than 2 million retinal scans performed regularly on patients since 2008. By pseudonymously linking these scans, at a patient level to data from the Hospital Episode Statistics database, to identify those patients who went on to develop AD, an algorithm can be trained to identify the patterns of retinal changes which are associated with the development of AD. Additionally, by linking the retinal images to a set of confounding variables, associated with the development of AD, a closely matched cohort of control scans which do not correspond to an AD diagnosis can be constructed.

The aim was to perform a pseudonymised linkage of retinal imaging data from Moorfields Eye Hospital to the HES database, in order to create a pseudonymised dataset of retinal images. This will be a database of retinal images linked at an individual image level to corresponding diagnoses of neurodegenerative disease. Cohorts of images will then be matched on the study ID.

This pseudonymised database will be maintained by the University College London Institute of Ophthalmology, a department within UCL's School of Life and Medical Sciences.

The initial outcome of this project will be a substantial research image database with relevant labels of neurodegenerative disease – 2-3 orders of magnitude greater in size than that which currently exists. The primary outcome from Moorfields Eye Hospital will be a comprehensive description of the morphological features of neurodegenerative disease in the retina. The ultimate outcome of this project will be a machine learning derived algorithm capable of identifying features suggestive of the development of dementia on the basis of an OCT scan of the patient’s retina. This system can then be evaluated with a prospective observational study to assess its applicability outside of Moorfield Eye Hospital's dataset.

The value of a reliable screening tool for AD would be vast; by facilitating intervention early in the disease process it would lead to improvements in terms of quality adjusted life years, and reduce mortality and the economic burden of caring for functionally impaired patients.

Funding comes from a small grant award by Fight for Sight UK and Alzheimer’s Research UK. The project methodology has been peer-reviewed by their respective Grant Committees and deemed worthy of award. The funders will neither have access to the requested data nor be involved in the processing of data but are likely to be involved in facilitating dissemination of outputs from this project. The funders will not influence or suppress the findings of this research.

The initial outcome of this project has been the establishment of a substantial research image database, containing NHS England data, with relevant neurodegenerative disease labels. The database was completed by March 2021 and access to this database is limited to UCL Trusted Research Environment (UCL Data Safe Haven) by designated members.

The primary outcome will be a comprehensive description of the morphological features of dementia in the retina, including details on how retinal morphology evolves throughout the disease course. These will form the basis for a series of submission to peer reviewed journals from 2022 onwards. Scientific findings from this project will be communicated through presentations at both national and international conferences, which extend beyond ophthalmology into cardiology and neurology. Results will be submitted to peer-reviewed journals across a range of fields including ophthalmology, neuroscience, epidemiology and cardiology. As the study has been peer-reviewed and received funding from Fight for Sight UK and Alzheimers Research UK, results may also be presented at forums supported by these charities. Presentations will be by members of the research team but may also come from two members of the public, who will sit on the Working Group of the study.

Engagement with a wide range of stakeholders will be sought. These goals are facilitated by the Chief Investigator, who has extensive experience in communicating research findings with the public across a range of settings as well as the Patient and Public Involvement and Engagement (PPIE) team at the NIHR Biomedical Research Centre at Moorfields Eye Hospital-University College London. Significant PPIE has already contributed to the establishment of the AlzEye database and been complimented by the UK Confidential Advisory Group (CAG) of the NHS Health Research Authority (HRA). In addition to surveying nearly 500 interested lay members at Moorfields Eye Hospital into the methodology of AlzEye, two members of the public will sit on the working group and dissemination of results is planned through both medical and public forums.

The conclusions of this study will also be of interest to non-medical research groups exploring linked health research, predictive modelling and implications of real-world studies on shaping public policy. The group also plans to present study findings at pertinent meetings for public health researchers. To engage with members of the public, results of the study will be presented at research open days at Moorfields Eye Hospital, seminars and symposia within University College London and public meetings. To further promote public interest and communication, two lay members from the AlzEye working group will also be offered the opportunity to present study results at meetings, such as those hosted by Fight for Sight UK. Digital settings will also be explored with lay summaries uploaded to websites - details of the study are already available on the Moorfields Eye Hospital and Fight for Sight UK websites as well as the public database, clinicaltrials.gov. These organisations additionally have well-established social media departments frequently used for dissemination of results. The outputs from this study will be under the ownership of the Sponsor, Moorfields Eye hospital.

Initial results from this study have now been submitted to BMJ Open (October 2021). The ultimate outcome of this project will be a machine learning derived algorithm capable of diagnosing pre-symptomatic dementia on the basis of an OCT scan of the patients retina. This is expected to be completed in 2022. Details of this data analysis tool will be publicly published in peer-reviewed journals.

