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Edge Air(1417) 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 40(1417) is a wired/wireless digital solid state X-ray detector that is based on flat-panel technology. The wireless LAN (IEEE 802.11a/g/w/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 X-ray images for radiographic diagnosis The RAW files can be further processed as DICOM compatible image files by a separate console SW program (K190866 / Xmaruview V1 (Xmaru Chiroview, Xmaru Podview) / Rayence Co., Ltd.) for a diagnostic analysis.

The provided text describes the Edge Air (1417) Digital Flat Panel X-ray Detector, a device intended to replace film or screen-based radiographic systems for general diagnostic procedures, excluding mammography. The submission argues for substantial equivalence to a predicate device, Edge Air (K172681).

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The submission primarily focuses on demonstrating substantial equivalence to a predicate device, rather than defining explicit acceptance criteria against a fixed standard. However, the comparisons provided between the proposed device and the predicate device can be interpreted as the performance metrics and their desired "acceptance" (i.e., being similar or equivalent to the predicate).

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

The document mentions "clinical images have been reviewed by a licensed radiologist" for the "clinical consideration test." However, it does not specify the exact sample size (number of images or patients) used for this clinical review or the demographics of the "similar age group and anatomical structures."

The data provenance is implicitly prospective for the clinical images used for comparison, as they involved "taking sample radiographs." The country of origin of the data is not specified.

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

Only one expert is mentioned: "a licensed radiologist." No specific details about the radiologist's experience (e.g., "10 years of experience") are provided beyond being "licensed" and an "expert opinion."

4. Adjudication Method for the Test Set

The adjudication method appears to be none beyond a single expert's opinion. The text states, "clinical images have been reviewed by a licensed radiologist to render an expert opinion." There is no mention of multiple readers, consensus, or a specific adjudication process for discrepancies.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

No MRMC comparative effectiveness study was done as described for an AI device. This submission is for a digital flat panel X-ray detector, which is a hardware component for image acquisition, not an AI-powered diagnostic tool. The device itself does not involve AI assistance for human readers in the sense of improving their diagnostic capability. The comparison is for image quality of two different hardware detectors.

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

Again, this question is not directly applicable to the device under review. The Edge Air (1417) is an X-ray detector, not a standalone algorithm. Its "performance" is measured by physical characteristics (MTF, DQE, NPS) and its ability to produce diagnostic images comparable to a predicate device. The imaging software (Xmaruview V1) is mentioned as a separate 510(k) (K190866), but the submission for the detector itself does not detail standalone performance of an algorithm.

7. The Type of Ground Truth Used

For the non-clinical tests (MTF, DQE, NPS), the ground truth is derived from physical measurements against established standards (IEC 62220-1).

For the "clinical consideration test," the ground truth is expert opinion/comparison by a single licensed radiologist, asserting similarity in image quality ("spatial and soft tissue contrast resolutions for both devices are equivalent"). It's a comparative visual assessment against images from the predicate device by an expert.

8. The Sample Size for the Training Set

The concept of a "training set" is not directly applicable here. This is a hardware device (X-ray detector). The imaging software (Xmaruview V1) might have had a training set if it involved AI, but the submission for the detector does not provide this information. The device's manufacturing and performance are based on engineering design and testing, not machine learning training.

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

Since there is no "training set" for the X-ray detector itself, this question is not applicable.

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