(57 days)
The Flat Panel Digital X-ray Detector 17HQ701G-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 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.
This document describes the premarket notification (510(k)) for the LG Electronics Inc. 17HQ701G-B Flat Panel Digital X-ray Detector. The submission aims to demonstrate substantial equivalence to a predicate device, not to prove superiority or innovation. Therefore, the "acceptance criteria" discussed are primarily related to meeting established X-ray device performance standards and demonstrating equivalence to a legally marketed predicate.
Here's an analysis of the acceptance criteria and supporting studies based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria are not explicitly listed as specific quantitative thresholds for clinical performance but are implied by adherence to general safety, performance, and equivalence standards for X-ray imaging devices. The document focuses on demonstrating that the proposed device performs comparably to its predicate and meets relevant non-clinical standards.
| Acceptance Criterion (Implied) | Reported Device Performance |
|---|---|
| Electrical Safety (ES60601-1) | The 17HQ701G-B complies with ES60601-1 (2005(R)2012 and A1:2012) |
| Electromagnetic Compatibility (IEC 60601-1-2) | The 17HQ701G-B complies with IEC 60601-1-2 (Edition 4.0 2014-02) |
| Radio Frequency Wireless Technology Compliance | Complies with FDA guidance "Radio Frequency Wireless Technology in Medical Devices" (August 14, 2013) |
| Software Validation (Moderate Level of Concern) | Software designed, developed, verified, and validated according to a software development process and FDA guidance "The content of premarket submissions for software contained in medical devices" (May 11, 2005). |
| Biocompatibility (ISO 10993-1) | Complies with ISO 10993-1 and series, "Biological evaluation of medical devices". |
| Imaging Performance (Detective Quantum Efficiency - DQE) | Performance test conducted according to IEC 62220-1. Reported DQE: Typ. 66% @0.1lp/mm (Proposed Device) vs. Typ. 72% @0.1lp/mm (Predicate Device). The gap analysis states this difference is "not related to the device's 'safety and 'performance.'" |
| Imaging Performance (Modulation Transfer Function - MTF) | Performance test conducted according to IEC 62220-1. Reported MTF: Typ. 84% @0.5lp/mm (Proposed Device) vs. Typ. 89% @0.5lp/mm (Predicate Device). The gap analysis states this difference is "not related to the device's 'safety and 'performance.'" |
| Imaging Performance (Limiting Resolution) | Reported High Contrast Limiting Resolution: 3.6 lp/mm (Same as Predicate Device). |
| Cybersecurity | Complies with FDA guidance "Content of Premarket Submissions for Management of Cybersecurity in Medical Devices" (October 18, 2018) and "Postmarket Management of Cybersecurity in Medical Devices" (December 28, 2016). |
| Labeling | Complies with CFR Part 801 and "Pediatric Information for X-ray Imaging Device Premarket Notifications" (November 28, 2017). |
| Substantial Equivalence to Predicate Device (K182348) | Demonstrated equivalence in Indications for Use, Intended Use, Scintillator type, Pixel Pitch, Resolution, Anatomical Sites, Exposure Mode, Semi Dynamic mode, Wireless standard, and Rating. Differences in Imaging Area, Pixel Matrix, DQE, and MTF are deemed not to adversely affect safety or performance. "Clinical data has been provided... to show that the device works as intended." |
2. Sample size used for the test set and the data provenance
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'." It further clarifies that this 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."
Crucially, the document does not specify the sample size, data provenance (e.g., country of origin, retrospective or prospective nature), or specific details of the clinical test set. It only broadly mentions that clinical data was provided. This suggests the clinical data was likely used for general verification rather than a specific performance study with a defined test set sample size for "acceptance criteria" in the AI sense.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
The document does not provide any information about the number or qualifications of experts used to establish ground truth for any test set. Given that the submission focuses on substantial equivalence to a predicate device and adheres to technical standards, an explicit ground truth establishment by clinical experts for a specific test set is not detailed in the provided text.
4. Adjudication method for the test set
The document does not provide any information regarding an adjudication method for a test set. This type of detail is typically associated with studies involving human interpretation or AI performance assessment against a consensus ground truth, which is not clearly described here.
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, a multi-reader multi-case (MRMC) comparative effectiveness study was not done or reported in this document. The purpose of this 510(k) submission is to demonstrate the substantial equivalence of an X-ray detector to a predicate device, not to evaluate the impact of AI assistance on human reader performance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The device is a Flat Panel Digital X-ray Detector, which is a hardware component for capturing X-ray images. It is not an AI algorithm in itself that would have a "standalone" performance without human-in-the-loop interaction. Its "performance" refers to its imaging characteristics (DQE, MTF, resolution).
The software mentioned is for the device's firmware and functionality, not an AI for image interpretation. Therefore, a standalone algorithm-only performance study as typically understood for AI-powered diagnostic software is not applicable and not reported.
7. The type of ground truth used
For the non-clinical performance tests (DQE, MTF, Resolution), the "ground truth" is established by physical measurements and adherence to international standards like IEC 62220-1.
For the general statement about "clinical data" provided, the type of ground truth used is not specified. Given the context of a 510(k) for an X-ray detector, it likely refers to standard clinical evaluations of image quality for diagnostic purposes, where the "ground truth" would implicitly be the physician's diagnostic conclusion or potentially follow-up information, but this is not explicitly stated.
8. The sample size for the training set
The device is an X-ray detector, not an AI model that requires a distinct "training set" of images for learning. The "software validation" relates to the device's firmware, not a diagnostic AI algorithm trained on a large image dataset. Therefore, the concept of a "training set" for an AI algorithm is not applicable to this submission.
9. How the ground truth for the training set was established
As there is no AI algorithm training set described, the method for establishing ground truth for a training set is not applicable to this document.
§ 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.