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0909FCC and 0909FCC-HS are indicated for digital imaging solution designed including head, neck, cervical spine, arm, leg and peripheral (foot, hand, wrist, fingers, etc.). The detectors are intended to replace the x-ray imager on film based radiographic diagnostic systems. Not to be used for mammography.

0909FCC and 0909FCC-HS are digital solid state X-ray detectors based on flat-panel technology. This radiographic image detector and processing unit consists of a scintillator coupled to Indium Ginc Oxide (IGZO) on TFT sensor. This device is connected to the user PC via wired LAN (ethernet cable) and it needs to be integrated with a radiographic imaging system. It does not operate as an X-ray generator controller but 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 separate console SW(Xmaru RF Lite) for a radiographic diagnosis and analysis. 0909FCC is a basic model. 0909FCC-HS is identical with a basic model except for marking of sheet not related to safety. 0909 FCC and 0909 FCC-HS are intended to capture dynamic images. The Xmaru RF lite imaging software is included in the system but the computer that receives the digital images is not provided with the system.

0909FCC and 0909FCC-HS are compatible with the X-ray generator, HTC-35B by Poskom Co.,Ltd, which is not provided with the system.

The provided text does not contain information about acceptance criteria for a diagnostic AI device, nor does it describe a study proving such a device meets acceptance criteria. The document is a 510(k) premarket notification for a digital flat panel X-ray detector (0909FCC, 0909FCC-HS), which is a hardware component for X-ray imaging systems, not an AI diagnostic device.

The summary of the document focuses on demonstrating substantial equivalence of the new detectors to a previously cleared predicate device (1212FCA). The "performance testing" section describes non-clinical bench testing related to image quality metrics of the X-ray detector itself, such as MTF (Modulation Transfer Function), DQE (Detective Quantum Efficiency), and NPS (Noise Power Spectrum), as per IEC 62220-1. These are physical performance characteristics of the imaging hardware, not diagnostic performance of an AI algorithm interpreting images.

Therefore, I cannot provide the requested information regarding acceptance criteria, study details, sample sizes, expert ground truth, adjudication methods, MRMC studies, or standalone AI performance, as these elements are not present in the provided text.

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