The world of radiology and medical imaging is always changing. It’s important to stay on top of the latest advancements and trends in medical imaging.
From a better patient experience to producing accurate results with the help of artificial intelligence, here are 5 trends to keep an eye on.
Improving Patient And Referring Physician Experiences
In 2018, the IMV Medical Information Division surveyed U.S. hospitals, labs, and clinics that perform CT procedures.1
403 CT sites were surveyed and asked about their main priorities for 2019 and beyond.
Departments indicated that their top two priorities are to improve the experience for both the referring physician and the patient.
For referring physicians, this means ensuring the CT department can satisfy their needs to the best of their ability.
On the patient side, CT departments want to increase their capabilities to reduce radiation doses to patients and improve their overall experience.
Other priorities include obtaining accreditation for non-hospitals, improving workflow and productivity while effectively managing increased CT procedure volumes.
Radiologists Will Work with Artificial Intelligence
Radiologists have been following the advancements in artificial intelligence for years. The latest research indicates that the best outcomes occur when Radiologists work closely with the advancements that AI provides in medical imaging.
A group of Korean researchers compared the performance of deep learning-based automatic detection (DLAD) algorithms versus radiologists when examining malignant pulmonary nodules on chest radiographs.
While the DLAD had an initial higher detection success rate, the best results occurred when radiologists examined the images first and used the DLAD as a secondary resource.
This is great news for radiologists, referring physicians and patients as the faster an abnormality is detected, the sooner treatment can begin.2
Speeding Up the Medical Imaging Process
It’s no secret that big data is playing a part in the evolution of medical technology, especially when it comes to radiology.
What may be a surprise is some of the major tech companies who excel in big data are also getting involved in medical imaging.
In August 2018, Facebook and the New York University School of Medicine announced their partnership to use AI to speed up the amount of time it takes to conduct MRI scans by up to 10x.3
It currently takes the machines anywhere from 15 minutes to an hour to complete a scan. This length of time can be difficult for young patients and those who suffer from claustrophobia or those who have difficulty lying down.
The increased speed will also make MRI scanners more accessible to rural areas and in other countries with limited access, where long scheduling backlogs are problematic.
Streamlining the Workflow
Perhaps one of the most pressing issues in radiology today is improving the workflow that must occur for a patient to get a CT scan and what happens with the imaging afterward.
According to a 2016 article in Diagnostic Imaging, some radiologists spend “as much as 35% of their day trying to figure out what test they should read next.”4
Hospitals, healthcare equipment, and software manufacturers are working to resolve the inefficiencies with standardization in naming schemas, patient information access, and structured reporting.5
Improving the Patient Experience
Speaking of MEG equipment, a research team in the United Kingdom has developed a MEG scanning system with better detection abilities as well as provide a much easier, and create a more positive experience for the patient.6
This is extremely good news for all patients, especially young children and those who are unable to use traditional fixed scanners, such as those with Parkinson's disease.
Current MEG equipment is heavy due to the sensors used to measure brain activity and requires bulky equipment to help them cool down. Additionally, traditional fixed scanners require patients to lay as still as possible while being scanned.
The new wearable brain scanner has been designed to eliminate the possibility for patient claustrophobia and allows the patient to function normally while it scans.
Overall Improved Experience
All of these medical imaging trends have the same goal: to improve the experience for everyone involved.
- 2018 CT Market Outlook Report. IMV Medical Information Division. November 2018. (Accessed February 19, 2019).
- Nam, Ju Gang, Park, Sunggyun, et al. “Development and Validation of Deep Learning-based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs.” Radiological Society of North America. September 25, 2018. (Accessed February 24, 2019). Available online: https://pubs.rsna.org/doi/abs/10.1148/radiol.2018180237. (Accessed February 19, 2019).
- Shead, Sam. “Facebook Aims To Make MRI Scans 10x Faster”. Forbes.com. August 20, 2018. (Accessed February 23, 2019). Available online: https://www.forbes.com/sites/samshead/2018/08/20/facebook-aims-to-make-mri-scans-10x-faster-with-nyu/#6c1b716e7a04. (Accessed February 19, 2019).
- Haar, Liza. “Clinical Efficiency in Radiology.” Diagnostic Imaging. April 28, 2016. Available online: https://www.diagnosticimaging.com/practice-management/clinical-efficiency-radiology. (Accessed February 19, 2019).
- “Tips to improve efficiency in radiology departments with radiology informatics.” Applied Radiology. September 4, 2017. Available online: https://appliedradiology.com/articles/tips-to-improve-efficiency-in-radiology-departments-with-radiology-informatics. (Accessed February 19, 2019).
- Grey, Colm. “Scientists unveil 3D-printed brain scanner you can wear playing ping pong.” Silicon Republic. March 22, 2018. (Accessed February 11, 2019). Available online: https://www.siliconrepublic.com/machines/3d-printed-wearable-brain-scanner. (Accessed February 19, 2019).