Learnings from this project thus far have been communicated through presentations as well as discussions with Health Data Research UK and NHSx. International presentations resulting from this dataset have been presented at the following:

Scientific events

• Annual Research in Vision and Ophthalmology Conference, the largest global conference dedicated to eye research, in May 2021.

• Swiss Retina awards October 2020

• Lisbon Ophthalmology Congress January 2020

Public events/coverage

• A TEDx Talk titled “Tackling Dementia with AI powered Eye Care” in March 2021

• Article in The Economist titled “A system based on AI will scan the retina for signs of Alzheimer’s” in December 2019

• Café Scientifique February 2019

Results will continue to be submitted to peer-reviewed journals across a range of fields including ophthalmology, neuroscience, epidemiology and cardiology. As the study has been peer-reviewed and received funding from Fight for Sight UK and Alzheimer’s Research UK, results may also be presented at forums supported by these charities. Presentations will be by members of the research team but may also come from two members of the public, who will sit on the Working Group of the study.

All published data will be in an aggregated form with small numbers suppressed in line with HES analysis guide.

Work on this project was initially delayed by the COVID-19 pandemic. Although NHS England HES admitted patient care data arrived in December 2019, the infrastructure needed for the export of the retinal images was in the process of being built when the pandemic started. Institutional priorities at Moorfields Eye Hospital towards the pandemic meant that the engineering/information technology team were tasked towards other priorities relating to potential vision loss and the development of digital infrastructure to combat the limitation on face-to-face clinics. Moreover, several of the research team (academic clinicians) were redeployed to intensive care units to support pandemic efforts.

Nonetheless, the AlzEye dataset was linked in 2021 and consists of approximately six million retinal images linked with neurodegenerative and cardiovascular disease outcome data providing an exciting, scientifically powerful, substrate for research. The initial publication for this project was published in BMJ Open in 2022.

This project has led to several scientific advances in this field. For example, work from this project identified that there are not only detectable retinal features in people with Parkinson disease (the fastest growing neurodegenerative disease globally), but that these retinal changes can be seen, on average seven years prior to clinical presentation. The work was highlighted as a case example of the importance of health data research in the NHS (https://digital.nhs.uk/data-and-information/keeping-data-safe-and-benefitting- the-public/powerful-moments/how-were-using-data-to-help-find-early-signs-of-parkinsons- disease) and received considerable public interest and support.

The project has also led to the development of a prediction model for all-cause dementia using retinal imaging data (https://iovs.arvojournals.org/article.aspx?articleid=2789614).

The Moorfields Eye Hospital NHS Foundation Trust (MEH) and University College London (UCL) require continued access to HES data to investigate the association between changes of the retina, as measured using retinal photography and scans, with the onset of dementia. UCL already have access to HES Accident and Emergency, Admitted Patient Care and Outpatient data, disseminated under previous iterations of this Agreement (version 0 and version 1).

Moorfields Eye Hospital NHS Foundation Trust and The University College London (UCL) are joint Data Controllers. The University College London is the only organisation which will process the data for the purpose of this research. Data processing will be undertaken within the School of Life and Medical Sciences within University College London.

A study working group, termed the AlzEye working group, consisting of the Chief Investigator, co-investigators, the Trust Caldicott Guardian and representatives from information technology and information governance convene quarterly to evaluate the management and ongoing progress of the trial. The study working group will not control the purpose for or manner in which the data are processed. The role of the working group is for study monitoring and advising on interpretation of the results.

The data processing is in line with Article 6(1)(e) ‘processing is necessary for the performance of a task carried out in the public interest’. Dementia affects more than 800,000 people in the UK alone and with the progressive shift in the age of the population, these numbers are likely to increase over the next decade. As deemed by the Confidential Advisory Group, there is strong public interest in the activity proceeding as ‘any advancement in detecting the onset of dementia had the potential for significant wider benefit’.

Public interest is in line with Article 9(2)(j) ‘processing is necessary for scientific or historical research purposes’.

Risks to participants' confidentiality arise through the transfer of identifying data to NHS Digital. This has been mitigated by closely consulting with NHS Digital and adhering to all data privacy standard operating procedures. In the worst case scenario, this would identify an individual as having had a retinal scan at some point in the last 10 years at Moorfields Eye Hospital. Subsequent data processing will take place on pseudonymised records and it is not envisaged that this would pose a risk to the individual participants.

The focus of this project is the development of a screening tool for the early detection of dementia. The most common form of dementia, Alzheimer’s Disease (AD), affects 26 million people globally, a figure expected to quadruple by 2050.

The most significant features of AD are the accumulation of plaques and tangled proteins in the central nervous system. The optic nerve and retina develop from the same embryonic tissue as the brain, and are thus a sensory extension of the central nervous system. As the only structure of the central nervous system not covered by bone, the retina provides unique access to direct imaging, which can be achieved using optical coherence tomography (OCT).

