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Clio Prime and Clio Pedo are USB-driven, digital intraoral x-ray sensors which are intended to acquire dental intraoral radiography images. Clio Prime or Clio Pedo shall be operated by healthcare professionals who are educated and competent to perform the acquisition of dental intraoral radiographs. Clio Prime or Clio Pedo can be used either in combination with special positioning devices to facilitate positioning and alignment with an x-ray beam, or Clio Prime or Clio Pedo can also be positioned by hand with the assistance of the patient.

Clio Prime and Clio Pedo are USB-driven digital sensors designed for health care professionals already acquainted with the standard procedures for acquiring dental intra-oral radiographs. Digital x-ray imaging is an aide for diagnosis and should always be confirmed by the doctor using additional Clio Prime or Clio Pedo procedures and other diagnostic aides for confirmation. Clio Pedo is a smaller version of Clio Prime and is for pediatric use. The Clio Prime and Clio Pedo design uses advanced ergonomic principles with four beveled corners, a moderate profile, and a rounded casing providing enhanced comfort for patients. Clio Prime or Clio Pedo is positioned in the patient's mouth in the same manner as intra-oral film is positioned. Each of Clio Prime and Clio Pedo has a CMOS x-ray imager that creates a digital imaqe from x-ray doses perceptible by the sensor. The digital image created is immediately visible on the screen of a personal computer connected to Clio Prime or Clio Pedo through the standard USB port. Image analysis software is not part of the submission. For Clio Prime or Clio Pedo to be used in a dental practice, an optional image analysis software will be necessary. Only with image analysis software can acquired images be optimized for specific diagnostic tasks, archived as image files, and printed out on a suitable printer. Software provides drivers and utilities for x-ray dose optimization, sensor activation and settings.

Here's an analysis of the provided text regarding the acceptance criteria and supporting study for the Clio Prime and Clio Pedo devices:

1. Table of Acceptance Criteria and Reported Device Performance:

The document primarily focuses on establishing substantial equivalence to predicate devices rather than defining specific numerical acceptance criteria. The key performance metric explicitly compared is the Modulation Transfer Function (MTF).

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

• Test Set Sample Size: Not explicitly stated as a number of distinct cases or patients. The clinical study involved providing "clinical images," but the quantity is not specified.
• Data Provenance: Not explicitly stated. The document refers to a "clinical study performance testing," but does not mention the country of origin, nor whether it was retrospective or prospective.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. The document only states that "Clio Prime or Clio Pedo shall be operated by healthcare professionals who are educated and competent to perform the acquisition of dental intraoral radiographs." It does not mention who evaluated the clinical images for ground truth.

4. Adjudication Method for the Test Set:

• Adjudication Method: Not specified.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of Improvement with AI vs. Without AI Assistance:

• MRMC Study: No MRMC study was described. The device is a digital intraoral x-ray sensor, not an AI-assisted diagnostic tool. Its performance was compared against predicate sensors.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done:

• A standalone performance characterization of the sensor itself was conducted through bench testing, specifically the MTF comparison. However, the device is explicitly intended to be used by trained healthcare professionals, and "Image analysis software is not part of the submission." Therefore, a standalone "algorithm only" performance (in the context of automated diagnosis) is not applicable or described for this device. The closest is the physical sensor performance.

7. The Type of Ground Truth Used:

• The document implies a combination of:
  • "Clinical images" from a clinical study, suggesting a comparison of image quality or diagnostic utility against a clinical gold standard (though not explicitly defined).
  • Bench testing data (e.g., MTF), which relies on standardized physical measurements and engineering specifications as ground truth.
  • Comparison to predicate devices: The primary method for establishing "substantial equivalence" is direct comparison of parameters and performance with an already cleared device.

8. The Sample Size for the Training Set:

• Not applicable/Not provided. The document describes a medical device (digital x-ray sensor), not a machine learning or AI model that requires a distinct training set.

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

• Not applicable/Not provided, as there is no mention of a training set for a machine learning model.

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