RADIOLOGY & IMAGING
were diagnosed at stage one and 11% were stage four.
The Manchester scheme also picked up a range of other heart and lung conditions, including Chronic Obstructive Pulmonary Disease (COPD). Four in five cancers were in the early stages (stage one and two), with one in five people having a previously undiagnosed lung condition and nine out of 10 at high risk of developing cardiovascular disease. The new projects will last initially for four years and NHS England will then evaluate the results to use as a basis for further roll out. Areas to receive funding will be: l North East and Cumbria Cancer Alliance – Newcastle Gateshead CCG
l Greater Manchester Cancer Alliance – Tameside and Glossop CCG
l Cheshire and Merseyside Cancer Alliance – Knowsley CCG and Halton CCG
l Lancashire and South Cumbria Cancer Alliance – Blackburn with Darwen CCG and Blackpool CCG
l West Yorkshire Cancer Alliance – North Kirklees CCG
l South Yorkshire Cancer Alliance – Doncaster CCG
l Humber, Coast and Vale Cancer Alliance – Hull CCG
l East of England Cancer Alliance – Thurrock CCG and Luton CCG
l East Midlands Cancer Alliance – Corby CCG and Mansfield and Ashfield CCG
l Wessex Cancer Alliance – Southampton CCG
Most, but not all schemes will use mobile scanning units, this will be dependent on local need – one scheme currently piloting in Liverpool targets clinics in various areas of the city and, where needed, patients are
London’s first mobile unit opened at the end of last year, and is currently moving between supermarket car parks. Over 7,000 Londoners expected to be invited for a lung health check-up through the scheme.
referred to hospital for a scan. Over two years they have they have found and treated more than 40 new cases of lung cancer, with over 75% at an early stage of the disease, when typically 70% of lung cancer cases are not diagnosed until a late stage in Liverpool, when treatment is more difficult. London’s first mobile unit opened at the end of last year, and is currently moving between supermarket car parks. Over 7,000 Londoners expected to be invited for a lung health check-up through the scheme. The potential flaw in this plan is that qualified radiologists are not an abundant resource and, as more images are taken, their workloads will soar.
Smarter imaging
Supported by standard, static imaging solutions, even the most experienced radiologists can take up to 10 minutes (or longer) to read a patient’s lung scans in sufficient detail to be able to inform next steps. As screening programmes intensify, radiologists’ capacity will be a challenge. It is all very well screening more patients proactively, but if this leaves radiologists with a backlog of images to read, there are likely to be processing bottlenecks which ultimately could delay interventions.
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Development and training of algorithms
It is therefore encouraging - and very timely - that artificial intelligence is now sufficiently mature and robust to offer a solution. It’s a technology we’ve been working within a range of cancer detection solutions; since 2014 we’ve been applying AI and machine learning to reading lung images. By showing our software Veolity all sorts of cancer-based images, even the most subtle early signs, we have trained our computer-aided detection algorithm to spot suspicious structures which even expertly-trained eye might miss – those which could indeed be cancer. Developed using machine-learning techniques, Veolity’s algorithm aim is to recognise potential signs of lung cancer, to the point that it now offers an indispensable and highly stable diagnostic support tool. Combining this technology with radiologists’ own readings has been seen to produce the best detection rates ever known - an impressive improvement compared to human-based readings alone, according to clinical studies of computer- aided detection success rates. This is crucial: radiologists retain complete control of their diagnostic process, but can benefit from support of valuable automatic features.
NOVEMBER 2019
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