The practice of radiology needs to change and it is important to continue the debate about the way forward. Marc Dewey, Vice Chair of Radiology at Charité – Universitätsmedizin Berlin, Germany, believes that value-based radiology will obtain a central role in addressing the present issues, with attention to three main areas of opportunity, as he stated during the Wilhelm Conrad Röntgen honorary lecture at ECR 2018.
First, the issue of too much imaging in the wrong patients could be overcome by better decisions about which individual patients, if any, should undergo an imaging procedure and when. This requires the integration of patient’s history into decision support modules such as for instance through the European Society of Radiology’s efforts iGUIDE and eGUIDE.
Second, the integration of artificial intelligence with human image analysis has great potential to increase consistency in radiological image analysis and reduce errors. Of greatest clinical value will be the bionic radiologist as a combined approach to leverage both the consistency of automatic analysis and individual nuances of human image analysis. “This will require a paradigm shift in how radiology is practiced: data science and artificial intelligence will be practically and physically integrated into the work flow of radiologists by seamless technology. The bionic radiologist will be a radiologist supervising the results generated by machine learning algorithms and integrating them with other clinical data for the final interpretationm,” Dewey said and compared it to the situation in the airplane cockpit where the autoflight system is used most of the time, but for the situations in which human interaction cannot be replaced one prefers to have a pilot on board.
Third, structured radiology reports provide a choice of pre-defined descriptions for instance of a mass or vascular abnormality for the many different types of imaging procedures, thereby maximising objectivity and reducing variability of prose text most often used in reports and enhancing the link between test results and treatment planning.
“Importantly and against general expectations that still persist, I strongly believe that for value-based radiology, we don’t need big data, we need good data.” Dewey thinks that success in the three areas of opportunity will free up the radiologist to be a more active participant in the nuances of patient care. “Those nuances – that automatic systems are not good at (yet) – can only emerge when radiologists spend more time talking to patients and other clinicians.”
Source: European Society of Radiology