Top Trends in Medical Imaging Technology

Understanding new developments and preparing for the future

internet of things

The enormity of changes in the field of medical imaging technology is hard to fathom. In an article on this topic, author James H. Thrall, M.D., chairman emeritus, Department of Radiology, at Massachusetts General Hospital, Boston, stated, “For the better part of 100 years, physics was the dominant scientific basis of radiology, and X-ray attenuation was the paramount measurable parameter.” And furthermore, today, “the richness of measurable parameters has taken medical imaging beyond organ anatomy and pathology into the realms of physiology, pharmacology and cellular and molecular biology,”[1] he explained.

The frenetic pace of change in healthcare today creates challenges of its own. Such challenges come in a myriad of forms, from new policies and legislation to novel use cases to new technology innovations. Yet, especially in technology innovation, several key trends are emerging in new modalities, mobile, the Internet of Things (IoT) and big data that hold the promise of significant positive impacts for radiology professionals.

 

Mobile and IoT

Mobile technology has made its way to healthcare. While many mobile healthcare applications exist, there are not many U.S. Food and Drug Administration (FDA)-approved medical imaging mobile applications. The majority of those that have been approved are used primarily for reference purposes.

In the medical imaging arena, many applications received 510(k) premarket notification from the FDA. Common-use cases include 3-D viewing, clinical collaboration and easy picture archiving and communication system (PACS) connectivity, which enables access to radiology reports and referral studies.

In contrast, the IoT has not yet been leveraged successfully in imaging. One potential area, however, is using the IoT to enhance the reading room experience for radiologists by controlling the screen brightness and contrast parameters, including the room lighting, based on the radiologist’s choices and reading protocols. Large imaging independent software vendors (ISVs) are investing in cloud-based IoT platforms which will eventually enable integration of their medical devices across the world. These platforms support integration with patient home monitoring, wellness planning, ambulatory and diagnostic workflows. IoT platforms are also helping complex imaging workstations to outsource their high intensive imaging algorithms to the cloud, and utilizing cloud-based applications to reduce the footprint on end-users’ devices. These platforms allow third-party software vendors or IT departments of healthcare organizations to customize and build their own IoT and analytics applications according to their needs.

Another technology trend that may emerge in the future is interconnectivity of medical imaging devices. These devices may be able to connect with one or multiple vendors and enable asset and fleet management, including finance-based operational analysis. Some of these integrations exist where device vendors are able to remotely perform preventive maintenance on their devices. The IoT has the capability to cater to multiple vendors and to undoubtedly become a trend in the future.

 

Big Data and Analytics Tools 

Big data analytics has gained prominence in the medical imaging arena in recent years for its critical contribution to the care continuum, along with other electronic health record (EHR) data in context. With the American College of Radiology’s (ACR) Imaging 3.0 initiative and the current focus on value-based healthcare delivery, analytics tools will go well beyond gathering operational metrics. From outcomes to reimbursements, protocols to patient experiences, the impact of data analytics will be far-reaching.

For example, analytics are extensively used to detect specific patterns identified with specific pathology. The imaging algorithms are capable of deriving metrics using intensive analysis of patterns in a given digital image, and output scores that complement the analyses made by the radiologist, which can be useful for quick diagnosis.

The future of analytics in diagnostic imaging data is promising. We can look forward to new and interesting features in the radiology information system (RIS) and PACS systems, especially those in the cloud, which might include analytics and impressive reports on operational and clinical data.

Enterprise-wide key performance indicators (KPIs) are derived from existing data sources inclusive of DICOM/HL7 transactions, log scraping, flat files, registries, database transactions, network parsing and configurations. These KPIs are customized to suit the needs of the provider, for clinical efficiency, operational efficiency, and overall patient comfort and care. They have been used for resource optimization since the start of the decade, but with the increased complexities of devices, and increased number of modalities, software systems and mobile devices, something as simple as time taken for a clinician to contact a technician on an average in a month could be easily measured and improved.

Read the article “Understanding How Big Data Will Change Healthcare.”

 

Trending Modalities

Mammography. Digital breast tomosynthesis (DBT), or 3-D mammography, is the exciting new standard in breast imaging due to its dramatic improvement in lesion visibility and in early cancer detection. With DBT, a series of images are generated along the breast instead of combining two projections of images. DBT enables radiologists to view each tissue layer independently, which reduces the number of errors as well as the number of recalls.[2] The combination of DBT with ultrasound and MRI enhances diagnostic accuracy even further. The push will continue as well to remove radiation from mammography, without compromising the information and image quality.

3-D Ultrasonic Holography. This technology gained traction this year and is anticipated to continue its growth in 2017. Because ultrasonic holography does not use dangerous radiation, it is ideal for preventive and post-operative examinations in breast cancer patients. The resolution of generated images is high in comparison to those of a normal ultrasound. In addition, the images are easily reproducible and allow automated computer-based data interpretation.

As we look ahead to 2017, exciting trends in medical imaging will continue as the impact of mobile applications, the IoT, big data analytics and new modalities continue to unfold.  itn

 

Dhaval Shah is senior vice president at CitiusTech. He has more than 16 years of experience in healthcare technology, spanning various domains including healthcare interoperability and enterprise application architecture. 

Prasanth Kollaikal is associate vice president at CitiusTech. He has more than 13 years of experience in the information technology industry, including a decade of experience in healthcare technology and consulting, primarily focused on provider and ISV segments.