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PHT-65LHS is intended to produce panoramic, cephalometric or 3D digital x-ray images. It provides diagnostic details of the dento-maxillofacial, ENT, sinus and TMJ for adult and pediatric patients. The system also utilizes carpal images for orthodontic treatment. The device is to be operated by healthcare professionals.

Green16 / Green18 (Model: PHT-65LHS) is an advanced 5-in-1 digital X-ray imaging system that incorporates PANO, CEPH (Optional), CBCT, 3D MODEL Scan and 3D PHOTO (Optional) imaging capabilities into a single system. PHT-65LHS, a digital radiographic imaging system, acquires and processes multi-FOV diagnostic images for dentists and ENT specialists. PHT-65LHS is a complete digital X-ray system equipped with imaging viewers, X-ray generator and a dedicated SSXI detector. The digital CBCT system is based on a CMOS digital X-ray detector. The CMOS CT detector is used to capture 3D radiographic images of head, neck, oral surgery, implant and orthodontic treatment. PHT-65LHS can also acquire 2D diagnostic image data in conventional panoramic and cephalometric modes.

The provided text is a 510(k) Summary for the Vatech Green16/Green18 (Model: PHT-65LHS) dental X-ray system. It describes the device, its intended use, and compares it to a predicate device (Green Smart, PHT-35LHS) to establish substantial equivalence.

However, the document does not describe a study that proves the device meets specific acceptance criteria related to a device's performance in analyzing medical images or making diagnostic predictions (e.g., an AI/ML device). Instead, it describes:

• Acceptance criteria for the imaging system itself: This refers to the fundamental image quality metrics (like MTF, DQE, NNPS, Contrast, Noise, CNR) and safety standards required for an X-ray imaging device to be cleared by the FDA for its intended purpose (producing panoramic, cephalometric, or 3D digital X-ray images).
• Performance data comparing the new device to a predicate device: This is to show that the new device's imaging capabilities are equivalent to or better than a previously cleared device.

Therefore, many of the requested items (e.g., sample size for training/test sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone algorithm performance, types of ground truth for AI/ML) are not applicable to this document as it pertains to the clearance of an imaging hardware system, not an AI/ML-driven diagnostic device.

Here's a breakdown of what can be extracted and what is not present, based on the provided text:

1. Table of acceptance criteria and reported device performance:

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

• The document mentions "Non-Clinical Test results" and "Clinical consideration and image quality evaluation report" but does not specify sample sizes for these tests.
• Data provenance (country of origin, retrospective/prospective) is not mentioned beyond the manufacturer being VATECH Co., Ltd. in Korea.

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

• Not applicable as this is not an AI/ML diagnostic device requiring expert-established ground truth for a test set. The "Clinical consideration and image quality evaluation report" implies human evaluation, but details are absent.

4. Adjudication method for the test set:

• Not applicable.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, and effect size:

• Not applicable. This is not an AI/ML CAD device for human readers.

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

• Not applicable. This is an X-ray imaging system, not an algorithm, so its "standalone" performance is its fundamental imaging capability, which is reported via metrics like MTF, DQE, NNPS.

7. The type of ground truth used:

• For the technical performance of the imaging system, the "ground truth" is established by physical phantoms and measurement protocols defined by international standards (e.g., IEC 61223-3-5).
• For "Clinical consideration and image quality evaluation," the "ground truth" would be the subjective assessment of image quality by healthcare professionals, but no details are provided on how this evaluation was structured.

8. The sample size for the training set:

• Not applicable. This device is not an AI/ML product developed with a training set.

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

• Not applicable.

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PaX i3D Ortho (TON-95LH) is a computed tomography x-ray system intended to produce cross-sectional images of the oral anatomy by reconstructing a three dimensional radiographic images from the same axial plane taken at different angles. It provides diagnostic details of the maxillofacial areas for a dental treatment in adult and pediatric dentistry. The system also acquires carpal images for orthodontic treatment. The device is operated and used by physicians, dentists, and x-ray technicians.

PaX-i3D Ortho (TON-95LH) is a dental radiographic imaging system with cone beam computed tomography (CBCT) to offer high definition digital diagnostic images in multi FOV for dental practitioners. Specifically designed for dental radiography of the teeth or jaws, TON-95LH is a complete dental X-ray system equipped with x-ray tube, generator and dedicated SSXI detector for dental CBCT radiography.

The PaX-i3D Ortho (TON-95LH) dental CBCT system is equipped with a CMOS digital Xray detector which is used to capture radiographic diagnostic image data of oral and maxillofacial anatomy and reconstruct a three dimensional (3D) image for dental treatments such as oral surgery, implant and orthodontic. The PaX-i3D Ortho (TON-95LH) dental CBCT system also can reconstruct 2D panoramic and cephalometric images from the same diagnostic image data which the system originally obtained.

