AI Analysis of Voice to Aid Laryngeal Cancer Diagnosis
Research type
Research Study
Full title
AI Analysis of Voice to Aid Laryngeal Cancer Diagnosis
IRAS ID
314561
Contact name
James Moor
Contact email
Sponsor organisation
St James's University Hospital
Duration of Study in the UK
1 years, 0 months, 1 days
Research summary
Rationale: More than 2,000 people are diagnosed with laryngeal cancer in the UK each year. Current diagnostic pathways refer patients to secondary care to be seen within 14 days of referral (the 2 week wait pathway). However, most people that are referred to consultants on this pathway do not have cancer but another benign pathology, or no specific abnormality. Such referrals could be considered as consumptive of clinician's time, a waste of resources, and potentially leads patients enduring unnecessary invasive, uncomfortable procedures, and undue stress. Screening programmes exist for a number of cancer diagnoses but not for Head & Neck cancer. Development of a screening tool for laryngeal cancer may ease the load on NHS workforce and better serve patients. Furthermore, patients identified as ‘high risk’ from a screening programme could be prioritised for further investigation leading to earlier diagnosis, better treatment outcomes and higher survival rates.
One of the commonly used diagnostic techniques used by clinicians is listening to the patient speak and rating different audible components of the voice. This demonstrates the audible difference between a healthy and ill patient. In this case, then we might assume that machine learning may be able to detect such patients using voice recordings.
Objective: We aim to explore the feasibility of using an AI tool for the detection of laryngeal cancer using voice recordings to support clinicians in early diagnosis and screening of patients.
Study design: Feasibility study with semi-structured interviews
Study population: The study population will be drawn from adult patients referred on the 2 week wait pathway for suspected Head & Neck Cancer to the ENT Department at Leeds Teaching Hospital NHS Trust.
REC name
HSC REC B
REC reference
23/NI/0105
Date of REC Opinion
22 Aug 2023
REC opinion
Further Information Favourable Opinion