qER-Quant
Qure.ai TechnologiesqER-Quant is an AI-powered software that processes non-contrast head CT scans to automatically identify and quantify key brain structures such as intracranial hyperdensities, lateral ventricles, and midline shift. It helps clinicians by providing volumetric data and visual overlays to aid in diagnosis and monitoring brain conditions over time.
Intended Use
The qER-Quant device is intended for automatic labeling, visualization and quantification of segmentable brain structures from a set of Non-Contrast head CT (NCCT) images. It automates identifying, labeling and quantifying the volume of segmentable brain structures identified on NCCT images and provides a comparative analysis for images acquired at multiple time points. It is indicated for use in the analysis of Intracranial Hyperdensities, Lateral Ventricles and Midline Shift.
Technology
qER-Quant is a standalone software that processes non-contrast head CT scans using a set of pre-trained convolutional neural networks (CNNs) for segmentation. It includes pre-processing to prepare DICOM images and post-processing to generate visual and tabular output. The software interacts with PACS to receive images and return results, outputting both PDF reports and labeled DICOM overlays.
Performance
Performance testing involved evaluating volume and shift measurement accuracy of target structures against manually labeled expert ground truth on a set of head CT scans. Accuracy was quantified using absolute error and Dice scores for intracranial hyperdensities (mean Dice 0.75), midline shift, and lateral ventricles (Dice ~0.75-0.79). Reproducibility testing using 20% of scans showed performance exceeded preset acceptance criteria. The software also passed system verification and validation checks.
Predicate Devices
No predicate devices specified
Device Timeline
- 1
Submission
4/23/2021
3 months - 2
FDA Approval
7/30/2021
Other devices from Qure.ai Technologies
- qCT LN Quant2024 • 510K
- qXR-LN2023 • 510K
- qXR-CTR2023 • 510K
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