The provided text describes a 510(k) premarket notification for the "PaX-i3D Ortho (TON-95LH)" dental computed tomography x-ray system. The submission aims to demonstrate substantial equivalence to a predicate device, the "PaX-Zenith3D." The information focuses on technical similarities and performance testing to support this claim, rather than defining specific acceptance criteria and a detailed study proving the device meets them in the context of clinical accuracy or diagnostic efficacy for specific conditions.

Therefore, many of the requested details about acceptance criteria, sample sizes, expert ground truth establishment, and comparative effectiveness studies are not explicitly present in the provided document. The document primarily discusses device-level performance benchmarks related to image quality and safety standards.

Here's a breakdown of the available information based on your request:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state numerical acceptance criteria. Instead, it focuses on demonstrating that the new device's performance is "equal or better" than the predicate device in specific technical aspects.

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

• Sample Size: Not explicitly stated for specific tests. The document refers to "laboratory and clinical performance testing" and "Non-clinical test and clinical consideration test." It does not provide the number of cases or images used in these tests.
• Data Provenance: Not specified. The testing was conducted by "qualified individuals employed by the sponsor." Given the manufacturer's address in Gyeonggi-Do, Republic of Korea, it's likely the testing was conducted there, but this is not explicitly stated. The nature (retrospective/prospective) is also not specified.

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

This information is not provided in the document. The testing described focuses on technical image quality metrics (MTF, DQE, NPS) rather than diagnostic accuracy requiring expert interpretation and ground truth.

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

This information is not provided in the document, as the testing described does not involve expert adjudication for diagnostic outcomes.

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 study was mentioned.
• This device is a dental CBCT system, a hardware device for image acquisition, not an AI-assisted diagnostic tool. Therefore, a study on human reader improvement with AI assistance is not relevant to this submission.

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

This is not applicable as the device is a hardware imaging system, not a standalone algorithm. The "standalone" performance here would refer to the image acquisition capabilities, which are assessed through technical metrics like MTF, DQE, and NPS.

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

The concept of a "ground truth" for diagnostic accuracy (e.g., pathology, outcomes data) is not applicable to the performance testing described. The "ground truth" for the technical image quality tests would be physical phantoms and established measurement techniques for MTF, DQE, and NPS.

8. The sample size for the training set:

This is not applicable as the device is a hardware imaging system, not a machine learning algorithm that requires a training set.

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

This is not applicable for the same reason as above.

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PCH-2500 is a digital extra oral source x-ray system intended to take panoramic and cephalometric images of the oral and maxillofacial anatomy to provide diagnostic information for adult and pediatric patients. The device should be operated and used by dentists, x-ray technicians and other professionals licensed by the law of the state in which the device is used.

PCH-2500 is a dental digital radiographic imaging system which is available in two different image acquisition modes. Specifically designed for dental radiography of the teeth or jaws. PCH-2500 can be equipped with four dedicated sensors for two different X-ray modalities : one panoramic (Xmaru1501CF), two cephalometric scan type (Xmaru2301CF and Xmaru3001CF) and three flat panel one shot ceph sensors (1210SGA, 910SGA and 1417PGA). The proposed device is available with two X-ray generator options. PCH-2500 offers the digital panoramic and cephalometric X-ray modality for dental radiographs. The multi platforms of PCH-2500 imaging mode provides a wide range of imaging options based on the patient diagnostic needs.

Here's a summary of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Acceptance Criteria and Device Performance

The provided document describes a 510(k) submission for the PCH-2500 dental digital radiographic imaging system. However, it does not explicitly list specific acceptance criteria with numerical targets that the device had to meet. Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (also named PCH-2500, K122155). The core argument is that the new device is an "upgraded version of the predicate device with the same model name, the same indications for use and technical characteristics" (Section 2).

The closest equivalent to "acceptance criteria" can be inferred from the technological characteristics comparison with the predicate device and the performance tests conducted to ensure safety and effectiveness.

Table 1. Inferred Acceptance Criteria and Reported Device Performance

Study that Proves the Device Meets the Acceptance Criteria:

The submission describes a set of tests to demonstrate substantial equivalence to the predicate device, rather than a single, large clinical study with specific acceptance criteria. The primary "study" is a compilation of various engineering tests, performance validations, and comparisons.

