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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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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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RiX70 DC X-ray Unit is designed for use in dental surgery to make endo-oral x-rays for diagnostic purposes. This equipment can be used to produce traditional x-rays developed using chemicals or, alternatively, it can be used with digital x-ray sensors.

The subject device is RiX70 DC X-rav Unit and it is an extraoral source dental x-ray system intended for intraoral imaging. The subject device is a device comprised of a double mobile and articulate support arm. At the opposite ends of the arm are located, respectively:

• A control unit equipped with wall plate, extension arm and wired control . device.
• A tube head with x-ray tube.
  X-ravs are produced using the high frequency and constant potential generators with a built in round collimator with the high frequency (HF) technology. X-rav emission at 70 kV and 7 mA (maximum power), and the xray unit automatically calculates the best exposure time (from 0.01 s to 2.00 s) based on the selected tooth and patient size, as well as an adjustable arm that allows for easy positioning. This device may also be adjusted manually to the user's specific radiographic technique.
  The system can be used either with conventional film or a digital imaging system.
  The RiX70 DC is available in two configurations: a wall-mount configuration and a floor-standing configuration, and provides for three selections of kVp: 60kVp, 65kVp, and 70kVp.

This submission is for an X-ray unit, which is hardware, not an AI/ML device. Therefore, the questions related to AI/ML device performance and testing (e.g., sample size for test set, number of experts, adjudication method, MRMC study, standalone performance, training set details) are not applicable.

Here's an analysis of the provided document focusing on the acceptance criteria and study for the RiX70 DC X-ray Unit:

Acceptance Criteria and Study for RiX70 DC X-ray Unit

The provided document describes the substantial equivalence determination for the RiX70 DC X-ray Unit to a predicate device (RX DC). The acceptance criteria primarily revolve around meeting recognized performance standards and demonstrating similar technological characteristics and safety profiles to the predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is an X-ray unit and not an AI/ML device, the acceptance criteria are based on compliance with electrical, safety, and performance standards. The "reported device performance" reflects the device's conformity to these standards and its characteristics compared to the predicate.

Study Proving Device Meets Acceptance Criteria:

The study to prove the device meets acceptance criteria is primarily a non-clinical performance study focusing on bench testing and compliance with recognized standards.

• Type of Study: Non-clinical (bench testing, standards compliance, comparison to predicate).
• Methodology:
  • Direct Comparison with Predicate Device: A detailed comparison of technological characteristics (Table 5.1) was performed to demonstrate substantial equivalence in terms of intended use, indications for use, and technological features. Differences were noted and implicitly deemed not to raise new questions of safety or effectiveness.
  • Compliance Testing to Recognized Standards: The device underwent rigorous testing to ensure conformity with various IEC and ISO standards related to medical electrical equipment safety, electromagnetic compatibility (EMC), radiation protection, usability, and software lifecycle processes.
  • Risk Analysis: A risk management process was conducted in accordance with ISO 14971.

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

• Sample Size: Not applicable in the traditional sense for an AI/ML model's test set. For an X-ray unit, the "sample" would be the device itself subjected to various tests outlined by the standards. These tests are typically performed on a limited number of units (e.g., one or a few production units) to demonstrate design and manufacturing compliance. The document does not specify the exact number of units tested but implies that tests were performed on the "subject device."
• Data Provenance: Not applicable in the context of clinical data provenance for an AI/ML model. The "data" here refers to test results from a lab environment. The CB certificate from IMQ Italy indicates the testing body and country of origin for the compliance testing.

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

• Not applicable. This is not an AI/ML device requiring expert ground truth for image interpretation. The "ground truth" for an X-ray unit is its ability to meet engineering specifications and safety standards as measured by calibrated equipment and assessed by qualified test engineers and regulatory bodies.

4. Adjudication Method for the Test Set:

• Not applicable. There is no subjective interpretation or consensus-building on image findings. Compliance is determined by objective measurements against predefined thresholds in standards.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done:

• No, an MRMC study was not done. This device is an X-ray unit, which produces images, it does not interpret them with or without AI assistance.

