Purpose: Rapid developments are occurring in artificial intelligence (AI) and machine learning (ML) applied to neuroimaging. To date, advances in this space have largely been limited to research cohorts with little real-world translation that is clinically meaningful for patients in psychiatry and neurology and those with associated neuropsychiatric symptoms. There is a lack of large real-world multimodal linked datasets combining MRI imaging, clinical variables and other biomarkers within more representative ethnically diverse and deprived populations with multiple neuropsychiatric and systemic co-morbidities, alongside the right infrastructure to link them. Participants: We linked brain MRI scans in South London and Maudsley (SLaM) NHS Trust (UK), with clinical data from electronic mental health and dementia records for patients across multiple clinical sites in South London harnessing the Clinical Record Interactive Search (CRIS) data platform from 2008-2022. Findings to date: 12,547 patients (age range 6-108, female 54%, male 46%) were identified with 14649 unique MR studies totalling 58620 MRI scans across 5 scanners with linked clinical data, from an ethnically diverse population (44% non-White), most with high social deprivation (n = 7424), and having a variety of diagnoses, of which F00-F09 Organic was the largest ICD category (n = 4628, 33% of total), followed by F20-F29 Schizophrenia and related disorders (n= 2151, 15% of total), and F30-F39 Mood [affective] disorders (n = 1607, 12% of total). The commonest recorded diagnoses were Alzheimer's Disease (n = 2849), Schizophrenia (n = 1021) and mild cognitive impairment (n = 740). Future Plans: SLaM Image Bank is an exceptionally rich real-world cohort with linked MRI and clinical data reflecting the diversity of the population of South London. It provides a unique platform for future testing of automated decision support tools that may identify unique signatures of diagnosis and neuropsychiatric symptom subtype, markers of prognosis, and provide stratification for interventions or trials that are potentially clinically meaningful. This will form the basis to which new linked data and MRI data will be added in order to grow this cohort alongside the potential additions of other imaging modalities, novel biomarkers, meta-data and patient groups in the future.

AVV has received grants from the Alzheimer's Society, Alzheimer's Research UK, and NIHR BRC, including an NIHR BRC Maudsley Neuroimaging Grant. RS declares research support received in the last 3 years from Janssen, GSK and Takeda.

AVV is funded by the National Institute for Health Research (NIHR) as NIHR Clinical Lecturer and supported by the NIHR Maudsley Biomedical Research Centre and the NIHR HealthTech Research Centre in Brain Health at King's College London and South London and Maudsley NHS Foundation Trust and King's College London (NQOD-04) as PI of SLaM Image Bank. DS is part-funded by National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. RS is part-funded by: i) the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust and King's College London; ii) the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHS Foundation Trust; iii) UKRI - Medical Research Council through the DATAMIND HDR UK Mental Health Data Hub (MRC reference: MR/W014386); iv) the UK Prevention Research Partnership (Violence, Health and Society; MR-VO49879/1), an initiative funded by UK Research and Innovation Councils, the Department of Health and Social Care (England) and the UK devolved administrations, and leading health research charities. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

This project is approved under CRIS Ethics (Oxford REC, reference 18/SC/0372), sub-project ID CRIS 21-123 and part of the NIHR Biomedical Research Centre Maudsley Neuroimaging Call (NQOD-04).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

The data are subject to the contractual restrictions of the data sharing agreements between South London and Maudsley NHS Trust and Kings College London and are therefore not available for access beyond the SLaM Image Bank research team without prior authorisation from the CRIS oversight (imaging) committee. Updates will be shared at www.brainregion.com/slamimagebank

https://www.brainregion.com/slamimagebank