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510(k) Data Aggregation
(82 days)
STEALTHSTATION PASSIVE INSTRUMENT OPTION
The StealthStation® System is intended as an aid for precisely locating anatomical locations in either open or percutaneous procedures. The StealthStation® System is indicated for any medical condition in which the use of stereotactic surgery may be considered to be safe and effective, and where a reference to a rigid anatomical structure, such as the skull, a long bone, or vertebra, can be identified relative to a CT or MR based model of the anatomy.
This submission describes updates made to the StealthStation® System to provide for optical tracking of instruments via the use of reflection of infrared light off of reflective spheres on the instruments.
The provided text does not contain detailed information about the acceptance criteria or a specific study that proves the device meets those criteria. It states that "Performance data was provided to support the claim of substantial equivalence" but does not elaborate on what that data entails, what the specific acceptance criteria were, or the methodology of the study.
Therefore, many of the requested fields cannot be populated from the given text.
Here's a breakdown of what can and cannot be extracted:
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A table of acceptance criteria and the reported device performance: This information is not explicitly provided. The summary states that the passive instrument option was shown to be "substantially equivalent" to the original StealthStation® System with active probes and the BrainLAB VectorVision System. However, it does not list specific performance metrics or acceptance thresholds.
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Sample size used for the test set and the data provenance: Not mentioned.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not mentioned.
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Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not mentioned.
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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 as this is a medical device for surgical navigation, not an AI for human reader assistance.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The device is a "StealthStation® System - Passive Instrument Option," which is a surgical navigation system, implying human-in-the-loop operation. No information is provided about a standalone algorithm performance.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not mentioned. For a surgical navigation system, ground truth would likely relate to the accuracy of instrument positioning relative to anatomical structures.
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The sample size for the training set: Not mentioned.
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How the ground truth for the training set was established: Not mentioned.
Summary of available information:
Category | Information from Text |
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Acceptance Criteria & Performance | The device was shown to be "substantially equivalent" to the original StealthStation® System with active probes and the BrainLAB VectorVision System. No specific performance metrics or acceptance criteria are detailed. |
Test Set Sample Size | Not mentioned. |
Test Set Data Provenance | Not mentioned. |
Experts for Ground Truth | Not mentioned. |
Expert Qualifications | Not mentioned. |
Adjudication Method | Not mentioned. |
MRMC Comparative Study | Not applicable (device is a surgical navigation system, not AI for human reader assistance). |
Standalone Performance | Not applicable (device is a surgical navigation system, implying human interaction). No data on algorithm-only performance. |
Type of Ground Truth | Not mentioned. (Likely related to positional accuracy for surgical navigation, but not specified). |
Training Set Sample Size | Not mentioned. (Given the nature of the device as a passive instrument option for an existing system, the "training" may have been more about calibration and validation against existing benchmarks rather than a typical AI model training set). |
Training Set Ground Truth Method | Not mentioned. (Again, likely related to established accuracy standards for surgical navigation systems and calibration methods rather than a data labeling process common in AI). |
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