(265 days)
QRmaster-H/Revo is a dedicated X-ray imaging device that acquires a 360-degree rotational X-ray sequence of images for use as diagnostic support in radiology of the dento-maxillo-facial complex and in the field of maxillofacial surgery. The device accomplishes this task by reconstructing a three-dimensional matrix of the examined volume, producing two-dimensional views of this volume, and displaying both 2D images and 3D renderings. This technique is known as cone beam computed tomography, or CBCT.
QRmaster-H/Revo is an extraoral 2D (panoramic) and 3D (CBCT) x-ray imaging system for use by dental professionals. The device is designed to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the body by lput the same axial plane taken at different angles. To accomplish this it uses a cone-shaped xray beam projected on a flat panel detector to capture a rapid series of 2D images using the standard narrow beam technique. Such images from a single 360° scan are reconstructed with special software to be viewed on 3D viewing stations (PCs) that are not part of the system.
The system makes use of a single flat panel detector for both panoramic and cone beam images. Three field of views (FOVs) provide targeted regions of interest that can be positioned by panoramic scout, two-dimensional scout, or four positioning laser beams.
QRmaster-H/Revo includes firmware to operate the device through a control panel attached to the main device. The device also includes image acquisition software that stores 3D images in standard DICOM format for export to third party viewing or image management software not part of the system. Users are expected to have or acquire such image management software for communication both with the device's image acquisition software and with third party 3D-viewing software. These latter applications are readily available in the domestic marketplace.
The provided text describes a 510(k) premarket notification for the QRmaster-H/Revo device, a Cone Beam Computed Tomography (CBCT) X-Ray System for dentistry. The document focuses on demonstrating substantial equivalence to predicate devices rather than proving the device meets specific acceptance criteria through a standalone study with detailed performance metrics.
Therefore, the requested information regarding acceptance criteria, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, and ground truth data for a specific study is not explicitly available within this document. The document primarily relies on comparisons to predicate devices and general performance and safety assessments.
However, I can extract what is provided regarding performance and studies.
1. Table of Acceptance Criteria and Reported Device Performance
As specific, quantifiable acceptance criteria with corresponding performance metrics are not detailed in the provided document, I will summarize the general performance and conclusions drawn.
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Diagnostic Relevance and Reliability of Images | Clinical images were examined by a qualified professor at Asahi University School of Dentistry and found to be diagnostically relevant and reliable. Sample 2D and 3D images utilizing test phantoms were also included in the submission. |
| Software Functionality and Safety (Risk Analysis) | A software level of concern analysis (including device risk analysis conforming to ISO 14971) determined "acceptable" residual risks. Verification and validation of the software included tests that confirmed its functionality. |
| Electrical and Laser Safety and Electromagnetic Compatibility (EMC) | Independent laboratory and in-house testing was performed to demonstrate conformance with recognized electrical (60601 et al) and laser device (60825-1) standards. Differences in technological features do not raise new issues of safety or effectiveness. Effective exposure (radiation dose) is equal to or lower than the predicates despite higher exposure times. |
| Substantial Equivalence to Predicate Devices | Both intended use and fundamental scientific technology are the same as predicate devices. The device and petition comply with relevant FDA guidance documents. |
2. Sample size used for the test set and the data provenance
- Test Set Sample Size: Not specified. The document mentions "clinical images" and "sample 2D and 3D images utilizing test phantoms," but no numerical sample size for either.
- Data Provenance: The "qualified professor" mentioned is from Asahi University School of Dentistry, implying the clinical image evaluation data originates from Japan. The document does not specify if the data is retrospective or prospective.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Number of Experts: "A qualified professor" (singular) was involved.
- Qualifications: "qualified professor at Asahi University School of Dentistry." Further specifics like years of experience or specialty (e.g., oral radiologist) are not provided.
4. Adjudication method for the test set
- Adjudication Method: Not specified. With only one expert mentioned, a formal adjudication process (like 2+1 or 3+1) is unlikely to have been used for establishing ground truth, as there are no multiple readings to resolve. The single expert likely provided a direct assessment.
5. 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
- MRMC Study: No, an MRMC comparative effectiveness study is not mentioned. The device is described as an X-ray imaging system, not an AI software intended to assist human readers in interpretation. The document focuses on the device's image acquisition capabilities and safety/equivalence, not on reader performance improvement with AI assistance.
6. If a standalone (i.e. algorithm only, without human-in-the-loop performance) was done
- Standalone Performance: The core device is an imaging system. Its "performance" in this context is assessed by the diagnostic relevance and reliability of the images it produces, as evaluated by an expert, and by technical metrics (e.g., electrical safety, EMC). It's not an algorithm that outputs a diagnostic decision in a standalone manner. The software mentioned is for operation, image acquisition, and risk analysis, not for standalone diagnostic interpretation.
7. The type of ground truth used
- Type of Ground Truth: For the "clinical images," the ground truth appears to be expert consensus/opinion (from the "qualified professor"). For the "sample 2D and 3D images utilizing test phantoms," the ground truth would inherently be based on the known properties of the phantoms.
8. The sample size for the training set
- Training Set Sample Size: Not applicable/not specified. The device is a hardware imaging system. While it has firmware and image acquisition software, the document doesn't describe a "training set" in the context of machine learning for image interpretation, as the device's function is image acquisition and reconstruction, not algorithm-based diagnosis.
9. How the ground truth for the training set was established
- Ground Truth for Training Set: Not applicable/not specified, as there's no mention of a machine learning model requiring a training set with associated ground truth for diagnostic interpretation.
§ 892.1750 Computed tomography x-ray system.
(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.