A number of small studies have identified morphological changes in the retinas of patients who have developed AD. However, plaque deposits in the brain can occur 15 years before the onset of clinical symptoms, and there is evidence to suggest that these plaques can be seen to form in the internal layers of the retina even before this.

The project objective is to characterise the changes in retinal parameters associated with the diagnosis and development of dementia, particularly Alzheimer’s Disease. The data includes HES labels of neurodegenerative disease from the HES outpatients and A&E database and covariate labels of diabetes mellitus and cardiovascular disease were requested for cohort matching as these other conditions can affect retinal structure.

Coding of diagnosis in HES outpatient data is less than 5% and therefore not practically useful for conducting this degree of large scale research. HES A&E data does not include ICD codes and dementia is not included in the A&E coding system. Strong agreement between HES APC and primary care data has already been demonstrated in multiple previous studies evaluating dementia coding.

Retention of HES outpatient data is helpful as it still does provide some patient data on diagnostic codes of dementia, in particular for the less common forms of dementia. In regards to A&E, it does not have ICD codes however HES A&E does still contain diagnostic information on other morbidities, such as cardiovascular disease and diabetes, which are required for covariate analysis and when comparing populations.

Pseudonymised patient record level HES data is required over a 10 year period in the London area to allow longitudinal analysis of scans in individuals developing neurodegenerative disease.

Due to the large number of patients included, the historical nature of the data, advanced age, risk of selection bias and difficulty in contacting patients, it would not be feasible to obtain consent from individuals. As a result, approval has been obtained from the Health Research Authority Confidential Advisory Group to process confidential information without consent under section 251 of the NHS Act 2006.

The purpose for processing the data pertains to a stand-alone project and the data will allow the largest and most in-depth analysis of retinal changes in dementia to be carried out. Cases have been defined as those with a HES label of Alzheimer’s disease (AD) and have been compared with controls. In addition, longitudinal analysis of cases will be analysed to identify retinal changes associated with an eventual diagnosis of AD.

Information is requested on individuals over the age of 40, who have attended Moorfields Eye Hospital and had a retinal scan between 01/01/2008 and 01/06/2018. In collaboration with machine learning partners within UCL, the Moorfields Eye Hospital propose to analyse their repository of more than 2 million retinal scans performed regularly on patients since 2008. By pseudonymously linking these scans, at a patient level to data from the Hospital Episode Statistics database, to identify those patients who went on to develop AD, an algorithm can be trained to identify the patterns of retinal changes which are associated with the development of AD. Additionally, by linking the retinal images to a set of confounding variables, associated with the development of AD, a closely matched cohort of control scans which do not correspond to an AD diagnosis can be constructed.

The aim was to perform a pseudonymised linkage of retinal imaging data from Moorfields Eye Hospital to the HES database, in order to create a pseudonymised dataset of retinal images. This will be a database of retinal images linked at an individual image level to corresponding diagnoses of neurodegenerative disease. Cohorts of images will then be matched on the study ID.

This pseudonymised database will be maintained by the University College London Institute of Ophthalmology, a department within UCL's School of Life and Medical Sciences.

The initial outcome of this project will be a substantial research image database with relevant labels of neurodegenerative disease – 2-3 orders of magnitude greater in size than that which currently exists. The primary outcome from Moorfields Eye Hospital will be a comprehensive description of the morphological features of neurodegenerative disease in the retina. The ultimate outcome of this project will be a machine learning derived algorithm capable of identifying features suggestive of the development of dementia on the basis of an OCT scan of the patient’s retina. This system can then be evaluated with a prospective observational study to assess its applicability outside of Moorfield Eye Hospital's dataset.

The value of a reliable screening tool for AD would be vast; by facilitating intervention early in the disease process it would lead to improvements in terms of quality adjusted life years, and reduce mortality and the economic burden of caring for functionally impaired patients.

Funding comes from a small grant award by Fight for Sight UK and Alzheimer’s Research UK. The project methodology has been peer-reviewed by their respective Grant Committees and deemed worthy of award. The funders will neither have access to the requested data nor be involved in the processing of data but are likely to be involved in facilitating dissemination of outputs from this project. The funders will not influence or suppress the findings of this research.

The initial outcome of this project has been the establishment of a substantial research image database, containing NHS Digital data, with relevant neurodegenerative disease labels. The database was completed by March 2021 and access to this database is limited to UCL Trusted Research Environment (UCL Data Safe Haven) by designated members.

