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The EVS 3643 and EVS 3643G Digital X-ray detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. This device is intended to replace film or screen based radiographic systems in all general purpose diagnostic procedures. This device is not intended for mammography applications.

The EVS 3643(G) is a wired/wireless flat-panel type digital X-ray detector that captures projection radiographic images in digital format within seconds, eliminating the need for an entire x-ray film or an image plate as an image capture medium. EVS 3643(G) differs from traditional X-ray systems in that, instead of exposing a film and chemically processing it to create a hard copy image, a device called a Detector is used to capture the image in electronic form.

The EVS 3643(G) Detector is an indirect conversion device in the form of a square plate in which converts the incoming X-rays into visible light. This visible light is then collected by an optical sensor, which generates an electric charges representation of the spatial distribution of the incoming X-ray quanta.

The charges are converted to a modulated electrical signal thin film transistors. The amplified signal is converted to a voltage signal and is then converted from an analog to digital signal which can be transmitted to a viewed image print out, transmitted to remote viewing or stored as an electronic data file for later viewing.

The provided text describes the acceptance criteria and a study conducted for the EVS 3643 and EVS 3643G Digital X-ray detectors.

Here's the breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

The document mentions a "single-blinded concurrence study" and "Clinical images were provided". However, it does not specify the sample size for the test set (number of images or cases).

The data provenance is also not explicitly stated regarding country of origin or whether it was retrospective or prospective. It only notes that the study was conducted "according to CDRH's Guidance for the Submission of 510(k)'s for Solid State X-ray Imaging Devices."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document does not specify the number of experts used or their qualifications for establishing ground truth in the clinical study. It refers to a "concurrence study," implying multiple readers, but provides no details.

4. Adjudication method for the test set

The document mentions a "single-blinded concurrence study," but does not describe the specific adjudication method used (e.g., 2+1, 3+1, none). The term "concurrence" suggests agreement among observers, but the process is not detailed.

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

The study described is a "single-blinded concurrence study" comparing the new x-ray detectors (EVS 3643G) to predicate devices to establish equivalent diagnostic capability. It is not an MRMC comparative effectiveness study evaluating the improvement of human readers with AI assistance. The device itself is a digital X-ray detector, not an AI-powered diagnostic tool. Therefore, there is no mention of effect size related to human reader improvement with AI.

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

The device is a digital X-ray detector, which captures images. It is not an algorithm that performs a diagnostic task independently. Therefore, a standalone algorithm-only performance study is not applicable to this device. The non-clinical data focuses on inherent device performance characteristics like DQE, MTF, and Resolution.

7. The type of ground truth used

The document states that the "concurrence study" confirmed that the new x-ray detectors "provide images of equivalent diagnostic capability." This implies that the ground truth for the clinical images was established through expert consensus on diagnostic capability, rather than pathology or specific disease outcomes.

8. The sample size for the training set

The document does not mention a training set or its sample size. This device is a hardware component (digital X-ray detector) and not a machine learning algorithm that requires a training set for model development.

9. How the ground truth for the training set was established

As there is no mention of a training set, the method for establishing its ground truth is also not applicable.

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