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The Cellvizio® 100 Series systems with Confocal Miniprobes™are confocal laser systems with fiber optic probes that are intended to allow imaging of the internal microstructure of tissues including, but not limited to, the identification of cells and vessels and their organization or architecture.

The CranioFlex™ (-,-C) Confocal Miniprobes™ are indicated to provide visualization within central nervous system during cranial diagnostic and therapeutic procedures such as tumor biopsy and resection.

The Cellvizio® 100 Series systems with Confocal Miniprobes™ are confocal laser systems with fiber optic probes that are intended to allow imaging of the internal microstructure of tissues. Confocal Miniprobes™ are intended to be used by qualified physicians to provide visualization of body cavities, organs, and canals during endoscopic and laparoscopic surgical procedures, including robot-assisted procedures and during neurosurgical procedures.

CranioFlex™ (-,-C) Confocal Miniprobes™ are used with Cellvizio® 100 Series systems to provide imaging of the brain through contact of their distal tip with the tissue. They are designed to be used and manually handled during neurosurgical procedures.

This document is a 510(k) Premarket Notification for the Cellvizio 100 Series Systems with Confocal Miniprobes, specifically the CranioFlex™ (-,-C) Confocal Miniprobes, for use in neurosurgical procedures.

Important Note: The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device. It does not present a study with specific acceptance criteria or performance metrics for an AI/algorithm-based device. The device described (Cellvizio with CranioFlex™ Miniprobes) appears to be an optical imaging system that provides direct visualization, not an AI or algorithm that interprets images or assists human readers. Therefore, many of the requested elements for AI acceptance criteria and studies (like MRMC studies, standalone algorithm performance, training set details, ground truth establishment for AI) are not applicable to this type of medical device submission.

The document primarily focuses on comparing the subject device's technological characteristics and intended use to a predicate neuro-endoscope and previously cleared reference devices from the same manufacturer.

Based on the provided text, here's an attempt to address the requested information, highlighting where the information is not applicable (N/A) due to the nature of the device:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria or performance metrics in the format typically seen for AI/algorithm-based devices (e.g., sensitivity, specificity, accuracy thresholds). The "acceptance" for this 510(k) relies on demonstrating substantial equivalence to a predicate device. This is achieved through qualitative comparisons of design, materials, indications for use, and technological characteristics, along with verification that risks are acceptable and don't raise new questions of safety or effectiveness.

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

The document does not describe a "test set" in the context of an algorithm evaluation with a specific number of cases or data provenance. The assessment for this 510(k) is based on technical comparison and risk analysis, not a prospective clinical study with a defined test set.

• Sample Size for Test Set: N/A (Not an algorithm evaluation study requiring a test set of cases).
• Data Provenance: N/A (The submission primarily relies on design specifications, materials, and comparison to predicate/reference devices, along with in-house testing for sterilization and biocompatibility). There is a mention of a "clinical feasibility study published in a peer reviewed journal" being used to confirm risk assessment, but no details on size, type, or provenance of that dataset are provided.

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

N/A. As this is not an AI/algorithm-based device being validated against a ground truth dataset, this information is not relevant or provided.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

N/A. Not applicable to this type of device submission.

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

N/A. This is not an AI-assisted diagnostic device; it's an imaging tool that provides direct visualization. Therefore, an MRMC study assessing AI assistance is not applicable.

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

N/A. This is a direct visualization device, not a standalone AI algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

N/A. The "ground truth" for this submission is implicitly the safety and effectiveness of the legally marketed predicate device (KARL STORZ Flexible Video-Neuro-Endoscope System) and the established safety and performance of the manufacturer's own reference devices (GastroFlex™ Confocal Miniprobes). The CranioFlex™ Miniprobe is asserted to be fundamentally the same device as the GastroFlex™ but with an expanded indication for use into neurosurgery, hence the comparison to a neuro-endoscope predicate.

8. The sample size for the training set

N/A. This is not an AI/machine learning device.

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

N/A. This is not an AI/machine learning device.

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Cellvizio® 100 Series Systems with Confocal Miniprobes™ are confocal laser systems with fiber optic probes that are intended to allow imaging of the internal microstructure of tissues.

CelioFlex™ UHD Confocal Miniprobes™ are intended to be used by qualified physicians to provide visualization of body cavities, organs, and canals during endoscopic and laparoscopic and laparoscopic surgical procedures, including robotic-assisted procedures.

