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Software used in a device that saves, enlarges, reduces, views as well as analyzes, transfers and prints medical images. (excluding fluoroscopic, angiographic, and mammographic applications.)

LG Acquisition Workstation Software ASHK100G is a diagnostic software for final postprocessed X-ray images of body parts of actual patients acquired through the integration of digital X-ray detectors (DXD+ASHK100G; refer to below list for the compatible LG DXD series) and X-ray generators. By integrating the [MWL] and the [PACS] server, this software can be used to check the information and images of the patients' body parts in real time in an HIS (Hospital Information System) based environment.

The provided text is a 510(k) Summary for the X-Clever (ASHK100G) device. Within this summary, information is given about performance testing relating to a new Wide Dynamic View (WDV) algorithm. However, the document does not provide a table of acceptance criteria, specific reported device performance metrics against those criteria, or the detailed study design (sample sizes, expert qualifications, adjudication methods, MRMC study details, ground truth specifics for test and training sets) that would typically be found in a detailed study report.

Here's a breakdown of the available information and what is not present:

1. Table of Acceptance Criteria and Reported Device Performance:

The document states: "The performance test results indicate that the WDV algorithm enhances the performance of the proposed medical device by normalizing tissue through the creation of a regional map based on image location and distribution characteristics. This leads to more natural and consistent images compared to those that rely solely on residual and image brightness signal composition."

However, this is a qualitative statement, not a table with specific acceptance criteria (e.g., quantitative metrics like AUC, sensitivity, specificity, or specific perceptual scores with thresholds) and corresponding numerical results.

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

• Sample size: Not specified.
• Data provenance: Not specified. The document only mentions "clinical opinions on the images processed with WDV," implying human readers were involved in assessing image quality, but it does not detail the origin of these images (e.g., country, retrospective/prospective).

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

The document mentions "clinical opinions on the images processed with WDV." This suggests that experts evaluated the images, but:

• Number of experts: Not specified.
• Qualifications of experts: Not specified (e.g., "radiologist with 10 years of experience").

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

Not specified. The process of how "clinical opinions" were combined or used to establish a ground truth or a performance measure is not detailed.

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:

• MRMC study: The document does not explicitly state that a formal Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done comparing human readers with and without AI assistance. It mentions "clinical opinions on the images processed with WDV," which implies human review of images processed by the device's new algorithm, but it doesn't describe a comparison between human performance with and without the device's assistance.
• Effect size of human reader improvement: Not reported.

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

The device (X-Clever ASHK100G) is described as "Software used in a device that saves, enlarges, reduces, views as well as analyzes, transfers and prints medical images." The "WDV algorithm" is an image processing algorithm. Its performance is assessed in terms of generating "more natural and consistent images." This evaluation implicitly refers to the standalone performance of the algorithm in processing images, but it's not a diagnostic algorithm outputting clinical findings directly. The "clinical opinions" are likely an assessment of the quality of the images produced by the algorithm, rather than its diagnostic accuracy for specific conditions.

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

The "ground truth" seems to be effectively expert opinion/consensus on image quality. The document explicitly states: "the performance test for the WDV algorithm includes clinical opinions on the images processed with WDV." It's not based on pathology, outcomes data, or a definitive diagnostic reference standard for a specific disease. Instead, it's about the perceived improvement in image characteristics.

8. The sample size for the training set:

Not specified. The document discusses a "new WDV algorithm" and "optimization process," indicating machine learning or image processing algorithm development, but it does not provide details on training data.

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

Not specified. As the training set size itself is not mentioned, neither is the method for establishing its ground truth.

Summary of Available Information (from the provided text):

• Device: X-Clever (ASHK100G), a medical image management and processing system.
• Key Change: Addition of a Wide Dynamic View (WDV) algorithm for image processing.
• Performance Claim for WDV: "enhances the performance of the proposed medical device by normalizing tissue through the creation of a regional map based on image location and distribution characteristics. This leads to more natural and consistent images compared to those that rely solely on residual and image brightness signal composition."
• Performance Evaluation: A "performance test for the WDV algorithm includes clinical opinions on the images processed with WDV."
• Conclusion: "the addition of the WDV feature has not had any negative impact on the performance and safety of the proposed device."
• Clinical Studies: "No clinical studies were considered necessary and performed. ... Therefore, a separate clinical study is not applicable in this case."

In essence, the document confirms that a performance test was conducted for the WDV algorithm using clinical opinions on image quality, and the results were positive (improved image naturalness and consistency). However, it lacks the detailed quantitative metrics, sample sizes, and expert qualification specifics typically requested for a comprehensive study description.

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