1. Sample size used for the test set and the data provenance:

   • Test Set: Not explicitly stated as a "test set" in the traditional sense of a clinical trial. The evaluation primarily involved device characteristics and performance metrics.
   • Data Provenance: The studies are laboratory and engineering tests conducted by the sponsor's qualified individuals, likely at the manufacturing facility in Gyeonggi-Do, Republic of Korea, as indicated by the submitter's address. The data is retrospective in the sense that it relies on comparisons to an already cleared predicate device and established standards.

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

   • The document mentions "an expert review of image comparisons for both devices" (Section 6).
   • The number of experts and their specific qualifications (e.g., "radiologist with 10 years of experience") are not specified in the provided text. It only states "qualified individuals employed by the sponsor" conducted laboratory and clinical performance testing (Section 5).

3. Adjudication method for the test set:

   • The document mentions "outcome of an expert review of image comparisons" (Section 6), but the specific adjudication method (e.g., 2+1, 3+1, none) is not described.

4. 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 comparative effectiveness study was done or reported. This device is a digital X-ray imaging system, not an AI-powered diagnostic tool. The focus is on the image acquisition system itself.

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

   • Not applicable. The device is an image acquisition system, not an algorithm. Its performance is evaluated based on image quality metrics and compliance with technical specifications and safety standards.

6. The type of ground truth used:

   • For technical performance: The "ground truth" was based on established industry standards (e.g., IEC standards for safety, ISO/NEMA standards for image quality metrics like MTF, DQE, NPS), and comparison to the performance characteristics of the legally marketed predicate device.
   • For clinical image evaluation: The "ground truth" was based on expert review of images produced by the device, likely assessing diagnostic utility and quality against established clinical imaging benchmarks, but the exact nature of this "ground truth" is not detailed (e.g., if it involved pathology confirmation or outcomes data).

7. The sample size for the training set:

   • Not applicable. This device is an X-ray imaging system, not a machine learning algorithm that requires a "training set" in the AI sense.

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

   • Not applicable. As the device is not an AI algorithm, no training set or its associated ground truth establishment mechanism is relevant to this submission.

In essence, the "study" demonstrating the device meets acceptance criteria is a comprehensive set of engineering, electrical, mechanical, and image quality tests, along with a direct comparison of all technical specifications to a pre-existing cleared predicate device (K122155). The conclusion of substantial equivalence is drawn from the satisfactory results of these tests and the identified similarities and acceptable changes from the predicate.

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PHT-6500 (PHT-60CFO) is a computed tomography x-ray system intended to produce panoramic, cephalometric or cross-sectional images of the oral anatomy on a real time basis by computer reconstruction of x-ray image data from the same axial plane taken at different angles. It provides diagnostic details of the anatomic structures by acquiring 360° rotational image sequences of oral and maxillofacial area for a precise treatment planning in adult and pediatric dentistry . The device is operated and used by physicians, dentists, and x-ray technicians.

PHT-6500 (PHT-60CFO), a dental radiographic imaging system, consists of three image acquisition modes; panoramic, cephalometire and cone beam computed tomography. Specifically designed for dental radiography of the teeth or jaws, PHT-6500 (PHT-60CFO) is a complete dental X-ray system equipped with x-ray tube, generator and dedicated SSXI detector for dental panoramic, cephalometric and cone beam computed tomographic radiography. The dental CBCT system is based on CMOS digital X-ray detector. CMOS CT detector is used to capture radiographic diagnostic images of oral anatomy in 3D for dental treatment such as oral surgery or implant. The device can also be operated as the panoramic and cephalometric dental x-ray system based on CMOS X-ray detector. The proposed device is available with two X-ray generator options.

• A pair of CT sensor and Pano sensor are assembled together, back to back, and fixed mechanically to the rotating X-ray gantry, facing the X-ray tube from the opposite side. Based on the choice of a modality, between CT and panorama, the mechanically attached sensors rotate automatically so an appropriate type of sensor is facing the X-ray tube for exposure.
• The type of CT sensor attached to the equipment determines the model name. The model name, PHT-6500, refers to the equipment mounted with Xmaru0712CF, and Xmaru1215CF Plus SSXI detector whereas PHT- 60 CFO model refers to the equipment mounted with Xmaru1215CF Master Plus and Xmaru1524CF Master Plus SSXI detector.

Here's an analysis of the provided text regarding the acceptance criteria and study for the PHT-6500 (PHT-60CFO) dental computed tomography X-ray system:

1. Table of Acceptance Criteria and Reported Device Performance:

The document is a Special 510(k) submission, which means the device is an upgraded version of a legally marketed predicate device with the same indications for use and technical characteristics. Therefore, the primary "acceptance criterion" is proving substantial equivalence to the predicate device (K122606). The performance testing focuses on demonstrating that the new components or changes do not negatively impact safety or effectiveness, and in some cases, show improvement or equivalence.

