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The X-View 3D PAN/X-View 2D PAN panoramic and cephalometric device is intended for dental radiographic examinations of teeth, jaw and TMJ areas by producing conventional 2D X-ray images as well as X-ray projection images of examined volume for the reconstruction of 3D view. The X-View 3D PAN/X-View 2D PAN dental panoramic and cephalometric device is intended for general populations as long as they are older than 10 years.

The device must only be operated and used by dentists and other legally qualified professionals.

The X-View PAN is manufactured by Trident s.r.l. and it can be sold under two different commercial names:

• X-View 3D PAN
• X-View 2D PAN

Both devices, depending on the configuration chosen, can be equipped with a cephalometric arm equipped with a 24x30 cm flat panel sensor for the execution of cephalometric radiographs of various formats and latero-lateral and antero-posterior projections. The cephalometric device can also be added in the field.

The device can be set in the configurations: Floor version with column and wall bracket and Floor version with column and standard base.

The subject dental X-ray system X-View is supported by software (firmware). The software is of Moderate Level of concern and is FDA-cleared.

The provided text is a 510(k) Summary for a medical device called X-VIEW 3D PAN/X-VIEW 2D PAN. It describes the device, its intended use, comparison to predicate devices, and performance data. However, the document does not contain information about specific acceptance criteria, a detailed study proving the device meets those criteria, or the specific performance metrics (e.g., sensitivity, specificity) of the device.

The document primarily focuses on demonstrating substantial equivalence by:

• Comparing technological characteristics with predicate devices.
• Listing adherence to various international standards (IEC 60601-1, IEC 60601-1-2, IEC 60601-1-3, IEC 60601-1-6/IEC 62366-1, IEC 60601-2-63, IEC 60825-1).
• Mentioning software verification and validation, risk analysis (ISO 14971), and biocompatibility.
• Stating that "Clinical tests were performed both in Italy at the University of Genoa and the clinical judgment made by ABR, President of Dental Imaging Consultants, LLC, have demonstrated the clinical validity of the X-View systems both in the execution of PAN-type exams and 3D volumetric exams. Images were presented and approved by the ABR Consultant." This is a general statement about clinical validation, not a detailed performance study with specific metrics, sample sizes, or ground truth establishment.

Therefore, I cannot provide the requested information from the given document as it does not contain quantifiable performance data or specified acceptance criteria for algorithm performance. The document focuses on showing the device is substantially equivalent to existing devices based on technical specifications and adherence to safety and performance standards rather than demonstrating specific diagnostic performance metrics of an AI or algorithmic component.

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DC-Air™, Athlos-1, Athlos-Air are intended to be used for a radiographic examination by a dental professional to assist in the diagnosing of diseases of the teeth, jaw, and oral structures.

DC-Air™, Athlos-1, Athlos-Air are suitable for general populations.

The subject device DC-Air™ (also known as Athlos-Air) is a wireless intraoral digital X-ray system that comprises of three (3) main components:

• (1) An intraoral X-ray image detector (sensor) with rechargeable battery for capturing X-ray images and which connects to the docking station via a wireless communications protocol (Bluetooth 5.0),
• (2) A docking station that acts as the receiver of the data (X-ray image) sent by the detector and which forwards the data to the operator's personal computer (PC) via USB connection. Also, the docking station functions as a charging station of the detector, and
• (3) An Imaging Software package.

The provided text describes the regulatory filing for the DC-Air™ device, focusing on its substantial equivalence to a predicate device (QuickRay HD). While it mentions performance data, it does not detail a comprehensive study with specific acceptance criteria, corresponding performance metrics, sample sizes, expert ground truth establishment, or MRMC studies that would typically be required to prove device performance against predefined acceptance criteria. Instead, it provides a general statement that images were "examined by doctors... and found to be diagnostically relevant and reliable" (Page 12, Performance Data 8).

Therefore, I cannot fulfill all parts of your request with the provided input. I will highlight what information is present and indicate what is missing.

Missing Information:

