REXTAR PRO is a portable X-ray system to be used by trained dentists and dental technicians as a mobile, extraoral x-ray source for producing diagnostic x-ray images using intraoral image receptors. It is intended for adult patients.

The REXTAR PRO is an X-ray device offering a lightweight, compact portable X-ray generator. The generator is a high frequency X-ray generator, with a high Output at 70kV / 2mA. The battery-powered device is a Ripple-free HF type of generating device. The REXTAR PRO X-ray function is controlled by Touch Screen and Button for convenience. The handheld device features a main body (X-ray tube head), rechargeable battery (handset), charger, and charger AC/DC power supply. REXTAR PRO uses a high-quality shielding material for shielding (using domestically produced 99.9% purity lead. The RETAR PRO minimizes the exposure of the users from X-ray scattering by adding a backscatter shield. The REXTAR PRO's uses a GRID Tube and is a specialized X-ray tube that improves the quality of the x-ray beam by controlling the flow of electrons through the GRID placed between the cathode and anode. It's application of the Focal Spot 0.2mm GRID Tube for clearer, high-quality imaging helps with the diagnosis for accurate procedures and minimizes patient radiation exposure.

The provided text does not contain information about acceptance criteria or a study proving the device meets acceptance criteria in the context of diagnostic performance or clinical effectiveness. The document provided is a 510(k) premarket notification review for the Rextar Pro, an extraoral source X-ray system, and focuses primarily on establishing substantial equivalence to a predicate device (REXTAR X, K132041) based on technical characteristics and safety standards.

The document discusses non-clinical performance testing for safety and electrical compatibility, specifically referencing:

• IEC 60601-2-65: Particular requirements for basic safety and essential performance of dental intra-oral X-ray equipment.
• IEC 60601-1: General requirements for basic safety and essential performance.
• IEC 60601-1-2: Electromagnetic disturbances—requirements and tests.
• FDA software guidance: Content of Premarket Submissions for Device Software Functions.
• Leakage Radiation Test: Measurements made at 15 different points around the device.

The conclusion states that the REXTAR PRO's radiation emitting level at the operator's perspective is fairly minimal compared to NCRP requirements (occupational radiation exposure to adults working with radioactive material to 5,000 mR (50 mSv) per year).

However, none of the requested information regarding diagnostic performance (e.g., sensitivity, specificity, AUC), sample sizes for test sets, expert qualifications, ground truth establishment for diagnostic evaluation, or MRMC studies are present in the provided text. The document confirms the device is intended for "producing diagnostic x-ray images using intraoral image receptors" but does not detail how the diagnostic quality or effectiveness of these images by the Rextar Pro itself was assessed against specific acceptance criteria.

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XERO a is an Hand-held intraoral dental x-ray equipment to produce X-ray images using intraoral image receptors. It is indicated for use by a dental technician for both adult and pediatric patients. This equipment is used in a professional healthcare facility environment.

XERO a is an Hand-held intraoral dental x-ray equipment to produce X-ray images using intraoral image receptors. It is indicated for use by a dental technician for both adult and pediatric patients. This equipment is used in the professional healthcare facility environment. But the image detectors (an integral part of a complete dental system) are not part of the device. The operation principle of the device involves emitting x-ray source when a high voltage is supplied to the X-ray tube assembly, which frees electrons from the cathode. They hit anode to produce X-rays. The device acquires images by emitting X-rays continuously on the human tooth. And the functions of the dental generator XERO a are supported by firmware. This is of basic firmware documentation level, and there is no external data exchange port in the device. Moreover, the XERO a is not wireless. The subject dental system is not a cyber device.

The provided text describes the 510(k) premarket notification for the XERO - C and XERO α intraoral dental X-ray equipment. However, the document does not contain information about a study proving the device meets acceptance criteria related to AI/algorithm performance, multi-reader multi-case (MRMC) studies, or standalone algorithm performance.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (Vatech Co., Ltd.'s EzRay Air Portable, K200182) through:

• Technological characteristics comparison: Showing similar design, mechanical features, electrical specifications, and adherence to relevant safety standards.
• Non-clinical data summary: Listing compliance with international and FDA-recognized consensus standards for medical electrical equipment safety, electromagnetic compatibility, usability, and specific requirements for dental X-ray equipment.
• Statement on clinical data: Explicitly stating that clinical studies are unnecessary to validate the safety and effectiveness of the device.

Therefore, I cannot provide the requested information regarding acceptance criteria, study details, sample sizes, expert involvement, adjudication methods, MRMC studies, standalone performance, or ground truth establishment for an AI/algorithm. This information is not present in the provided 510(k) summary.

The device described is a medical imaging device (X-ray equipment), not an algorithm or AI software for image analysis that would typically have the kind of performance metrics and study designs you've asked about.

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The unit is intended to produce panoramic or cephalometric digital x-ray images. It provides diagnostic details of the dento-maxillofacial, sinus and TMJ for adult and pediatric patients. The system also utilizes carpal images for orthodontic treatment. The device is to be operated by physicians, dentists, and x-ray technicians.