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

The document does not explicitly state a specific human "test set" sample size or data provenance (country of origin, retrospective/prospective) in the context of clinical performance evaluation directly. The emphasis is on non-clinical testing and expert evaluation of images.

• Non-clinical testing: This involved evaluating physical characteristics like MTF, DQE, and NPS for the new detectors and X-ray generators. No patient data is typically involved in these tests.
• Clinical image evaluation: This was "performed for each X-ray generator" (Page 6, 7), but the number of cases or patients, or their origin, is not specified. Given the nature of a Special 510(k) and the statement about "no significant difference in efficiency and safety," it's likely this involved expert review of a limited set of images rather than a large-scale clinical trial with a defined patient cohort.

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

The document mentions "qualified individuals employed by the sponsor" evaluating laboratory and clinical performance testing (Page 5), and "a separate clinical image evaluation is performed for each X-ray generator" (Page 7). However, it does not specify the number of experts or their qualifications (e.g., "radiologist with 10 years of experience").

4. Adjudication Method for the Test Set:

The document does not specify an adjudication method (e.g., 2+1, 3+1, none) for any clinical image evaluations. Given the focus on demonstrating equivalence and the lack of detail on reader studies, it's highly probable that a formal, multi-reader adjudication process as seen in AI efficacy studies was not conducted or deemed necessary for this Special 510(k).

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned or performed in the provided text. The document refers to clinical image evaluations to assess the X-ray generator's effect on image quality, but it does not describe a study comparing human readers with and without AI assistance or any other comparative effectiveness study. This type of study is more common for devices claiming enhanced diagnostic performance or AI integration, which is not the primary focus of this Special 510(k) (which focuses on an upgraded version of an existing device).

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

This device is an X-ray imaging system, not an AI algorithm. Therefore, the concept of "standalone (algorithm only)" performance like in AI devices does not apply in the same way. The performance is intrinsically linked to the hardware generating the images. The non-clinical tests (MTF, DQE, NPS) could be considered "standalone" in that they evaluate the physical imaging components themselves, separate from a human interpreter.

7. The Type of Ground Truth Used:

For the non-clinical tests (MTF, DQE, NPS), the "ground truth" would be objective physical measurements and established engineering standards.

For the "clinical image evaluation," the ground truth is most likely based on expert consensus/opinion regarding diagnostic image quality, comparing images from the upgraded device to those from the predicate device or a reference standard, to ensure no degradation in diagnostic utility. The document's statement about "diagnostic image quality of new sensors is equal or better" (Page 6) suggests this. There is no mention of pathology or outcomes data being used for ground truth.

8. The Sample Size for the Training Set:

The concept of a "training set" is typically associated with machine learning or AI algorithms. Since this submission is for an upgraded X-ray hardware system, there is no mention of a training set in the context of AI model development.

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

As there is no mention of a training set for an AI algorithm, this question is not applicable to the provided document.

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The VEX-S100W is an extraoral source of X-rays, intended to be used for producing diagnostic dental radiographs for treatment of disease of the teeth, jaw and oral structures.

VEX-S100W is an extraoral source dental X-ray system intended for intraoral imaging. It consists of X-ray generator, X-ray controller, beam limiting device, operation panel and mechanical arm. The X-ray controller allows for accurate exposure control, and an adjustable mechanical arm allows for easy positioning. The system can be used either with conventional film or a digital imaging system.

The VEX-S100W is an extraoral source dental X-ray system. The submission indicates that no clinical testing was performed or relied upon for this premarket notification. The device is claimed to be substantially equivalent to the predicate device, ESX (K092103), based on similar indications for use and technical characteristics.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not explicitly define "acceptance criteria" as a set of quantified performance targets for diagnostic accuracy or clinical outcomes. Instead, it relies on demonstrating compliance with international standards and similarity to a predicate device. The performance testing described is focused on verifying compliance with specifications affecting image quality and patient dose, and detecting malfunctions.

The table below presents relevant performance specifications of the proposed device as compared to the predicate device. The "Acceptance Criteria" implicitly are that the device meets these specified technical characteristics and demonstrates satisfactory performance according to the cited engineering and safety standards.

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

The submission explicitly states: "This premarket notification submission for a determination of substantial equivalence does not require nor rely on the clinical testing." Therefore, there is no clinical "test set" in the traditional sense of patient data in this submission. The "test set" refers to the device itself being tested for compliance with engineering and safety standards. No specific sample size of images or patients is mentioned as no clinical studies were performed. The testing was conducted on the VEX-S100W device itself.

