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.

Natural language processing spots reporting gaps, racial bias
Finding such discrepancies is critical to the continuity of patient care, as medical records and reports are often utilized across multiple providers and facilities.
Lung disease reporting system improves consistency—so why is it underutilized?
ILD-RADS was developed to address issues with inconsistency when reading high-resolution CT scans of the lungs in patients with a suspected interstitial lung disease.
ChatGPT both passes and fails at translating free-text into structured reports
While the latest ChatGPT models show promise in easing the reporting burden on radiologists in the future, they aren't up to the task just yet.
GPT-4 spots radiology report errors in less time, at a lower cost
The large language model can identify report errors seven times more quickly than human readers, new study reveals.
Google teams with Bayer to address radiologist burnout via AI
"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday.

Example of the four types of breast tissue density. The density of fibroglandular tissue inside the breast impacts the ability to easily see cancers. Cancers are very easy to spot in fatty breasts, but are almost impossible to find in extremely dense breasts. These examples show craniocaudal mammogram findings characterized as almost entirely fatty (far left), scattered areas of fibroglandular density (second from left), heterogeneously dense (second from right), and extremely dense (far right). RSNA

Experts developed a deep learning model that can estimate breast density

When tested, the model achieved a performance comparable to that of human experts.

April 10, 2023

pulmonary embolism on CT pulmonary angiography

AI work list prioritization tool significantly decreases PE turnaround times

The FDA-approved tool works by reprioritizing CTPA exams to the top of a radiologist’s work list when the scan is positive for PE.

April 5, 2023

Follow-up adherence affected by how and when imaging orders are placed

These are factors that healthcare systems can and should control, experts recently suggested in a new JACR paper.

April 5, 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..

Radiologists develop point-of-care AI for chest X-rays

Radiologists used an AI tool-building platform to create their model(s), which allows clinicians the opportunity to develop AI models without any prior training in data sciences or computer programming.

April 3, 2023

Structured reports with a 'forcing function' for recommendations improve follow-up adherence

In a study that included hundreds of radiologist recommendations for additional imaging, there was a threefold increase in follow-up adherence when radiologists utilized a voluntary closed-loop communication tool that required structured recommendations.

March 31, 2023

'Quite impressive': ChatGPT generates a nuclear medicine report

The generated report included indication, findings laid out numerically, TNM stage, impression and follow-up recommendations.

March 27, 2023

Example of natural language processing converting the radiologist's dictation into text. This system from M-Model highlighted key words the artificial intelligence will use text in the report and for labeling the report file for later key word searches or data mining.

How NLP can 'revolutionize' structured reporting

The continued emergence of natural language processing has caught the eye of experts in the field, with some suggesting its use could streamline the process of integrating structured reporting across the specialty.

March 20, 2023

Traditional methods continue to outperform AI in some orthopedic scenarios

A new meta-analysis suggests that when it comes to hip fractures, AI algorithms do not always live up to their hype.

March 17, 2023

Around the web

Cardiovascular Business

AI improves CT assessments, boosts care for real-world heart patients

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.

Cardiovascular Business

AI predicts cardiovascular risk during CT scans—no invasive tests or contrast required

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

Radiology Business

Google teams with Bayer to address radiologist burnout via AI

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