May 31, 2019 — Intelerad Medical Systems announced a $75 million investment in research and development (R&D) to expand its solutions portfolio, with an emphasis on cloud technology and artificial intelligence (AI) solutions.

It is not surprising that pressure is mounting for medical providers to improve the care outcomes of their patients. Also unsurprising is that these same providers are being pressured to do so while keeping a lid on expenses.

This juxtaposition marks a time of enormous opportunity for both the providers of healthcare and the vendors of healthcare equipment. But this opportunity only can be realized if vendors partner with providers to provide operational support in the crucial phase of transformation that we are now in.

62-year-old female patient presenting for 3D screening mammogram. Location of an indeterminate low-density circumscribed mass was not clearly determined as at the skin line or just under the surface.
Upon call-back, circular mole markers were used to mark all moles on the breast, immediately identifying the suspicious finding as a skin mole.
42-year-old female patient presenting a yearly routine screening mammogram in 3D. Right CC shows an opacity in the anterior aspect of the breast in the retroareolar area.
Upon call-back, a pellet marker was placed on the nipple and nipple in profile view was taken, confirming opacity seen on the prior 3D mammogram was the nipple superimposed over the anterior aspect of the breast.
Olive Peart

In recent years there has been a lot of debate about the role of the mammographer with regard to examining the patient’s breast. There are in fact two types of breast examination — the clinical breast examination (CBE) and the breast self-examination (BSE).
At ACC 2019, Siemens unveiled a version of its go.Top CT optimized for cardiovascular imaging. The newly packaged scanner can generate data needed to do CT-based FFR (fractional flow reserve).
SyncVision iFR Co-registration from Philips Healthcare maps pressure readings onto the angiogram

The fingerprints of value-added medicine were all over products and works-in-progress on the exhibit floor of the annual meeting of the American College of Cardiology (ACC).
Arjen Radder

Change is a consistent theme in our world today, no matter where you look. In healthcare, change — while slower than other industries — is happening in almost every direction. We’re seeing patient and imaging volumes growing exponentially, telehealth expanding access to care, the patient experience becoming increasingly consumer-driven and more data per clinical image than ever before. At the same time however, healthcare is shifting toward a value-based care model, and there is some speculation and confusion on how it will actually improve outcomes and control costs.
Einstein Healthcare Network found that use of automated power injectors reduced CT contrast extravasation rates over a 30-month period.

As of 2015, approximately 79 million computed tomography (CT) scans were performed each year in the U.S. Of those, 36 million, or nearly half, utilize contrast media, according to Ryan K. Lee, M.D., MBA, MRMD, magnetic resonance medical director, director of quality and section chief of neuroradiology for Einstein Healthcare Network in Pennsylvania. This is part of a growing trend in the U.S., where in 2016 there were 245 CT scans performed per 1,000 population.

In this study, the client was a large enterprise health system serving 1.4 million patients across the United States with over 11 hospital locations, over 6,000 in bed capacity and over 50 satellite clinics. They processed over 1.5 million studies annually and used various picture archiving and communication systems (PACS) across the organization.

iCAD’s ProFound AI is one example of artificial intelligence used to improve detection of anomalies in radiological images. The software identifies breast lesions and assigns a score representing its confidence the lesion is malignant.
The Lesion Certainty of Finding score is 100 percent. Above, the score is 99 percent.

Much has been made in recent years about the explosion of artificial intelligence (AI) in radiology and how it might impact the role of radiologists themselves. But artificial intelligence is, by definition, artificial. In an itnTV video from the 2018 Radiological Society of North America (RSNA) annual meeting, ITN Contributing Editor Greg Freiherr explored how AI cannot take the place of people, but it can help people get what they need.
Larry Sitka
Jef Williams

Medical imaging and informatics are critical to delivering care and managing wellness. Imaging was an early adopter of technology in healthcare. Decades before the ubiquity of electronic health records (EHR), imaging (radiology specifically) had moved away from analog processes (the lightbox and film) to a digital healthcare footprint. But serving as early adopters of digital health came with an upside and a downside.
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