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MuCheck is an independent computer based verification of the monitor unit or dose calculated by the primary radiation treatment planning system.

The intended use of the MuCheck software has been extended to include an optional module, Gamma-Knife QA Check to independently verify the dose for single or multiple points that have been previously calculated by the Gamma Knife treatment planning system or other points as determined by the physicist.

The Gamma-Knife QA Check Program is a software program that is designed to operate on an IBM compatible personal computer in a Windows environment. It has been designed to onerate either in a stand alone mode independent of the Gammaknife treatment planning grown or to import plans from the GammaKnife treatment planning system. It does not connect to a control any radiation hardware device. Gamma Knife QA Check performs dose calculations to verify the dose calculated by the primary GammaKnife radiation treatment planning system.

The provided K091602 document focuses on the substantial equivalence of the "Mucheck Gamma-Knife QA Check" software to predicate devices. It describes the device's function as a quality assurance tool for verifying dose calculations in Gamma-Knife radiation treatment planning.

However, the document explicitly states:
"Clinical testing was not required to demonstrate substantial equivalence or safety and effectiveness."

This crucial statement means that a formal study demonstrating the device meets specific acceptance criteria based on clinical performance data (like those typically associated with medical imaging or diagnostic AI) was not performed or required for this 510(k) clearance.

Instead, the submission relied on non-clinical verification and validation tests.

Therefore, I cannot provide all the requested information because the nature of this 510(k) submission does not involve:

1. A table of acceptance criteria and reported device performance based on clinical or comparative studies. The "acceptance criteria" here refer to internal system specifications and matching results with the primary planning system.
2. Sample size for the test set and data provenance: No clinical test set.
3. Number of experts and their qualifications for ground truth: No clinical ground truth established.
4. Adjudication method for the test set: Not applicable.
5. Multi-reader multi-case (MRMC) comparative effectiveness study: Not performed. This device is a software tool for dose calculation verification, not a diagnostic aid for human readers.
6. Standalone performance study: The non-clinical tests compared the device's calculations to the primary planning system.
7. Type of ground truth used: For non-clinical tests, the "ground truth" was the expected calculation results or the results from the primary Gamma-Knife treatment planning system.
8. Sample size for the training set: As the device performs deterministic dose calculations based on established physics principles, it is highly unlikely to involve a "training set" in the machine learning sense. The software would be developed and verified against known physics models and calculation engines.
9. How ground truth for the training set was established: Not applicable in the context of a machine learning training set.

Based on the provided document, here's what can be inferred or directly stated regarding performance and verification:

1. Table of Acceptance Criteria and Reported Device Performance (Non-Clinical Focus)

• Note: The document only mentions "All system specifications were met" and "test results all matched very closely." It does not provide specific quantitative acceptance criteria or detailed performance metrics in the format of a clinical study. The criteria were likely internal for software verification.

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

• Test Set Size: Not explicitly stated. The document refers to "non-clinical tests" conducted using "the Gamma-Knife treatment planning system and Gamma-Knife QA Check." This implies a set of test cases or scenarios were run, but the number is not quantified.
• Data Provenance: Not applicable in terms of patient data or clinical images. The "data" would be input parameters for dose calculation, derived from configurations or plans within the Gamma-Knife treatment planning system.

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

• Not applicable as no clinical ground truth was established by external experts. The verification likely involved internal engineers or physicists ensuring the software's calculations aligned with expected physics models or the predicate device's calculations.

4. Adjudication method for the test set:

• Not applicable. This device is a software calculator, not a diagnostic tool requiring expert adjudication.

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, an MRMC comparative effectiveness study was not done. This device is a dose calculation verification software, not an AI-powered diagnostic tool for human readers.

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

• Yes, in essence. The "non-clinical tests" evaluated Gamma-Knife QA Check's calculations directly against those of the primary Gamma-Knife treatment planning system. This constitutes an "algorithm only" comparison for its intended function (dose calculation verification).

7. The type of ground truth used:

• For the non-clinical tests, the "ground truth" was effectively:
  • Expected scientific/physics calculations: The software's output was compared against established radiation physics models.
  • Predicate device's calculations: The results were compared to the primary GammaKnife treatment planning system (which itself would have been verified and validated).

8. The sample size for the training set:

• Not applicable. This device performs deterministic calculations based on algorithms for radiation dose, not machine learning that requires a "training set" of data.

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

• Not applicable. As it's not a machine learning model, there is no "training set" or corresponding ground truth establishment in that context. The "ground truth" for the software's development and internal validation would stem from established radiation physics principles and previous, validated dose calculation methods.

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