The device is an advanced 2-in-1 digital X-ray imaging system that incorporates PANO and CEPH (Optional) imaging capabilities into a single system and acquires 2D diagnostic image data in conventional panoramic and cephalometric modes.
The device is not intended for CBCT imaging.
VistaPano S is identified as panoramic-only models for VistaPano S Ceph.
ProVecta S-Pan Ceph and ProVecta S-Pan are alternative model for VistaPano S Ceph and VistaPano S respectively.
The subject device has different model names designated for different US distributors:

• -VistaPano S Ceph, VistaPano S: DÜRR DENTAL
• ProVecta S-Pan Ceph, ProVecta S-Pan: AIR TECHNIQUES ।
  Key components of the device
• 1. VistaPano S Ceph 2.0 (Model: VistaPano S Ceph), VistaPano S 2.0 (Model: VistaPano S) digital x-ray equipment (Alternate: ProVecta S-Pan Ceph 2.0 (Model: ProVecta S-Pan Ceph), ProVecta S-Pan 2.0 (Model: ProVecta S-Pan))
• 2. SSXI detector: Xmaru1501CF-PLUS, Xmaru2602CF
• 3. X-ray generator
• 4. PC system
• 5. Imaging software

The provided text describes the substantial equivalence of the new VATECH X-ray imaging systems (VistaPano S Ceph 2.0, VistaPano S 2.0, ProVecta S-Pan Ceph 2.0, ProVecta S-Pan 2.0) to their predicate device (PaX-i Plus/PaX-i Insight, K170731).

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

Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly stated as numerical metrics in a table. Instead, the document focuses on demonstrating substantial equivalence to a predicate device. This is a common approach for medical device clearance, where the new device is shown to be as safe and effective as a legally marketed device. The "performance" in this context refers to demonstrating that the new device functions similarly or better than the predicate, especially for the new "non-binning" mode.

The study aims to show that the new device's performance is equivalent or better than the predicate device, particularly for the new "HD mode (non-binning)" in CEPH imaging. The primary comparison points are:

Study Details:

The provided document is a 510(k) summary, not a detailed study report. Therefore, some specific details about the study methodology (like expert qualifications or full sample sizes for clinical images) are not granularly described. However, we can infer some information:

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

   • The document states "Clinical images obtained from the subject and predicate devices are evaluated and compared." However, the exact sample size for this clinical image evaluation (the "test set" in AI/ML terms) is not specified.
   • The data provenance is implied to be from a retrospective collection of images, likely from VATECH's own testing/development or existing clinical sites that used the predicate device and potentially early versions of the subject device. The country of origin for the clinical images is not explicitly stated, but given the manufacturer is based in Korea ("VATECH Co., Ltd. Address: 13, Samsung 1-ro 2-gil, Hwaseong-si, Gyeonggi-do, 18449, Korea"), it's reasonable to infer some data might originate from there.
   • For the bench testing, the sample size is also not specified, but it would involve phantoms.

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

   • The document mentions "Clinical images obtained from the subject and predicate devices are evaluated and compared." However, it does not specify the number of experts, their qualifications, or how they established "ground truth" for these clinical images. The evaluation is described in general terms, implying a qualitative assessment of general image quality ("general image quality of the subject device is equivalent or better than the predicate device").

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

   • The document does not describe any formal adjudication method for the clinical image evaluation. It simply states "evaluated and compared."

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, an MRMC study was NOT done. This device is an X-ray imaging system, not an AI-assisted diagnostic tool for interpretation. The study focused on demonstrating the image quality of the system itself (hardware and associated basic image processing software) as being substantially equivalent or better than a predicate system, not on improving human reader performance with AI assistance. The "VisionX 3.0" software is an image viewing program, not an AI interpretation tool.

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

   • This is not applicable in the sense of a diagnostic AI algorithm. The performance evaluation is inherently about the "algorithm" and physics of the X-ray system itself (detector, X-ray generator, image processing pipeline) without human interaction for image generation, but humans are integral for image interpretation. The device's performance (image quality, resolution, DAP) is measured directly, similar to a standalone evaluation of a sensor's capabilities.

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

   • For the bench testing, the ground truth was based on physical phantom measurements (e.g., line pair resolution, contrast using phantoms).
   • For the clinical image evaluation, the "ground truth" or reference was implicitly the subjective assessment of "general image quality" by unspecified evaluators, compared to images from the predicate device. There is no mention of an objective clinical ground truth like pathology or patient outcomes.

7. The sample size for the training set:

   • The document describes an X-ray imaging system, not a device incorporating a machine learning model that requires a "training set" in the conventional sense. Therefore, there is no mention of a training set sample size. The software mentioned (VisionX 3.0) is a general image viewing program, not a deep learning model requiring a specific training dataset.

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

   • Not applicable, as no external "training set" for a machine learning model is described.

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X Sensor is 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.

