Mobile notifications alert radiologists and emergency care clinicians as soon as a head CT scan with a critical abnormality has been detected. Working closely with the scanning modality and PACS, the tool picks up scans as soon as they are completed.
A worklist notification, coupled with non-diagnostic preview images sent to treating physicians’ mobile phones helps ensure that critical scans are reviewed as soon as possible.
This enables streamlining of the head CT scan interpretation workflow by automating the initial screening and triage process, thus decreasing the time to diagnosis and expediting treatment. The preview images are also useful in centres where 24-hour onsite radiology coverage is not available. A comprehensive de-identification system ensures that Protected Health Information is not transmitted when sending non-diagnostic images through the app.
Mobile notifications are not available in the United States and Europe.
Radiology worklists can prove complex to manage, especially in tele-radiology settings or imaging centers with high scan volume. ‘STAT’ designations coded at the time of ordering the CT scan don’t always reflect the degree of severity of the abnormality on the image.
The qER triage and worklist prioritization tool helps meet stroke and trauma reporting standards and maintain consistent turn-around times for critical abnormalities. The tool works by assigning an ‘AI-stat’ designation or a red dot indicator to head CT scans with acute bleeds, infarcts, mass effect or midline shift. The list can then be sorted using this designation. A brief description of the abnormality(‘ICH’, or ‘fracture’) is also displayed on the list to enable quick selection of the next scan to read.
AI algorithms detect most head CT findings and presents them to as a pre-read for confirmation. This shortens read time and helps prevent clinicians from missing subtle abnormalities. The tool generates a full text report that is used to pre-populate the radiology reporting template, saving dictation time. The report includes the name and nature of at the abnormality detected, as well as its anatomical location within the brain, severity and extent.
qER quantifies the volume of intracranial bleeds, infarcts and brain ventricles at a level of precision that is surpasses radiologists.
While semiautomated methods, supervised quantification are time-consuming, qER accomplishes fully automated abnormality segmentation(outlining) and quantification. This capability is used by clinicians to track the progress of patients with traumatic brain injury, infarcts and hydrocephalus and by researchers to develop new quantitative outcome measures of brain pathology.