The primary outcome will be a comprehensive description of the morphological features of dementia in the retina, including details on how retinal morphology evolves throughout the disease course. These will form the basis for a series of submission to peer reviewed journals from 2022 onwards. Scientific findings from this project will be communicated through presentations at both national and international conferences, which extend beyond ophthalmology into cardiology and neurology. Results will be submitted to peer-reviewed journals across a range of fields including ophthalmology, neuroscience, epidemiology and cardiology. As the study has been peer-reviewed and received funding from Fight for Sight UK and Alzheimers Research UK, results may also be presented at forums supported by these charities. Presentations will be by members of the research team but may also come from two members of the public, who will sit on the Working Group of the study.

Engagement with a wide range of stakeholders will be sought. These goals are facilitated by the Chief Investigator, who has extensive experience in communicating research findings with the public across a range of settings as well as the Patient and Public Involvement and Engagement (PPIE) team at the NIHR Biomedical Research Centre at Moorfields Eye Hospital-University College London. Significant PPIE has already contributed to the establishment of the AlzEye database and been complimented by the UK Confidential Advisory Group (CAG) of the NHS Health Research Authority (HRA). In addition to surveying nearly 500 interested lay members at Moorfields Eye Hospital into the methodology of AlzEye, two members of the public will sit on the working group and dissemination of results is planned through both medical and public forums.

The conclusions of this study will also be of interest to non-medical research groups exploring linked health research, predictive modelling and implications of real-world studies on shaping public policy. The group also plans to present study findings at pertinent meetings for public health researchers. To engage with members of the public, results of the study will be presented at research open days at Moorfields Eye Hospital, seminars and symposia within University College London and public meetings. To further promote public interest and communication, two lay members from the AlzEye working group will also be offered the opportunity to present study results at meetings, such as those hosted by Fight for Sight UK. Digital settings will also be explored with lay summaries uploaded to websites - details of the study are already available on the Moorfields Eye Hospital and Fight for Sight UK websites as well as the public database, clinicaltrials.gov. These organisations additionally have well-established social media departments frequently used for dissemination of results. The outputs from this study will be under the ownership of the Sponsor, Moorfields Eye hospital.

Initial results from this study have now been submitted to BMJ Open (October 2021). The ultimate outcome of this project will be a machine learning derived algorithm capable of diagnosing pre-symptomatic dementia on the basis of an OCT scan of the patients retina. This is expected to be completed in 2022. Details of this data analysis tool will be publicly published in peer-reviewed journals.

Learnings from this project thus far have been communicated through presentations as well as discussions with Health Data Research UK and NHSx. International presentations resulting from this dataset have been presented at the following:

Scientific events

• Annual Research in Vision and Ophthalmology Conference, the largest global conference dedicated to eye research, in May 2021.

• Swiss Retina awards October 2020

• Lisbon Ophthalmology Congress January 2020

Public events/coverage

• A TEDx Talk titled “Tackling Dementia with AI powered Eye Care” in March 2021

• Article in The Economist titled “A system based on AI will scan the retina for signs of Alzheimer’s” in December 2019

• Café Scientifique February 2019

Results will continue to be submitted to peer-reviewed journals across a range of fields including ophthalmology, neuroscience, epidemiology and cardiology. As the study has been peer-reviewed and received funding from Fight for Sight UK and Alzheimer’s Research UK, results may also be presented at forums supported by these charities. Presentations will be by members of the research team but may also come from two members of the public, who will sit on the Working Group of the study.

All published data will be in an aggregated form with small numbers suppressed in line with HES analysis guide.

The initial outcome of this project has been the establishment of a substantial research image database, containing NHS Digital data, with relevant neurodegenerative disease labels. The database was completed by March 2021 and access to this database is limited to UCL Trusted Research Environment (UCL Data Safe Haven) by designated members.

Work on this project has been delayed by the COVID-19 pandemic. Although NHS Digital HES admitted patient care data arrived in December 2019, the infrastructure needed for the export of the retinal images was in the process of being built when the pandemic started. Institutional priorities at Moorfields Eye Hospital towards the pandemic meant that the engineering/information technology team were tasked towards other priorities relating to potential vision loss and the development of digital infrastructure to combat the limitation on face-to-face clinics. Moreover, several of the research team (academic clinicians) were redeployed to intensive care units to support pandemic efforts.

Nonetheless, the AlzEye database has now been constructed and consists of more than 4 million retinal images linked with neurodegenerative and cardiovascular disease outcome data providing an exciting, scientifically powerful, substrate for research. The initial publication for this project has been submitted in October 2021 to BMJ Open. As such, the proposed benefits above have not yet been yielded.