CelioFlex™ UHD Confocal Miniprobes™ are used with Cellvizio® 100 Series systems to provide imaging of the internal microstructure of body cavities, organs, and canals through contact of their distal tip with the tissues. They are designed for use during laparoscopic surgical procedures, including robot-assisted procedures.

CelioFlex™ UHD Confocal Miniprobes™ have a "grabule" (previously cleared in K151593 and K160416) on their distal tip. The "grabule" has been designed as a grip for laparoscopic grasping accessories, facilitating user control of the miniprobe distal tip during conventional laparoscopic procedures while preventing potential wear to the Miniprobe tip that repeated handling by forceps might cause. The diameter of the "grabule" is fitted for insertion of CelioFlex™ UHD Confocal Miniprobes™ through trocars with diameter larger or equal to 5 mm.

CelioFlex™ UHD Confocal Miniprobes are also compatible with laparoscopy robot-assisted procedures. Robotic arm graspers can be used to manipulate CelioFlex™ UHD Confocal Miniprobes.

During robotic-asisted procedures, CelioFlex™ UHD Confocal Miniprobes™ are inserted through a pre-installed trocar. When the CelioFlex™ UHD distal end appears on the monitor. the surgeon uses the robotic accessory to grasp the distal part of the Confocal Miniprobe™ or "grabule", with the laparoscopic grasper to position the Confocal Miniprobe-TM facing the tissue to be imaged.

Here's an analysis of the provided text regarding the acceptance criteria and study for the CelioFlex™ UHD Confocal Miniprobes™:

Acceptance Criteria and Device Performance

The provided documentation describes the acceptance criteria and performance for the CelioFlex™ UHD Confocal Miniprobes™ used with Cellvizio® 100 Series Systems, specifically focusing on their use during robot-assisted laparoscopic procedures.

Table 1: Acceptance Criteria and Reported Device Performance

Study Information

The document describes verifications and validations performed, primarily to demonstrate the substantial equivalence of the device for robot-assisted procedures, building upon previous clearances for conventional laparoscopic use.

1. Sample Size, Test Set, and Data Provenance:

   • Test Set Sample Size:
     • For the "Grasp and Release Test with grasping robotic accessory," 8 samples were used.
     • For the "Bend and Flexibility Test with grasping robotic accessory," 8 samples were used.
     • For the other tests (Biocompatibility, Reprocessing, Laser Safety, Imaging Quality, Trocar Compatibility), the specific sample sizes are not explicitly stated in this summary, but they are implied to be part of the predicate device submissions (K151593 and K160416).
   • Data Provenance: The studies described are prospective in nature, as they involve performing specific tests on the devices to assess their performance under defined conditions. The country of origin of the data is not specified, but the applicant's address is Paris, France.

2. Number and Qualifications of Experts for Ground Truth:

   • This document focuses on device performance and safety testing rather than diagnostic accuracy involving human experts. Therefore, the concept of "experts used to establish the ground truth" in a clinical diagnostic sense is not directly applicable here. The "Pass" results are based on meeting predefined engineering and safety requirements.

3. Adjudication Method for Test Set:

   • Again, this is not a clinical study involving human interpretation of results requiring adjudication. The tests have clear pass/fail criteria based on objective measurements and observations (e.g., "no loss of imaging performance or broken and/or loose components").

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No, an MRMC comparative effectiveness study was not done. This document pertains to the physical and functional performance of a medical device (endoscopic probe) and its safety for a specific surgical procedure, not the diagnostic accuracy or interpretative performance of a reading algorithm or human readers.

5. Standalone (Algorithm Only) Performance Study:

   • No, a standalone (algorithm only) performance study was not done. This device is a physical diagnostic tool (a confocal miniprobe) used by a surgeon, not an AI algorithm. The performance being evaluated is the physical integrity and imaging capability of the probe itself during manipulation.

6. Type of Ground Truth Used:

   • The "ground truth" used for these tests is based on engineering specifications, safety standards, and functional performance criteria. For example, the criteria dictate that the device must maintain imaging performance and not break or loosen components after specific manipulation cycles. This is not clinical pathology, expert consensus on diagnostic findings, or outcomes data in the usual sense for an AI diagnostic device.

7. Sample Size for Training Set:

   • There is no training set mentioned or implied, as this is not an artificial intelligence or machine learning device. The "training" in this context refers to the development and previous testing of the predicate devices.

8. How Ground Truth for Training Set was Established:

   • Since there is no training set, this question is not applicable.

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