• Specific Acceptance Criteria: The document does not list quantitative acceptance criteria (e.g., minimum sensitivity, specificity, or AUC).
• Reported Device Performance against Acceptance Criteria: Since acceptance criteria are not stated, there is no direct table showing the device meeting these criteria. The document states images were "diagnostically relevant and reliable" but provides no quantitative metrics.
• Sample Size for the Test Set: No specific number of images or patients in a test set is provided.
• Data Provenance (Country of Origin, Retrospective/Prospective): This information is not explicitly stated for the "examined images."
• Number of Experts and Qualifications for Ground Truth: While three doctors are named (Robert Sachs D.D.S., John M. Steinberg D.D.S., and Steven R. Gluck D.D.S.), their specific qualifications beyond "D.D.S." (Doctor of Dental Surgery) and their experience levels are not detailed.
• Adjudication Method: No method for resolving discrepancies among experts (e.g., 2+1, 3+1) is described.
• Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: The document does not mention an MRMC study or any comparison of human readers with vs. without AI assistance. The device itself is an X-ray sensor, not an AI diagnostic aid.
• Standalone Performance: The performance data mentioned (Page 12, Performance Data 8) describes human examination of images from the device, not a standalone algorithm's performance.
• Type of Ground Truth Used: The ground truth appears to be expert consensus (the three D.D.S. doctors), but it's not explicitly labeled as such, nor are specifics on how this consensus was reached.
• Sample Size for the Training Set: This is a performance study, not an AI training study. The device is a hardware sensor.
• Ground Truth Establishment for Training Set: Not applicable as it's a hardware device, not an AI model.

Here's a summary of the available information regarding the device's performance assessment:

Device: DC-Air™, Athlos-1, Athlos-Air (Intraoral Digital X-ray Sensor)

Study Purpose (Implied): To demonstrate the diagnostic relevance and reliability of images produced by the DC-Air™ sensor.

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: Not specified. The text mentions "X-ray images taken using the DC-Air™," implying an unspecified number of images.
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).

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

• Number of Experts: Three.
• Qualifications: Doctors Robert Sachs D.D.S., John M. Steinberg D.D.S., and Steven R. Gluck D.D.S. (Doctor of Dental Surgery). No further detail on experience (e.g., years in practice, specialization) is provided.

4. Adjudication Method for the Test Set:

• Method: Not specified. It's only stated that the doctors "examined" the images and "found" them to be diagnostically relevant and reliable, implying a consensus or individual findings without detailing the agreement process.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• No, a MRMC comparative effectiveness study was not explicitly mentioned or performed. This device is an imaging sensor, not an AI-based diagnostic tool. The performance claim relates to the quality of the generated images for human interpretation, not an AI's impact on human reading.

6. Standalone Performance:

• Not directly applicable in the AI context. The performance mentioned refers to the quality of the images produced by the sensor for human interpretation, not an algorithm performing a diagnostic task independently.

7. The Type of Ground Truth Used:

• Type: Expert consensus (from the three D.D.S. doctors). No mention of pathology or outcomes data as ground truth.

8. The Sample Size for the Training Set:

• Not applicable. This document describes the testing of a hardware device's image output, not the training of a machine learning model.

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

• Not applicable. (See point 8).

Summary of Device Features and Technical Benchmarking (from Table 6-1):

While not directly "acceptance criteria" for a study proving clinical performance in the AI sense, the document does list various technical specifications and comparisons to the predicate device. These are more akin to engineering and imaging performance metrics rather than clinical outcome measures.

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I-View Gold sensors are digital dental intraoral sensors intended to collect dental x-ray photons and convert them into electronic impulses that may be stored, viewed, and manipulated for diagnostic use by dentists.

The subject I-View Gold and Imagen Gold sensors are intraoral digital x-ray systems comprised of two components: (1) an intraoral detector which connects to a PC via a USB port: and (2) an Image Management Software package.

The subject comes in two sizes: Size 1 is 600mm² and Size 2 is 884mm² and two brand names.

Direct digital systems acquire images with a sensor that is connected to a computer to produce an image almost instantaneously following exposure.

This document describes the marketing clearance for the I-View Gold and Imagen Gold Dental Sensors (K200625). The submission focuses on demonstrating substantial equivalence to a legally marketed predicate device (EzSensor Classic, K153060), rather than providing detailed acceptance criteria and a standalone study proving the device meets those specific acceptance criteria for performance metrics like diagnostic accuracy.

The FDA's 510(k) clearance process primarily evaluates whether a new device is "substantially equivalent" to a legally marketed predicate device in terms of intended use, technological characteristics, and safety and effectiveness. It does not typically require the applicant to establish novel performance acceptance criteria or conduct a de novo clinical study to prove those criteria are met, especially for devices with well-understood technology and established clinical pathways like dental X-ray sensors.

Therefore, the requested information regarding "acceptance criteria" and "the study that proves the device meets the acceptance criteria" in the context of diagnostic performance (e.g., sensitivity, specificity, accuracy for a specific clinical task) is not found in this 510(k) summary. The document focuses on demonstrating that the new device functions similarly and is as safe and effective as the predicate based on bench testing (SSIX Report, electrical safety, EMC, software documentation) and comparison of technical specifications.

