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.

long covid lung CT

Some long COVID patients continue to display multi-organ damage one year after recovery

A new study utilizing multi-organ MRI scans recently identified organ impairment in 62% of COVID long haulers six months after their initial diagnosis; 29% of these individuals continued to display damage in at least one organ at the 12-month mark.

February 15, 2023

Radiomics can predict major cardiac events using CCTA images

A CCTA-based radiomics method was recently found to be more accurate in identifying potentially problematic plaques than conventional CCTA anatomical parameters alone.

February 15, 2023
Why is cloud computing is being adopted in radiology? Amy Thompson, a senior analyst at Signify Research, explains what she is seeing in radiology PACS and enterprise imaging system in the market in terms of cloud adoption. She said there has been rising interest in adopting cloud over the past few years, and the COVID pandemic showed amity healthcare systems the value of having a cloud-based system for easier remote access to patient data and imaging.

Cloud storage helps solve radiology IT and cybersecurity issues and is growing

Amy Thompson, a senior analyst at Signify Research, explains why radiology is rapidly adopting cloud data storage solutions.

 

February 13, 2023
Chest X-ray. Using an explainable artificial intelligence (AI) model, researchers were recently able to accomplish highly accurate labeling on large datasets of publicly available chest radiograph X-rays.. 

Natural language processing generates CXR captions comparable to those from radiologists

Recent developments in NLP technology have improved its ability to recognize semantics and context, making it more likely that NLP could generate coherent medical reports without radiologist assistance. 

February 10, 2023
Thyroid

Which risk stratification system is best for classifying thyroid nodules?

A new analysis compared the results of 39 published studies and nearly 50,000 patient cases to rank the performances of six different thyroid nodule stratification systems.

February 8, 2023

Amyloid plaque patterns on PET imaging predict Alzheimer's progression in asymptomatic patients

Experts involved in the new research suggest that identifying these spatiotemporal variations could play an important role in clinical research and precision medicine. 

February 8, 2023

6 tips for integrating NPPs into imaging practice

The role of non-physician practitioners will inevitably continue to grow in healthcare, but how will their presence impact radiology?  

February 6, 2023
An example of an FDA cleared radiology AI algorithm to automatically take a cardiac CT scan and identify, contour and quantify soft plaque in the coronary arteries. The Cleerly software then generates an automated report with images, measurements and a risk assessment for the patient. This type of quantification is too time consuming and complex for human readers to bother with, but AI assisted reports like this may become a new normal over the next decade. Example from Cleerly Imaging at SCCT 2022.

Legal considerations for artificial intelligence in radiology and cardiology

There are now more than 520 FDA-cleared AI algorithms and the majority are for radiology and cardiology, raising the question of who is liable if the AI gets something wrong.

February 3, 2023

Around the web

Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans. 

"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday. 

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