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The 2430TCA Digital Flat Panel X-Ray Detector is indicated for digital imaging solution designed for a mammographic system. It is intended to replace film or screen based mammographic systems in screening mammography. Xmaru W is an integrated software solution indicated for use with the 2430TCA detector.

2430TCA is a digital mammography X-ray detector that is based on flat-panel technology. This mammographic image detector and processing unit consists of a CsI scintillator coupled to a TFT sensor. This device needs to be integrated with a mammographic imaging system. It can be utilized to capture and digitalize X-ray images for mammographic screening. The RAW files can be further processed as DICOM compatible image files by separate console SW, Xmaru W, for a mammographic screening. 2430TCA detector is connected to the viewing station via a LAN cable.

The provided text is a 510(k) summary for the Rayence 2430TCA with Xmaru W, a digital mammography system. While it discusses the device's characteristics and compares it to a predicate device (2430MCA with Xmaru W), it does NOT contain detailed information about acceptance criteria for an AI/software component, nor a specific study proving it meets such criteria in terms of AI performance.

The document primarily focuses on demonstrating substantial equivalence of the detector (2430TCA) to its predicate (2430MCA) based on physical characteristics, imaging performance (MTF, DQE, NPS), and human expert review of images. It also mentions general software (Xmaru W) but doesn't detail any AI functionality or its validation.

Therefore,Based on the provided FDA 510(k) summary, I cannot provide the requested information about acceptance criteria and a study proving an AI component of the device meets those criteria.

The document discusses the substantial equivalence of a Full-Field Digital Mammography System (including a detector and image processing software). It focuses on the hardware (2430TCA detector) and its image quality parameters (MTF, DQE, NPS) compared to a predicate device. While it mentions "Xmaru W is an integrated software solution," it does not describe any specific AI or machine learning functionality within this software, nor does it discuss validation studies for such a component.

The "Summary of Performance Testing" section describes:

• Human expert review of plain radiographic images from the 2430TCA and 2430MCA, concluding "overall, better image quality of the same anatomical position in the separate patients" for 2430TCA.
• Non-clinical tests (MTF, DQE, NPS) performed on the detector, not an AI algorithm.

Therefore, many of the specific points you've asked for (e.g., sample size for test set, number of experts for ground truth, adjudication method, MRMC study, standalone performance, training set details) are not present in this document because it is focused on the performance of a digital X-ray detector and its fundamental image quality, not an AI algorithm.

If this device were to have an AI component for advanced image analysis (e.g., CADe for lesion detection), that information would typically be in a separate section detailing the AI's performance validation, often with a different set of acceptance criteria and study designs that align with the specific AI function (e.g., sensitivity, specificity, FROC analysis, reader studies). This document does not suggest the presence or validation of such an AI component for diagnostic aid.

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