The Moorfields Eye Hospital NHS Foundation Trust (MEH) and University College London (UCL) require HES data to investigate the association between changes of the retina, as measured using retinal photography and scans, with the onset of dementia. UCL already have access to HES Accident and Emergency and Outpatient data, disseminated under a previous iteration of this Agreement (DARS-NIC-116883-L8W9Q-0.6). MEH and UCL now require HES Admitted Patient Care for the same purpose under this amended Agreement. The only purpose for processing the data is for medical research.

Moorfields Eye Hospital NHS Foundation Trust and The University College London (UCL) are joint Data Controllers. The University College London is the only organisation which will process the data for the purpose of this research. Data processing will be undertaken within the School of Life and Medical Sciences within University College London.

A study working group, termed the AlzEye working group, consisting of the Chief Investigator, co-investigators, the Trust Caldicott Guardian and representatives from information technology and information governance convene quarterly to evaluate the management and ongoing progress of the trial. The study working group will not control the purpose for or manner in which the data are processed. The role of the working group is for study monitoring and advising on interpretation of the results.

The data processing is in line with Article 6(1)(e) ‘processing is necessary for the performance of a task carried out in the public interest’. Dementia affects more than 800,000 people in the UK alone and with the progressive shift in the age of the population, these numbers are likely to increase over the next decade. As deemed by the Confidential Advisory Group, there is strong public interest in the activity proceeding as ‘any advancement in detecting the onset of dementia had the potential for significant wider benefit’.

Public interest is in line with Article 9(2)(j) ‘processing is necessary for scientific or historical research purposes’.

Risks to participants' confidentiality arise through the transfer of identifying data to NHS Digital. This will be mitigated by closely consulting with NHS Digital and adhering to all data privacy standard operating procedures. In the worst case scenario, this would identify an individual as having had a retinal scan at some point in the last 10 years at Moorfields Eye Hospital. Subsequent data processing will take place on pseudonymised records and it is not envisaged that this would pose a risk to the individual participants.

The focus of this project is the development of a screening tool for the early detection of dementia. The most common form of dementia, Alzheimer’s Disease (AD), affects 26 million people globally, a figure expected to quadruple by 2050.

The most significant features of AD are the accumulation of plaques and tangled proteins in the central nervous system. The optic nerve and retina develop from the same embryonic tissue as the brain, and are thus a sensory extension of the central nervous system. As the only structure of the central nervous system not covered by bone, the retina provides unique access to direct imaging, which can be achieved using optical coherence tomography (OCT).

A number of small studies have identified morphological changes in the retinas of patients who have developed AD. However, plaque deposits in the brain can occur 15 years before the onset of clinical symptoms, and there is evidence to suggest that these plaques can be seen to form in the internal layers of the retina even before this.

The project objective is to characterise the changes in retinal parameters associated with the diagnosis and development of dementia, particularly Alzheimer’s Disease. The data currently includes HES labels of neurodegenerative disease from the HES outpatients and A&E database. Additional covariate labels of diabetes mellitus and cardiovascular disease were requested for cohort matching as these other conditions can affect retinal structure.

Coding of diagnosis in HES outpatient data is less than 5% and therefore not practically useful for conducting this degree of large scale research. HES A&E data does not include ICD codes and dementia is not included in the A&E coding system. This amended Agreement is therefore to obtain HES Admitted Patient Care (APC) data. Strong agreement between HES APC and primary care data has already been demonstrated in multiple previous studies evaluating dementia coding. This amendment will not link a new cohort but instead expand on the previous linkage with one additional HES APC dataset.

Retention of HES outpatient data is helpful as it still does provide some patient data on diagnostic codes of dementia, in particular for the less common forms of dementia. In regards to A&E, it does not have ICD codes however HES A&E does still contain diagnostic information on other morbidities, such as cardiovascular disease and diabetes, which are required for covariate analysis and when comparing populations.

Pseudonymised patient record level HES data is required over a 10 year period in the London area to allow longitudinal analysis of scans in individuals developing neurodegenerative disease.

Due to the large number of patients included, the historical nature of the data, advanced age, risk of selection bias and difficulty in contacting patients, it would not be feasible to obtain consent from individuals. As a result, approval has been obtained from the Health Research Authority Confidential Advisory Group to process confidential information without consent under section 251 of the NHS Act 2006.

The purpose for processing the data pertains to a stand-alone project and the data will allow the largest and most in-depth analysis of retinal changes in dementia to be carried out. Cases have been defined as those with a HES label of Alzheimer’s disease (AD) and have been compared with controls. In addition, longitudinal analysis of cases will be analysed to identify retinal changes associated with an eventual diagnosis of AD.

