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.

Charles E. Kahn, Jr., MD, MS, Editor of the the journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine. He has been heavily involved in radiology informatics and has seen up close the evolution of radiology toward deeper integration with AI. #RSNA

VIDEO: Use cases and implementation strategies for radiology artificial intelligence

Charles Kahn, Jr., MD, editor of the the journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine, explains the work involved integrating AI in radiology systems and the role of AI in augmenting patient care.

VIDEO: Assessing radiology AI and understanding programatic bias

Charles E. Kahn, Jr., MD, MS, editor of the the RSNA journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine, discusses the need to validate AI algorithms with your own patient population data.

Google Cloud intros ambitious branch dedicated to medical imaging

A Big Four tech company has launched a platform it hopes will accelerate data interoperability and AI adoption in, specifically, medical imaging.

Cardiovascular information systems (CVIS) combine imaging and reporting into one system that allows access across the cardiovascular service line. Here are 7 trends in CVIS according to KLAS.

VIDEO: 7 trends in cardiovascular information systems seen by KLAS

Monique Rasband, vice president of imaging, cardiology and oncology, KLAS Research, explains a few of the key technology trends in cardiovascular information systems (CVIS).

Transplanted lungs react to COVID in a distinctive way

Clinicians treating COVID-19 patients who have transplanted lungs and lower airway infection should order molecular testing in addition to, or regardless of, imaging findings.

Specialty-specific workflow training could increase radiologist satisfaction with EHRs

Clinicians who receive specialty-specific workflow training are 24 times more likely to agree that the EHR meets their functionality needs, according to a new KLAS report.

Monique Rasband from KLAS Research shares trends in PACS and radiology informatics.

VIDEO: 6 key trends in PACS and radiology informatics observed by KLAS

Monique Rasband, vice president of imaging, cardiology and oncology, KLAS Research, shares some of technology trends observed in radiology PACS and and imaging informatics since 2019.

For monitoring purposes, AI-aided MRI does what liver biopsy does with less risk, lower cost

Patients with autoimmune hepatitis may be better monitored across disease stages by AI-augmented multiparametric MRI than by liver biopsy, as the imaging has proven less costly and is inherently less risky due to its noninvasiveness.

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