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

There is no mention of experts establishing ground truth for a clinical test set, as no clinical testing was performed or relied upon. The ground truth for the engineering performance tests would be defined by the specified technical parameters and safety standards, the evaluation of which would be conducted by qualified engineers or technicians in a testing laboratory.

4. Adjudication method for the test set

Not applicable, as no clinical test set requiring adjudication of findings was used.

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 study or any clinical study involving human readers or AI assistance was performed. This device is an X-ray generator, not an image analysis or AI diagnostic tool.

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

Not applicable, as this device is a physical X-ray system, not an algorithm.

7. The type of ground truth used

For the engineering and safety performance tests, the "ground truth" would be the technical specifications and regulatory requirements outlined in standards like IEC61223-3-4, IEC60601-1, etc. Compliance with these established standards and specifications serves as the basis for satisfactory performance.

8. The sample size for the training set

Not applicable. As no clinical testing was performed and the device is an X-ray generator, there is no "training set" of data in the context of machine learning or AI.

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

Not applicable, as there was no training set.

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PCH-2500 (PaX-i) is a digital extra oral source x-ray system intended to take panoramic and cephalometric images of the oral and maxillofacial anatomy to provide diagnostic information for adult and pediatric patients. The device should be operated and used by dentists, x-ray technicians and other professionals licensed by the law of the state in which the device is used.

PCH-2500 (PaX-i) is a dental digital radiographic imaging system which is available in two different image acquisition modes. Specifically designed for dental radiography of the teeth or jaws, PCH-(PaX-i) can be equipped with four dedicated sensors for two different X-ray modalities : one panoramic (Xmaru1501CF), one cephalometric scan type (Xmaru2301CF) and two flat panel one shot ceph sensors (1210SGA and 910SGA). PCH-2500 (PaX-i) offers the digital panoramic and cephalometric X-ray modality for dental radiographs. The multi platforms of PCH-2500 (PaX-i) imaging mode provides a wide range of imaging options based on the patient diagnostic needs.

Here's a breakdown of the acceptance criteria and study information based on the provided text, focusing on the new component (910SGA sensor) as this is a Special 510(k) submission primarily addressing changes to an existing device:

1. Table of Acceptance Criteria and Reported Device Performance

The submission is a Special 510(k) for PCH-2500 (PaX-i), primarily introducing a new cephalometric sensor (910SGA). The acceptance criteria for this sensor are implicitly set by its equivalence to the predicate device and the performance of other sensors within the PCH-2500 (PaX-i) system, as well as general performance standards for dental X-ray imaging.

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

The document does not explicitly state the numerical sample size for the "test set" (i.e., the images used for the expert review). It only mentions "image comparisons for both devices." The data provenance is not explicitly stated as retrospective or prospective, nor is the country of origin specified for the images used in the expert review.

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

The document states an "expert review of image comparisons" was conducted, but it does not specify the number of experts used or their qualifications.

4. Adjudication Method for the Test Set

The document mentions an "expert review," but it does not describe an adjudication method (e.g., 2+1, 3+1). It implies a consensus or comparison against a standard, but no specific method is outlined.

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

No, the document does not indicate that a Multi Reader Multi Case (MRMC) comparative effectiveness study was done. The evaluation primarily focused on demonstrating substantial equivalence to a predicate device through technical specifications, safety/EMC testing, and an expert review of image comparisons. There is no mention of human readers improving with AI assistance, as this is an imaging device, not an AI-assisted diagnostic tool.

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

This question is not directly applicable in the context of this submission. The device is an X-ray imaging system, not an algorithm. Its performance is evaluated as an imaging system, which inherently produces images for human interpretation. The "non-clinical and clinical consideration report for the new SSXI detector, 910SGA" would assess the detector's capability to produce diagnostic images, effectively acting as its standalone performance.

7. The Type of Ground Truth Used

The ground truth for the "image comparisons" was established through expert review. This implies a comparison of diagnostic quality and features between images produced by the new 910SGA sensor and the predicate device's sensors. The ultimate "ground truth" for dental X-ray images is typically the clinical diagnosis or assessment derived by a qualified professional from those images.

8. The Sample Size for the Training Set

The document does not mention a training set or its sample size. This is a hardware submission, not a machine learning algorithm submission, so a traditional "training set" as understood in AI/ML is not applicable.

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

Since there is no training set mentioned, this question is not applicable.

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The PaX-Uni3D is a computed tomography x-ray system which is a diagnostic x-ray system intended to produce panoramic, cephalometric and cross-sectional images for dental examination and diagnosis of diseases of the teeth, jaw and oral structure by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles.

