Imaging Informatics

Imaging informatics (also known as radiology informatics, a component of wider medical or healthcare informatics) includes systems to transfer images and radiology data between radiologists, referring physicians, patients and the entire enterprise. This includes picture archiving and communication systems (PACS), wider enterprise image systems, radiology information. systems (RIS), connections to share data with the electronic medical record (EMR), and software to enable advanced visualization, reporting, artificial intelligence (AI) applications, analytics, exam ordering, clinical decision support, dictation, and remote image sharing and viewing systems.

Hands-free, generative AI system reduces radiologists' time spent creating reports
"Application of these technologies represents potential areas to combat burnout," researchers wrote recently in the Journal of the American College of Radiology.
Radiomics-based tool predicts fracture risk in COPD patients
Such technology can be leveraged to improve risk assessments without accruing additional expenses for patients or clinicians, potentially filling in gaps where DXA exams fall short.
Many radiology PowerPoints inadvertently put private health information at risk
Many of these files are still readily available online, and numerous contain PHI that is “easily accessible,” a new analysis reveals.
Incidental finding characteristics that warrant communication
Three factors are associated with true high-risk findings—imaging protocols for aortic valve implantation planning, imaging area, and cardiology department orders.
GPT-4 as accurate as neurologists in predicting final diagnosis based on MRI reports
The large language model can also outperform other human providers, radiologists included, new study shows.

MRI radiomics could change the future of breast cancer treatment

Radiomics methodologies could change how care plans are managed for patients with breast cancer by identifying those most likely to benefit from specific treatments.

October 19, 2022

University of Rochester Medical Center in the US selects Sectra Enterprise Imaging in the cloud

Linköping, Sweden and Shelton, CT – October 17, 2022– International medical imaging IT and cybersecurity company Sectra (STO: SECT B) will provide enterprise imaging as a cloud subscription service (Sectra One Cloud), throughout the University of Rochester Medical Center (URMC). This will allow the US health system scalability as enterprise imaging volumes grow, in a secure and fully managed cloud environment.

October 19, 2022

An example of commercially available artificial intelligence (AI) automated grading of breast density on mammograms from the vendor Densitas..

VIDEO: Role of AI in breast imaging with radiomics, detection of breast density and lesions

Connie Lehman, MD, chief of breast imaging, co-director of the Avon Comprehensive Breast Evaluation Center at Massachusetts General Hospital, discusses how artificial intelligence (AI) is being implemented in breast imaging.

October 18, 2022

Total body PET/CT scans may offer benefits for evaluating arthritis

Low-dose scans showed high agreement with joint-by-joint rheumatological evaluations.

October 17, 2022

Brain imaging scans unlock mysteries about depression and resilience

The new findings may contain important implications for neuromodulation therapies to treat depression symptoms.

October 17, 2022

VIDEO: KLAS shares trends in enterprise imaging and AI

Monique Rasband, vice president of imaging, cardiology and oncology, KLAS Research, explains some of technology trends KLAS researchers have found in enterprise imaging system and radiology artificial intelligence (AI).

October 13, 2022

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.

October 12, 2022

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.

October 11, 2022

Imaging Informatics

Hands-free, generative AI system reduces radiologists' time spent creating reports

Radiomics-based tool predicts fracture risk in COPD patients

Many radiology PowerPoints inadvertently put private health information at risk

Incidental finding characteristics that warrant communication

GPT-4 as accurate as neurologists in predicting final diagnosis based on MRI reports