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.

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Lessons learned from 7 years of structured radiology reporting at 1 institution

The University Medical Center Mainz recently surveyed radiologists and referrers to gather feedback on the change. 

Brain imaging artificial intelligence is a primary area of concentration for AI because oif the critical nature of fast detection and treatment for patients. This is an example of the AI applications displayed by third-party advanced visualization vendor TeraRecon at RSNA 2022.

What is the ROI on AI adoption in radiology?

Radiology makes up the vast majority of FDA-cleared AI algorithms, but with minimal or no reimbursement, hospital administrators may ask whether AI’s value justifies its expense.

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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.

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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. 

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. 

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Stronger report wording, direct calls to referrers help boost outpatients’ follow-up imaging odds

Only 65% of patients actually receive recommended additional imaging in this setting, with a median turnaround time of 50 days, according to a new study.

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How one radiology department increased use of its alert system for critical imaging findings

Almost 10% of radiology reports contain such an alert and communication of them is crucial to keeping patients safe and avoiding malpractice lawsuits. 

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.