Lung cancer care in the covid-19 aftermath

How AI can support radiology teams

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Healthcare practitioners continue to deserve our applause for their immense dedication to taking care of covid-19 patients over the last months. As many countries are establishing a new ‘normal’, in which the virus is present but fairly under control, we have the headspace to reflect on the impact of the pandemic and prepare for future challenges.

In early June, we attended the British Institute of Radiology (BIR) virtual event on covid-19 imaging. Aidence’s Lizzie Barclay and Jeroen van Duffelen joined a great lineup of speakers who shared lessons learnt from dealing with the disease and perspectives on post-pandemic developments. In the context of amplified challenges, we showed how AI can support radiologists dealing with the post-covid lung cancer workload. (You can view the complete talk here.)

Covid-19 and the lung cancer pathways

The coronavirus disease has brought dramatic changes to all healthcare pathways. The general response from medical institutions has been increasing the capacity for covid-19 and emergency patients. This goes hand-in-hand with reducing capacity for routine healthcare practice. Patients themselves have also been avoiding seeking medical advice or presenting late. As a result, the impact on non-communicable diseases, such as cardiovascular disease, diabetes, and cancer, appears to be significant; time and research will show just how significant.

In lung cancer care, covid-19 has led to a reduction in all pathways leading to diagnosis. Surgeries and treatments have been postponed. Lung cancer screening, in particular, is on hold or has stopped completely; thousands of early lung cancers are thus ‘missed’, and patients are expected to present at a later, probably less treatable stage. Patients’ fears of going to a hospital due to the perceived presence of infection, as well as the economic impact of unemployment or insurance loss, are further obstacles to cancer screening. In the UK, as an example, an estimated two million people are waiting for cancer screening and treatment.

Overall, the impact will most likely be a poorer survival prognosis for patients at risk or diagnosed with the disease. At the BIR event, professor Muntzer Mughal, Clinical Lead for the North Central and East London Cancer Alliance, showed a model of additional demand for lung cancer-related activity going well into 2021. Lung cancer care post-covid may just be a ‘crisis after the crisis’.

From normalization to acceleration

Besides the patient impact, we must consider the strain on the medical staff. Covid-19 cases are still being reported, yet not at peak levels, a trend that will hopefully be maintained. Radiology teams are gradually returning to ‘normal’ practice – one with the added precautions of equipment cleaning and social distancing to minimize further infections.

In the medium-term, radiology departments will have to catch up on non-urgent scans. The volume of work will most likely create new time pressures or stress for radiologists. In some countries, normalisation efforts will further face a shortfall of modalities (such as the UK’s relatively low number of scanners per capita).

For the future, we foresee an ‘acceleration’ phase. Once normalisation has resumed, healthcare systems will want to make changes that had been in place before covid-19. Lung cancer screening, for instance, will likely ramp up. The NHSE Long Term Plan for lung health checks set a target to diagnose 75% (vs. the current 50%) of all cancers at an early stage (1 or 2) by 2028, so there might be a push to meet these targets. Throughout these developments, healthcare systems will also maintain a reserve capacity to cope with possible next covid waves.

Healthcare practitioners who have been under pressure since the onset of the pandemic may, therefore, be asked to deal with an increased workload post-covid, testing their resilience and own health.

AI in the new ‘normal’

The above considerations, as well as the many gaps covid-19 has highlighted within healthcare systems, account for extra demand to bring in technology that can improve these systems. Artificial intelligence (AI) presents opportunities to augment healthcare by taking on some of the time-consuming tasks from human hands. Doing so, it contributes to economic benefits and better patient care. Initiatives such as the NHSX AI lab are recognising this potential.

Following numerous discussions we held with medical institutions and radiologists over the past months, we see several roles for AI in the post-covid lung cancer pathway:

Routine practice

  • AI systems are well-equipped to spot subtle patterns on medical images. Having a second pair of eyes when analysing chest CTs can support incidental nodule detection, thus picking up early lung cancers. .
  • Nodule volumetric measurements with AI can speed up decision-making by automatically providing insight into nodule growth rates.
  • AI-driven productivity increase would allow radiology teams to stay on top of reporting of the non-urgent scans, within the turnaround time targets.


  • AI features can  maximise efficiency in processing screening scans. For example, Veye Reporting supports radiologists with the detailed reporting protocol. For a more in-depth look at AI for lung cancer screening, read Lizzie Barclay’s recent article.

Within all use cases, AI can and should facilitate remote working patterns. One of the takeaways from the covid-19 crisis is that remote radiology allows for effective reporting while maintaining social distance; giving radiologists the option to work from home post-covid would increase flexibility in their workday. For AI solutions not to block remote work, they must fully integrate with the radiology workflow and system. It is why, now more than ever, AI medical imaging solutions should be agnostic to PACS.

The reset button

The British Institute of Radiology referred to covid19 as the ‘reset button’ for radiology. The question is: how can radiology emerge even stronger post-covid-19? It is important to seize the current moment and prepare for the expected post-covid scan volumes and requirements. Leveraging the power of technology is one of the opportunities to do things differently in what will be a different order of things.


About Catalina

Catalina Barzescu is Content Manager at AidenceAfter graduating from the Erasmus University Rotterdam with a master’s degree in media and journalism, she made her way to MedTech via e-learning, travel, and humanitarian aid. Her interests are storytelling and data science with a purpose. The articles she signs reflect the work and ideas of the various teams at Aidence – medical, tech, regulatory, and business.

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