Search Results

Edge Air Digital Flat Panel X-Ray Detector is indicated for digital imaging solution designed for general radiographic system for human anatomy. It is intended to replace film or screen based radiographic system in all general purpose diagnostic procedures. Not to be used for mammography.

Edge Air is a wired/wireless digital solid state X-ray detector that is based on flat-panel technology. The wireless LAN (IEEE 802.11a/g/n/ac) communication signals images captured to the system and improves the user operability through high-speed processing. This radiographic image detector and processing unit consists of a scintillator coupled to an a-Si TFT sensor. This device needs to be integrated with a radiographic imaging system. It can be utilized to capture and digitalize Xray images for radiographic diagnosis The RAW files can be further processed as DICOM compatible image files by a separate console SW program (K160579 / Xmaru View V1 and Xmaru PACS/ Rayence Co., Ltd.) for a diagnostic analysis.

This document describes the equivalence of the OSKO, INC. Edge Air Digital Flat Panel X-ray Detector to a predicate device, the Rayence Co., Ltd. 1717WCC. The focus is on demonstrating that the Edge Air performs similarly to the predicate device, rather than establishing novel acceptance criteria for improved diagnostic accuracy.

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

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a substantial equivalence submission, the "acceptance criteria" are primarily based on demonstrating similar performance to the predicate device. The performance metrics are reported in terms of comparison.

2. Sample Size Used for the Test Set and Data Provenance

The document mentions "talking sample radiographs of similar age group and anatomical structures" for the clinical image review. However, the specific sample size of images or patients for the test set is not explicitly stated.

The data provenance for the clinical images is not explicitly stated in terms of country of origin, but it is implied to be for human anatomy and diagnostic procedures. It is a prospective comparison of images taken with the Edge Air and the predicate device.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts

One expert was used for the clinical image review. The expert is described as a "licensed radiologist." No specific details about years of experience are provided.

4. Adjudication Method for the Test Set

The adjudication method appears to be a single expert review. The licensed radiologist reviewed images from both the Edge Air and the predicate device to render an opinion on their similarity and diagnostic image quality. There is no mention of multiple readers or consensus methods.

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. This submission is for a digital flat panel X-ray detector, which is a hardware device for image acquisition, not an Artificial Intelligence (AI) diagnostic tool. Therefore, the concept of human readers improving with or without AI assistance is not applicable here.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done

Yes, in essence, standalone performance was assessed through non-clinical tests.
The non-clinical tests (MTF, DQE, NPS) are measures of the device's inherent imaging performance characteristics without human interpretation. These tests were conducted by "using the identical test equipment and same analysis method described by IEC 6220-1." The comparison against the predicate device's specifications serves as the standalone performance evaluation.

7. The Type of Ground Truth Used

For the non-clinical tests (MTF, DQE, NPS), the ground truth is based on standardized physical measurements as described by IEC 6220-1.

For the clinical image review, the ground truth is based on expert opinion/consensus by a licensed radiologist regarding the visual similarity and diagnostic quality of the images. This is a form of expert consensus, although only one expert is mentioned.

8. The Sample Size for the Training Set

The document specifies the Edge Air detector "uses the same flat panel x-ray detector as that used in the predicate device, K162519, and that no changes were necessary to either the hardware or firmware of the device." It also states it uses the "same version of imaging software Xmaru View 1 / Xmaru PACS (K160579)."

Given that this is a 510(k) submission for a device demonstrating substantial equivalence to a predicate, and the hardware and software are identical to the predicate, there is no mention of a separate "training set" for the Edge Air device's image processing. The underlying technology (detector and software) would have been "trained" or developed during the creation of the predicate device and the imaging software (K160579). The context here is not an AI algorithm that requires a distinct training set for this specific submission.

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

As explained above, this submission does not explicitly discuss a new "training set" for the Edge Air device. The device leverages existing, established hardware and software from the predicate. Therefore, the question of how a training set's ground truth was established for the Edge Air is not applicable in this document's context, as it's not a new AI-driven diagnostic system requiring novel training data. The "ground truth" for the predicate device and its associated software would have been established during their respective development and clearance processes.

Ask a specific question about this device