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

• Not applicable. This is an X-ray unit, not an AI/ML algorithm. Its "standalone performance" is its ability to generate X-rays within specified parameters and meet safety standards.

7. The Type of Ground Truth Used:

• Engineering Specifications and Recognized International Standards: The "ground truth" for this device is compliance with the objective electrical, mechanical, radiation, and software safety requirements defined in the listed IEC and ISO standards (e.g., IEC 60601-1, IEC 60601-1-2, IEC 60601-1-3, IEC 60601-1-6, IEC 60601-2-65, IEC 62304, IEC 62366, ISO 14971). The device's performance metrics (like leakage radiation, focal spot size, tube voltage, current, exposure time) are compared against the requirements and specifications, some of which are standardized.

8. The Sample Size for the Training Set:

• Not applicable. This is an X-ray unit, not an AI/ML device that requires training data.

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

• Not applicable.

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I-View dental sensor is used for a radiographic examination by a dental professional to assist in the diagnosing of diseases of the teeth, jaw and oral structures.

The subject device I View is an 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 Mangement Software package.

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

The Size 1 sensor is also known as factory code S11684-12; Size 2 sensor is known as factory code S116845-12. I View and Imagen Sensor will both have Size 1 and Size 2. Two different trade names are for marketing purposes.

The provided text is a 510(k) summary for the "I View and Imagen Sensor" dental x-ray system, which is a Class II medical device. The document states that the subject device is substantially equivalent to a predicate device, the "QuickRay HD." The primary method used to demonstrate this equivalence is by asserting that the subject device is identical in hardware and firmware to the predicate device, with only the software package being different (though its functionality is claimed to be the same).

Here's an analysis of the acceptance criteria and the study as described in the document:

1. Table of Acceptance Criteria and Reported Device Performance

Because the device is claimed to be identical to a predicate that was already cleared, the acceptance criteria are largely linked to demonstrating this identity and conformity to relevant standards rather than establishing new performance metrics.

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

The document does not describe a new, specific "test set" in terms of patient images or cases for the subject device. Instead, it relies on:

• Clinical images from the predicate device: The text states, "Clinical images were examined by Dr. Parham... and found to be diagnostically relevant and reliable. These tests were provided for the predicate device submission..."
• The provenance of these predicate clinical images is vague, only mentioning "Dr. Parham, a qualified practitioner in Ormond Beach, FL." It does not specify the country of origin of the data nor whether it was retrospective or prospective.

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

• The document mentions one expert: "Dr. Parham, a qualified practitioner in Ormond Beach, FL."
• Qualifications: Described as a "qualified practitioner." No further details on specific certifications (e.g., dentist, radiologist), years of experience, or specialty are provided.

4. Adjudication Method for the Test Set

• None specified for the subject device. The reliance is on a single "qualified practitioner" for the predicate device's clinical images. There's no mention of a consensus or multi-reader adjudication process described for either the predicate's original evaluation or for the current submission.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, an MRMC comparative effectiveness study was not done. The submission establishes substantial equivalence primarily through technical and functional identity to a predicate device, not through a comparative clinical study. Therefore, no effect size of human readers improving with or without AI assistance is reported.

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

• No, a standalone study was not done as the device itself is a digital x-ray sensor for capturing images, not an AI algorithm for interpreting them without human involvement. The "Deep-View" software is an "image management software package" that assists dental professionals in diagnosing, implying human-in-the-loop performance. While the software has its own prior clearance (K160386), this document doesn't detail a standalone performance study for the interpretation aspect within this submission.

7. The Type of Ground Truth Used

• For the clinical performance validation (from the predicate device), the ground truth appears to be based on expert assessment/consensus (from Dr. Parham). The statement "found to be diagnostically relevant and reliable" implies an expert opinion as the ground truth. There is no mention of pathology, long-term outcomes data, or other objective measures for ground truth.

