(117 days)
EzDent Web is a dental imaging software that is intended to provide viewer and image processing tools for maxillofacial radiographic images. These tools are available to view and interpret a series of DICOM compliant dental radiology images and are meant to be used by trained medical professionals such as radiologist and dentist.
EzDent Web is intended for use as software to acquire, view, and save 2D and 3D image files, to load DICOM project files from panorama, cephalometric, and intra-oral imaging equipment, and to provide 3D visualization and 2D analysis. EzDent Web is not for use for diagnostic purposes.
EzDent Web is a dental imaging software that enables you to save, manage, view and process patients' images. EzDent Web is equipped with management and processing system for various 2D and 3D images. In addition. EzDent Web provides media contents for patient consultation and user friendly instruction to assist your use of the software.
EzDent Web provides you with the following functions using patient images in 2D and 3D.
- Manage patient information
- View patient images in 2D/3D using tools for image processing and view function.
- Use high resolution 3D VR to view 3D images in the optimized view for user intent.
- Consult patients using media contents provided for patient consultation.
EzDent Web can be used in a networked environment. If EzDent Web is installed in several computers, the patient and image database can be shared among them and used on different workstations.
The provided text describes EzDent Web, a dental imaging software, and its substantial equivalence to predicate devices (EzDent-i and Ez3D-i v5.2). However, it does not contain specific acceptance criteria, detailed study designs, or performance metrics that would allow for a comprehensive answer to all parts of the request.
Here's a breakdown of what can be extracted and what is missing based on the provided document:
Description of Acceptance Criteria and Proving Device Adherence
The document states that "SW verification/validation and the measurement accuracy test were conducted to establish the performance, functionality and reliability characteristics of the modified devices. The device passed all of the tests based on pre-determined Pass/Fail criteria."
However, the specific "pre-determined Pass/Fail criteria" (acceptance criteria) and the "reported device performance" are not detailed in the provided text. Therefore, a table explicitly outlining these cannot be generated from this document.
Detailed Information about the Study:
1. Table of Acceptance Criteria and Reported Device Performance:
| Acceptance Criteria (Not explicitly stated in document) | Reported Device Performance (Not explicitly stated in document) |
|---|---|
| Specific criteria for image management, viewing, processing, accuracy of measurements, and system reliability are not provided. | The document only states that the device "passed all of the tests based on pre-determined Pass/Fail criteria." No quantitative results or specific performance metrics are given. |
2. Sample Size Used for the Test Set and Data Provenance:
- Sample Size: Not specified in the document.
- Data Provenance: Not specified in the document (e.g., country of origin, retrospective or prospective).
3. Number of Experts and their Qualifications for Ground Truth Establishment:
- Not specified in the document. The document mentions the software is "meant to be used by trained medical professionals such as radiologist and dentist," but it does not describe their involvement in establishing ground truth for testing.
4. Adjudication Method for the Test Set:
- Not specified in the document.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- Was it done? No, the document does not mention an MRMC study or any comparison of human readers with or without AI assistance.
- Effect Size: Not applicable, as no MRMC study is reported.
6. Standalone (Algorithm Only) Performance Study:
- Was it done? The document describes "SW verification/validation and the measurement accuracy test" and that the "device passed all of the tests." This suggests a standalone performance evaluation of the software's functionalities. However, specific details of this standalone performance (e.g., accuracy, precision for specific tasks) are not provided. The device is purely software, so its "performance" would inherently be standalone in its function.
7. Type of Ground Truth Used:
- Not specified in the document. Given the context of dental imaging software for viewing and processing, potential ground truths could include expert consensus on image quality, accurate measurement validation, or comparison to established benchmarks for image processing functions. However, the document does not elaborate.
8. Sample Size for the Training Set:
- The document describes a "verification/validation" study for the modified device and states its similarity to predicate devices. It does not mention a "training set" in the context of an AI/machine learning model, which this device, as described, does not appear to be. It's a medical image management and processing system.
9. How Ground Truth for the Training Set was Established:
- Not applicable, as a "training set" in the context of machine learning is not mentioned or implied for this device. The document describes a software system for viewing and processing images, not an AI diagnostic tool that requires a training phase.
§ 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).