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The HD Mediastinoscope is intended to aid the surgeon in viewing the mediastinum and facilitate the introduction and removal of surgical instruments during ENT endoscopic surgical procedures.

The HD Mediastinoscope is a reusable videoendoscope intended to be used in conjunction with the X-link module of the Image1 S Camera Control Unit. The HD Mediastinoscope is comprised of four main components: CMOS sensor at the distal end of the endoscope, an oval insertion portion (spatula), handle, and internal LED light source. The spatula can accommodate up to 2 x 5 mm instruments.

Here's an analysis of the provided text regarding the acceptance criteria and study for the HD Mediastinoscope:

Due to the nature of the device (a physical surgical instrument rather than an AI/software device), the provided document does not contain information typically found in acceptance criteria and studies for AI/ML devices, such as sensitivity, specificity, or AUC.

Based on the provided text, the "acceptance criteria" appear to be related to the device's technical specifications and safety/effectiveness in comparison to predicate devices, rather than specific performance metrics like those for an AI algorithm.

Acceptance Criteria and Reported Device Performance

The "acceptance criteria" are implied through the comparison with existing predicate and reference devices and compliance with recognized standards. The "performance" is demonstrated through non-clinical testing, particularly a cadaver test study.

Details of the Study (Non-AI/ML Device)

Since this is a traditional medical device (mediastinoscope) and not an AI/ML device, many of the requested points related to AI/ML studies (sample size for test set, data provenance, number of experts for ground truth, adjudication method, MRMC study, standalone performance, training set size, ground truth for training set) are not applicable or not specified in this 510(k) summary.

However, based on the information provided:

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

   • The primary non-clinical performance test mentioned is a cadaver test study.
   • The sample size (number of cadavers or tests performed) is not specified in the document.
   • The data provenance (country of origin, retrospective/prospective) is not specified.

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

   • The document mentions "a cadaver test study was conducted to demonstrate that the change in spatula design...". It does not specify the use of "experts" to establish a "ground truth" in the way an AI/ML study would (e.g., radiologists labeling images). Instead, the study likely involved technical assessment and observation by qualified personnel (e.g., surgeons, engineers).
   • Not explicitly stated in terms of "ground truth experts" for an AI/ML context.

3. Adjudication method for the test set:

   • Not applicable / Not specified for this type of device and study.

4. 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, an MRMC study was not conducted. This is not an AI-assisted device.

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

   • Not applicable. This is a physical surgical instrument, not an algorithm.

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

   • For the cadaver study, the "ground truth" would likely be the direct observation and technical assessment of the device's performance in a cadaveric model (e.g., ease of introduction, visualization, ability to facilitate instrument use, assessment of tissue damage, etc.) by the study investigators. This is not a "ground truth" in the sense of a diagnostic label for an AI.

7. The sample size for the training set:

   • Not applicable. This device does not use a training set as it is not an AI/ML product.

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

   • Not applicable.

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The HD Mediastinoscope is intended to aid the surgeon in viewing the mediastinum and facilitate the introduction and removal of surgical instruments during ENT endoscopic surgical procedures.

The components subject of this submission are: HD Mediastinoscope (Part Number: 10973HD), and the IMAGE1 S CCU. The CCU consists of the IMAGE1 S Connect Module (Model Number: TC200US) and IMAGE1 S X-Link (Model Number: TC301US).

This document describes the FDA's 510(k) clearance for the Karl Storz HD Mediastinoscope (K202272). The device is intended to aid surgeons in viewing the mediastinum and facilitating the introduction and removal of surgical instruments during ENT endoscopic procedures.

The information provided focuses on the substantial equivalence determination based on non-clinical performance data, rather than a study proving the device meets AI-specific acceptance criteria. Therefore, most of the requested information regarding AI model performance, ground truth establishment, expert review, and clinical study details is not present in the provided text.

Here is a breakdown of what can be extracted and what is not available based on the request:

1. A table of acceptance criteria and the reported device performance

The document does not specify quantitative acceptance criteria in a table format for performance. Instead, it states compliance with recognized standards and successful completion of various bench tests.

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

The document explicitly states: "Clinical testing was not required to demonstrate the substantial equivalence to the predicate devices. Non-clinical bench testing was sufficient to establish the substantial equivalence of the modifications." This means there was no clinical test set in the traditional sense for assessing device performance in a human population. All testing was non-clinical bench testing. Therefore, sample size and data provenance (country, retrospective/prospective) related to a clinical test set are not applicable here.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable, as no clinical test set or ground truth in the context of diagnostic interpretation (e.g., for an AI model) was established. The ground truth for bench testing would be metrology standards and physical measurements.

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

Not applicable, as no clinical test set involving human readers or interpretation was performed.

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 mediastinoscope (a physical viewing instrument), not an AI-assisted diagnostic tool.

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

Not applicable. This is not an algorithm-only device.

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

For the non-clinical bench testing, the ground truth would be based on established engineering and optical metrology standards, and potentially manufacturer specifications for the device's components. For biocompatibility and reprocessing, the ground truth is compliance with the listed ISO and AAMI standards.

8. The sample size for the training set

Not applicable, as this is not an AI/ML device that requires a training set.

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

Not applicable, as this is not an AI/ML device.

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