PaX-Uni3D (PHT-7500), a dental radiographic imaging system, consists of dual image acquisition modes; panoramic, cephalometirc and cone beam computed tomography. Specifically designed for dental radiography of the teeth or jaws, PaX-Uni3D (PHT-7500) is a complete dental X-ray system equipped with x-ray tube, generator and dedicated SSXI detector for dental panoramic, cephalometric and cone beam computed tomographic radiography. The dental CBCT system is based on CMOS digital X-ray detector. CMOS CT detector is used to capture radiographic diagnostic images of oral anatomy in 3D for dental treatment such as oral surgery or implant. The device can also be operated as the panoramic and cephalometric dental x-ray system based on CMOS X-ray detector.

The provided text describes a 510(k) submission for a dental X-ray imaging system, PaX-Uni3D (PHT-7500). The submission aims to demonstrate substantial equivalence to a predicate device, PaX-Uni3D (K090467). The document focuses on non-clinical performance and safety data, rather than a clinical study evaluating the device's diagnostic performance compared to a baseline or human readers.

Here's a breakdown of the requested information based on the provided text, noting where specific details are not available:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a quantitative, diagnostic performance sense (e.g., sensitivity, specificity, accuracy thresholds). Instead, it primarily focuses on demonstrating equivalence to the predicate device through technical specifications and adherence to international safety and performance standards.

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

The document mentions "an expert review of image comparisons for both devices" and "Non-clinical & Clinical considerations according to FDA Guidance 'Guidance for the submissions of 510(k)'s for Solid State X-ray Imaging Devices.'" However, it does not specify the sample size (number of images or patients) used for this "expert review" or "clinical consideration." The data provenance (e.g., country of origin, retrospective or prospective) is also not explicitly stated.

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

The document refers to "an expert review of image comparisons." It does not specify the number of experts or their precise qualifications (e.g., "radiologist with 10 years of experience").

4. Adjudication Method for the Test Set

The document mentions "an expert review of image comparisons" but does not describe any specific adjudication method (e.g., 2+1, 3+1, none) used to establish ground truth or resolve discrepancies among experts.

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

No MRMC comparative effectiveness study is mentioned in the provided text. The submission focuses on demonstrating substantial equivalence through technical specifications and non-clinical performance, rather than evaluating the diagnostic improvement of human readers with or without AI assistance.

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

The device itself is an X-ray imaging system, not an AI algorithm performing diagnostic tasks. Therefore, the concept of "standalone (algorithm only without human-in-the-loop performance)" as usually applied to AI models is not relevant in this context. The performance evaluation is related to the image quality and physical specifications of the imaging system.

7. The Type of Ground Truth Used

For the "expert review of image comparisons," the implicit "ground truth" would likely be the expert consensus or judgment on the diagnostic quality and clinical utility of the images produced by the new device compared to the predicate device. The specific criteria for this judgment are not detailed, but it would relate to image resolution, clarity, ability to visualize relevant anatomical structures, and potential for diagnosis. There is no mention of pathology or outcomes data being used as ground truth for this comparison.

8. The Sample Size for the Training Set

This document describes a 510(k) for an X-ray imaging system, not an AI-powered diagnostic algorithm that would typically have a "training set." Therefore, the concept of a training set sample size is not applicable to this submission.

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

As there is no "training set" for an AI algorithm in this context, this question is not applicable. The device is a hardware system for image acquisition.

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PaX-Flex3D is a computed tomography x-ray system intended to produce panoramic, cephalometric or cross-sectional images of the oral anatomy on a real time basis by computer reconstruction of x-ray image data from the same axial plane taken at different angles. It provides diagnostic details of the anatomic structures by acquiring 360° rotational image sequences of oral and maxillofacial area for a precise treatment planning in adult and pediatric dentistry. The device is operated and used by physicians, dentists, and x-ray technicians.

PaX-Flex3D (PHT-7000), a dental radiographic imaging system, consists of dual image acquisition modes; panoramic, cephalometirc and cone beam computed tomography. Specifically designed for dental radiography of the teeth or jaws, PaX-Flex3D (PHT-7000) is a complete dental X-ray system equipped with x-ray tube, generator and dedicated SSXI detector for dental panoramic, cephalometric and cone beam computed tomographic radiography. The dental CBCT system is based on CMOS digital X-ray detector. CMOS CT detector is used to capture radiographic diagnostic images of oral anatomy in 3D for dental treatment such as oral surgery or implant. The device can also be operated as the panoramic and cephalometric dental x-ray system based on CMOS X-ray detector.

Here's a summary of the acceptance criteria and study information for the PaX-Flex3D (PHT-7000) based on the provided 510(k) summary.

