King’s College London & AI Centre for Value Based Healthcare

Implementation of the Federated Learning Interoperability Platform (FLIP) across multiple NHS Trusts to accelerate algorithm training to improve patient diagnosis

UPDATED MARCH 2024

The AI Centre for Value-Based Healthcare (AI Centre) is a consortium of academic, NHS and industry partners led by King’s College London (KCL) and based at St Thomas’ Hospital. The AI Centre’s partner organisations include University College London (UCL), Imperial College London, Queen Mary’s University London and the Health Innovation Network, supported by numerous industry partners including Scan and NVIDIA.

The diverse research teams within the AI Centre develop and train sophisticated AI algorithms from a vast wealth of NHS medical images and patient pathway data to create new healthcare tools powered by federated learning, to provide faster diagnosis, personalised therapies and effective screening across a range of conditions and procedures. AI algorithms perform better when they have more data to train on, but it must be remembered healthcare patient data is highly confidential and sensitive.

Project Background

In July 2019, the Scan AI team led a proof of concept (POC) with Kings College London to design a GPU-accelerated compute cluster to develop AI-powered medical imaging at the point of care. In contrast to traditional medical testing, which involves sending scans for further analysis by specialists, point of care testing allows the results gained from X-rays, CT scans or MRI to be delivered and analysed immediately, in real-time with the patient-clinician interaction. The POC success resulted in reference cluster design of an NVIDIA DGX A100, an 3XS EGX A30 and a 210TB NetApp AFF A800 storage array. This supported the development of the Artificial Intelligence Development Engine (AIDE) firmware, installed on the first cluster at King’s College Hospital NHS Foundation Trust in October 2021.

Following the validation of proof of concept system design it was decided to add a Run:ai software layer onto the cluster to further increase GPU utilisation. Run:ai enables flexible resource management and consumption so that users can easily access GPU fractions, multiple GPUs or clusters of GPUs for workloads of every size and stage of the AI lifecycle.

Subsequently, in October 2021 AIDE clusters were also installed at University College London NHS Foundation Trust and at Guy’s and St Thomas’ NHS Foundation Trust. These were followed by Imperial College Healthcare NHS Trust in January 2022, and University Hospital Sussex NHS Foundation Trust in February 2022. You can learn more about this phase in our AIDE project case study.

The Federated Learning Interoperability Platform

Following the launch of AIDE, the Federated Learning Interoperability Platform (FLIP) was developed to expand the training datasets using a federated server to train models on locally available patient data at each Trust, whilst retaining anonymity and confidentiality. To facilitate this the existing five AIDE clusters were installed with the FLIP firmware so they would act as the federated servers, whilst smaller clusters were scheduled to be installed in a further five NHS Trusts, to creation anonymised dataset coverage over 18 million patients. These smaller clusters were made up of an NVIDIA-certified 3XS EGX A30 server and a 45TB PEAK:AIO software-defined storage appliance.

The FLIP solution allows AI researchers to develop clinical applications on NHS patient data without the information ever leaving the local Trust network. There is no transferring of any confidential information out of each NHS Trust, which means that researchers can train their applications on vastly more data without compromising sensitive patient data. FLIP also incorporates dedicated secure data storage for processing and analysis within each NHS Trust. Data from across the Trusts’ patient records systems will be transferred into this secure enclave for curating and aggregation, unifying medical imaging scans from Picture Archiving and Communications Systems (PACS) - the industry-standard storage system incorporating different medical imaging types, and other electronic health data.

Throughout 2022, smaller AIDE clusters were installed at East Kent Hospitals University NHS Foundation Trust, Lewisham and Greenwich NHS Trust and Barts Health NHS Trust. In 2023, the original King’s College London POC DGX-2 cluster was relocated to a London datacentre for installation of the AIDE and FLIP layers, improved management and monitoring, reconfiguration of the NetApp array, refreshment of the network switches and installation of an updated Run:ai image.

Next Steps

During 2024, further expansion of the AIDE / FLIP solutions are scheduled, to complete the ten London-based sites. This is accompanied by a planned expansion outside the capital for the first time, with the federated learning concept scheduled for installation at the University Hospitals Birmingham NHS Foundation Trust, early in the year.

Check back here to see how this multi-year project expands further.

The Scan Partnership

Scan has been the glue between the collaborative partners at every stage of this multi-year, consistently-evolving project. Coordination and communication with KCL, the AI Centre, NVIDIA, NetApp, PEAK:AIO, Run:ai and the nationwide NHS Trust community has proved critical in the smooth delivery of each element of this federated learning solution. It has enabled better detection and diagnostics for many conditions and the continued improved patient care and outcomes for over 18 million NHS users.

Project Wins

Accelerate diagnosis from CT and MRI scans

Enhanced detection and faster diagnosis of prostate cancers

Image analysis in real-time for improved clinician-patient interaction

Scan initiated the guided POC and was instrumental in design of the first DGX cluster supporting its installation, upgrades and monitoring. For the AIDE clusters, Scan and its in-house 3XS Systems division developed a bespoke NVIDIA-certified EGX server to integrate with NVIDIA servers and networking, again installing and maintaining on each NHS site. All these hardware deployments have been further supported by Scan’s system engineers and data science consultancy team.

"This is a huge milestone for the AI Centre. I would like to thank all of our partners and funders for their collaboration and contribution towards both FLIP and AIDE. It is only in this way of multidisciplinary collaborations whereby healthcare innovations have a chance of adoption.”

Prof. Sebastien Ourselin

Head of Biomedical Engineering & Imaging Sciences, KCL

"When you are working with complex data, privacy becomes increasingly complicated. Researchers require access to this complex data in order to train robust AI algorithms. FLIP massively mitigates the risk of any breaches in patient data privacy – keeping patient data safe behind a secure firewall."

Dr M. Jorge Cardoso

CTO, London Medical Imaging and AI Centre for Value Based Healthcare

"Many thanks to the whole Scan team, for the support and help during the planning and deployment of the expanded cluster. Special thanks to Eyal for the preparation work on the switches and the precious info provided before, during and after the deployment.”

Davide Poccecai

IT Manager, School of Biomedical Engineering and Imaging Sciences, KCL

Speak to an expert

You’ve seen how Scan has helped KCL, the AI Centre and its partners to introduce AI technology into medical and healthcare scenarios. Contact our expert AI team to discuss your project requirements.