Axial Medical Printing Limited · Class II · Cleared Sep 18, 2025
| K-number | K250369 |
| Device name | Axial3D Insight |
| Applicant | Axial Medical Printing Limited |
| Product code | QIH |
| Device class | Class II |
| Decision date | Sep 18, 2025 |
| Decision | Substantially Equivalent |
| Regulation | 892.2050 |
Axial3D Insight is a cloud-based image segmentation software that converts DICOM imaging data from medical scanners into 3D digital files or physical replicas using additive manufacturing. The output is intended for treatment planning and diagnostic purposes in trauma, orthopedic, maxillofacial, and cardiovascular applications, and must be used alongside other diagnostic tools and expert clinical judgment.
The proposed device uses the same software interface, computer platforms (Microsoft Edge v104, Safari v15, Chrome v103), supported modalities (CT and CTA), image registration, segmentation features (automated tools with smart editing), view manipulation, volume rendering, and ROI measurements as the predicate device. Both devices process imaging data through a combination of automated and manual segmentation tools.
Not stated in this summary. The document references FDA guidance on General Principles of Software Validation (January 11, 2002) and uses the RADPEER framework from the American College of Radiology (ACR) for clinical segmentation assessment, but does not cite specific consensus standards such as ISO, IEC, or ASTM.
The proposed device is substantially equivalent because it shares identical intended use, device classification (Class II), product code (QIH), regulatory name, and technological characteristics with the predicate Axial3D Insight (K232841). The sole difference is the addition of a Predetermined Change Control Plan (PCCP) for future machine learning model modifications, which does not alter current device safety or effectiveness. Clinical validation studies demonstrate equivalent performance in segmentation accuracy and clinical utility across the same anatomical applications.
View the full FDA submission: accessdata.fda.gov