(253 days)
The DENTRIα series is a Computed Tomography X-Ray imaging device specialized in diagnosing general dental treatments and orthodontic purpose using Panoramic and Cephalometric images respectively. In addition DENTRIα series is used in the field of Otolaryngology by capturing 360 degree rotation sequence of the head and neck areas, including the ENT and dentomaxillofacial areas for a dental treatment in adult and pediatric dentistry and obtains x-ray images from different angles and calculate though computer-processed to produce 3D x-ray tomographic images. The DENTRIα series is used by physicians, dentists, and x-ray technologists.
This Equipment is a Dental X-Ray imaging device used for diagnostic purpose in dental treatment. The operating principle of this device is obtaining the tomographic images by rotating arm to get the recombination data, X-ray generator and detector rotate around the patient to irradiate the X-ray, and penetrated X-ray is measured by the detector, When the X-ray is irradiated on the teeth area for instance, large amount of X-ray is attenuated because objects such as bones are highly dense, On the contrast, X-ray is more permeable to small molecules with low density such as skin or tissue, so more X-ray would pass through the subject. By measuring data obtained from measuring the X-rav is reconstructed by the software to display and analyze the anatomical structure for the diagnosis purposes.
The DENTRIα Series are classified as shown below.
DENTRIa: CT Mode + PANORAMA Mode
DENTRI-Ca: CT Mode + PANORAMA Mode + CEPHALO Mode (ONE-SHOT)
DENTRI-Sa: CT Mode + PANORAMA Mode + CEPHALO Mode (SCAN)
This document is a 510(k) summary for the DENTRIα series of Computed Tomography (CT) X-Ray imaging devices. It primarily focuses on demonstrating substantial equivalence to predicate devices rather than providing a detailed study of acceptance criteria and device performance in the context of a clinical trial for a new AI/CAD device. Therefore, much of the requested information regarding acceptance criteria, study design, ground truth establishment, sample sizes, and expert adjudication for an AI device is not explicitly present in the provided text.
However, I can extract the information that is available and indicate where the requested details are not provided due to the nature of this type of submission (a 510(k) for a medical imaging device, not an AI/CAD system).
Here's an attempt to answer based on the provided document:
1. Table of acceptance criteria and the reported device performance
The document does not specify formal "acceptance criteria" for diagnostic performance in the way one would for an AI/CAD system (e.g., sensitivity, specificity thresholds). Instead, it focuses on comparative performance with predicate devices for technical characteristics and demonstrating diagnostic quality through non-clinical and limited clinical data.
The "reported device performance" is primarily presented as technical specifications and compliance with standards, and a general statement about diagnostic quality.
| Category | Acceptance Criteria (Not explicitly stated as such for diagnostic performance, implied by substantial equivalence) | Reported Device Performance (Comparative to Predicate Devices #1 and #2) |
|---|---|---|
| Intended Use | Equivalent to predicate devices | Similar: Diagnosing general dental treatments, orthodontic purposes using Panoramic and Cephalometric images, and Otolaryngology by capturing 360-degree rotation of head and neck areas (ENT and dentomaxillofacial) for 3D X-ray tomographic images in adult and pediatric dentistry. Used by physicians, dentists, and X-ray technologists. |
| Operation Mode | Equivalent to predicate devices | Same: CT, Panorama, Cephalo (One shot type & Scan type) |
| Image Properties | Adequate for diagnostic purposes, comparable to predicate devices for safety and effectiveness. | Detectors: Flat panel for CT/Panorama/One-shot Cephalo, CCD for Scan Cephalo. (Details in Section 5, "Description of the Device," and Section 8, "Substantial Equivalence," comparing specific models, resolution, pixel size, MTF, DQE, and active area to predicate devices. Slight differences in MTF and DQE noted but deemed not to affect safety/effectiveness for diagnosis.) |
| Dose Information | Within acceptable limits and comparable to predicate devices, not exceeding 50% of IEC 60601-2-63 requirements. | CT Mode (CTDIw): 11.12 mGy (Proposed) vs. 8.34 mGy (Predicate #1) and 10.61 mGy (Predicate #2). Panorama (DAP): 198.8 mGy·cm² (Proposed Xineos-1313), 119.0 mGy·cm² (Proposed PaxScan1313DX) vs. 159.0 mGy·cm² (Predicate #2). Cephalo One shot (DAP): 26.7 mGy·cm² (Proposed) vs. 38.4 mGy·cm² (Predicate #2). Cephalo Scan (DAP): 21.3 mGy·cm² (Proposed) vs. 65.8 mGy·cm² (Predicate #2). Differences are within acceptable range and do not exceed 50% of IEC 60601-2-63. |
| Safety Standards | Compliance with relevant international standards. | AAMI ES60601-1, IEC 60601-1-2, IEC 60601-1-3, IEC 60601-2-63, IEC 61223-3-4, and 21 CFR 1020.30, 31, and 33. |
| Software | Designed and developed according to a software development process, verified, and validated (MODERATE level of concern). | Original and OTS software (image viewer) used. Reconstruction type is FBP. Complies with FDA guidance "The content of premarket submissions for software contained in medical devices, on May 11, 2005." |
2. Sample size used for the test set and the data provenance
The document mentions "clinical images of patients are presented as the clinical data including date and signature by a licensed professional." However, it does not specify the sample size (number of patients/cases) for this clinical data, nor does it explicitly state the data provenance (e.g., country of origin, retrospective or prospective nature of this specific clinical image set). Since it's a Korean manufacturer, the images likely originated from Korea, but this is not explicitly stated. The context implies it was likely a retrospective collection given the wording "clinical images...are presented."
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
The document states: "The report concluded that the images taken with the subject device are of good diagnostic quality." It also mentions "clinical data including date and signature by a licensed professional."
- Number of experts: Not specified. It only mentions "a licensed professional" in the singular, but a formal clinical study usually involves multiple experts.
- Qualifications of those experts: "licensed professional" – no specific qualifications (e.g., radiologist, years of experience) are provided.
4. Adjudication method for the test set
Not specified. Given the lack of detail on the number of experts and how ground truth was established, no adjudication method is mentioned.
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 was not conducted or reported in this 510(k) summary. This submission is for a conventional medical imaging device, not an AI/CAD system necessitating such a study design.
- Effect size of human readers with/without AI assistance: Not applicable, as this is not an AI/CAD device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a medical imaging device (hardware and software for image acquisition and reconstruction), not a standalone algorithm. The device produces images for human interpretation.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The ground truth for the "clinical data" is implied to be a subjective assessment by a "licensed professional" that the images are of "good diagnostic quality." This is a general statement rather than a rigorous, objective ground truth established by expert consensus, pathology, or outcomes data typically used for evaluating AI/CAD diagnostic performance.
8. The sample size for the training set
Not applicable. This is a conventional CT X-ray system, not an AI/CAD system, so there is no "training set" in the context of machine learning. The device uses established image reconstruction algorithms (FBP is mentioned).
9. How the ground truth for the training set was established
Not applicable, as there is no training set for an AI/CAD system mentioned.
§ 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.