(49 days)
The CS 9600 is extraoral system intended to produce two-dimensional digital X-ray images of the dento-maxillofacial, ENT (Ear, Nose and Throat), cervical spine and wrist regions at the direction of healthcare professionals as diagnostic support for pediatric and adult patients.
The CS 9600 can be upgraded to produce cephalometric digital X-ray images. This includes imaging the hand and wrist to obtain carpus image for growth and maturity assessment.
CS 9600 is an extraoral system intended to produce two-dimensional and three-dimensional digital X-ray images of the dento-maxilofacial, ENT (Ear, Nose and Throat), cervical spine and wrist regions at the direction of healthcare professionals as diagnostic support for pediatric and adult patients.
The CS 9600 can be upgraded to produce cephalometric digital X-ray images. This includes imaging the hand and wrist to obtain carpus image for growth and maturity assessment.
CS 9600 is a cone-beam computed tomography (CBCT) x-ray system. It means CS 9600 rotates around the patient, capturing data using a cone-shaped x-ray beam. These data are used to reconstruct a two or a three-dimensional (3D) image of the following regions of the patient's anatomy: dental (teeth); oral and maxillofacial region (mouth, jaw and neck); ears, nose and throat region (ENT); cervical spine or wrist region.
Additional features such as low dose mode, scout image and metal artifact reduction are also provided by the CS 9600.
The CS 9600 can also be upgraded with cephalometric modality. The cephalometric modality of the proposed device CS 9600 is the same than the one available in the reference device K151087. The cephalometric mode works with a narrow beam linear scanning process called a "slot technique". The patient head is scanned in lines with a flat, fan-shaped x-ray beam.
The provided text describes the CS 9600 device, an extraoral system for producing 2D and 3D digital X-ray images, and its substantial equivalence to predicate devices. It specifically details the addition of an optional cephalometric modality.
Here's an analysis of the acceptance criteria and the study that proves the device meets those criteria, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance:
The document doesn't present a formal table of acceptance criteria with specific quantitative thresholds. Instead, it describes performance through comparison to predicate devices and general statements about clinical effectiveness. The core "acceptance criteria" appear to be met by demonstrating substantial equivalence to these predicate devices.
| Feature / Modality | Predicate Device (K181136) Performance | Reference Device (K151087) Performance (for Ceph) | CS 9600 Reported Performance | Acceptance Standard |
|---|---|---|---|---|
| Panoramic Modality | Present, same specifications as CS 9600 | N/A | Present, same specifications as predicate K181136 | Substantial Equivalence to K181136 |
| 3D Modality | Present, same specifications as CS 9600 | N/A | Present, same specifications as predicate K181136 | Substantial Equivalence to K181136 |
| Cephalometric Modality (Optional) | Not present in primary predicate | Present, with detailed specifications | Present, identical to reference device K151087 | Substantial Equivalence to K151087 |
| Image Quality (Cephalometric) | N/A | Not explicitly stated but implied acceptable | "acceptable clinical effectiveness" and "clinically usable diagnostic quality" | Qualified expert review |
| EMC & Electrical Safety | Implicitly met by predicate | Implicitly met by reference | Meets IEC 60601-1, IEC 60601-1-2, IEC 60601-1-3, IEC 60601-2-63 | Compliance with specified IEC/AAMI standards |
| Software Validation | Implicitly met by predicate | Implicitly met by reference | Validated according to FDA Guidance for Software and Cybersecurity | Compliance with specified FDA Guidances |
| DICOM Conformance | Implicitly met by predicate | Implicitly met by reference | Meets NEMA PS 3.1-3.20 | Compliance with NEMA DICOM Set |
| Pediatric Information | Implicitly met by predicate | Implicitly met by reference | Provides design features and instructions for pediatrics | Compliance with FDA Guidance on Pediatric Information |
2. Sample Size Used for the Test Set and Data Provenance:
The document does not explicitly state the sample size for the test set. It mentions "clinical images representative of the range of the different cephalometric radiological exams were taken." This implies a set of images was used, but the exact number is not provided. The data provenance (country of origin, retrospective/prospective) is also not stated.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications:
The document states that "The cephalometric images were reviewed by a qualified expert." It indicates a single expert was used. The specific qualifications of this expert are not detailed beyond "qualified expert."
4. Adjudication Method for the Test Set:
No adjudication method is described. The review was conducted by a single "qualified expert."
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:
No MRMC comparative effectiveness study was mentioned. The study focused on technical comparisons and single-expert clinical review, not on comparing human reader performance with and without AI assistance.
6. If a Standalone (algorithm only without human-in-the-loop performance) was done:
The device described is an X-ray imaging system, not an AI algorithm. Therefore, a standalone performance study of an algorithm independent of human interaction is not applicable in this context. The "performance testing" was for the imaging system itself.
7. The Type of Ground Truth Used:
For the cephalometric images, the ground truth was established through expert consensus (or rather, the opinion of a single "qualified expert") who "evaluated [the images] to be of acceptable clinical effectiveness for the proposed indications for use" and "deemed to be of a clinically usable diagnostic quality."
8. The Sample Size for the Training Set:
The document describes performance testing for an imaging device, not an AI algorithm. As such, there is no mention of a "training set" in the context of machine learning. The device's performance is established based on its physical characteristics, image quality, and regulatory compliance, rather than by training on a dataset.
9. How the Ground Truth for the Training Set Was Established:
As mentioned above, the concept of a "training set" for an AI algorithm is not applicable to the information provided for this medical imaging device.
§ 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.