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The LR 5200 Laser Film Recorder is indicated for use in providing diagnostic quality medical images on film for aid in physician diagnosis, including the printing of images from various digital imaging source modalities, including, but not limited to, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, Computed Radiography, Digital Mammography, and Nuclear Medicine.

The modification involves replacing the controller function of the currently marketed MG3000 component of the LR5200 system so that a new controller can transmit image information from an Ethernet to the LR 5200 at up to 100 MB/sec. The communications board in the LR5200 will also be modified to accept the new communications approach. The MG3000 will still be used in some applications, e.g., to interface a non-networked imaging modality directly to the LR 5200, or to interface a non-DICOM modality to a network.

This 510(k) summary describes a modification to an existing medical image hard copy device, the LR DICOM Controller, which replaces a component of the LR5200 system to allow for faster image transmission. The submission primarily focuses on demonstrating substantial equivalence to the predicate device, not on presenting novel performance data for the device. Therefore, many of the requested elements for describing a study proving the device meets acceptance criteria are not directly applicable or available in this document.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics for the LR DICOM Controller. The testing described is "proper performance to specifications through various in-house reliability and imaging performance demonstration tests." The "acceptance criteria" appear to be implicit in the device meeting its "specifications" for transmitting image information at up to 100 MB/sec and maintaining image quality suitable for diagnostic use, consistent with the predicate device.

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

Not applicable/Not provided. The document mentions "in-house reliability and imaging performance demonstration tests" but does not specify the sample size of images or the type of data used (e.g., retrospective or prospective, country of origin). Given the nature of the device (a controller for a printer), these tests would likely involve technical performance verification rather than clinical imaging studies on patient data.

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

Not applicable/Not provided. The testing described focuses on the technical performance of the controller and its ability to transmit images without degradation, not on interpreting images for diagnostic accuracy. Therefore, there's no mention of experts establishing ground truth for a test set of images.

4. Adjudication Method for the Test Set

Not applicable/Not provided. As no clinical test set requiring ground truth establishment by experts is described, no adjudication method is mentioned.

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

No. An MRMC study was not performed. The submission is for a device modification aimed at technical performance enhancement (faster data transmission) and maintaining substantial equivalence, not for assessing the impact of AI on human reader performance.

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

Yes, in a conceptual sense, the "performance demonstration tests" would evaluate the standalone technical performance of the LR DICOM Controller in managing image data transfer and output to the film recorder, separate from human interaction or interpretation. However, specific metrics are not provided.

7. The Type of Ground Truth Used

Not applicable. For a device like this, "ground truth" would relate to the fidelity of image transmission and output. This would involve comparing the input digital image data to the output on film for accuracy and quality, rather than a diagnostic ground truth established by experts or pathology. The document implies technical specifications were the "ground truth" for performance.

8. The Sample Size for the Training Set

Not applicable. This device is a hardware/software controller for a medical image printer. It does not employ machine learning or AI that would require a "training set" in the conventional sense.

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

Not applicable, as no training set for an AI/ML algorithm is involved.

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