(66 days)
The Flat Panel Digital X-ray Detector 17HQ901G-B is indicated for digital imaging solution designed for general radiographic system for human anatomy. It is intended to replace film or screen based radiographic systems in all general purpose diagnostic procedures. Not to be used for mammography.
This model is an x-ray imaging device, a system that can acquire and process X-ray images as digital images. It utilizes amorphous silicon and a high-performance scintillator to ensure sharp high-definition image quality with the resolution of 3.6 lp/mm and the pixel pitches of 140 um. This device is a flat panel based X-ray image acquisition device. This device must be used in conjunction with an operating PC and an X-ray generator. This device can be used for digitizing and transferring X-ray images for radiological diagnosis. The data transmission between the Detector and PC can be enabled with a wired (cable) or wireless connection.
The provided text describes the regulatory clearance of a medical device (17HQ901G-B) and its substantial equivalence to a predicate device (14HQ901G-B). However, it does not contain information about acceptance criteria or a specific study proving the device meets those criteria, especially in the context of an AI/ML algorithm's performance.
The document primarily focuses on demonstrating the new device's equivalence to a previously cleared device for the purpose of FDA 510(k) clearance. This involves comparing technical specifications and showing compliance with various electrical safety, electromagnetic compatibility, software validation, biocompatibility, and cybersecurity standards.
Here's a breakdown of the requested information based on the provided text, highlighting what is missing:
1. A table of acceptance criteria and the reported device performance
The document does not specify quantitative acceptance criteria or a performance study to demonstrate the device meets such criteria for an AI/ML algorithm. It mentions performance tests for imaging devices in general, like IEC 62220-1 for Detective Quantum Efficiency (DQE):
| Performance Metric (from IEC 62220-1) | Predicate Device (14HQ901G-B) | Proposed Device (17HQ901G-B) | Acceptance Criteria |
|---|---|---|---|
| DQE @ 0.1 lp/mm | Typ. 78% | Typ. 78% | Not specified |
| MTE @ 0.5 lp/mm | Typ. 84% | Typ. 84% | Not specified |
| High Contrast Limiting Resolution (LP/mm) | 3.6 lp/mm | 3.6 lp/mm | Not specified |
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
This information is not provided in the document. The document states: "Clinical data has been provided according to FDA guidance document 'Guidance for the Submission of 510(k)s for Solid State X-ray Imaging Devices'. The data was not necessary to establish substantial equivalence based on the modifications to the device but provided further evidence in addition to the laboratory performance data to show that the device works as intended." This implies that while clinical data was submitted, its details, including sample size, provenance, and study design, are not explicitly included in this 510(k) summary.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)
This information is not provided. The document makes no mention of expert involvement in establishing ground truth for any test set.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
This information is not provided.
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
This information is not provided. The device described is a flat panel digital X-ray detector, which is a hardware component for imaging, not an AI-assisted diagnostic tool. Therefore, an MRMC study comparing human readers with and without AI assistance would not be applicable to this specific device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not provided. As noted above, this device is a hardware component, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
This information is not provided.
8. The sample size for the training set
This information is not provided. The device is a hardware detector, and the document does not discuss any AI/ML models that would require a training set.
9. How the ground truth for the training set was established
This information is not provided. (Consistent with point 8.)
In summary: The provided FDA 510(k) summary focuses on demonstrating the substantial equivalence of a new Flat Panel Digital X-ray Detector (17HQ901G-B) to an existing predicate device (14HQ901G-B) based on technical specifications and compliance with standards. It does not describe the evaluation of an AI/ML algorithm or its associated acceptance criteria, performance studies, sample sizes, expert ground truth, or adjudication methods typically found in submissions for AI/ML-powered medical devices. The "clinical data" mentioned served to further support the intended function and safety of the hardware device rather than the performance of an AI algorithm.
§ 892.1680 Stationary x-ray system.
(a)
Identification. A stationary x-ray system is a permanently installed diagnostic system intended to generate and control x-rays for examination of various anatomical regions. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II (special controls). A radiographic contrast tray or radiology diagnostic kit intended for use with a stationary x-ray system only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.