Advances in medical imaging technologies might suggest that the increased speed and automation of certain tasks have liberated the schedules of imaging professionals. For instance, an X-ray exam has evolved from requiring 25 minutes of exposure at the end of the 19th century to just a few seconds, or even less, today.

However, if you search for “radiologist” on PubMed, six of the first ten results address their increasingly complex roles, burnout, or even depression. Despite the time savings, the number of examinations has surged, and therapeutic follow-ups demand more imaging. The role of imaging is 1) preventive, with cancer screening campaigns for breast and lung cancer, 2) diagnostic, and 3) curative, with a rise in interventional radiology.

Examinations are becoming more complex to analyze, and the multitude of biomarkers associated with images makes the task exhaustive and extremely challenging, especially in emergency contexts. This is where AI plays a crucial role in supporting radiologists in their expanding duties.

It is essential to restore radiologists’ time with patients. The relentless pace to complete successive examinations leaves radiologists with less patient interaction time. Therefore, we must collaborate to provide automated tools, leveraging AI or other techniques, that relieve radiologists of repetitive, non-value-added tasks. Approximately 80% of imaging examinations are normal. A tool that could differentiate these cases from those requiring a radiologist’s attention would save significant time.

Globally, radiologists are also deeply involved in clinical research, indirectly contributing to the advancement of imaging techniques. This is particularly vital in the context of an aging population and the shift toward personalized/precision medicine and the development of information technologies.

In the future, I envision a successful radiology practice characterized by collaboration and communication with various specialists in a multidisciplinary approach; patient-centered care; dedicated time for research and continuous learning; as well as a balance between professional and personal life. Each of these areas will greatly benefit from the integration of AI and automation processes.

Written by Fayçal Djeridane, Olea Medical’s CEO

[1] Feldman A (1989). « A sketch of the technical history of radiology from 1896 to 1920 ». Radiographics. 9 (6): 1113–1128. doi:10.1148/radiographics.9.6.2685937.

[2] Ou X, et al. Recent Development in X-Ray Imaging Technology: Future and Challenges. Research (Wash D C). 2021. doi: 10.34133/2021/9892152