Information is requested on individuals over the age of 40, who have attended Moorfields Eye Hospital and had a retinal scan between 01/01/2008 and 01/06/2018. In collaboration with machine learning partners within UCL, the Moorfields Eye Hospital propose to analyse their repository of more than 2 million retinal scans performed regularly on patients since 2008. By pseudonymously linking these scans, at a patient level to data from the Hospital Episode Statistics database, to identify those patients who went on to develop AD, an algorithm can be trained to identify the patterns of retinal changes which are associated with the development of AD. Additionally, by linking the retinal images to a set of confounding variables, associated with the development of AD, a closely matched cohort of control scans which do not correspond to an AD diagnosis can be constructed.

The aim was to perform a pseudonymised linkage of retinal imaging data from Moorfields Eye Hospital to the HES database, in order to create a pseudonymised dataset of retinal images. This will be a database of retinal images linked at an individual image level to corresponding diagnoses of neurodegenerative disease. Cohorts of images will then be matched on the study ID.

This pseudonymised database will be maintained by the University College London Institute of Ophthalmology, a department within UCL's School of Life and Medical Sciences.

The initial outcome of this project will be a substantial research image database with relevant labels of neurodegenerative disease – 2-3 orders of magnitude greater in size than that which currently exists. The primary outcome from Moorfields Eye Hospital will be a comprehensive description of the morphological features of neurodegenerative disease in the retina. The ultimate outcome of this project will be a machine learning derived algorithm capable of identifying features suggestive of the development of dementia on the basis of an OCT scan of the patient’s retina. This system can then be evaluated with a prospective observational study to assess its applicability outside of Moorfield Eye Hospital's dataset.

The value of a reliable screening tool for AD would be vast; by facilitating intervention early in the disease process it would lead to improvements in terms of quality adjusted life years, and reduce mortality and the economic burden of caring for functionally impaired patients.

Funding comes from a small grant award by Fight for Sight UK and Alzheimer’s Research UK. The project methodology has been peer-reviewed by their respective Grant Committees and deemed worthy of award. The funders will neither have access to the requested data nor be involved in the processing of data but are likely to be involved in facilitating dissemination of outputs from this project. The funders will not influence or suppress the findings of this research.

The initial outcome of this project will be a substantial research image database, containing NHS Digital data, with relevant neurodegenerative disease labels. The database will be completed by March 2019 and access to this database will be limited to UCL School of Life and Medical Sciences.

The primary outcome will be a comprehensive description of the morphological features of dementia in the retina, including details on how retinal morphology evolves throughout the disease course. These will form the basis for a series of submission to peer reviewed journals (e.g. NEJM & Nature) from early 2020 onwards.

Scientific findings from this project will be communicated through presentations at both national and international conferences, which extend beyond ophthalmology into cardiology and neurology. Results will be submitted to peer-reviewed journals across a range of fields including ophthalmology, neuroscience, epidemiology and cardiology. As the study has been peer-reviewed and received funding from Fight for Sight UK and Alzheimer’s Research UK, results may also be presented at forums supported by these charities. Presentations will be by members of the research team but may also come from two members of the public, who will sit on the Working Group of the study.

Engagement with a wide range of stakeholders will be sought. These goals are facilitated by the Chief Investigator, who has extensive experience in communicating research findings with the public across a range of settings as well as the Patient and Public Involvement and Engagement (PPIE) team at the NIHR Biomedical Research Centre at Moorfields Eye Hospital-University College London. Significant PPIE has already contributed to the establishment of the AlzEye database and been complimented by the UK Confidential Advisory Group (CAG) of the NHS Health Research Authority (HRA). In addition to surveying nearly 500 interested lay members at Moorfields Eye Hospital into the methodology of AlzEye, two members of the public will sit on the working group and dissemination of results is planned through both medical and public forums.

The conclusions of this study will also be of interest to non-medical research groups exploring linked health research, predictive modelling and implications of real-world studies on shaping public policy. The group also plans to present study findings at pertinent meetings for public health researchers.

To engage with members of the public, results of the study will be presented at research open days at Moorfields Eye Hospital, seminars and symposia within University College London and public meetings. The methodology of this study will be presented to the open public science initiative, Café Scientifique, which facilitates interactions between researchers and the public in Spring 2019. To further promote public interest and communication, two lay members from the AlzEye working group will also be offered the opportunity to present study results at meetings, such as those hosted by Fight for Sight UK. Digital settings will also be explored with lay summaries uploaded to websites - details of the study are already available on the Moorfields Eye Hospital and Fight for Sight UK websites as well as the public database, clinicaltrials.gov. These organisations additionally have well-established social media departments frequently used for dissemination of results.

The outputs from this study will be under the ownership of the Sponsor, Moorfields Eye hospital.

Initial results from this study are anticipated to be disseminated 1 year following receipt of data from NHS Digital, therefore February 2020.