X Sensor is a digital intraoral sensor which acquires digital intra-oral images. X Sensor acquires intra oral images with a sensor that is connected to a computer to produce an image almost instantaneously following exposure. The primary advantage of direct sensor systems is the speed with which images are acquired. X Sensor includes the firmware for the sensor and the previously cleared imaging software "ExDent-I".

The provided text is a 510(k) summary for the X Sensor, a digital dental intraoral sensor. It describes the device's technical characteristics, intended use, and its comparison to a predicate device (EzSensor XHD). However, this document does not contain the detailed information necessary to fully answer your request regarding acceptance criteria and the study proving the device meets these criteria in the context of AI/ML performance.

Specifically, the document focuses on regulatory clearance for a medical device (an X-ray sensor) based on hardware and image quality performance relative to a predicate device, as well as electrical, mechanical, and software safety. It does not mention any AI/ML components or studies evaluating AI/ML performance.

Therefore, many parts of your request, such as those related to AI/ML specific acceptance criteria, sample sizes for AI/ML test and training sets, expert adjudication, MRMC studies, or standalone algorithm performance, cannot be answered from the provided text.

However, I can extract information related to the device's general performance testing and comparison to the predicate device, which serves as a form of "acceptance" for medical device clearance.

Here's what can be extracted and how it relates to your request, with a clear indication of what information is not present:

Acceptance Criteria and Device Performance (General Device Performance)

Based on the document, the "acceptance criteria" appear to be meeting or exceeding the performance of the predicate device (EzSensor XHD) in key technical metrics and demonstrating adequate image quality for diagnostic use.

Study Information (Based on Available Text)

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

   • The document states "The clinical images obtained from the X Sensor and EzSensor XHD were reviewed and rated comparatively."
   • Specific sample size for the clinical images reviewed is NOT provided.
   • Data provenance (country of origin, retrospective/prospective) is NOT provided. Given it's a 510(k) for a device like an X-ray sensor, the "test set" likely refers to physical images generated during bench testing and some limited clinical image capture, rather than a large dataset for AI/ML validation.

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

   • The document states "The clinical images obtained from the X Sensor and EzSensor XHD were reviewed and rated comparatively."
   • The number of experts and their qualifications are NOT specified. This phrasing suggests a qualitative human review of generated images to ensure diagnostic utility.

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

   • Adjudication method is NOT specified. The review appeared to be a comparative assessment of image quality.

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 study was performed or discussed. This device is an X-ray sensor, not an AI-assisted diagnostic tool in the sense of an algorithm interpreting images for a human. It provides the images.

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

   • This is NOT applicable. The "device" is the sensor itself, which captures images. There is no mention of an algorithm that performs standalone diagnostic interpretations.

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

   • For the image quality assessment, the "ground truth" seems to be clinical utility/diagnostic adequacy as judged by human review of images generated by both the new device and the predicate device. Quantitative metrics (DQE, MTF, NPS) also served as objective performance measures.

7. The sample size for the training set:

   • NOT applicable/NOT provided. This document describes a medical device, an X-ray sensor, not an AI/ML algorithm that requires a "training set" in the context of machine learning. The "training" for such a device would be its engineering and design optimization.

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

   • NOT applicable/NOT provided. As above, there's no mention of a machine learning training set or associated ground truth.

Summary of Limitations:

The provided document is a regulatory submission for an X-ray sensor. It focuses on demonstrating substantial equivalence to a predicate device based on technical specifications, image quality, and regulatory compliance (electrical safety, EMC, software documentation, cybersecurity). It does not describe an AI/ML diagnostic algorithm or any studies related to its performance, and therefore cannot answer the specific questions posed about AI/ML acceptance criteria and validation.

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The DUO Sensors are USB driven intraoral sensors which are intended to acquire intraoral radiographic images. The DUO Sensors shall be operated by trained healthcare professionals, who are educated and competent to perform the acquisition of intraoral radiographs.

The DUO Sensors can be used either in combination with special positioning devices to facilitate positioning and alignment with the X-ray beam or they may also be positioned by hand with the assistance of the patient.

The DUO sensors are intended for any dental practice that uses X-ray equipment for intraoral diagnostic purposes. DUO sensors can be used by trained dental professionals for patients receiving intraoral X-ray examinations and procedures for capturing digital X-ray images. Captured digital X-ray images can be used for examinations and diagnostic purposes with the help of optional image analysis software. The optional image analysis software is not part of this submission. DUO sensors can be used with dental positioning devices and holders to assist with aligning an X-ray source beam with the sensor and anatomy.

The DUO sensors are USB-driven digital X-ray sensors designed for health care professionals who are already acquainted with the standard procedures for acquiring dental intraoral radiographs. Digital X-ray imaging is an aide for diagnosis and should always be confirmed by the doctor using appropriate additional diagnostic aides, professional judgment, and experience.

The DUO Sensors are indirect converting X-ray detectors. A scintillating material converts the incident Xrays into visible light, this light is coupled optically to a CMOS technology light detection imager, and then converted to digital data.

