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Lux HD 35 Detector and Lux HD 43 Detector are indicated for digital imaging solutions designed to provide general radiographic diagnosis for human anatomy including both adult and pediatric patients. They are intended to replace film/screen systems in all general-purpose diagnostic procedures. Lux HD 35 Detector and Lux HD 43 Detector are not intended for mammography or dental applications.

Lux HD 35 Detector and Lux HD 43 Detector are digital flat panel detector. They support the single frame mode, with the key component of TFT/PD image sensor flat panel of active area: 35cm×43cm (Lux HD 35 Detector)/42.67cm × 42.67cm (Lux HD 43 Detector) .The differences between two models are overall change in the dimensions of the image receptor. The sensor plate of Lux HD 35 Detector and Lux HD 43 Detector is direct-deposited with CsI scintillator to achieve the conversion from X-ray to visible photon. The visible photons are transformed to electron signals by diode capacitor array within TFT panel, which are composed and processed by connecting to scanning and readout electronics, consequently to form a panel image by transmitting to PC through the user interface. The major function of the Lux HD 35 Detector and Lux HD 43 Detector is to convert the X-ray to digital image, with the application of high resolution X-ray imaging. Both kinds of detectors are the key component of DR system. The Digital Radiographic Imaging Acquisition Software Platform - DR is part of the system, it is used to acquire, enhance, view image from Lux HD 35 Detector and Lux HD 43 Detector.

The provided text is a 510(k) summary for a medical device (Lux HD 35 Detector and Lux HD 43 Detector). It details the device's characteristics, intended use, and comparison to a predicate device to demonstrate substantial equivalence.

However, the provided document does not contain information about the acceptance criteria nor a study that proves the device meets specific performance criteria through a clinical evaluation involving human readers, ground truth establishment, or sample sizes related to AI/algorithm performance.

The "Non-clinical study" section primarily discusses:

• Electrical Safety and EMC testing: Adherence to IEC/ES 60601-1 and IEC 60601-1-2.
• Biological Evaluation: Evaluation of materials contacting operators/patients based on FDA guidance.
• Non-clinical Considerations: Stating substantial equivalence to the predicate device for non-clinical aspects mentioned in FDA guidance for solid-state X-ray imaging devices.
• Clinical Consideration: Stating that intended use, fundamental scientific technology, regulatory requirements, non-clinical performance, labeling, and quality-assurance programs are the same as the predicate device. It explicitly mentions: "There is no any negative change about clinical performance from predicate device."
• Wireless testing: Compliance with ANSI IEEE C63.27-2017.
• Cybersecurity testing: Compliance with section 524B(b)(2) of the Federal Food, Drug, and Cosmetics Act.

This submission clearly relies on demonstrating substantial equivalence to a predicate device (Carestream Health, Inc. Focus HD 43 Detector, K213529) through technical and safety comparisons, rather than presenting a performance study with acceptance criteria and results for an AI/algorithm.

Therefore, I cannot populate the table or answer the specific questions about "acceptance criteria and the study that proves the device meets the acceptance criteria" as they pertain to AI/algorithm performance, ground truth, expert adjudication, or MRMC studies. The document does not describe such a study.

The crucial information regarding acceptance criteria and performance data for an AI/algorithm, as requested in your prompt, is absent from the provided text. The document is a 510(k) a summary for a hardware device (X-ray detector) and focuses on the safety and performance equivalency to a predicate hardware device. It does not provide data on AI/algorithm performance against a clinical ground truth.

If this device were to include an AI component that required such a study for its clearance, that information would typically be detailed in a separate section of the 510(k) submission, outlining the AI's intended use, performance metrics, validation strategy, and results against a defined ground truth. This document does not contain that.

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The Digital Wireless Intraoral X-Ray Sensor (Pluto0002XW) is used in conjunction with dental Radiography in medical units. The product is used for dental X-ray examination and the diagnosis of structural diseases. The product is expected to be used in hospitals and clinics, operated and used by trained professionals under the guidance of doctors. This device is not intended for mammography and conventional photography applications.

This device is suitable for providing dental radiography imaging for both adult and pediatric.

The Pluto0002XW Digital Wireless Intraoral X-Ray Sensor (Hereinafter referred to as Pluto0002XW) contains the digital intra-oral sensor. It features a 20um pixel pitch CMOS sensor with directly deposited CsI:Tl scintillator which ensures optimal resolution.

The major function of the Pluto0002XW is to convert the X-ray to digital image, with the application of high resolution X-ray imaging. Pluto0002XW is the key component of intra-oral DR system, enables to complete the digitalization of the medical X-ray imaging with the intra-oral DR system software.

The iRay intra-oral software (iRayDR) is part of the system, it is used to acquire, enhance, analyze, view and share images from the sensor.

This FDA document, K230998, is a 510(k) summary for a Digital Wireless Intraoral X-Ray Sensor. It focuses on demonstrating substantial equivalence to a predicate device rather than detailing extensive performance studies against specific acceptance criteria for diagnostic efficacy. Therefore, much of the requested information regarding "acceptance criteria" and "study that proves the device meets the acceptance criteria" in terms of clinical performance and AI-assistance aspects (e.g., MRMC studies, standalone AI performance) is not present as this device is a hardware component (X-ray sensor) and not an AI/ML-driven diagnostic software.

