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PreXion3D Explorer PRO is intended to produce two-dimensional digital x-ray images including panoramic and cephalometric image, and three-dimensional digital x-ray images of the dental, oral, maxillofacial region, ENT (Ear, Nose and Throat) and neck region at the direction of healthcare professionals as diagnostic support for adult and pediatric patients. Cephalometric imaging also includes the hand and wrist to obtain carpus images for growth and maturity assessment.

PreXion3D Explorer PRO consists of a scanner, which is used for generating X-ray and detecting image data, and a console, which is used for operating the scanner and managing the data. The scan data acquired by the scanner will be transferred to the Console. PreXion3D Explore Image Analysis System will then perform the image analysis (2D/3D) or image edition (creating crosssection diagram, etc.), and output the image to a printer.

X-ray image data is acquired while the rotation arm is rotating around the secured "patient's head" at a constant speed. X-rays, which are emitted from X-ray generator (built in one side of rotation arm), pass through a patient and are detected by the flat panel detector (built in the other side of rotation arm). The detected X-ray absorption data is used to process image reconstruction on the Console to create the 3D image (CT scan), the tomographic image (CT scan, CT-Panoramic scan) and Cephalometric Scan.

The provided text is a 510(k) Premarket Notification summary for the PreXion3D Explorer PRO, a Computed Tomography X-Ray System. It primarily focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance data and does not contain information about the acceptance criteria or a study proving that the device meets specific performance criteria for an AI/CADe/CADx algorithm.

The document details the device's technical specifications, compared to predicate devices, and lists various standards it complies with (e.g., electrical safety, radiation safety, software validation, biocompatibility). It explicitly states: "There was no human clinical testing required to support the medical device as the indications for use is equivalent to the predicate device."

Therefore, based on the provided text, I cannot extract the information required to populate the fields related to acceptance criteria, clinical study design, expert involvement, or AI/software performance metrics (such as MRMC studies, standalone performance, or effect sizes of AI assistance). The device is a hardware imaging system, and its approval is based on equivalence to existing hardware, not on the performance of a novel AI algorithm that requires specific clinical validation metrics.

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