The design of the sensor assembly supports the automatic detection of incident X-rays to generate digital images for intraoral applications, once armed via a software command. The digital image created is immediately visible on the screen of a personal computer connected to the DUO sensor through the standard USB port. For DUO sensors to be used in a dental practice, an optional image analysis software will be necessary. Image analysis software is not part of the submission. DUO captured X-ray images are suitable for recognition of normal anatomical structures, dental pathologies, and abnormal conditions.

The DUO sensors support USB2.0 connectivity to computers using a dedicated electronic assembly and a sensor software driver. Functions of the DUO sensors are controlled by software drivers and utilities support sensor activation and settings.

The DUO sensors are manufactured with the same device firmware as the predicate device, Brasseler GEM.

This submission describes a dental digital X-ray sensor, DUO1 and DUO2, which is substantially equivalent to the predicate device, Brasseler GEM.

Here's the breakdown of the acceptance criteria and supporting study details:

1. Table of Acceptance Criteria and Reported Device Performance

The FDA submission for K241649 is a 510(k) premarket notification, which relies on demonstrating substantial equivalence to a legally marketed predicate device rather than setting specific quantifiable acceptance criteria for novel claims. Therefore, the "acceptance criteria" here refer to demonstrating comparable performance to the predicate device (Brasseler GEM) for key technical aspects.

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

• Test Set Description: The document refers to "clinical images captured with both the devices in a performance testing report which were evaluated by US dentists."
• Sample Size: The exact number of patients or images in the clinical performance test set is not specified in the provided text.
• Data Provenance: The images were evaluated by "US dentists." It is not explicitly stated whether the data was retrospective or prospective. Given the clinical image evaluation, it suggests real-world acquisition but the exact study design (e.g., controlled prospective collection vs. retrospective existing images) is not detailed.

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

• Number of Experts: The document states that the clinical images "...were evaluated by US dentists." The exact number of dentists is not specified.
• Qualifications of Experts: The experts are described as "US dentists." Specific qualifications such as years of experience, subspecialty (e.g., board-certified oral and maxillofacial radiologists), or academic affiliations are not provided.

4. Adjudication Method for the Test Set

• Adjudication Method: The document only states that images "were evaluated by US dentists." It does not describe any specific adjudication method (e.g., 2+1, 3+1 consensus, independent reads with no consensus).

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

• A formal MRMC comparative effectiveness study that quantifies improvements in human reader performance (e.g., AUC, sensitivity, specificity) with AI versus without AI assistance was not performed or described. The clinical performance testing involved dentists evaluating images from both devices, implying a comparative visual assessment, but not a controlled MRMC study in the context of AI assistance. The device itself is an intraoral sensor, not an AI diagnostic tool.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• This device (DUO sensors) is a hardware component for acquiring images, not an AI algorithm for image analysis. Therefore, a standalone algorithm performance study is not applicable in the traditional sense. The submission states, "Image analysis software is not part of the submission" and "The optional image analysis software is not part of this submission."

7. Type of Ground Truth Used

• For the clinical performance testing, the ground truth was based on the visual evaluation and judgment of US dentists comparing images from DUO sensors to those from the predicate Brasseler GEM. This can be considered a form of expert consensus/reader judgment on image quality and diagnostic utility, but specific "ground truth" for disease presence/absence (like pathology or outcomes data) is not explicitly detailed as this is not an AI diagnostic device. The statement "DUO captured X-ray images are suitable for recognition of normal anatomical structures, dental pathologies, and abnormal conditions" implies the images were assessed for their ability to show such features.

8. Sample Size for the Training Set

• The provided text does not mention a training set for the DUO sensors. As this is a hardware device (sensor) and not an AI diagnostic algorithm, a "training set" in the context of machine learning is not applicable here. The device uses established CMOS and scintillator technologies and is compared against a predicate device.

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 concept of establishing ground truth for a training set is not applicable to this submission.

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The Lucas Lifecare's Life Ray handheld is indicated for use only by a trained and qualified dentist or dental technicians for both adult and pediatric subjects for producing diagnostic dental images using various intraoral image sensors/receptors.

LifeRay™ is a battery-operated, handheld, dental X-ray device. LifeRay™ employs a 100 kHz highfrequency DC X-ray generator. This oil-cooled and shielded tube head is energized by a rechargeable lithium-ion battery pack. The battery is housed under to enable portability. The battery gets charged when the device is docked into its cradle, which is powered through an AC - DC power supply. To focus exposure on the specified zone of the subject, and limit radiation leaking elsewhere out of the device, a shielded beam-limiting cone is engaged to the tube head. This restricts the X-ray field to 60 mm diameter, compatible to dental image receptors. An additional transparent, circular backscatter shield is provided which shall be permanently mounted around the exit of the beam limiting cone to arrest radiation scattering back from the subject, so clinicians can perform in proximity. A wrist lanyard facilitates secure grip, and an inclination display aids in consistent repeatability of radiographs. LifeRay™ employs a fixed tube current of 2.6 mA, but has three selectable tube voltages: 60, 65, or 70 kVp. Exposure duration can be set between 10 ms to 1 s in steps of 10 ms. All these presets can be selected from the home screen of the display through a practical keypad to achieve the best radiograph results.

