Artificial intelligence project for improved sarcoma diagnoses for patient benefit

Plain English summary of protocol

Background and study aims
Cancer treatment is determined by how tumours are classified by pathologists, who provide diagnoses which encompass prognoses and predictions of responses to therapies.
Reaching a tissue diagnosis today requires more time than hitherto allocated to pathologists, driven by the rapidly increasing knowledge of important prognostic factors, an understanding of the molecular basis of disease and the availability of targeted and personalised treatments. Diagnoses must be highly specific and accurate, distinguishing cancer subtypes from each other and from other diseases such as bone and soft tissue tumours versus regenerative /degenerative musculoskeletal (MSK) disease.
The increasing workload and complexity in reaching pathological diagnoses is compounded by a declining workforce: 29% of all UK-based pathologists are aged 55 and over. MSK pathology is specifically affected as there is a serious shortfall in pathologists in this subspecialty area.
Although primary MSK sarcomas represent about 2% of all cancers, there are over 100 subtypes described, as well as many common conditions that mimic sarcoma. The diagnosis has huge treatment implications and therefore crucially important to get right. Sarcomas can occur anywhere in the body (e.g. breast, lung) so they are frequently first encountered by non-expert MSK pathologists. This often leads to excessive consultant time in reaching diagnoses, and ordering inappropriate and excessive immunohistochemical and genetic tests. This protracts patients’ journeys to treatment, resulting in unnecessary costs.
This study aims to find out whether artificial intelligence (AI) is a solution to these challenges and can help support (not replace) pathologists as already shown for common cancers (e.g. prostate and bowel).

Who can participate?
Patients who had a diagnosis of sarcoma or a mimic of sarcoma and whose tissue has been processed as part of their clinical care. The study is fully inclusive of all genders, age ranges, ethnicities and members of all socio-economic groups.

What does the study involve?
As AI requires large numbers of cases and pathology slides must be digitised to generate whole-slide images (WSIs). The availability of digital scanners across the UK has made this possible. This study will gather large numbers of sarcoma cases using archived slides/data from the last 40 years and prospectively. Members of direct clinical care teams will gather pathology images/data from up to 50,000 patients. The project will run for 10 years (collecting images/data for 5 years and 5 years follow-up).

What are the possible benefits and risks of participating?
The study aims to produce an AI algorithm to aid sarcoma diagnosis in the future. There are no direct benefits or risks to current patients.

Where is the study run from?
University College London (UK)

When is the study starting and how long is it expected to run for?
March 2023 to December 2033

Who is funding the study?
The majority of the funding has been secured from UK Research and Innovation (UKRI) along with smaller grants from Tom Prince Cancer Trust, Skeletal Cancer Trust, Sarcoma UK, Chordoma UK and Bone Cancer Research Trust (UK)

Who is the main contact?
Prof. Adrienne M Flanagan, a.flanagan@ucl.ac.uk

Contact information

Prof Adrienne Flanagan
Public, Scientific, Principal investigator

University College London
Cancer Institute
Huntley Street
London
WC1E 6BT
United Kingdom

ORCID ID	0000-0002-2832-1303
Phone	+44 (0)7980290621
Email	a.flanagan@ucl.ac.uk

Study information

Eligibility

Locations

Countries of recruitment

• United Kingdom
• England
• Wales

Study participating centres

Results and Publications

Study outputs

Editorial Notes

06/12/2024: Study's existence confirmed by Sheffield Teaching Hospitals NHS Foundation Trust.