par John R. Fischer
, Senior Reporter | May 14, 2018
From the May 2018 issue of HealthCare Business News magazine
Last fall, radiologists from across the nation competed against one another for a chance to be recognized at the 2017 Radiological Society of North America conference in Chicago. Punching away at their keyboards night and day, their task was to create an algorithm to predict bone age via X-ray.
Competitions like this are becoming increasingly common as radiology stakeholders put vast amounts of time, money and labor into exploring the seemingly endless frontiers for enhancing imaging through software analytics. Ultimately, the common goal is to extract, analyze and integrate information from images into everyday practice, raising the bar on quality and timeliness of care through technology.
This emerging discipline, called imaging informatics, extends beyond interpreting scans to encompass all aspects of imaging workflow, and has been germinating ever since film transitioned to digital. Today, the expectations for imaging informatics to transform radiology are greater than ever before.
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“It’s going to have applications throughout the delivery of the imaging services to patients and communication to clinicians,” Kevin McEnery, director of innovation imaging informatics at the University of Texas MD Anderson Cancer Center, told HCB News. “Over time, you’ll see applications of machine learning and other statistical-based processes to better understand patients. I think you’ll see examples of retrieving information for radiologists, informing decision support, and helping the radiologist to essentially prioritize work lists.”
McEnery, along with other experts, notes that with such innovations on the horizon, now is the time for providers, vendors and other health care players to look over, assess and redefine their own roles in order to effectively implement and nurture these capabilities when they arrive in their practices, enhancing workflow and subsequently, patient care.
‘Synthesizers of information’
The idea of using AI to interpret images and assist in diagnosis is getting closer to becoming a reality, and one specific area where software developers are already finding promise is in deciphering the genomics of a tumor.
“That sort of thing was almost unthinkable just a handful of years ago and now we have a very high accuracy for that tool," said Bradley Erickson, associate chair in the department of radiology at Mayo Clinic. "I think that really expands the value of imaging that’s being done today and increases the amount of information we can collect.”