1. Table of Acceptance Criteria (Performance Specifications) and Reported Device Performance:

The document primarily focuses on demonstrating substantial equivalence to a predicate device rather than explicitly stating acceptance criteria as pass/fail thresholds for clinical outcomes. Instead, it lists the technical and imaging specifications of the proposed device and compares them to the predicate device. The "reported device performance" is implicitly that the new device meets or is comparable to these specifications, as a conclusion of substantial equivalence is made.

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

The document mentions "an expert review of image comparisons" but does not specify the sample size (number of images or cases) used for this "clinical consideration" or "image comparison" part of the evaluation. It also does not specify the data provenance (e.g., country of origin, retrospective or prospective nature) for this image comparison.

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

The document states "an expert review of image comparisons." It does not specify the number of experts involved or their specific qualifications (e.g., radiologist with X years of experience).

4. Adjudication Method for the Test Set:

The document mentions "an expert review" but does not specify any adjudication method (e.g., 2+1, 3+1, none) for resolving discrepancies among experts.

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

No, a MRMC comparative effectiveness study was not explicitly mentioned or described. The submission focuses on demonstrating substantial equivalence primarily through technical specifications and an "expert review of image comparisons" between the new device and its predicate. There is no mention of human readers improving with or without AI assistance, as the device itself is an imaging system, not an AI-powered diagnostic tool.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

This section is not applicable as the device is an X-ray imaging system (hardware and associated software for reconstruction and viewing), not an AI algorithm. Its "performance" is its ability to produce diagnostic images.

7. The Type of Ground Truth Used:

For the "expert review of image comparisons," the ground truth was expert consensus (an "expert review" concluding that images from both devices were substantially equivalent in terms of safety and effectiveness).

8. The Sample Size for the Training Set:

This information is not applicable. The device is an imaging system, not a machine learning algorithm that requires a "training set" in the conventional sense for performance evaluation in a 510(k) submission like this. The design and engineering of the device are based on established physics and medical imaging principles.

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

This information is not applicable for the reasons stated in point 8.

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PaX-Duo3D Plus is a computed tomography x-ray system intended to take panoramic and cross-sectional images of the oral and craniofacial anatomy to provide diagnostic information for adult and pediatric patients. The device is operated and used by physicians, dentists, dental assistants, x-ray technicians and other professionals who are licensed by the law of the State in which he or she practices to use the device.

PaX-Duo3D Plus (PCT-5000), a dental radiographic imaging system, consists of dual image acquisition modes; panorama, and cone beam computed tomography. Specifically designed for dental radiography of the teeth or jaws, PaX-Duo3D Plus (PCT-5000) is a complete dental X-ray system equipped with x-ray tube, generator and dedicated SSXI detector for dental panoramic and cone beam computed tomographic radiography. The dental CBCT system is based on CMOS digital X-ray detector. CMOS CT detector is used to capture radiographic diagnostic images of oral anatomy in 3D for dental treatment such as oral surgery or implant. The device can also be operated as the panoramic dental x-ray system based on CMOS X-ray detector.

The PaX-Duo3D Plus (PCT-5000) device introduces new cone beam CT sensors (Xmaru0712CF, Xmaru1215CF Plus, Xmaru1215CF Master Plus). The study supporting its substantial equivalence to the predicate device, PaX-Duo3D Plus (K102102), focused on demonstrating similar performance characteristics.

Here's a breakdown of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document primarily focuses on demonstrating substantial equivalence to a predicate device by comparing technical specifications and adherence to safety and performance standards, rather than defining specific diagnostic performance acceptance criteria for a novel AI algorithm. The performance of the new sensors is evaluated against the predicate device's established performance through non-clinical and clinical considerations.

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

The document mentions "nonclinical and clinical consideration" and an "expert review of image comparisons" for both devices. However, no specific sample size for a test set (e.g., number of patients or images) is explicitly stated. The data provenance (country of origin, retrospective or prospective) is also not specified.

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

The text refers to an "expert review of image comparisons." However, the number of experts used is not specified, nor are their specific qualifications (e.g., "radiologist with 10 years of experience") provided.

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

The adjudication method used for the "expert review of image comparisons" is not explicitly stated.

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 Multi-Reader Multi-Case (MRMC) comparative effectiveness study was described for the device. The study primarily focuses on demonstrating substantial equivalence of the new hardware through technical specifications and expert review, not on AI-assisted diagnostic improvement. Therefore, no effect size for human reader improvement with AI assistance is reported.

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

This device is an X-ray imaging system, not an AI algorithm. Therefore, the concept of a "standalone (algorithm only without human-in-the-loop performance)" study does not apply in this context. The performance described relates to the image acquisition capabilities of the hardware.