The provided document describes the FDA 510(k) premarket notification for the LifeRay™ Intraoral Handheld X-ray device. However, it does not contain specific acceptance criteria, reported device performance data, sample sizes for test or training sets, details about ground truth establishment (number/qualifications of experts, adjudication methods), or information about MRMC studies or effect sizes for AI assistance.

The document focuses on demonstrating substantial equivalence to a predicate device (KaVo NOMAD Pro 2 Handheld X-ray System K173319) based on technological characteristics and non-clinical test data adhering to various IEC standards.

The only mention of "clinical performance data" is qualitative: "Clinical radiographic images using of LifeRay™ and the predicate device have been reviewed and compared to determine the substantial equivalence. Both intraoral X-ray systems generate adequate anatomical details using an intra oral sensor. Difference in edge definition and grayscale of bony structures for both images were negligible. Both intraoral X-ray systems generate sufficient X-ray levels to obtain acceptable edge definition and grayscale of bony and soft tissue images." This is a general statement, not a scientific study with quantitative metrics, defined acceptance criteria, or statistical analysis.

Therefore, I cannot provide the requested information about acceptance criteria and a study proving device performance in the format you asked, as the document does not contain this level of detail. It is a regulatory submission focused on substantial equivalence rather than a detailed performance study report.

Here's a breakdown of what can be extracted and what is missing:

Acceptance Criteria and Study for Performance (Information Not Provided in Document)

The document does not describe specific acceptance criteria tied to quantitative performance metrics for diagnostic image quality, nor does it detail a formal study that proves the device meets such criteria through quantitative measures. The "Clinical Performance Data" section is a qualitative statement of comparability.

Information that could not be extracted from the provided document:

1. A table of acceptance criteria and the reported device performance: This is absent. The document only offers a qualitative statement about image quality being "adequate" and "negligible" differences compared to the predicate.
2. Sample sizes used for the test set and the data provenance: Not specified.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not specified, as no formal ground truth establishment for a diagnostic performance study is described.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable, as no such study 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: Not applicable. This device is an X-ray generator, not an AI-powered diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an algorithm, but hardware.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable, as no formal diagnostic performance study with ground truth is detailed. The "clinical performance data" section refers to a review and comparison of images, implying subjective assessment rather than a structured ground truth process.
8. The sample size for the training set: Not applicable, as this is a hardware device, not an AI model.
9. How the ground truth for the training set was established: Not applicable, as this is a hardware device, not an AI model.

What the document does provide regarding the "study" context:

The document focuses on "Non-Clinical Test Data" and "Clinical Performance Data" used to establish Substantial Equivalence to a predicate device.

• Non-Clinical Test Data: This section details compliance with various international standards related to electrical safety, electromagnetic compatibility, radiation protection, X-ray tube assemblies, and dental intra-oral X-ray equipment. These are engineering and safety standards, not diagnostic performance metrics based on clinical images.
  • IEC 60601-1 Edition 3.2 2020-08 (General Safety)
  • IEC 60601-1-2 Edition 4.1 2020 (Electromagnetic Disturbances)
  • IEC 60601-4-2 Edition 1.0 2016-05 (Electromagnetic Immunity)
  • IEC 60601-1-3 Edition 2.1 2013-04 (Radiation Protection)
  • IEC 60601-2-28 Edition 3.0 2017 (X-ray Tube Assemblies)
  • IEC 60601-2-65 Edition 1.2 2021 (Dental Intra-oral X-ray Equipment)
  • IEC 62133-2: Edition 1.0 2017: (Lithium System)
  • IEC 62304 Edition 1.1 2015-06 (Software Life Cycle Processes - Note: The device is explicitly stated as not being a "cyber device" or subject to cybersecurity risks, and "not capable of network connection" which implies minimal software functionality on device itself)
• Clinical Performance Data:
  • Description: "Clinical radiographic images using of LifeRay™ and the predicate device have been reviewed and compared to determine the substantial equivalence. Both intraoral X-ray systems generate adequate anatomical details using an intra oral sensor. Difference in edge definition and grayscale of bony structures for both images were negligible. Both intraoral X-ray systems generate sufficient X-ray levels to obtain acceptable edge definition and grayscale of bony and soft tissue images."
  • Nature: This is a qualitative, comparative assessment, likely performed by the manufacturer or their chosen evaluators, rather than a blinded, multi-reader study with predefined metrics.
  • Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). Implicitly, it was likely internal testing by the manufacturer.

