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Intended for use by a qualified/trained physician or technician on both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography.

RadmediX AcuityPDR combines components into a complete mobile x-ray system, including software, a generator/collimator combination, and digital radiography panels. Radmedix combines components from various manufacturers into a complete mobile x-ray system. The customer selects one (or more) of the following digital x-ray receptor panels: DRTech 4343A, (K192400); DRTech 4343W, (K193017); AcuityDR (K171137); AcuityDR 1417 (K162552 EVS 3643, EVS 3643G) or AcuityDR 1717 (K162555 EVS 4343, EVS 4343G). In addition, the customer selects one of three software packages: Accuvue+ (K130883), AccuVueMED, (K152172) or AccuVue (K141440). The generator can be battery operated. A single battery charge produces 200 Exposures at max KV and MAS settings. The battery charger is UL Listed and the internal lithium ion battery is overcharge and overcurrent protected. A typical acquisition computer would be a Lenovo P53S or a Dell Precision 3541.

This document describes a medical device, AcuityPDR, a mobile X-ray system, and its 510(k) submission for FDA clearance. The submission relies on demonstrating substantial equivalence to a predicate device (MinXray CMDR 2CW).

Here's an analysis of the requested information based on the provided text:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state acceptance criteria in the form of quantitative performance metrics for the AcuityPDR device itself. Instead, it focuses on demonstrating "substantial equivalence" to a predicate device. The acceptance criteria for this type of submission are typically that the device performs as safely and effectively as the predicate and has the same indications for use.

The device performance is reported implicitly through the comparison table on page 4, showing that the AcuityPDR either matches or has comparable/equivalent functionality to the predicate in various technical parameters.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document explicitly states in section 6, "Clinical testing. Not required for a determination of substantial equivalence." This indicates that no clinical test set was used for this specific submission. The submission relies on non-clinical testing (bench testing, standards compliance) and comparison to the predicate device.

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)

Since no clinical test set was required or used for this submission, there is no mention of experts being used to establish ground truth for a test set.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

As no clinical test set was used, no adjudication method is mentioned.

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 MRMC study was performed as clinical testing was "Not required for a determination of substantial equivalence." The device is a mobile X-ray system, not an AI-powered diagnostic tool, so the concept of human readers improving with AI assistance is not applicable in this context.

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

This is not an AI algorithm; it's a mobile X-ray system. Therefore, standalone algorithm performance is not applicable. The performance is assessed through compliance with electrical and safety standards for X-ray devices and comparison of technical specifications to a predicate.

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)

For this type of 510(k) submission, "ground truth" is primarily established by:

• Compliance with recognized electrical, safety, and performance standards for X-ray generating equipment (e.g., IEC 60601 series, 21 CFR 1020).
• Demonstration that the device's technical specifications and intended use are substantially equivalent to a legally marketed predicate device.
• Component certifications: "All of the components subject to the CDRH performance standard are certified to comply with the standard by their respective manufacturers."

8. The sample size for the training set

The document does not describe a training set for an AI model, as this is not an AI device. The "training" for such a device would refer to its design and manufacturing processes adhering to established engineering principles and standards.

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

Not applicable, as no AI model or training set is described. The "ground truth" for the device's design and manufacturing relies on established medical device regulations, design controls, and industry standards for X-ray imaging equipment.

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