The ultimate outcome of this project will be a machine learning derived algorithm capable of diagnosing pre-symptomatic dementia on the basis of an OCT scan of the patient’s retina. This is expected to be completed in 2020-2021. Thereafter this screening tool can be evaluated with a prospective observational study to assess its applicability outside of MEH's dataset, with a view to incorporation into future clinical trials. Details of this data analysis tool will be publicly published in peer-reviewed journals.

All published data will be in an aggregated form with small numbers suppressed in line with HES analysis guide.

The Moorfields Eye Hospital NHS Foundation Trust (MEH) and University College London (UCL) require HES data to investigate the association between changes of the retina, as measured using retinal photography and scans, with the onset of dementia. The only purpose is for medical research.

Moorfields Eye Hospital NHS Foundation Trust and The University College London (UCL) are joint Data Controllers. The University College London School of Life and Medical Sciences is the Data Processor for the purpose of this research.

A study working group, termed the AlzEye working group, consisting of the Chief Investigator, co-investigators, the Trust Caldicott Guardian and representatives from information technology and information governance will convene quarterly to evaluate the management and ongoing progress of the trial. The study working group will not control the purpose for or manner in which the data are processed. The role of the working group is for study monitoring and advising on interpretation of the results.

The proposed data processing is in line with Article 6(1)(e) ‘processing is necessary for the performance of a task carried out in the public interest’. Dementia affects more than 800,000 people in the UK alone and with the progressive shift in the age of the population, these numbers are likely to increase over the next decade. As deemed by the Confidential Advisory Group, there is strong public interest in the activity proceeding as ‘any advancement in detecting the onset of dementia had the potential for significant wider benefit’.

Public interest is in line with Article 9(2)(j) ‘processing is necessary for scientific or historical research purposes’.

Risks to participants' confidentiality arise through the transfer of identifying data to NHS Digital. This will be mitigated by closely consulting with NHS Digital and adhering to all data privacy standard operating procedures. In the worst case scenario, this would identify an individual as having had a retinal scan at some point in the last 10 years at Moorfields Eye Hospital. Subsequent data processing will take place on pseudonymised records and it is not envisaged that this would pose a risk to the individual participants.

The focus of this newly undertaken project is the development of a screening tool for the early detection of dementia. The most common form of dementia, Alzheimer’s Disease (AD), affects 26 million people globally, a figure expected to quadruple by 2050.

The most significant features of AD are the accumulation of plaques and tangled proteins in the central nervous system. The optic nerve and retina develop from the same embryonic tissue as the brain, and are thus a sensory extension of the central nervous system. As the only structure of the central nervous system not covered by bone, the retina provides unique access to direct imaging, which can be achieved using optical coherence tomography (OCT).

A number of small studies have identified morphological changes in the retinas of patients who have developed AD. However, plaque deposits in the brain can occur 15 years before the onset of clinical symptoms, and there is evidence to suggest that these plaques can be seen to form in the internal layers of the retina even before this.

The project objective is to characterise the changes in retinal parameters associated with the diagnosis and development of dementia, particularly Alzheimer’s Disease. The data required includes HES labels of neurodegenerative disease from the HES outpatients and A&E database. Additional covariate labels of diabetes mellitus and cardiovascular disease are requested for cohort matching as these other conditions can affect retinal structure. Pseudonymised patient record level HES data is required over a 10 year period in the London area to allow longitudinal analysis of scans in individuals developing neurodegenerative disease. Due to the large number of patients included, the historical nature of the data, advanced age, risk of selection bias and difficulty in contacting patients, it would not be feasible to obtain consent from individuals. As a result, approval has been obtained from the Health Research Authority Confidential Advisory Group to process confidential information without consent under section 251 of the NHS Act 2006.

The purpose for processing the data pertains to a stand-alone project and the data will allow the largest and most in-depth analysis of retinal changes in dementia to be carried out. Cases will be defined as those with a HES label of Alzheimer’s disease (AD) and will be compared with controls. In addition, longitudinal analysis of cases will be analysed to identify retinal changes associated with an eventual diagnosis of AD.

Information is requested on individuals over the age of 40, who have attended Moorfields Eye Hospital and had a retinal scan between 01/01/2008 and 01/06/2018. In collaboration with machine learning partners within UCL, the Moorfields Eye Hospital propose to analyse their repository of more than 2 million retinal scans performed regularly on patients since 2008. By pseudonymously linking these scans, at a patient level to data from the Hospital Episode Statistics database, to identify those patients who went on to develop AD, an algorithm can be trained to identify the patterns of retinal changes which are associated with the development of AD. Additionally, by linking the retinal images to a set of confounding variables, associated with the development of AD, a closely matched cohort of control scans which do not correspond to an AD diagnosis can be constructed.

