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Mars1417V-TSI wireless digital flat panel detector and Mano4336W wireless digital flat panel 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. The device is not intended for mammography or dental applications.

Mars1417V-TSI and Mano4336W Wireless Digital Flat Panel Detectors (Hereinafter referred to as Mars1417V-TSI and Mano4336W) are the kind of wireless digital flat panel detectors. They support the single frame mode, with the key component of TFT/PD image sensor flat panel of active area: 34.56cm×42.00cm. Mars1417V-TSI and Mano4336W are totally same except for label and model name.

The sensor plate of Mars1417V-TSI and Mano4336W 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 Mars1417V-TSI and Mano4336W 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, enable to complete the digitalization of the medical X-ray imaging with the DR system software.

iRay SDK(include iDetector) is intend to supply API interface for DR system manufacturers. DR system manufacturer control the detector by SDK interface. SDK is not intend to be used directly by other users beside DR system manufacturers.

The provided text is a 510(k) summary for the iRay Technology Taicang Ltd. Wireless Digital Flat Panel Detectors (Models Mars1417V-TSI, Mano4336W). This document does not contain details about acceptance criteria, a specific study proving the device meets those criteria, or clinical performance data in the context of diagnostic accuracy. These types of studies (like MRMC or standalone performance evaluations with ground truth) are typically required for AI-powered diagnostic devices, which this is not.

This document focuses on establishing substantial equivalence to a predicate device (Mars1417XF-CSI, K182551) based on non-clinical performance characteristics, safety, and technological characteristics, rather than clinical performance for diagnostic tasks.

Therefore, most of the requested information regarding acceptance criteria, study details, sample sizes, expert qualifications, and ground truth establishment for diagnostic accuracy cannot be extracted from this document.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

The document does not explicitly state acceptance criteria for diagnostic performance or present a table comparing such criteria to reported diagnostic performance. It focuses on technical specifications and safety standards.

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

This information is not provided in the document. The substantial equivalence argument relies on non-clinical performance and safety testing, not on a clinical test set for diagnostic accuracy with patient data.

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)

This information is not provided because there was no clinical diagnostic performance study described. The document is about the technical specifications and safety of the X-ray detector, not an AI or diagnostic algorithm that requires expert ground truth.

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

This information is not provided as there was no clinical diagnostic performance study 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 such study is mentioned or implied in this 510(k) summary. This device is a digital flat panel detector, a hardware component for X-ray imaging, not an AI-assisted diagnostic software.

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

No standalone diagnostic algorithm performance study is mentioned. This device is a digital flat panel detector, not a diagnostic algorithm.

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

Not applicable, as no clinical diagnostic performance study with ground truth was described.

8. The sample size for the training set

Not applicable, as this device is a hardware component and not an AI/ML algorithm that requires a training set of imaging data.

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

Not applicable, as this device is a hardware component and not an AI/ML algorithm that requires a training set with established ground truth.

In summary: The provided 510(k) summary is for an X-ray detector, a hardware device. The equivalence argument is based on technical specifications, electrical safety, EMC testing, and biological evaluation, comparing it to a legally marketed predicate device. It does not involve AI/ML components or clinical diagnostic accuracy studies that would require the establishment of ground truth by experts from a sample of patient data. Therefore, most of the questions regarding clinical study design for diagnostic performance cannot be answered from this document.

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