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The ALI comPACS Data Compression Module for Diagnostic Images is an accessory to the ALI UltraPACS (K925965/A) Picture Archiving and Communication System. Through the use of JPEG and Motion JPEG lossy compression, ALI comPACS is intended to provide:

1. significant reductions in the amount of electronic storage space for digitized diagnostic still images and digitized video of diagnostic images while maintaining medically acceptable diagnostic quality of the images; and
2. significant reductions in the amount of time to transmit digitized diagnostic still images and digitized video of diagnostic images from storage to viewing sites, while maintaining medically acceptable diagnostic quality of the images.

The ALI comPACS Data Compression Module for Diagnostic Images is an accessory to the ALI UltraPACS (K925965/A) Picture Archiving and Communication System. ALI comPACS uses industry standard JPEG and Motion JPEG lossy compression for the compression of digitized diagnostic still images and digitized video of diagnostic images, respectively.

Here's an analysis of the provided text, extracting the requested information about acceptance criteria and the supporting study:

Acceptance Criteria and Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document explicitly states the primary goal is "maintaining medically acceptable diagnostic quality." However, it does not define what "medically acceptable diagnostic quality" means in terms of specific, quantifiable metrics (e.g., image quality scores, diagnostic accuracy, detection rates). It only describes the mechanism (lossy compression) and the ranges applied. Therefore, the "reported device performance" in the table above refers to the claims and features related to achieving this goal, rather than documented quantitative results against defined acceptance criteria.

Study Information

The provided document describes the device and its intended use, as well as a comparison to a substantially equivalent device. However, it does not describe a clinical study or performance testing that proves the device meets the "medically acceptable diagnostic quality" claim. The document relies on the following for demonstrating efficacy:

• Substantial Equivalence: The core argument for safety and effectiveness is based on substantial equivalence to the CEMAX-ICON Archive Manager 2.0 and Autorad modules (K955092). The document meticulously compares the features of ALI comPACS to the predicate device, highlighting similarities and distinguishing features (primarily the Motion JPEG capability for video).
• Industry Standard Technology: It highlights that ALI comPACS uses "industry standard JPEG and Motion JPEG lossy compression." It asserts that "Motion JPEG is an intraframe JPEG compression format... which is essentially a storage format for sequential JPEG compressed images presented at a chosen frame rate. Thus Motion JPEG compression does not raise any additional issues of safety or effectiveness beyond those already addressed by JPEG compression itself." This implies that because JPEG is a recognized standard, its application here is inherently acceptable, and Motion JPEG, being based on JPEG, carries the same assumed safety and effectiveness.
• User Control and Preference: The document states, "The clinical operator selects the compression ratio based on medical preference of two images/videos, one the original image/video and the second the image/video compressed to the desired lossy compression ratio." This places the onus of determining "medically acceptable diagnostic quality" on the clinical operator's judgment at the point of use, rather than through a pre-defined validation study.

Given this, the following sections cannot be fully answered as no such study is described in the provided text.

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

• Not applicable. No specific performance study with a test set generating new data is described. The document relies on substantial equivalence and the inherent nature of JPEG and Motion JPEG compression.

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

• Not applicable. No specific performance study with a test set subject to expert review is described. The document references "medical preference" by a "clinical operator" when selecting compression ratios, but this is not part of a formal ground truth establishment process for a validation study.

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

• Not applicable. No formal test set and ground truth adjudication is 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

• Not applicable. This device is a data compression module, not an AI diagnostic assistant. Thus, an MRMC study comparing human readers with and without AI assistance is not relevant to its function and was not performed.

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

• Not applicable. While the algorithm operates standalone in compressing data, no standalone performance study (e.g., quantitative image quality metrics, diagnostic accuracy without human review of compressed images vs. original) is described in the provided text. The device's efficacy is tied to the concept of "medically acceptable diagnostic quality" as judged by a human operator.

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

• Implicit based on "medical preference" by clinical operators. For the operation of the device, the ground truth for "medically acceptable diagnostic quality" is established by the clinical operator visually comparing original and compressed images to their "medical preference." For the regulatory claim, the ground truth is implicitly derived from the acceptance of JPEG compression as an industry standard and the substantial equivalence to a predicate device. No formal external ground truth (e.g., pathology, long-term outcomes, expert consensus on a standardized dataset) is described as being used to validate the device itself.

8. The sample size for the training set

• Not applicable. This device is a rule-based compression algorithm (JPEG/Motion JPEG); it does not employ machine learning or require a training set in the conventional sense.

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

• Not applicable. As above, no training set or machine learning components are described for this device.

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