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510(k) Data Aggregation
(114 days)
The Scopis Extended Instrument Set EM is indicated for any medical condition in which the use of stereotactic surgery may be appropriate, and where reference to a rigid anatomical structure in the field of ENT surgery, such as the paranasal sinuses, mastoid anatomy, can be identified relative to a CT or MR based model of the anatomy.
Example procedures include, but are not limited to the following ENT procedures:
- Transsphenoidal access procedures;
- Intranasal procedures:
- . Sinus procedures, such as Maxillary antrostomies, Ethmoidectomies, Sphenoidotomies/Sphenoid explorations, Turbinate resections, and Frontal sinusotomies:
- . ENT related anterior skull base procedures.
The Scopis Extended Instrument Set EM is a set of accessories for the Scopis Hybrid Navigation Unit EM and is intended to localize the patient, track the position of the patient, display the position of navigated instruments on a model of the patient's anatomy based on preoperative images (CT or MRI) using electromagnetic tracking technology. The position of the instruments and the patient are localized within an electromagnetic field produced by a field generator. The navigation of instruments relative to the patient's anatomy is established via registration of the patient's anatomy to the image set via fiducial markers, anatomical landmarks, or surface matching. The position of navigated instruments is then displayed on the model from the image set.
The Scopis Extended Instrument Set EM consists of:
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- Navigation Software (NOVA AR)
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- Navigated instruments with integrated localizers
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- Patient tracker with integrated localizer
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- Non-tracked accessories for mechanical fixation
The Scopis Extended Instrument Set EM is a set of accessories for the Scopis Hybrid Navigation Unit EM, intended to localize the patient, track the position of the patient, and display the position of navigated instruments on a model of the patient's anatomy based on preoperative CT or MRI images using electromagnetic tracking technology.
Here's an analysis of the acceptance criteria and the study proving the device meets them:
1. Table of Acceptance Criteria and Reported Device Performance:
| Acceptance Criteria (from predicate devices) | Reported Device Performance (Scopis Extended Instrument Set EM) |
|---|---|
| Fiagon predicate K133573: Navigation Accuracy of 0.9 mm ± 0.34 mm (for Precision Pointer equivalent) | Scopis Hybrid Navigation System EM (K161491) Navigation Accuracy (Precision Pointer EM): 0.49 mm ± 0.27 mm |
| Fiagon predicate K141456: Bench Accuracy of 0.7 mm to 1.2 mm ± 0.29 mm to 0.42 mm (for Registration pointer equivalent) | Scopis Extended Instrument Set EM Bench Accuracy (Registration pointer EM-D): 0.64 mm ± 0.27 mm |
2. Sample Size Used for the Test Set and Data Provenance:
The document only states "bench testing of the navigation accuracy was performed". It does not specify the sample size (number of measurements or trials) for the test set or the data provenance (e.g., country of origin, retrospective or prospective).
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts:
Not applicable. The ground truth for the test set appears to be based on physical measurements of navigation accuracy on a test bench, not on expert consensus of medical images.
4. Adjudication Method for the Test Set:
Not applicable. The "study" appears to be a bench test involving physical accuracy measurements, not a human-adjudicated test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The document describes bench testing for navigation accuracy, not a study involving human readers or AI assistance.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:
Yes, the described performance testing is a standalone assessment of the device's accuracy. The "bench testing of the navigation accuracy" assesses the algorithm and hardware's ability to precisely track and display instrument positions, independent of a human operator's performance in a surgical setting.
7. Type of Ground Truth Used:
The ground truth used for the performance testing was physical measurements of navigation accuracy. This likely involves comparing the device's reported position of an instrument to its actual physical position, as measured by a highly accurate reference system on a test bench.
8. Sample Size for the Training Set:
The document does not provide any information regarding the sample size for a training set. This is a medical device clearance, and the focus is on the safety and effectiveness of the device as a whole, not specifically on the details of an AI model's training if one were present as a distinct component. The "Navigation Software (NOVA AR)" is listed, but its development methodology (e.g., if it uses machine learning and thus a training set) is not detailed.
