How artificial intelligence supports early lung cancer diagnosis

Daniel Drieling, product manager at MeVis Medical Solutions, explains how technology can come to the rescue when diagnosing lung cancer on a global scale.

Despite being the number one cancer globally, across populations of men and women combined, lung cancer is notoriously challenging to spot early enough for positive treatment outcomes. Usually symptoms occur in late stages of the disease, when successful treatment becomes more and more difficult. Unlike various other types of cancer, such as breast cancer, which can be checked for in a number of different ways, lung cancer requires targeted medical imaging to determine what’s going on.

It is for this reason that governments internationally are increasingly launching strategic screening campaigns – such as NHS England’s mobile lung health checks, where portable CT scanners are being dispatched to areas of the country where rates of lung disease are higher than average. The thinking is that by looking out for the earliest signs of problems among at-risk groups (smokers, those working in potentially harmful environments, and so on), health services will save more lives, and reduce the significant long-term costs of trying to treat late-stage cancer.

Increased vigilance means increased workloads for radiologists

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. 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.

Development and training of algorithms

So it is 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 the most 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.

Boosting human capacity

Combined, human and machine are now detecting even the most difficult to spot signs of cancer – the signals that might otherwise have been overlooked, especially where radiologists are under increased time pressure. Importantly, the software has the potential to process heavy workloads at high speed too, allowing experienced radiologists to comfortably and reliably assess more cases per hour.

It isn’t only in the reading of baseline studies and complex follow-up comparisons that AI-based technology is leaving its mark, and lightening workloads. Our Veolity software automatically extracts lung nodules from medical images and provides comparable volumetric measurements that help to assess findings. It also makes short work of planning further patient treatment, by matching findings and established reporting guidelines including management recommendations.

For hard-pressed health services, and at-risk populations, use of AI-based detection techniques in mass-scale lung cancer screening is a win-win. Thanks to our implementation of Veolity directly for large OEM healthcare equipment providers, and via strategic distribution partnerships including that with SynApps Solutions in the UK, MeVis Medical Solutions AG is recognised to be the world’s leading specialist in image-based lung cancer screening solutions – with established deployments and continuously increasing enquiries worldwide. This illustrates the scale of the technology’s potential in making more of radiologists’ time, and improving outcomes for lung cancer patients.

As instances of cancer continue to rise, it is becoming increasingly essential that medical professionals are able to draw on every tool available to them, to keep ahead of symptoms and apply early treatment. Patient outcomes and healthcare budgets depend on it.


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