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Focus HD 43 Detector is indicated for digital imaging solutions designed to provide general radiographic diagnosis for human anatomy including both adult and pediatric patients. It is intended to replace film/screen systems in all generalpurpose diagnostic procedures. The device is not intended for mammography or dental applications.

Focus HD 43 Detector is a kind of wireless digital flat panel detector. It supports the single frame mode, with the key component of TFT/PD image sensor flat panel of active area: 42.67cm×42.67cm. The sensor plate of Focus 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 Focus 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, enable to complete the digitalization of the medical X-ray imaging with the DR system software. SDK(include iDetector) is intended 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. Focus HD 43 Detector. It states that the device is substantially equivalent to a predicate device (Mars1717X Wireless Digital Flat Panel Detector, K210314).

Crucially, the document does NOT contain information about a study proving the device meets acceptance criteria derived from a performance study with human readers or AI algorithms. Instead, it focuses on demonstrating substantial equivalence through non-clinical testing and comparison of technical specifications with a previously cleared predicate device.

Therefore, I cannot provide the requested information regarding acceptance criteria and a study proving the device meets those criteria, as typically seen in performance claims for AI/CADe devices or new clinical functionalities. The information given indicates a different pathway to market clearance for this type of device (a digital X-ray detector).

However, I can extract the information provided about the device's technical specifications and the comparison to its predicate, which implicitly serves as the "acceptance criteria" for demonstrating substantial equivalence for this type of hardware device.

Here's an attempt to structure the available information relevant to the prompt, acknowledging the absence of a "study" in the typical sense of AI/clinical performance, and focusing on the technical equivalence:

Acceptance Criteria and Study for Focus HD 43 Detector (Based on Substantial Equivalence to Predicate Device)

The "acceptance criteria" for the Focus HD 43 Detector are primarily its substantial equivalence in performance characteristics to the legally marketed predicate device, the Mars1717X Wireless Digital Flat Panel Detector (K210314). The "study" proving this equivalence is a series of non-clinical tests and direct comparison of specifications.

1. Table of Acceptance Criteria and Reported Device Performance

For a device like an X-ray detector, acceptance criteria are generally based on meeting or exceeding the technical specifications of a predicate device, along with demonstrating safety and electromagnetic compatibility. The following table showcases the comparison provided in the 510(k) summary:

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

• Test Set Sample Size: Not applicable in the context of a clinical test set with patient data for performance evaluation. The "tests" were non-clinical engineering and safety tests.
• Data Provenance: The 510(k) summary explicitly states that "Non-clinical studies have been performed," and "All test results are meet the standard requirements." The testing was conducted by the manufacturer, iRay Technology Taicang Ltd. (China). The data refers to engineering and safety performance data, not patient-specific clinical data.

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

• Not applicable. Ground truth as typically defined for clinical/AI performance studies (e.g., expert radiological reads, pathology) was not established for this device's premarket clearance, as it's a hardware device demonstrating substantial equivalence through non-clinical testing.

4. Adjudication Method for the Test Set

• Not applicable. There was no human "adjudication" of images for clinical ground truth. Non-clinical tests typically adhere to defined protocols and measurement standards.

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

• No. An MRMC study is relevant for assessing human reader performance, often with and without AI assistance, or comparing different imaging modalities/interpretations. This 510(k) is for a digital X-ray detector hardware, not an AI or CADe device.

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

• No. This is not an algorithmic device in the sense of AI/CADe. Its performance is demonstrated through its physical characteristics and image acquisition capabilities, which are then used by human readers and integrated into existing DR systems.

7. Type of Ground Truth Used

• The "ground truth" for this device's acceptance is based on engineering specifications, safety standards compliance (e.g., IEC/ES 60601-1, IEC 60601-1-2, ISO 10993-1), and direct comparison to the technical characteristics of a legally marketed predicate device. There is no clinical or pathological "ground truth" derived from patient outcomes involved in this specific premarket notification.

8. Sample Size for the Training Set

• Not applicable. This device is a hardware component (digital flat panel detector) and does not involve AI or machine learning that requires a "training set" of data.

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

• Not applicable, as there is no training set for this device.

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