9. How the Ground Truth for the Training Set Was Established:
The document does not provide any information on how ground truth for a training set was established. As mentioned in point 8, details about the software's development, especially if it involved machine learning requiring a training set, are not present in this document.
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(253 days)
The Scopis Hybrid Navigation System EM is indicated for any medical condition in which the use of stereotactic surgery may be appropriate, and where reference to a rigid anatomical structure in the field of ENT surgery, such as the paranasal sinuses, mastoid anatomy, can be identified relative to a CT or MR based model of the anatomy.
Example procedures include, but are not limited to the following ENT procedures:
- · Transsphenoidal access procedures;
- Intranasal procedures;
· Sinus procedures, such as Maxillary antrostomies, Sphenoidotomies/Sphenoid explorations, Turbinate resections, and Frontal sinusotomies;
· ENT related anterior skull base procedures.
The Scopis Hybrid Navigation System EM displays the position of navigated instruments on a model of the patient's anatomy based on preoperative images (CT or MRI) using electromagnetic tracking technology. The position of the instruments and the patient are localized within an electromagnetic field produced by a field generator. The navigation of instruments relative to the patient's anatomy is established via registration of the patient's anatomy to the image set via fiducial markers, anatomical landmarks, or surface matching. The position of navigated instruments is then displayed on the model from the image set.
The Scopis Hybrid Navigation System EM consists of:
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- Navigation Unit
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- Electromagnetic field generator
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- Patient tracker with integrated localizers
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- Navigation instruments with integrated localizers
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- Navigation software (Nova Basic)
This document describes the Scopis Hybrid Navigation System EM, an image-guided surgery system for ENT procedures. The information provided focuses on its substantial equivalence to a predicate device, as demonstrated through performance data.
Here's a breakdown of the requested information:
1. Table of Acceptance Criteria and Reported Device Performance:
| Acceptance Criteria (Predicate Device Performance) | Reported Device Performance (Scopis Hybrid Navigation System EM) |
|---|---|
| Navigation Accuracy: 0.9 ± 0.34 mm | Navigation Accuracy: 0.49 ± 0.27 mm |
2. Sample size used for the test set and the data provenance:
- Test Set Sample Size: Not explicitly stated. The document mentions "bench testing of the navigation accuracy was performed," suggesting a controlled laboratory environment without specifying the number of measurements or tests conducted.
- Data Provenance: The data is a result of "bench testing," meaning it was generated in a controlled laboratory setting (likely in Germany, given the submitter's address). It is prospective data collection for the purpose of demonstrating device performance.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
This information is not provided in the document. Bench testing typically relies on metrology equipment and standardized procedures for ground truth, rather than expert human interpretation.
4. Adjudication method for the test set:
This information is not applicable and therefore not provided. The assessment of navigation accuracy in bench testing relies on direct measurement against a known physical standard, not on human adjudication of classifications.
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:
A multi-reader multi-case (MRMC) comparative effectiveness study was not conducted and is not relevant for this type of device. The Scopis Hybrid Navigation System EM is an image-guided surgery system, not a diagnostic AI system that "reads" cases or assists human readers in interpretation. Its performance is measured by its navigational accuracy.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Yes, the performance testing described is essentially a standalone (algorithm only) assessment of the device's navigation accuracy during bench testing. No human interaction or in-vivo performance is described in the provided "Performance Data" section for establishing substantial equivalence.
7. The type of ground truth used:
The ground truth used for the bench testing would be a precisely measured physical standard or reference, against which the device's navigational output is compared. For example, a known physical position measured by a highly accurate metrology system would serve as the ground truth for the "0.49 ± 0.27 mm" accuracy measurement.
8. The sample size for the training set:
This information is not provided and is not directly applicable in the context of this submission. The Scopis Hybrid Navigation System EM is an image-guided navigation system that uses patient-specific CT or MR images as reference. While the software itself would have been developed and tested, the document focuses on the performance of the product rather than the development of deep learning models requiring a "training set" in the typical sense.
9. How the ground truth for the training set was established:
This information is not provided and is not directly applicable for the reasons stated in point 8.
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