Search Results

rainbow MCT is a computed tomography x-ray system intended to produce 3D and panoramic diagnostic images of the maxillofacial areas for treatment planning for adult and pediatric patients. The device is operated and used by physicians, dentists, and x-ray technicians.

Rainbow 3D Image Viewer software functions for acquiring, saving, searching, displaying, diagnosing and sending digital X-ray image data in dental practices and clinics.

rainbow MCT is a cone beam CT X-ray device for generating sectional images of dental images such as tooth, nasal cavity and temporomandibular joint. this is a medical diagnostic equipment designed to generate sectional images by placing X-ray source opposite to the imaging detector unit and rotating it around a patient. 2D images of the region of interest are reconstructed using a mathematical algorithm in 3 dimensional volumetric view and displayed on the computer monitor.

The system is composed of X-ray generator, X-ray detector, X-ray collimator, main frame, rotation unit, PC and Monitor, etc. in compliance with US performance standard and regulatory requirement.

This document describes the premarket notification (510(k)) for the Dentium Co., Ltd rainbow MCT (K200270), a computed tomography x-ray system. The information provided focuses on demonstrating substantial equivalence to predicate devices rather than a standalone clinical study of an AI algorithm. Therefore, many of the requested criteria related to AI performance, such as multi-reader multi-case (MRMC) studies, effect sizes, and specific details about training/test set ground truth establishment for AI, are not applicable or not explicitly detailed in this document, as the device itself is an imaging system and not an AI/ML software.

The document primarily discusses the technical and performance characteristics of the imaging device itself, ensuring it meets standards comparable to existing predicate devices.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not present a formal "acceptance criteria" table in the way one might see for an AI algorithm's performance metrics (e.g., AUC, sensitivity, specificity targets). Instead, it compares the rainbow MCT's technical specifications and imaging performance metrics against those of predicate devices (K181432, ProVecta 3D Prime with VistaSoft; and K102196, PaX-Zenith3D). The "acceptance" is implied by demonstrating similar or better performance compared to these legally marketed devices.

Summary of differences and claims: The document states, "The MTF, DQE and pixel resolution of the subject device performed similar or better than those of the predicate and reference device. All test results were satisfactory."

2. Sample Size for the Test Set and Data Provenance

The document describes non-clinical testing of the device's physical and technical performance (e.g., electrical, mechanical, environmental safety, EMC, imaging properties per IEC standards). It does not refer to a "test set" in the context of a dataset of patient images used to evaluate an AI algorithm's diagnostic performance. Therefore, sample size and data provenance (country, retrospective/prospective) for a patient image test set are not applicable here.

The tests performed were:

• Electrical, mechanical, environmental safety testing according to IEC 60601-1, IEC 60601-1-3, IEC 60601-2-63.
• EMC testing in accordance with IEC 60601-1-2.
• Non-clinical & Clinical considerations according to FDA Guidance "Guidance for the submissions of 510(k)'s for Solid State X-ray Imaging Devices."
• Acceptance test according to IEC 61223-3-4 and IEC 61223-3-5.

All these refer to technical and performance benchmarks, often using test phantoms or controlled environments, not patient data for diagnostic accuracy assessment.

3. Number of Experts and Qualifications for Ground Truth

Not applicable. As this is a 510(k) for an imaging device, not an AI diagnostic algorithm, there's no mention of experts establishing ground truth from patient images for a diagnostic performance study. The ground truth for the performance characteristics (e.g., MTF, DQE) is inherent to the physical properties of the imaging system and measured using standardized methods and phantoms.

4. Adjudication Method for the Test Set

Not applicable. No diagnostic image test set or human interpretation adjudication is described.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. A MRMC comparative effectiveness study was not done, as the submission is for the imaging device itself, not an AI-assisted interpretation tool. The document explicitly states: "Clinical Data: Not required for a finding of substantial equivalence."

6. Standalone (Algorithm Only) Performance

Not applicable. This submission is for a medical imaging device, not an AI algorithm.

7. Type of Ground Truth Used

The "ground truth" for the device's performance is based on technical specifications and measurements obtained through standardized testing procedures using phantoms and controlled setups (e.g., MTF, DQE measurements, electrical safety tests). It is not based on expert consensus, pathology, or outcomes data from patient cases in a diagnostic context.

8. Sample Size for the Training Set

Not applicable. The device is a hardware imaging system; it does not involve machine learning or training on a dataset of patient images.

9. How the Ground Truth for the Training Set Was Established

Not applicable. See point 8.

Ask a specific question about this device