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How to Improve Access to Expertise in Cancer Imaging

Practical steps to improve situation in the context of changing landscape of cancer imaging
15 May 2019
Staging and Imaging

An article published on 3 May 2019 in the Journal of Clinical Oncology outlines practical steps to foster improved patient access to cancer imaging expertise. The paper is an outcome of a workshop hosted by the US National Cancer Policy Forum and tackles the subjects such as a need for improving education and training in cancer imaging, expanding access to expertise in cancer imaging, increasing integration and collaboration among specialties in cancer care, improving adoption use of clinical decision support, support innovation in cancer imaging, and improving data curation, integration, and sharing. 

In first part of the paper, the authors discuss the changing landscape of cancer imaging in the context of the risk for diagnostic errors. An accurate cancer diagnosis relies on imaging techniques and the integration of expert imaging interpretations with pathology and clinical findings. Radiologists have developed, and are continuously refining, more sophisticated methods to assess treatment response and toxicity. These methods and new imaging techniques require specialised training and experience. However, training opportunities are often lacking. 

Subspecialty radiologists participate in multidisciplinary cancer care teams and can provide more clinically relevant cancer imaging interpretations because they keep abreast of the latest developments in cancer biology and treatment, are well acquainted with the natural history of specific tumour types, and have ready access to the knowledge and expertise of multiple cancer specialists. 

In a part of paper on workforce and care delivery challenges, the authors wrote that radiologists with subspecialty expertise are in short supply in many locations with most subspecialty radiologists located in urban areas. Cancer imaging is not a formally recognised subspecialty in most countries. Subspecialisation in radiology is generally by organ or system, which does not ensure intensive training or expertise in cancer imaging. 

Expansion of dedicated cancer imaging fellowship programmes could help alleviate a shortage of subspecialised expertise, which is usually gained through fellowship training and/or by participation on multidisciplinary cancer care teams. Modern cancer imaging principles are not treated in depth in medical school or residency training, and few continuing medical education courses are dedicated to cancer imaging. 

As a result, most radiology practice models are not organised to deliver consistent, high-quality cancer imaging services. Optimal practice models could include either referral to tertiary subspecialty multidisciplinary tumour board groups or blended generalist/specialist staffing in large community practices with a formalised conduit to subspecialty second opinions. Telemedicine or telementoring, with continuous supervision, feedback, and coaching for all team members, could enable broad implementation of these models. 

In a part of paper on the increase of clinical decision support and standardised reporting, the authors wrote that radiology in general, and cancer imaging in particular, stands to benefit greatly from the application of machine learning and artificial intelligence. In addition, in recent years, there has been a major shift from narrative, free-style reports to structured image reporting. Although it is still in its infancy, synoptic reporting, involving use of discrete entry options and standardised lexicons with embedded learning modules, is expected to facilitate complete capture of necessary information in a standardised and structured format.

The authors conclude that in order to expand patient access to cancer imaging expertise, leaders in radiology and healthcare community will need to develop and implement strategies to enhance expertise in cancer imaging.

 

Reference

Nass SJ, Cogle CR, Brink JA et al. Improving Cancer Diagnosis and Care: Patient Access to Oncologic Imaging Expertise. Journal of Clinical Oncology; Published online before print 3 May, 2019. DOI: 10.1200/JCO.18.01970

Last update: 15 May 2019

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