8. The Sample Size for the Training Set

• The document does not describe a training set in the context of machine learning or AI algorithms for image interpretation for this device. The software "Deep-View" is an image management software. If the term "training set" refers to data used to develop the core firmware/hardware for image acquisition, that information is not provided or deemed unnecessary given the equivalence claim to the predicate.

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

• As no training set (in the ML/AI sense) is described, this information is not applicable and not provided in the document. The device is an image acquisition hardware, not an image interpretation AI, making the concept of a "training set" for ground truth determination irrelevant to this 510(k) submission.

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ReadeR is a dental imaging system indicated for capturing, digitization and processing of intra oral x-ray images stored in imaging plate recording media.

ReadeR system is intended to be used only by dentist and other qualified dental professionals to process x-ray images exposed to the imaging plates from the intraoral complex of the skull.

The ReadeR is a computer radiography system which produces the x-ray diagnostic image in digital format instead of using traditional screens and film. This device does not have a wireless transmission. The device utilizes reusable x-ray storage phosphor plate (IP) that is sensitive to x-ray and stores latent image when it is exposed to x-ray. After x-ray exposure to the x-ray storage phosphor plate, x-ray storage phosphor plate is scanned by means of laser in the device. Latent image in the x-ray storage phosphor plates is released in a form of light by laser scanning. Then the light is collected and converted into a form of digital image. The signal processing is made to the digital image data such as the digital filtering, the gain and offset correction and flat fielding. The image can then be viewed on a computer workstation, adjusted if necessary, the stored locally, sent to an archive, printed or sent to PACS system.

After acquisition of the latent image from the x-ray storage phosphor plate, it is erased thoroughly to be reused.

The provided text is a 510(k) summary for the Trident s.r.l. device, ReadeR, VieweR, QuickScan PSP. It asserts substantial equivalence to a predicate device, the NICAL SMART MICRO CR System. However, it does not contain information about a study proving the device meets acceptance criteria in the way typically expected for a new device's performance claims.

Instead, the document's core argument for substantial equivalence is that the subject device is, in essence, the same as the predicate device with minor external differences and re-branding. This means the acceptance criteria and performance are essentially inherited from the predicate device.

Here's an attempt to extract and format the information as requested, with caveats due to the nature of the document:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a substantial equivalence submission based on the subject device being "the same" as the predicate, there are no specific "acceptance criteria" for the subject device beyond matching the predicate's specifications. The reported performance is essentially identical to the predicate.

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

• Sample Size for Test Set: The document mentions "Clinical images were provided" but explicitly states they "were not necessary to establish substantial equivalence" and that "bench performance data" was the primary basis. No specific sample size for a test set of clinical images used for a performance study is provided.
• Data Provenance: Not specified for any clinical images provided. The bench testing (e.g., electrical safety, EMC, software validation) was performed by laboratories in Italy and the USA.

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

• Not applicable. The document relies on the predicate device's established performance and bench testing of the subject device. There is no mention of expert-established ground truth for a clinical test set for the ReadeR device itself.

4. Adjudication Method for the Test Set

• Not applicable, as no described clinical performance test set requiring adjudication is detailed.

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 MRMC or comparative effectiveness study is mentioned. This device is an imaging system, not an AI-powered diagnostic tool, and the focus is on substantial equivalence to an existing device rather than reader improvement with AI.

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

• Not applicable. This is a hardware imaging system with associated software, not a standalone algorithm.

7. The Type of Ground Truth Used

• For the technical specifications, the "ground truth" is the established technical specifications and performance of the legally marketed predicate device, backed by bench test results for the subject device.
• "Clinical images were provided" but their role in establishing "ground truth" or performance criteria for this 510(k) is downplayed.
• No pathology or outcomes data is referenced for the subject device.

8. The Sample Size for the Training Set

• Not applicable. This document describes a medical imaging device, not an AI/machine learning model that would typically have a "training set."

9. How the Ground Truth for the Training Set was Established

• Not applicable, as there is no training set mentioned for an algorithm.

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