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510(k) Data Aggregation
(30 days)
The PointerShell Universal and PointerShell LS are intended as an aid for precisely locating anatomical structures in either open or percutaneous procedures. It is indicated for use with the Fiagon Navigation system using electromagnetic navigation.
Both the instruments are 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:
ENT Procedures; Transphenoidal 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 Fiagon Navigation - PointerShell Universal and PointerShell LS are reusable instruments intended to be used with the Fiagon Navigation system. The instruments are electromagnetically navigated devices that are
- Instrument adapters (designed for mechanical connection to shavers or surgical instruments a. with different diameters without motor).
Each device incorporates a sensor device, which is tracked by the navigation system with in the lowenergy magnetic field of a field generator (part of the navigation system)
The navigation software (part of the navigation system) displays the position of the instruments in preoperative scans (e.g., CT, MRI, fluoroscopy)
This document describes Fiagon GmbH's K160479 510(k) submission for the PointerShell Universal and PointerShell LS, which are intended as an aid for precisely locating anatomical structures in either open or percutaneous procedures using electromagnetic navigation.
Here's an analysis of the provided information regarding acceptance criteria and the supporting study:
1. Table of Acceptance Criteria and Reported Device Performance:
The document doesn't explicitly state quantitative acceptance criteria in a dedicated table format. However, it indicates a comparison against the predicate devices. The implicit acceptance criterion for precision/accuracy is that the new devices perform comparably to or better than the predicate devices, which had a mean target registration error of less than 1.5 mm.
| Performance Metric | Acceptance Criteria (Implied from Predicate) | Reported Device Performance (PointerShell Universal) | Reported Device Performance (PointerShell LS) |
|---|---|---|---|
| Bench Accuracy (Mean Target Registration Error) | < 1.5 mm | 1.1 mm | 1.1 mm |
2. Sample Size Used for the Test Set and Data Provenance:
The document states, "A mean bench accuracy as target registration error of 1.1 mm for Pointershell Universal and 1.1 mm for PointerShell LS was measured for the new devices, which compares to the values mean < 1.5 mm for the predicate devices in an identical test setup."
- Sample Size: The document does not specify the exact number of measurements or the sample size used for the test set (the new devices). It only provides the mean accuracy.
- Data Provenance: The study was a "bench accuracy" test, implying it was conducted in a laboratory setting. The country of origin of the data is not explicitly stated, but since Fiagon GmbH is in Germany, it is likely the testing was conducted there. It is a prospective test specifically for this submission.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications:
The type of test conducted was "bench accuracy" measuring target registration error. This is a technical performance measurement against a known physical target, not a clinical assessment requiring expert interpretation of images or patient outcomes. Therefore, no human experts were used to establish the ground truth for this specific performance test. The ground truth would be the precisely known physical locations in the bench setup.
4. Adjudication Method for the Test Set:
As no human experts were involved in establishing the ground truth for the bench accuracy test, no adjudication method was applicable or used.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
No, an MRMC comparative effectiveness study was not done for this submission. The testing described is solely focused on the technical precision and accuracy of the device in a bench setting, not on its impact on human reader performance or diagnostic accuracy.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:
Yes, a standalone performance evaluation was done. The "bench accuracy" test described measures the performance of the navigation system (including the PointerShell instruments) in precisely locating anatomical structures. This is a direct measurement of the device's technical capability without human interpretation or intervention in the measurement of accuracy itself.
7. Type of Ground Truth Used:
The ground truth used for the bench accuracy test was known physical locations/targets. In a bench test for navigation systems, targets with precisely known coordinates are typically used to assess the system's ability to accurately register and track instruments relative to those targets.
8. Sample Size for the Training Set:
The document describes a 510(k) submission for a geometrically modified instrument. It does not mention any "training set" in the context of machine learning or AI algorithms. The PointerShell devices are hardware instruments that integrate with the existing Fiagon Navigation system, which uses electromagnetic tracking technology. The core navigation technology itself would have been developed and validated previously (e.g., in K141456), but this submission is for new physical instruments, not a new or re-trained algorithm.
9. How the Ground Truth for the Training Set Was Established:
As there is no mention of a training set in the context of an AI/ML algorithm for this specific submission, this point is not applicable. The device is a hardware instrument, not a software-only AI/ML medical device where a training set would be common.
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(29 days)
The GuideWire 0.6 is intended as an aid for precisely locating anatomical structures in either open or percutaneous procedures. It is indicated for use with the Fiagon Navigation system using electromagnetic navigation.
It 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:
ENT Procedures; Transphenoidal 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 Fiagon Navigation - FlexPointer 1.5 is a reusable instrument intended to be used with the Fiagon Navigation system. The instrument is an electromagnetically navigated devices that is
- a. Navigated pointing devices (maleable, sensor within the tip)
Each device incorporates a sensor device, which is tracked by the navigation system with in the low-energy magnetic field of a field generator (part of the navigation system)
The navigation software (part of the navigation system) displays the position of the instruments in preoperative scans (e.g., CT, MRI, fluoroscopy)
The provided text describes the 510(k) premarket notification for the Fiagon Navigation – GuideWire 0.6. This document primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study with acceptance criteria for a novel AI device. Therefore, much of the requested information (like multi-reader multi-case studies, expert adjudication for ground truth, or details on a training set for an AI) is not applicable or not available in this document.
However, I can extract the available performance data and infer an acceptance criterion based on the comparison to the predicate device.
1. Table of acceptance criteria and the reported device performance
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Bench accuracy comparable to the predicate device (mean 1.24 mm, SD 0.44 mm) | Mean bench accuracy of 1.27 mm (Standard deviation 0.4 mm) |
2. Sample size used for the test set and the data provenance
The document does not explicitly state the sample size (e.g., number of measurements or trials) used for the bench accuracy test for the new device or the predicate. The data provenance (country of origin, retrospective/prospective) is also not mentioned, as this is a bench test, not clinical data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. This was a bench accuracy test, not a clinical study involving expert interpretation of medical images.
4. Adjudication method for the test set
Not applicable. This was a bench test.
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 document describes a medical device (guidewire) used in image-guided surgery, not an AI or imaging diagnostic tool that would typically involve human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This device is a guidewire, a physical instrument, not an algorithm.
7. The type of ground truth used
For the bench accuracy test, the 'ground truth' would be the known, precisely measured physical position or target, against which the device's measured position is compared. This is inherent to a bench accuracy test of a navigation device.
8. The sample size for the training set
Not applicable. This device is a physical instrument, not an AI model requiring a training set.
9. How the ground truth for the training set was established
Not applicable.
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