Feature article

How new technology can aid radiologists

Technology can impact multiple aspects of everyday life, both positively and negatively. This may be true in the case of under-staffed radiology departments who must adapt to new technology, even as they rush to scan and evaluate patients as accurately and quickly as possible. Different applications and smart devices could help radiologists increase efficiency and quality and possibly reduce the cost of scanning patients.

Mobile applications

Mobile apps are used on a daily basis by most Americans of all ages. Some people use games or entertainment apps for fun while others use organization apps to ease the stress in their daily lives. Similarly, radiologists have a number of apps to assist with their everyday work and communicating with patients.These apps have a variety of uses, like providing a way to read scans on the go for busy radiology departments, conferring with other radiology departments, and increasing patient comfort.

Radiologists are not always at their computers and sometimes need to inspect MRI exams as soon as possible. When needed, mobile apps allow them to assess an MRI on their tablets or phones.2 The average smart-device screen shows enough detail and quality to enable clinical decisions. This also helps doctors to be able to review the exam after the radiologist has completed their report. When radiologists want a second opinion, some apps enable them to post the images, without naming the patient, and receive feedback and support from others in the field.1 This is done through databases that store the studies for additional information. With this feature, the number of repeated scans could decrease, because multiple radiologists can look at and give their opinion on the study.

Another common usage for radiology apps is to inform and familiarize a patient of their upcoming exams. This is done through the use of virtual reality apps for both children and adults. Some apps allow kids up to the age of four to experience the procedure before they climb into the scanner, which may reduce the need for sedation.3 Preparing the kids helps to enable them to lay still during the exam. Adults who have claustrophobia or anxiety about being in an MRI machine have shown improvements with apps designed for them as well.4 One study showed a marked decrease in anxiety and need for sedation with the exposure to a virtual reality app that simulates the sights and sounds of an MRI machine. These virtual reality applications not only help to ease a child's or adult's fear but also could lessen the motion from the subject.

Smart devices and device applications

Meanwhile, smart devices are improving efficiency for radiologists by prioritizing patient needs and providing diagnostic support through quality image assessment. This has begun in some radiology departments through the use of deep learning on both new and old scanners.5,6,7 Some applications already exist for this, though more are being researched and may debut in the future. Manufacturers upload images of abnormalities to computers whose algorithms work to establish parameters for image assessment. Through the use of these algorithms, the computer can provide initial categorization to prioritize which scans need to be assessed first. Later, when the radiologist completes their initial review, the computer provides additional insights into what, if anything, has been flagged for further review. This helps to ensure accurate readings, possibly reducing the number of necessary repeat scans.

Device applications can be used to expedite and improve initial imaging. Acceleration software can result in up to a 40% reduction in the time.8 Certain cardiac software can help to correct for respiratory motion and complete the exam in under ten minutes.9 These scans can be done while maintaining good image quality, potentially allowing for more scanned patients throughout the course of a day. The more scans that are completed per day could lead to a lower cost per patient and perhaps better efficiency of the lab.

MR and many radiologists have embraced the need for technological advances through the use of mobile and scanner applications and smart devices. Applications have helped to assist radiologists in reading scans without being at their computer and get second opinions from experts. They have also helped to increase the comfort level and reduced the number of motion artifacts for each patient. Smart devices and devices that use advanced applications can now read scans alongside computers utilizing deep learning to generate more accurate reports. Additionally, these devices could perform faster scans and implement motion correction software without losing quality within an image. These advances have started to help make an impact on the medical community and will likely continue to do so as technology progresses.


1. Katherine Harmon. "Your MRI is calling: FDA approves first medical iPhone app." Scientific American. 7 February 2011. Web. 26 November 2018. <https://blogs.scientificamerican.com/observations/your-mri-is-calling-fda-approves-first-medical-iphone-app/>.

2. Robert Dostie. "Best radiology apps for 2018." Carestream.com. 12 December 2017. Web. 26 November 2018. <https://www.carestream.com/blog/2017/12/12/best-radiology-apps-2018/>.

3. Jonathan Ashmore. "MRI scans are horrible for kids - so I created a virtual reality app to help." The Guardian. 13 September 2018. Web. 26 November 2018. <https://www.theguardian.com/society/2018/sep/13/mri-scan-children-virtual-reality-app>.

4. Richard K.J. Brown, et al. "Virtual Reality Tool Simulates MRI Experience." Tomography. September 2018; 4(3): 95-98. Web. 26 November 2018. <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6173786/>.

5. Nicholas Bien. "Don't Just Scan This: Deep Learning Techniques for MRI." Standford AI for Healthcare. 7 February 2018. Web. 27 November 2018. <https://medium.com/stanford-ai-for-healthcare/dont-just-scan-this-deep-learning-techniques-for-mri-52610e9b7a85>.

6. Sarah Rubenoff. "How AI & Machine Intelligence is Assisting Clinicians." insideHPC.com. 27 July 2018. Web. 26 November 2018. <https://insidehpc.com/2018/07/ai-machine-intelligence-clinicians/>.

7. Muhammad Faisal Siddiqui, Ahmed Wasif Reza and Jeevan Kanesan. "An Automated and Intelligent Medical Decision Support System for Brain MRI Scan Classification." PLoS Online. 2015; 10(8). Web. 27 November 2018. <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4539225/>.

8. "Improve Quality and Reduce Scan Time with HyperSense." itnonline.com. 24 February 2017. Web. 27 November 2018. <https://www.itnonline.com/content/improve-quality-and-reduce-scan-time-hypersense>.

9. Clare Scott. "New MRI Scanning Technology from GE Healthcare Goes Beyond 3D: ViosWorks Produces Images of the Human Heart in Seven Dimensions." 3DPrint.com 4 December 2015. Web. 27 November 2018. <https://3dprint.com/109228/ge-healthcare-viosworks-7d/>.