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510(k) Data Aggregation
(11 days)
FLEXVIEW SYSTEM
The Guidant FLEXView™ System is indicated for use in minimally invasive surgery allowing access for delivery and placement of surgical instruments (e.g., Guidant Microwave Ablation Probe). It is indicated for patients requiring blunt dissection of tissue including structures in the thoracic space.
The FLEXView™ System includes the following components: the Cannula Assembly (with fixed, integrated visualization lens), the Routing Snare, and the Retrieval Tool.
The Cannula Assembly mates a plastic lens to the tip of a Guidant 7mm Extended Length Endoscope, to enable visualization of anatomy in dry or wet environments (including in contact with tissue). This Cannula is delivered to the surgical site by way of a surgical port. The Cannula Assembly has a total of three lumens. The largest of these receives the 7mm Extended Length Endoscope. The other two lumens are intended to receive the Routing Snare, which consists of a sheathed wire with loops at either end, and then subsequently the Retrieval Tool, which is a sheathed stainless steel shaft with an exposed stainless steel ball at its tip. After delivering the Routing Snare via the service port to the position of interest within the thoracic space, the Retrieval Tool enables capture of the Snare by providing a retaining feature for engagement. The Routing Snare can then be used to route and place another surgical instrument such as the Guidant Microwave Ablation Probe. The FLEXView™ System is a single use device, supplied sterile.
The provided document is a 510(k) Premarket Notification for the Guidant FLEXView™ System. It states that "The results of verification testing demonstrate that the FLEXView™ System meets the established acceptance criteria and performs in a manner equivalent to the predicate devices." However, it does not provide specific details regarding the acceptance criteria themselves, the reported device performance, or the study design information (sample sizes, data provenance, ground truth establishment, expert qualifications, adjudication methods, or specific study types like MRMC or standalone performance).
Therefore, based only on the provided text, a comprehensive answer to your request is not possible beyond what is explicitly stated in the "Performance data" section.
Here's a breakdown of what can and cannot be answered from the provided text:
1. A table of acceptance criteria and the reported device performance
Acceptance Criteria | Reported Device Performance |
---|---|
Not specified | "meets the established acceptance criteria and performs in a manner equivalent to the predicate devices." |
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample size for test set: Not specified.
- Data provenance: Not specified.
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 specified. The document refers to "verification testing" but does not detail how ground truth was established or if experts were involved in that process.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not specified.
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
- MRMC study: Not specified. This device is not an AI-assisted diagnostic tool, but rather a surgical instrument system, so an MRMC study as typically understood for AI in imaging is unlikely to be relevant.
- Effect size of human improvement with AI: Not applicable, as this is not an AI device for human reader assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable in the typical sense for an algorithm. The "verification testing" refers to the performance of the physical device system.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not specified.
8. The sample size for the training set
- Not applicable as this is a physical medical device, not a machine learning algorithm that requires a training set.
9. How the ground truth for the training set was established
- Not applicable.
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