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The AeroDR SYSTEM 2 is indicated for use in generating radiographic images of human anatomy. It is intended to replace radiographic film/screen system in general-purpse diagnostic procedures.

The AeroDR SYSTEM 2 is not in mammography. fluoroscopy, tomography and angiography applications.

The AeroDR SYSTEM 2 is a digital imaging system to be used with diagnostic x-ray systems. A new AeroDR Detector (flat panel digital detector: hereafter P-51) and AeroDR Generator Interface Unit2 has been just added to AeroDR SYSTEMS (The predicate devices:K102349, K113248, K120477, K130936) to function together such as with Console CS-7 (operator console), AeroDR Interface Unit, AeroDR Interface Unit2, AeroDR Generator Interface Unit, AeroDR Access Point and AeroDR Battery Charger, AeroDR Battery Charger2 and perform fundamentally same as Aero DR SYSTEMS do in physical and performance characteristics such as in device design, material safety and physical properties. Therefore, images captured with the flat panel digital detector in the AeroDR SYSTEM 2 can be communicated to the operator console via wired connection or wireless, depend on user's choice. The AeroDR SYSTEM 2 is just developed to meet user's compact layout needs without changing fundamental functions of the predicate devices.

AeroDR SYSTEM 2 is only connected with X-ray devices which are regally marketed in the United States of America and are compatible with XGIF, UEC, XIF Board along with certain electronic requirement, Specific signal controls for hardware and software and accessories described in Operation manual and Installation manual which is also fulfilled how to compatibility test at the time of installation also. In addition, for the use of pediatric, X-ray control system for pediatric are required.

The provided document, a 510(k) summary for the AeroDR SYSTEM 2, does not contain detailed information about acceptance criteria and a study proving the device meets those criteria in the format requested. The document focuses on demonstrating substantial equivalence to a predicate device, AeroDR SYSTEMS.

However, based on the information provided, here's what can be extracted and inferred:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly list specific quantitative acceptance criteria or a performance table. Instead, it states that the AeroDR SYSTEM 2 was evaluated for "equivalent evaluation outcome" to the predicate device. The performance characteristics mentioned are qualitative comparisons to the predicate device.

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

The document mentions "Non clinical and clinical testing" but does not specify the sample size for these tests or the data provenance (e.g., country of origin, retrospective/prospective).

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

This information is not provided in the document.

4. Adjudication Method for the Test Set:

This information is not provided in the document.

5. Multi Reader Multi Case (MRMC) Comparative Effectiveness Study:

The document does not mention an MRMC comparative effectiveness study or any effect size of human readers improving with AI vs. without AI assistance. The AeroDR SYSTEM 2 is a digital radiography system, not an AI-assisted diagnostic tool.

6. Standalone Performance:

The document implies standalone performance testing ("Bench Testing," "Non clinical and clinical testing") was conducted to demonstrate equivalence to the predicate device. However, it does not explicitly state "algorithm only without human-in-the-loop performance" as would be relevant for an AI device. As it's a hardware/software system for image generation, its standalone performance refers to its ability to capture and process images equivalently to the predicate.

7. Type of Ground Truth Used:

The document does not explicitly state the type of ground truth used for the "clinical testing." Given the context of a diagnostic imaging system, it would typically involve images reviewed against a clinical standard, but the specific nature (e.g., expert consensus, pathology, outcomes data) is not detailed.

8. Sample Size for the Training Set:

The document does not mention a training set or its size. This is consistent with a device seeking substantial equivalence to a predicate, where the focus is on verification and validation against established standards and predicate performance rather than training a novel algorithm from scratch.

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

Not applicable, as no training set is mentioned for an AI model.

Summary of what is present and absent regarding acceptance criteria and study details:

The document primarily acts as a 510(k) summary, aiming to prove substantial equivalence to existing predicate devices based on various safety, performance, and technical characteristics. It asserts that "equivalent evaluation outcome" was achieved in performance, non-clinical, and clinical testing, and that there were "no safety and effectiveness and performance issue or no differences were found" compared to the predicate. However, it lacks the detailed quantitative acceptance criteria, specific study designs, sample sizes, and expert qualification information that would be typically found for studies evaluating novel AI algorithms or clinical efficacy with precise endpoints.

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