Summary Table of What could be extracted:

• "Both intraoral X-ray systems generate adequate anatomical details using an intra oral sensor."
• "Difference in edge definition and grayscale of bony structures for both images were negligible."
• "Both intraoral X-ray systems generate sufficient X-ray levels to obtain acceptable edge definition and grayscale of bony and soft tissue images."
  Quantitative Performance (from specifications for comparison):
• Exposure Time: 0.01s -1.0s (vs predicate 0.02s-1.0s)
• mA: 2.6 mA fixed (vs predicate 2.5 mA fixed)
• kVp: Adjustable 60, 65, 70 (vs predicate 60 kVp fixed) |
  | Sample Size (Test Set) | Not specified. (The document states "Clinical radiographic images...have been reviewed and compared," implying a set of images, but no quantity is given.) |
  | Data Provenance | Not specified (e.g., country of origin, retrospective/prospective). |
  | Experts for Ground Truth | Not specified. No formal ground truth establishment process for diagnostic accuracy is described. The "review and comparison" could have been done by internal personnel. |
  | Adjudication Method | Not applicable, as no formal study with expert reads and ground truth adjudication is presented. |
  | MRMC Comparative Study | Not applicable. This device is a hardware X-ray generator, not an AI diagnostic assistant. |
  | Standalone Performance | Not applicable. This is a hardware device, its "performance" is in generating X-rays of a certain quality, which is indirectly assessed via the qualitative image comparison and directly via compliance with safety/performance standards. |
  | Type of Ground Truth Used | Not applicable in the traditional sense of a diagnostic accuracy study. The "clinical performance" here refers to image comparability for the purpose of demonstrating substantial equivalence, not establishing diagnostic accuracy against a verified ground truth. |
  | Training Set Sample Size | Not applicable. This is a hardware device, not an AI model. |
  | Training Set Ground Truth Method | Not applicable. This is a hardware device, not an AI model. |

In conclusion, for a handheld intraoral X-ray device seeking 510(k) clearance, the emphasis is on demonstrating safety, effectiveness, and substantial equivalence to a legally marketed predicate device, primarily through engineering and hardware performance standards (Non-Clinical Test Data) and general qualitative image comparability (Clinical Performance Data) rather than rigorous clinical diagnostic accuracy studies common for software algorithms or novel diagnostic tools.

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The device is a diagnostic X-ray system, which is intended to be used by trained dental technicians as an extra-oral X-ray source for producing diagnostic x-ray images using intra-oral receptors. Its use is intended for both adults and pediatric subjects.

The device is a diagnostic X-ray system, which is intended to be used by trained dental technicians as an extra-oral X-ray source for producing diagnostic x-ray images using intra-oral receptors.

I am sorry, but the provided text from the FDA 510(k) clearance letter for the Remex-GR100 does not contain any information about acceptance criteria or a study proving the device meets those criteria, nor does it describe an AI component.

The document is a standard FDA clearance letter for an extraoral X-ray system, confirming its substantial equivalence to predicate devices and outlining the regulatory requirements for the manufacturer. It specifies the device's indications for use: "intended to be used by trained dental technicians as an extra-oral X-ray source for producing diagnostic x-ray images using intra-oral receptors. Its use is intended for both adults and pediatric subjects."

Therefore, I cannot provide the requested information about acceptance criteria, device performance, sample sizes, expert involvement, adjudication methods, MRMC studies, standalone performance, ground truth types, or training set details because this information is not present in the provided text.

To answer your questions, I would need a different document, such as a summary of the clinical or performance testing data submitted to the FDA for the device, or a specific study report.

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The RAYSCAN a- P, SC, OCL, OCS panoramic X-ray imaging system with Cephalostat is an extra-oral source X-ray system, intended for dental radiographic examination of the teeth, jaw, and oral structures, to include panoramic examinations and implantology and for TMJ studies and cephalometry. Images are obtained using the standard narrow beam technique.

RAYSCAN α-Expert (RAYSCAN α-P, SC, OCL, OCS) provides panoramic for scanning teeth, jaw and oral structures. By rotating the C-arm, which houses a high-voltage generator, an all-in-one Xray tube and a detector on each end, panoramic images of oral and maxillofacial structures are obtained byrecombining data scanned from different angles. Functionalities include panoramic image scanning for obtaining images of whole teeth, and a Cephalometric scanning option for obtaining Cephalic images.

The provided text describes a 510(k) premarket notification for the "RAYSAN α-Expert" dental X-ray system. The submission affirms its substantial equivalence to a predicate device, K142058. While it outlines several tests conducted to support this claim, it does not provide explicit acceptance criteria in a table format nor does it detail a specific study with quantitative performance metrics for a direct comparison against such criteria.

Here's a breakdown of the information that can be extracted, and where there are gaps regarding the requested specifics:

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

The document does not provide a table of acceptance criteria with corresponding device performance metrics. Instead, it states that "All test results were satisfactory" for performance (imaging performance) testing conducted according to IEC 61223-3-4. It also mentions that "a licensed practitioner reviewed the sample clinical images and deemed them to be of acceptable quality for the intended use." This indicates a subjective assessment of image quality rather than quantitative performance against defined acceptance criteria.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Test Set Sample Size: The document mentions that "images were gathered from all detectors of RAYSCAN α-Expert using protocols with random patient age, gender, and size" and that "Clinical imaging samples were collected from new detectors on the proposed device at the two offices where the predicate device was installed for the clinical test images." However, it does not specify the exact number of images or patients in the clinical test set.
• Data Provenance: The images were collected "at the two offices where the predicate device was installed for the clinical test images." The manufacturer is Ray Co., Ltd. located in South Korea. It's implied these are prospective clinical images gathered for the purpose of the submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Number of Experts: "The clinical performance of RAYSCAN α-Expert were clinically tested and approved by two licensed practitioners/clinicians."
• Qualifications of Experts: They are described as "licensed practitioners/clinicians." No specific details such as years of experience, specialization (e.g., radiologist, dentist), or board certification are provided.

