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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.

This device is not intended for use on patients less than approximately 21 kg (46 lb) in weight and 113 cm (44.5 in) in height; these height and weight measurements approximately correspond to that of an average 5 year old.

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, Panoramic scan) and Cephalometric Scan.

This FDA 510(k) summary does not contain information about an AI/ML-based medical device. Instead, it describes a Computed Tomography X-Ray System (PreXion3D Explorer PRO) which is a hardware device used for generating X-ray images, and the accompanying software primarily performs image analysis and reconstruction, not AI-driven diagnostic assistance.

Therefore, the requested information regarding acceptance criteria and study proving device meets acceptance criteria, including details about sample sizes, expert qualifications, ground truth establishment, MRMC studies, and standalone performance for an AI/ML-based system, cannot be extracted from the provided text.

The document details the technical specifications of the PreXion3D Explorer PRO and compares it to a predicate device (an earlier model of the same product). The performance data mentioned are non-clinical hardware and software verification tests against established standards (e.g., electrical safety, electromagnetic compatibility, radiation safety, software verification and validation, biocompatibility), not clinical performance data related to diagnostic accuracy validated through expert reads or ground truth.

Summary of what is present:

• Device: PreXion3D Explorer PRO, a Computed Tomography X-Ray System.
• Purpose: Produces 2D (panoramic, cephalometric) and 3D (CT) digital x-ray images of dental, oral, maxillofacial, ENT, and neck regions for diagnostic support.
• Predicate Device: PreXion3D Explorer PRO (Model: P03A), K203784.
• Evidence for Substantial Equivalence: Primarily non-clinical performance data demonstrating compliance with various national and international standards (e.g., IEC 60601 series, ISO 10993 series, IEC 62304 for software).
• Clinical Performance Data: "There was no human clinical testing required to support the medical device as the indications for use is equivalent to the predicate device." This explicitly states that no clinical studies were performed for this submission to prove performance against specific diagnostic objectives, as it relies on the predicate's established safety and efficacy.

Information NOT present (and therefore cannot be provided as requested):

• Acceptance criteria related to AI/ML diagnostic performance (e.g., sensitivity, specificity, AUC).
• Any details about a study demonstrating the device meets such AI/ML performance acceptance criteria.
• Sample sizes for test sets where ground truth for AI performance is established.
• Data provenance for AI/ML test sets.
• Number/qualifications of experts for ground truth establishment.
• Adjudication methods.
• MRMC comparative effectiveness study results or effect sizes for human readers with/without AI assistance.
• Standalone (algorithm-only) performance.
• Type of ground truth used (expert consensus, pathology, outcomes data).
• Sample size for AI/ML training set.
• How ground truth for an AI/ML training set was established.

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