BowelSys: an AI tool to enhance FIT diagnostic yield and improve bowel cancer detection in symptomatic patients

Faecal immunochemical testing (FIT) measures faecal haemoglobin concentration (f-Hb).

FIT can be used to manage patients presenting in primary care with unexplained lower gastrointestinal (GI) symptoms that may be indicative of bowel cancer in primary care prior to (or alongside) an urgent referral, or for triaging in secondary care to guide the management of referred patients.

The threshold for a positive FIT result in symptomatic patients is 10µg Hb/g faeces. Any participant exceeding this pre-set FIT threshold value is referred for endoscopic services (e.g., sigmoidoscopy or colonoscopy) to identify any medically actionable cause of bleeding i.e., colorectal cancer (CRC) or a precancerous adenoma (polyp).

Coupled to increased sensitivity of FIT vs. traditional guaiac-based f-Hb detection, the number of referrals from primary care for endoscopic procedures is rising.

A 2021 study determined the positive predictive value of FIT in a low-risk symptomatic population was 7.0%. This indicates a false-positive rate of 93%, meaning 13 patients with f-Hb \>10 µg Hb/g faeces underwent sigmoidoscopy or colonoscopy to identify one CRC.

There is an immediate and pressing **unmet need** to improve FIT's diagnostic yield for detecting bowel cancer. This will reduce endoscopy referrals, protecting patients from unnecessary invasive screening that can cause bowel perforation (a serious adverse event that can be lethal), and costs £322**-**£548 per procedure. Data already collected by the clinical collaborators to this project has revealed scope to modulate personalised FIT thresholds for symptomatic patients based on specific individual data variables that could help to refine onward referrals.

**SOLUTION:** Advanced Expert Systems Ltd (AES) have joined clinical specialists from University Hospitals Coventry & Warwickshire Midlands NHS Trust, York and Scarborough Teaching Hospital NHS Foundation Trust (York), and University Hospitals of Leicester NHS Trust (Leicester) to develop an AI-based software platform 'BowelSys' to interpret FIT result in the context of other clinical and non-clinical risk factors associated with the development of bowel cancer.

As a multivariate stratification model, BowelSys enables a personalised interpretation of FIT result and optimises clinical resources by risk. High-risk patients are fast-tracked for further investigation, whilst patients with low-to-no risk have further investigations delayed. This will enable clinical resources to be used more efficiently, with high-risk patients fast-tracked for endoscopy, enabling earlier and better detection of neoplasias.

**TIMELINESS:** Due to Covid-19, there is now additional impetus to reduce unnecessary endoscopy referrals to comply with infection control measures, tackle long waiting lists, improve NHS efficiency, and reduce costs.