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

The document states, "A licensed practitioner reviewed the sample clinical images and deemed them to be of acceptable quality for the intended use." It implies individual review, but does not specify any formal adjudication method (e.g., whether the two practitioners independently reviewed images and consensus was reached, or if there was a third adjudicator in case of disagreement).

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

• MRMC Study: No MRMC comparative effectiveness study is mentioned. This device is an X-ray imaging system, not an AI-assisted diagnostic tool for humans, so this type of study would not be applicable. The comparison is between the new device's image quality and the image quality of the predicate device.
• Effect Size: Not applicable.

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

This refers to an X-ray imaging device, not an algorithm. Therefore, "standalone (algorithm only)" performance is not applicable. The device's primary function is image acquisition.

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

The ground truth for the clinical image quality assessment appears to be expert opinion/consensus (from two licensed practitioners) regarding whether the images were "of acceptable quality for the intended use." There's no mention of pathology or outcomes data for establishing ground truth.

8. The sample size for the training set

The document mentions software validation, but this X-ray system is not described as an AI/ML device that requires a distinct "training set" in the context of machine learning model development. This question is not directly applicable to the type of device described.

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

As the device is not described as involving an AI/ML model with a training set, this question is not directly applicable. The software mentioned is for saving patient and image data, inquiries, and image generation, and was validated according to FDA guidance for software in medical devices, not specific AI/ML training.

Summary of what is present and what is missing:

• Acceptance Criteria/Performance Table: Not provided in the requested format. General statement of "satisfactory" test results and "acceptable quality."
• Test Set Sample Size & Provenance: Sample size not quantified. Provenance is South Korea, likely prospective.
• Number & Qualification of Experts: Two licensed practitioners/clinicians. No further qualification details.
• Adjudication Method: Not specified.
• MRMC Study: Not applicable.
• Standalone Performance: Not applicable.
• Type of Ground Truth: Expert opinion on image quality.
• Training Set Sample Size: Not applicable (not an AI/ML device in this context).
• Training Set Ground Truth: Not applicable.

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The Handheld Dental X-ray System, model XVbeam2000, is indicated for use only by a trained and qualified dentist or dental technician as an extraoral X-ray source to produce diagnostic X-ray images using intraoral image receptors. Its use is intended for both adult and pediatric subjects.

The subject device Handheld Dental X-ray System, model XVbeam2000, is a battery-operated, portable extraoral X-ray source system that is designed to generate X-rays to produce diagnostic quality intraoral X-ray images utilizing intraoral image receptors. The device can be used with three receptor types: film, digital intraoral X-ray sensors, and phosphor plates. The subject device is designed for use in a dental office or similar environments (hospital ward etc.) where appropriate safeguards are implemented. The subject device XVbeam2000 is an X-ray device with a DC generator. The handheld device features a main body (X-ray tube head), rechargeable battery (handset), charger, and charger AC/DC power supply. A beam-limiting cone is incorporated within the device. Internal and external shielding provide sufficient radiation protection to allow the clinician to remain in the operatory with the patient. The power is supplied by a rechargeable Lithium-Ion battery core pack built into a handset. This facilitates portability of the device.

The provided text is a 510(k) summary for a medical device (XVbeam2000 Handheld Dental X-ray System). This type of document is a premarket notification to the FDA to demonstrate that the device is substantially equivalent to a legally marketed predicate device, not a study proving the device meets specific acceptance criteria through clinical trials or performance studies that would typically generate the requested information.

Therefore, the requested information about acceptance criteria for device performance, sample sizes, expert ground truth, adjudication methods, MRMC studies, standalone performance, and training set details are not explicitly available in the provided document. The document focuses on demonstrating substantial equivalence through non-clinical performance testing and compliance with recognized standards.

However, I can extract the information that is present and note where the requested information is not provided.

Acceptance Criteria and Device Performance (Based on Non-Clinical Testing and Compliance with Standards)

The document states that "The test results show that all of the performance specifications have met the acceptance criteria. Verification and validation testing of the device was found acceptable to support the claim of substantial equivalence."

While specific numerical acceptance criteria and reported device performance for individual metrics are not tabulated, the document generally indicates that the device met the requirements of several FDA-recognized consensus standards for medical electrical equipment and X-ray systems.

Here's a table summarizing the general approach taken, as specific performance criteria and reported values are not detailed in the provided text:

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The Handheld X-ray System is indicated for use only by a trained and qualified dentist or dental technician for both adult and pediatric subjects as an extraoral dental X-ray source to produce X-ray images using intraoral image receptors.

