(15 days)
SICAT Implant is a software application for the visualization of imaging information of the oral-maxillofacial region. The imaging data originates from medical scanners such as CT or DVT scanners. SICAT Implant is intended for use as planning and simulation software to aid qualified dental professionals in the placement of dental implants and the planning of surgical treatments. The dental professionals' planning data may be exported from SICAT Implant and used as input data for CAD or Rapid Prototyping Systems.
SICAT Implant is a pure software device. SICAT Implant is a software application for the visualization of imaging information of the oral-maxillofacial region. The imaging data originates from medical scanners such as CT or DVT scanners. SICAT Implant is intended for use as planning and simulation software to aid qualified dental professionals in the placement of dental implants and the planning of surgical treatments. SICAT Implant allows to name, position, move, rotate, resize and visualize dental implants and other planning objects (i.e. nerve canals) within the visualized 3D volume. Thus, dental professionals like implantologists are enabled to precisely plan the positions, orientations, types and sizes of implants to be placed in the patient's mandible/maxilla together with the related surgical procedures. The dental professionals' planning data may be exported from SICAT Implant and used as input data for CAD or Rapid Prototyping Systems.
The provided text is a 510(k) summary for the SICAT Implant, a software device. It states that the device is "substantially equivalent" to predicate devices (SimPlant System and GALILEOS Implant System) based on intended use, features, and technical characteristics. The summary mentions "Performance testing to validate the safety and effectiveness of the SICAT Implant system included validation testing and bench tests of the software functions." However, it does not provide details regarding specific acceptance criteria, study methodologies, sample sizes, ground truth establishment, expert involvement, or statistical results for performance.
Therefore, the requested details about acceptance criteria and the study proving the device meets them cannot be extracted from this document. The document primarily focuses on establishing substantial equivalence to previously cleared devices rather than presenting a detailed performance study against specific acceptance criteria.
Based on the provided text, the following information is missing:
- A table of acceptance criteria and the reported device performance: Not provided.
- Sample sized used for the test set and the data provenance: Not provided.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not provided.
- Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not provided.
- If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not indicated or described.
- If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not explicitly stated or detailed. The device is described as "aid[ing] qualified dental professionals," implying a human-in-the-loop scenario, but no performance metrics are given.
- The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not provided.
- The sample size for the training set: Not provided.
- How the ground truth for the training set was established: Not provided.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).