Here's a breakdown of what can be extracted about "acceptance" and "testing" from the provided document, framed within the substantial equivalence argument, and what information is not available:

Information Available/Inferred from the Document:

1. A table of acceptance criteria and the reported device performance:

   • Acceptance Criteria (Implied for Substantial Equivalence): The implicit "acceptance criterion" is that the technological characteristics and performance are comparable to the predicate device (EzSensor Classic, K153060) to ensure equivalent safety and effectiveness.
   • Reported Device Performance (Comparative Metrics): The table Compares technological characteristics. The "performance" here refers to measured physical and technical parameters, not diagnostic accuracy. The reported values for the subject device are expected to be sufficiently similar to the predicate to establish equivalence.

   Characteristic	Acceptance Criteria (Implicit: Comparable to Predicate)	Reported Device Performance (Subject Device)	Predicate Device Performance
   Common Name	Intraoral Digital X-Ray Sensor	Intraoral Digital X-Ray Sensor	Intraoral Digital X-Ray Sensor
   Indications for Use	Same as predicate	Same as predicate	Same as subject
   Intended Use	Same as predicate	Same as predicate	Same as subject
   Principles of operation	Same as predicate ('X-ray radiation => scintillator => fiber optic => CMOS => electronics => PC')	Same as predicate	Same as subject
   Sensor Thickness (mm)	4.8 mm	4.8	4.8
   USB Module	Integrated USB 2.0 module	Integrated USB 2.0 module	Integrated USB 2.0 module
   Pixel Pitch (Full/Binning mode)	14.8 / 29.6	14.8 / 29.6	14.8 / 29.6
   DQE (6lp/mm, Full/Binning mode)	0.38 / 0.34	0.38 / 0.34	0.38 / 0.34
   MTF (3lp/mm, Full/Binning mode)	0.642 / 0.630	0.642 / 0.630	0.642 / 0.630
   Typical dose range (Incisor & Canine)	300 ~ 500	300 ~ 500	300 ~ 500
   Typical dose range (Molar)	400 ~ 600	400 ~ 600	400 ~ 600
   Standards of Conformity	Compliance with relevant IEC/ISO standards	Listed standards achieved	Listed standards achieved
   Biocompatibility	Not warranted (no patient contact)	Not warranted (no patient contact), single-use protective barrier used	Not warranted (no patient contact), single-use protective barrier used
   Electrical Safety & EMC	Compliance with IEC 60601-1, IEC 60601-1-2	Conforms to standards	Conforms to standards

2. Sample sizes used for the test set and the data provenance:

   • Test Set Sample Size: Not applicable/Not specified for a clinical performance test. The "test set" here refers to the physical units subjected to bench testing (e.g., for electrical safety, EMC, SSIX report). The sample size for these engineering tests is not provided in this summary.
   • Data Provenance: The tests are "Non-Clinical Performance Data." There is no mention of patient data (images) or their provenance (country of origin, retrospective/prospective) because a clinical study was not presented for this 510(k) submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not applicable. No clinical test set with ground truth established by experts is described, as this is a substantial equivalence submission relying on bench testing and comparison to a predicate, not a de novo clinical performance study for diagnostic accuracy.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not applicable. No clinical test set requiring adjudication is described.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No. This device is a digital X-ray sensor, not an AI-powered diagnostic aid. Therefore, no MRMC study or assessment of AI assistance to human readers was performed or presented.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • Not applicable. This device is a hardware sensor with image acquisition and management software, not an algorithm for autonomous diagnostic performance.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • Not applicable for clinical ground truth. The "ground truth" for the non-clinical tests would be defined by engineering specifications and reference standards (e.g., a calibrated measurement for DQE, MTF).

8. The sample size for the training set:

   • Not applicable. This is a hardware device with associated image processing firmware/software, not a machine learning model that requires a training set in the AI sense.

9. How the ground truth for the training set was established:

   • Not applicable. See point 8.

Summary of what's provided related to "proving" performance:

The document states "Bench tests were performed and the SSIX Report is shown in this submission. Additional certificates for the device are also within this submission." These tests (e.g., DQE, MTF, electrical safety, EMC) provide objective measurements of the device's physical and technical performance parameters, which are then compared to the predicate device to argue for substantial equivalence. The "proof" here is that these technical specifications are essentially identical to those of the cleared predicate device, and the device conforms to relevant safety and performance standards (IEC, ISO).

In a 510(k), especially for a device like this, the "acceptance criteria" for clearance are primarily:

• Same intended use as the predicate.
• Same technological characteristics as the predicate OR different technological characteristics that do not raise new questions of safety and effectiveness.
• Performance data (bench testing) demonstrating that the device is as safe and effective as the predicate.

This submission explicitly concludes: "The subject and the predicate device have the same intended use and the same technological features. I View Gold and Imagen Gold Sensors and share the same principles of operation, sensor technology, use the same USB connection to PC and use similar imaging firmware. The conclusion is that the subject device is as safe and effective as the predicate." The "study" proving this is the collection of non-clinical bench tests and the detailed comparative analysis of technical specifications presented in the submission.

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