However, based on the provided text, we can glean information about the non-clinical studies performed to demonstrate safety and effectiveness for substantial equivalence.

Here's an attempt to answer your questions based solely on the provided text:

Acceptance Criteria and Device Performance (Non-Clinical)

The document does not present a table of acceptance criteria for diagnostic performance (e.g., sensitivity, specificity, accuracy) as it's not a diagnostic AI device or a comparative clinical study for human interpretation. Instead, the "acceptance criteria" can be inferred from the standards the device was tested against for safety, electromagnetic compatibility (EMC), wireless functionality, cybersecurity, and biocompatibility. The "reported device performance" is simply that the device "meet[s] the standard requirements" for these tests.

No explicit quantitative acceptance criteria or reported performance for diagnostic accuracy, sensitivity, or specificity are provided because this device is an imaging sensor, not a diagnostic algorithm that interprets images.

Study Details (Non-Clinical as reported in the 510(k) summary)

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

   Acceptance Criterion (Inferred from Standard Compliance)	Reported Device Performance (Summary Statement)
   Electrical Safety (IEC/ES 60601-1, IEC60601-2-65)	"All test results are meet the standard requirements."
   EMC Testing (IEC 60601-1-2)	"All test results are meet the standard requirements."
   Wireless Functionality & Coexistence (ANSI IEEE C63.27-2017)	"All test results are meet the standard requirements."
   Cybersecurity (Federal Food, Drug, and Cosmetics Act section 524B(b)(2))	"...to provide a reasonable assurance that the subject device with its wireless capabilities are cybersecure."
   Biocompatibility (ISO10993-1)	"the evaluation results and test result assured the safety the same as the predicate device."

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

   • Not applicable for clinical performance data. The document describes non-clinical engineering and safety tests. Thus, "sample size" would refer to the number of devices or test conditions, which are not specified in detail.
   • Data Provenance: Not specified, but generally, these tests are conducted in certified labs (often in the country of manufacture, China in this case, or by accredited third-party labs). The testing is prospective for the purpose of the 510(k) submission.

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

   • Not applicable. This relates to clinical diagnostic interpretation by experts, which is not evaluated for this hardware device.

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

   • Not applicable. This relates to clinical diagnostic interpretation.

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, an MRMC study was not done. This device is an X-ray sensor, not an AI diagnostic tool. The document does not describe any human reader studies, with or without AI assistance.

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

   • No, a standalone algorithm performance study was not done. This device is hardware.

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

   • Not applicable for clinical diagnostic ground truth. For the non-clinical tests, the "ground truth" is compliance with the specified international and national safety and performance standards (e.g., IEC, ANSI IEEE, ISO).

8. The sample size for the training set:

   • Not applicable. This pertains to AI/ML model training, which is not mentioned for this device.

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

   • Not applicable. This pertains to AI/ML model training, which is not mentioned for this device.

In summary: The provided FDA document (a 510(k) summary) for the Digital Wireless Intraoral X-Ray Sensor focuses on demonstrating substantial equivalence through non-clinical performance and safety testing. It does not contain information related to clinical diagnostic performance, AI performance, or human-reader studies, as the device is a data acquisition component (X-ray sensor), not a diagnostic interpretation tool or AI software.

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Used in conjunction with a pulsed dental X-ray machine, the CS 6200 is intended for medical institutions to perform static digital X-ray imaging facilitating the diagnosis of the teeth, jaw, mouth, and other structural diseases.

The CS 6200 is a USB-driven digital intraoral X-ray sensor based on CMOS technology that is specially designed for acquiring real-time high-quality dental diagnostic images. Image data acquired from the device can be transmitted via a USB 2.0 port to a workstation for display and processing.

The provided text is a 510(k) Summary for the iRay Imaging Technology (Haining) Limited Digital Intraoral X-Ray Sensor (Model CS 6200). It does not contain information about acceptance criteria or a specific study proving the device meets these criteria in the format requested.

The document focuses on demonstrating substantial equivalence to a predicate device (iRay Technology Co., Ltd. PlutoX Digital Intraoral X-Ray Imaging System, K210312) through non-clinical testing. It outlines the technological characteristics of both the proposed and predicate devices and states that non-clinical studies were performed to show equivalence in various performance aspects.

Specifically, it mentions:

• Nonclinical Considerations: "According to the Guidance for the Submission of 510(k)s for Solid State X-ray Imaging Devices, the non-clinical studies have been performed and the results have shown that the CS 6200 are substantially equivalent to the predicate devices on the Market (K210312): Dose to output signal transfer function, Signal to noise ratio, uniformity, Defect, Minimum triggering dose rate, Modulation transfer function (MTF), Spatial resolution, Low contrast resolution and Image Acquisition time."
• Clinical Consideration: "Clinical data is not needed to characterize performance and establish substantial equivalence. The non-clinical test data characterizes all performance aspects of the device based on well-established scientific and engineering principles."

Therefore, I cannot populate the table or answer the specific questions about acceptance criteria, sample sizes, expert involvement, or adjudication methods for clinical studies, as the submission explicitly states that clinical data was not required or provided. The study performed was a non-clinical equivalence study based on technical specifications and performance measurements, not a human reader or image interpretation study.

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