Automated Image Analysis in Routine Radiology Workflow

Bringing quantitative MRI analysis into clinical radiology workflow.

Quantitative MRI metrics for multiple sclerosis (MS)—including lesion volume, new or enlarging lesions, and brain atrophy—have long been used in research but have rarely been incorporated into routine radiology practice. A collaborative project between Biogen and Siemens Healthineers demonstrated the feasibility of translating these quantitative metrics into clinical use by co-developing and integrating a fully automated image analysis tool directly into the radiology workflow at three hospitals (see Siemens Communications for more details).

To support objective treatment decisions at the individual patient level, the results are presented alongside reference metrics derived from age- and sex-matched healthy individuals. This allows radiologists and neurologists to review quantitative findings alongside raw images, enabling more effective monitoring and tracking of disease progression as part of standard clinical care.

DICOM-native integration for seamless clinical deployment.

The analysis tool was designed to integrate seamlessly into existing PACS and radiology infrastructure. Once scans are acquired, images are automatically routed to an analysis pipeline running on the Siemens syngo.via Frontier platform. After review and approval by radiologists, the results are stored in PACS as DICOM secondary captures, making them accessible to neurologists for informed treatment decisions.

• Clinical Integration Scans are automatically routed for processing, and results are reviewed and approved before being stored in PACS as DICOM secondary captures
• Algorithm The solution includes AI-based lesion segmentation with heuristics to flag potential false positives, as well as a novel brain segmentation method that combines separate T1 and 3D FLAIR segmentations using image-quality-based weighting and scanner calibration
• Multi-Site Deployment The tool was deployed across three hospital sites, with site-specific scanner calibration, protocol validation, and institutional IT integration
• Clinical Impact The system enabled objective tracking of MS disease progression in individual patients as part of the standard of care