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

For the "expert review of image comparisons" mentioned, the ground truth was based on expert review/consensus comparing images from the new device with those from the predicate device. The document does not mention pathology or outcomes data for this comparison.

8. The sample size for the training set:

As this is a hardware device submission and not an AI algorithm, the concept of a "training set" in the context of machine learning is not applicable or mentioned in the document.

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

Since there is no mention of a training set for an AI algorithm, the method for establishing its ground truth is not applicable or described.

In summary, the provided document is a 510(k) summary for a dental X-ray imaging system. The study described focuses on demonstrating the device's adherence to safety and performance standards and its substantial equivalence to a predicate device through non-clinical testing and an expert review of image comparisons, rather than evaluating the diagnostic performance of an AI-powered system with specific acceptance criteria related to disease detection or measurement.

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PCH-2500 is digital extra oral source x-ray system intended to take panoramic and cephalometric images of the oral and maxillofacial anatomy to provide diagnostic information for adult and pediatric patients. The device should be operated and used by dentists, x-ray technicians and other professionals licensed by the law of the state in which the device is used.

PCH-2500 is a dental digital radiographic imaging system which is available in two different image acquisition modes. Specifically designed for dental radiography of the teeth or jaws, PCH-2500 can be equipped with three dedicated sensors, each for two X-ray modalities : panoramic (Xmarul 501CF), cephalometric scan type (Xmaru2301CF) and oneshot ceph sensor type (1210SGA). PCH-2500 offers the digital panoramic and cephalometric X-ray modality for dental radiographs. The multi platforms of PCH-2500 imaging mode provides a wide range of imaging option based on the customer's diagnostic needs.

Here's a breakdown of the acceptance criteria and study information for the PCH-2500 device, based only on the provided text:

Important Note: The provided text is a 510(k) summary for a medical device. This type of document is designed to demonstrate substantial equivalence to an already legally marketed device, not necessarily to provide a comprehensive clinical study report proving efficacy against a specific set of clinical acceptance criteria. Therefore, much of the requested information (like specific performance metrics for acceptance criteria, sample sizes for test/training sets, expert qualifications, and MRMC study details) is not present in the given text.

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary for PCH-2500 primarily focuses on demonstrating substantial equivalence to the predicate device, PaX-Flex3D, by comparing technical characteristics and performance specifications. There are no explicit "acceptance criteria" for diagnostic accuracy or clinical outcomes stated. Instead, the performance is presented as meeting certain technical specifications.

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

The provided text does not specify a sample size for a test set in the context of clinical performance evaluation (e.g., number of patients/images used to assess diagnostic accuracy). The non-clinical performance and clinical consideration report for the SSXI detector (1210SGA) is "provided separately in this submission," but details are not given here.

The data provenance for the device performance testing mentioned (e.g., electrical, mechanical, EMC, acceptance tests according to IEC standards) would be from in-house engineering and testing as per standard regulatory requirements, likely conducted in Korea Republic (manufacturer's country). No clinical trial data is detailed. The expert review of image comparisons is mentioned, but without specifics of the dataset.

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

The text mentions an "expert review of image comparisons" for both the PCH-2500 and the predicate device. However, it does not specify the number of experts, their qualifications, or how they established a "ground truth" for a test set. This review seems to be part of the substantial equivalence argument, likely comparing image quality or diagnostic utility rather than rigorously establishing a ground truth for a clinical condition.

4. Adjudication Method for the Test Set

Since the text does not detail a clinical test set with specific ground truth establishment, no adjudication method (e.g., 2+1, 3+1) 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 MRMC comparative effectiveness study is mentioned or implied. The PCH-2500 is a digital X-ray imaging system, not an AI-powered diagnostic tool, and the submission predates widespread clinical AI in radiology.

6. If a Standalone (i.e. algorithm only without human-in-the loop performance) Was Done

Not applicable. The PCH-2500 is a hardware imaging device, not a standalone algorithm.

7. The Type of Ground Truth Used

For the technical performance aspects, the "ground truth" is adherence to established technical standards (e.g., IEC, NEMA) and the performance of the predicate device. For potential image quality assessments by experts (implied by "expert review of image comparisons"), the ground truth would inherently be expert opinion/consensus on image quality and diagnostic features. Pathology or outcomes data are not mentioned as being used for ground truth.

8. The Sample Size for the Training Set

Not applicable/Not provided. As this is an X-ray imaging system, there isn't a "training set" in the machine learning sense. Any calibration or factory testing would involve proprietary methods not detailed here.

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

Not applicable/Not provided. See point 8.

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