These are hand-held portable battery operated x-ray generators for dental purposes. The Portable Dental X-Ray is an X radiation controlled emissions generator system, i.e., once put into service, is intended to be moved from one location to another by a person, used together with appropriate capture devices to generate intraoral radiological images for dental assessment, diagnosis and treatment. This equipment has exposure programs that can be applied to a variety of patients and has predefined exposure parameters depending on the type of patient. The operator is free to change these parameters depending on the situation. The equipment's human-machine interface consists of a control panel located on the top of the equipment, a local trigger button and a remote trigger (hard wired). The triggers are "dead-man" triggers, meaning they release and interrupt the exposure. The Portable Dental X-Ray was designed to be used in adult and children patients by trained dentists and dental technicians to produce X-ray images for diagnosis. The Portable Dental X-Ray is indicated for the production of intraoral medical images of teeth, mandible and oral structures; it assists in the diagnosis of diseases, planning of surgical treatment and monitoring. It is exclusively for dental use, and must be used and handled by qualified and trained health professionals according to the User Manual.

The provided text is an FDA 510(k) summary for a portable dental X-ray system. It focuses on demonstrating substantial equivalence to a predicate device rather than detailing specific acceptance criteria and a study proving the device meets those criteria, particularly in the context of an AI/algorithm-based medical device.

Therefore, many of the requested details about acceptance criteria, study design for AI evaluation (sample size, data provenance, expert ground truth, adjudication, MRMC, standalone performance, training set details), are not present in this document.

The document primarily covers non-clinical testing for safety, EMC, and basic performance of the X-ray system itself, not an AI algorithm.

However, based on the information provided, here's what can be extracted and what information is missing:

Information Present in the Document (Related to Device Performance Testing, Not AI):

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

  • The document primarily lists performance characteristics of the device and compares them to a predicate, rather than defining "acceptance criteria" in a quantitative, pass/fail sense for an AI.
  • For the X-ray device itself, non-clinical tests were performed.
  • Accepted Performance (device characteristics vs. predicate):
    • Indications for Use: Same as predicate.
    • Models: Proposed device has two (60 kV 2.5 mA, 65 kV 2.5 mA); predicate has one (60 kV 2.5 mA). "ALMOST IDENTICAL"
    • Timer Range: Proposed device 0.01 to 1 sec (0.01 sec steps); predicate 0.02-1.00 sec (0.01 sec steps). "Slightly greater range of steps."
    • Duty Cycle: Both 1:60. "SAME"
    • Waveform: Both DC. "SAME"
    • mA: Both 2.5 mA fixed. "SAME"
    • Where Used: Both Dental offices. "SAME"
    • Operating Temp. Range: Proposed device +10°C to +35°C; predicate -5°C to +40°C.
    • Supply Voltage (for battery charging): Proposed device 100-240 V~, 50-60 Hz; predicate 110/120V or 220/240V. "SAME (Charger is UL listed)"
    • Battery: Proposed device Rechargeable Lithium-ion, 21.6V - 2.50Ah; predicate Rechargeable Lithium-ion, 22.2V; 1.7 A-hr.
    • Electrical Safety Standards: Both ANSI/AAMI ES60601-1: A1:2012, C1:2009/(R)2012 and A2:2010/(R)2012, etc. "SAME"
    • EMC: Both IEC60601-1-2 Ed. 4. "SAME"
    • X-Ray Performance: Both 21 CFR 1020.30, 1020.31; IEC 60601-1-3; IEC 60601-2-65. "SAME"

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

  • Not applicable as this is not an AI/algorithm dataset evaluation.
  • However, for the non-clinical bench testing: "Bench Testing was performed to confirm compliance with the FDA Radiation Safety requirements of the Code of Federal Regulations including: accuracy and reproducibility specifications (kV, ma, time) and aluminum equivalence." The sample size for these bench tests (e.g., number of exposures, equipment tested) is not specified.

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

  • For the X-ray device itself, "Image Evaluation: Using a digital image receptor (cleared in K230732) images were acquired and were found to be of diagnostic quality for dental applications." This implies a qualitative assessment by an unnamed expert or group. The ground truth for "diagnostic quality" is not explicitly defined (e.g., against a gold standard).
  • For radiation safety, compliance was against regulatory standards (CFR).

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

  • Not applicable as this is not an AI/algorithm that requires a training set.

Information NOT Present in the Document (and likely not relevant to this specific 510(k) as it's for an X-ray generator, not an AI/CADe system):

• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience): Not applicable for an X-ray generator submission.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 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: Not applicable.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• 8. The sample size for the training set: Not applicable as this is not an AI/algorithm driven device.

In summary: The provided FDA 510(k) summary is for a Portable Dental X-Ray generator, not an AI-powered diagnostic device. Therefore, the detailed requirements for AI acceptance criteria and study designs are not addressed in this document. The document focuses on demonstrating the substantial equivalence of the X-ray generator's basic performance, safety, and electromagnetic compatibility to a legally marketed predicate device.

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