When I googled “Trends in Medical Radiography”, there was articles for days! Medical Radiography, a field in which x-rays are used to take images to confirm pathologies, is built on technological advances. Since the discovery of diagnostic x-rays in 1895 by Wilhelm Rontgen, technological advances have been exponential. Two trends that are headlining Medical Radiography are Artificial Intelligence and Global TeleRadiology.
Artificial Intelligence (AI)
The fear that AI would take over human jobs is not coming true as originally thought. What is being seen is that AI can augment the human radiologist’s work. Radiologists have interpersonal communication, quality assessment, and education, all traits lacking when AI works on its own. Though AI can work faster on its own, diagnostic results are better when teamed with a radiologist using the AI for a second look. AI algorithms provide increased diagnostic accuracy, using molecular markers not perceptible to the human eye. AI programs can take small amounts of data, usually a result of imaging parameters that reduces patient dose, and equate it to a sample size with large amounts of data. This therefore reduces a patient’s radiation dose and scan time without compromising the quality of the image. Programs that can detect disease earlier than before results in early intervention and better prognosis. In augmenting the work of a radiologist, AI helps reduce radiologist burnout in a field where resources are decreasing. AI can not only enhance image interpretive skills, but certain applications can also improve department workflow, finance management and process improvement. Currently, work is on creating ways to monitor the AI’s effectiveness and clinical value, as well as addressing any legal or ethical issues.
Academically, as AI is continually increasing, adapting and changing in usefulness, it will be difficult to keep our students current with the trends. What we teach in class may be outdated by the time they reach their clinical practicums. The goal will be to encourage adaptability and versatility that reaches their whole career, since the evolution of AI won’t be stopping anytime soon.
One far-reaching goal in Medical Imaging is to increase efficiency. Not only is time often money, but more importantly time is often life. Third world countries or remote areas often don’t have radiologists on site to report an image. Images have to be sent to trained radiologists elsewhere in the world. The time to transmit an image, without the loss of image quality is better than ever. Advances in information storage and conversion can sustain the quality of the images no matter how far or remote they need to be transmitted. Every second counts when faster diagnosis and treatment can lead to a better prognosis.
In the classroom, students should have experience working with “cloud” information storage. The work of a technologist to competently use this space is paramount to connecting images and patient information to radiologists. Free cloud spaces like Google Drive can easily be incorporated into activities in the classroom, and encouraged to students for personal use.
Photo credit: https://www.trackactive.co/artificial-intelligence-and-health/
ECPI University. (n.d). The biggest trends in Medical radiography. [web log comment]. Retrieved from https://www.ecpi.edu/blog/biggest-trends-medical-radiography-weve-seen-year
L Campbell. (2019, January 15). Top 3 diagnostic imaging trends for 2019. [web log comment]. Retrieved from https://www.carestream.com/blog/2019/01/15/top-3-diagnostic-imaging-trends-for-2019/
Palmer, W.J. (2019, January 8). 7 radiology trends that will define 2019. Retrieved from https://www.diagnosticimaging.com/di-executive/7-radiology-trends-will-define-2019
Palmer, W.J. (2018, October 4). Artificial intelligence in radiology: Friend or foe? Retrieved from https://www.diagnosticimaging.com/di-executive/artificial-intelligence-radiology-friend-or-foe