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The DRYVIEW CHROMA Imaging System is intended to provide hard copy images from digital imaging source output signals. The device is intended for use with DRYVIEW CHROMA film and reflective media. The device will interface with a variety of digital modalities, including, but not limited to, CR (Computed Radiology), DR (Digital Radiology), CT (Computerized Tomography), MRI (Magnetic Resonance Imaging). The images are to be used for medical diagnosis and referral to physicians and their patients. The DRYVIEW CHROMA Imaging System is not intended for use with FFDM or CR Mammography systems.

The DRYVIEW CHROMA Imaging System is an inkjet printing system. The DRYVIEW CHROMA Imaging System (CHROMA System) receives medical data including image and clinical report data from a digital modality. This data is received from medical image source devices (modalities) over a network and communicated to the CHROMA device via digital communication standard, DICOM. User control is performed directly by the modality or through the host control. The CHROMA System device prints the information received using piezoelectric inkjet technology. Tiny ink droplets are propelled from pizeoelectric nozzles in inige toenhology. " in media to form the image or report communicated by the digital modality. The CHROMA System device prints on transparent polyester based (film) as well as reflective (paper) media. Media is removed from a cartridge and transported into the CHROMA System device. Print data and media merge within the device. The CHROMA System employs the use of test patterns to verify imaging performance. A test pattern generator is incorporated to assure consistency between input signals and output density. Software is used to control the image management and machine functions. The information sent to the DICOM interface is used by the DICOM Interface to choose the correct set of printing parameters and halftone patterns for optimal image quality.

This looks like a 510(k) premarket notification for a medical imaging hardcopy device (an inkjet printer). Typically, for such a device, the "acceptance criteria" and "study" would focus on demonstrating that the output (the printed image) meets certain quality and consistency standards to be fit for medical diagnosis. However, the provided document focuses more on substantial equivalence to a predicate device and adherence to general safety and quality standards rather than detailed performance metrics of image quality that would be established through a clinical study.

Therefore, the information requested, particularly regarding clinical study details (sample size, ground truth, experts, MRMC studies), is largely not present in this document because this type of device (a printer) is evaluated differently than, for example, a diagnostic AI algorithm.

Here's a breakdown of what can be extracted and what is not available from the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

• Not explicitly stated for a "test set" in the context of clinical performance evaluation. The document describes meeting voluntary standards and substantial equivalence, which implies engineering and system-level testing, but not a patient-data-driven "test set" in the diagnostic sense.
• Data Provenance: Not applicable. The "data" are digital images from various modalities (CR, DR, CT, MRI) that the printer receives. The provenance of these images themselves is not relevant to the printer's performance evaluation as described.

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

• Not applicable. This device is a printer. Its performance is assessed through technical specifications and comparison to a predicate device, not by expert interpretation of printed images in a diagnostic study where ground truth would be established.

4. Adjudication method for the test set

• Not applicable. See point 3.

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. This is not an AI-assisted diagnostic device. It is a hardcopy printer. MRMC studies are not relevant nor mentioned.

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

• Not applicable. This is a printer, not a diagnostic algorithm. Its function is to reproduce digital images on physical media. Its "performance" is about faithful reproduction and reliability, not diagnostic accuracy.

7. The type of ground truth used

• Not applicable. The concept of "ground truth" for diagnostic accuracy (e.g., pathology, outcomes data) does not apply to a medical image hardcopy device like this. The closest analogous concept would be the fidelity of the printed output to the digital input, which is assessed through technical printing parameters and test patterns.

8. The sample size for the training set

• Not applicable. This is a hardware device (printer) with embedded software for control and image processing. It is not an AI/machine learning model that undergoes "training" on a dataset in the conventional sense.

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

• Not applicable. See point 8.

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