MEH's and UCL's aim is for UCL to perform a pseudonymised linkage of retinal imaging data from Moorfields Eye Hospital to the HES database, in order to create a pseudonymised dataset of retinal images. This will be a database of retinal images linked at an individual image level to corresponding diagnoses of neurodegenerative disease. Cohorts of images will then be matched on the study ID.

This pseudonymised database will be maintained by the University College London Institute of Ophthalmology, a department within UCL's School of Life and Medical Sciences.

The initial outcome of this project will be a substantial research image database with relevant labels of neurodegenerative disease – 2-3 orders of magnitude greater in size than that which currently exists. The primary outcome from Moorfields Eye Hospital will be a comprehensive description of the morphological features of neurodegenerative disease in the retina. The ultimate outcome of this project will be a machine learning derived algorithm capable of identifying features suggestive of the development of dementia on the basis of an OCT scan of the patient’s retina. This system can then be evaluated with a prospective observational study to assess its applicability outside of Moorfield Eye Hospital's dataset.

The value of a reliable screening tool for AD would be vast; by facilitating intervention early in the disease process it would lead to improvements in terms of quality adjusted life years, and reduce mortality and the economic burden of caring for functionally impaired patients.

Funding comes from a small grant award by Fight for Sight UK and Alzheimer’s Research UK. The project methodology has been peer-reviewed by their respective Grant Committees and deemed worthy of award. The funders will neither have access to the requested data nor be involved in the processing of data but are likely to be involved in facilitating dissemination of outputs from this project. The funders will not influence of suppress the findings of this research.

The initial outcome of this project will be a substantial research image database, containing NHS Digital data, with relevant neurodegenerative disease labels. The database will be completed by March 2019 and access to this database will be limited to UCL School of Life and Medical Sciences.

The primary outcome will be a comprehensive description of the morphological features of dementia in the retina, including details on how retinal morphology evolves throughout the disease course. These will form the basis for a series of submission to peer reviewed journals (e.g. NEJM & Nature) from early 2020 onwards.

Scientific findings from this project will be communicated through presentations at both national and international conferences, which extend beyond ophthalmology into cardiology and neurology. Results will be submitted to peer-reviewed journals across a range of fields including ophthalmology, neuroscience, epidemiology and cardiology. As the study has been peer-reviewed and received funding from Fight for Sight UK and Alzheimer’s Research UK, results may also be presented at forums supported by these charities. Presentations will be by members of the research team but may also come from two members of the public, who will sit on the Working Group of the study.

Engagement with a wide range of stakeholders will be sought. These goals are facilitated by the Chief Investigator, who has extensive experience in communicating research findings with the public across a range of settings as well as the Patient and Public Involvement and Engagement (PPIE) team at the NIHR Biomedical Research Centre at Moorfields Eye Hospital-University College London. Significant PPIE has already contributed to the establishment of the AlzEye database and been complimented by the UK Confidential Advisory Group (CAG) of the NHS Health Research Authority (HRA). In addition to surveying nearly 500 interested lay members at Moorfields Eye Hospital into the methodology of AlzEye, two members of the public will sit on the working group and dissemination of results is planned through both medical and public forums.

The conclusions of this study will also be of interest to non-medical research groups exploring linked health research, predictive modelling and implications of real-world studies on shaping public policy. The group also plans to present study findings at pertinent meetings for public health researchers.

To engage with members of the public, results of the study will be presented at research open days at Moorfields Eye Hospital, seminars and symposia within University College London and public meetings. The methodology of this study will be presented to the open public science initiative, Café Scientifique, which facilitates interactions between researchers and the public in Spring 2019. To further promote public interest and communication, two lay members from the AlzEye working group will also be offered the opportunity to present study results at meetings, such as those hosted by Fight for Sight UK. Digital settings will also be explored with lay summaries uploaded to websites - details of the study are already available on the Moorfields Eye Hospital and Fight for Sight UK websites as well as the public database, clinicaltrials.gov. These organisations additionally have well-established social media departments frequently used for dissemination of results.

The outputs from this study will be under the ownership of the Sponsor, Moorfields Eye hospital.

Initial results from this study are anticipated to be disseminated 1 year following receipt of data from NHS Digital, therefore February 2020.

The ultimate outcome of this project will be a machine learning derived algorithm capable of diagnosing pre-symptomatic dementia on the basis of an OCT scan of the patient’s retina. This is expected to be completed in 2020-2021. Thereafter this screening tool can be evaluated with a prospective observational study to assess its applicability outside of MEH's dataset, with a view to incorporation into future clinical trials. Details of this data analysis tool will be publicly published in peer-reviewed journals.

All published data will be in an aggregated form with small numbers suppressed in line with HES analysis guide.

Yielded Benefits is not a requirement for new applications.