(25 days)
CBCT, panoramic x-ray imaging system with cephalostat, is an extra oral source x-ray system, which is intended for dental radiographic examination of the teeth, jaw, and oral structures, specifically for panoramic examinations and implantology and for TMJ studies and cephalometry, and it has the capability, using the CBVT technique, to generate dental maxillofacial 3D images. The device uses cone shaped x-ray beam projected on to a flat panel detector, and the examined volume image is reconstructed to be viewed in 3D viewing stations. 2D Image is obtained using the standard narrow beam technique.
RCT700 is 3D computed tomography for scanning hard tissues like bone and teeth. By rotating the c-arm which is embedded with high voltage generator all-in-one x-ray tube and a detector on each end, CBCT images of dental maxillofacial is attained by recombining data from the same level that are scanned from different angle.
Panoramic image scanning function for attaining image of whole teeth, cephalometric scanning option for attaining cephalic image, and Model Scan option for attaining dental model CBCT image are included.
The provided text describes a 510(k) premarket notification for the RCT700 dental x-ray system, which is intended for dental radiographic examinations. The submission focuses on demonstrating substantial equivalence to predicate devices, rather than proving a new device's performance against specific acceptance criteria for a novel clinical function.
Therefore, the document does not present acceptance criteria in the typical sense of a clinical trial for diagnostic performance (e.g., sensitivity, specificity, AUC) or a comparative effectiveness study with AI assistance. Instead, the "acceptance criteria" are implied by demonstrating that the new device's performance, particularly its imaging capabilities, is similar to or not worse than the predicate devices, and that it meets applicable safety and performance standards.
Here's an attempt to structure the information based on your request, acknowledging the limitations of the provided document in terms of specific acceptance criteria and detailed study designs usually associated with AI/diagnostic device performance.
1. A table of acceptance criteria and the reported device performance
The document does not specify quantitative acceptance criteria. Instead, it relies on demonstrating that the performance of the new device is "similar" to the predicate device and that all tests performed achieved "satisfactory" results. The primary performance attributes considered are related to imaging quality and safety as per relevant IEC standards.
| Acceptance Criteria Category (Implied) | Reported Device Performance | Study that Proves Device Meets Criteria |
|---|---|---|
| Imaging Quality (CBCT, Panoramic, Cephalometric) | "Similar to that of the predicate device" (for detector performance) | Bench testing according to IEC 61223-3-4 and IEC 61223-3-5. Non-clinical performance report. Clinical images were observed and verified by licensed practitioners/clinicians. |
| Safety | "Satisfactory" | Electrical, mechanical, and environmental safety testing according to IEC 60601-1, IEC 60601-1-3, IEC 60601-1-6, IEC 60601-2-63, and EMC testing according to IEC 60601-1-2. |
| Software Functionality & Safety | "Satisfactory" (Level of concern: "moderate") | Validated according to FDA guidance "Guidance for the Content d Premarket Submissions for Software Contained in Medical Devices" and "Content of Premarket Submissions for Management of Cybersecurity in Medical Devices". Risk analysis of software. |
| Patient Dosage | "Satisfies the designated tolerance" | Bench testing as part of performance testing. |
| Technical Specifications (e.g., Pixel Size, Magnification) | Comparison tables show similar or identical specifications to predicate devices. | Bench testing (implied by specification reporting). |
2. Sample size used for the test set and the data provenance
- Test Set Sample Size: The document states that "Clinical imaging samples are collected from the new detector on propose device at the 2 offices where the predicate device is installed on clinical consideration report for the clinical test images." It also mentions "random patient age, gender, and size." However, a specific number/sample size for the clinical test set is not provided.
- Data Provenance: The general statement implies the data is retrospective (collected from existing offices where the predicate device is installed) and likely from South Korea, as the manufacturer is based there and no other country is mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Number of Experts: "two licensed practitioners/clinicians"
- Qualifications: "licensed practitioners/clinicians" – specific medical specialty (e.g., dentist, radiologist) or years of experience are not specified. They observed and verified that the dental X-ray system works as intended and that "the clinical diagnosis and structures are acceptable in the region of interests."
4. Adjudication method for the test set
The document states, "As licensed practitioners or clinician diagnoses of the images, it might be proved that the clinical diagnosis and structures are acceptable in the region of interests." This suggests that the two experts independently reviewed the images and (presumably) reached a consensus or agreement that the images were clinically acceptable. However, no formal adjudication method (e.g., 2+1, 3+1) is explicitly described. It is implied that their assessment confirmed clinical acceptability.
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
No, an MRMC comparative effectiveness study involving AI assistance for human readers was not performed or mentioned. The device is an x-ray imaging system, not an AI-powered diagnostic aid. This submission is about demonstrating substantial equivalence of a new imaging system incorporating new detectors, not an AI product.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
No, a standalone algorithm-only performance study was not performed or mentioned. As stated above, this is an imaging device, not an AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The "ground truth" for the clinical images appears to be expert clinical diagnosis/assessment by the "two licensed practitioners/clinicians" that "the clinical diagnosis and structures are acceptable in the region of interests" based on visual inspection of the images. No pathology or outcomes data is mentioned as ground truth.
8. The sample size for the training set
The document describes premarket notification for an imaging device, not a machine learning or AI algorithm. Therefore, no training set (in the context of AI/ML) is mentioned or applicable.
9. How the ground truth for the training set was established
As there is no training set for an AI/ML algorithm mentioned, this question is not applicable to the provided document.
§ 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.