Enterprise Imaging

Enterprise imaging brings together all imaging exams, patient data and reports from across a healthcare system into one location to aid efficiency and economy of scale for data storage. This enables immediate access to images and reports any clinical user of the electronic medical record (EMR) across a healthcare system, regardless of location. Enterprise imaging (EI) systems replace the former system of using a variety of disparate, siloed picture archiving and communication systems (PACS), radiology information systems (RIS), and a variety of separate, dedicated workstations and logins to view or post-process different imaging modalities. Often these siloed systems cannot interoperate and cannot easily be connected. Web-based EI systems are becoming the standard across most healthcare systems to incorporate not only radiology, but also cardiology (CVIS), pathology and dozens of other departments to centralize all patient data into one cloud-based data storage and data management system.

Cardiology still No. 2 in FDA-cleared clinical AI algorithms, trailing only radiology
Cardiology continues to be one of the most influential healthcare specialties when it comes to utilizing artificial intelligence.
Eye-tracking reveals radiologists' reading habits when utilizing AI support
Rather than test artificial intelligence's ability to detect malignant lesions on imaging, researchers instead recently explored how it impacts radiologists' interpretation processes.
Most oncologists prefer cancer-specific structured radiology reports
Despite this, not all radiologists are on board with routinely using oncology templates.
'Technical issue' prevents providers from receiving alerts on actionable imaging findings for 3 years
The system uses color coded flags to alert general practitioners that a patient's imaging report contains "serious or unexpected” findings.
Generative AI model shows potential for reading chest X-rays used for TB screenings
Generative artificial intelligence models have shown great potential for improving multiple aspects of the radiology field, but a new analysis cautions that they still require significant oversight.

CDS-generated report cards help reduce imaging orders for lower back pain

Using clinical decision support (CDS) to send primary care providers (PCPs) personalized report cards evaluating their ordering decisions can reduce outpatient lumbar spine (LS) MRI orders for lower back pain (LBP), according to a new study published in the American Journal of Roentgenology.

Radiologists inconsistent with how they convey diagnostic certainty

Diagnostic certainty phrases (DCPs) are common in radiology reports, helping the radiologist convey certainty in an imaging finding or its clinical significance. According to a new study published in Academic Radiology, however, radiologists use a wide variety of DCPs, and reducing this variation could improve the overall quality of radiology reports.

Amazon releases AI language processing service for patient records, radiology reports

Tech company Amazon has launched a new medical language processing service that, by using artificial intelligence (AI), can extract data from patient records and reports to help healthcare professionals make better treatment decisions, address data privacy and decrease overall costs, according to a report published Nov. 28 by TechCrunch.

What radiologists should know about point-of-care photographs

Point-of-care photographs obtained at the same time as medical imaging studies can be helpful for radiology providers. According to a new perspective piece published in the American Journal of Roentgenology, however, specialists should still make sure they do their homework before using such photographs in their practice.

RSNA 2018: What to make of the increased hype surrounding AI in radiology

Radiologist Paul Chang, MD, medical director of enterprise imaging at the University of Chicago, began his presentation Tuesday, Nov. 27, at RSNA 2018 by saying radiologists were in need of a reality check when it comes to artificial intelligence (AI).

RSNA 2018: Researchers turn to AI to protect imaging equipment from cyberattacks

Medical imaging equipment is highly susceptible to cyberattacks, putting hospitals and imaging centers at a serious risk of losing functionality of those systems and even having data stolen by an outside entity. This concerning issue is the focus of two studies being presented at RSNA 2018 in Chicago.

Ambra Health and Google Cloud Collaborate to Advance Healthcare Research with Anonymized Medical Imaging Data

Ambra Health, makers of the leading cloud-based, medical image management suite, today announced a new collaboration with Google Cloud to advance healthcare research with anonymized medical imaging data.

Monthly reviews improve adverse event reporting in interventional radiology

Monthly conference compliance reviews could improve unprompted adverse event (AE) reporting among interventional radiologists, according to a Penn Medicine study published Nov. 20 in the Journal of the American College of Radiology.

Enterprise Imaging

Cardiology still No. 2 in FDA-cleared clinical AI algorithms, trailing only radiology

Eye-tracking reveals radiologists' reading habits when utilizing AI support

Most oncologists prefer cancer-specific structured radiology reports

'Technical issue' prevents providers from receiving alerts on actionable imaging findings for 3 years

Generative AI model shows potential for reading chest X-rays used for TB screenings