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To provide for access and allow for visualization of the surgical field during brain and spinal surgery. Indications may include subcortical access to diseases such as the following:

• Primary/Secondary Brain Tumors
• · Vascular Abnormalities/Malformations
  · Intraventricular Tumors/Cysts

The NICO BrainPath and accessories are designed to provide minimally invasive access to neurological tissues. The design specifically supports the creation of an atraumatic surgical corridor to access the brain. These BrainPath devices are part of what is being called the BrainPath Approach™, which integrates the expanding neurosurgical armamentarium of trajectory planning and navigation, optics, corridor resection and biopsy, and tissue preservation. To date, the BrainPath technology has been used to successfully access primary and secondary brain tumors, vascular abnormalities or malformations, and intraventricular tumors and cysts.

The BrainPath consists of multiple-sized reusable and re-sterilizable obturators with coordinating single patient use disposable sheaths. The obturator and sheath are assembled in the operating room immediately prior to use. After placement, the obturator is removed leaving behind the sheath which provides a 13.5 mm or 11 mm surgical corridor.

The provided text focuses on the 510(k) premarket notification for the NICO BrainPath device, specifically for an updated version (K172433) compared to a predicate device (K150378). This is a submission for device substantial equivalence, not a study proving the device meets acceptance criteria in terms of diagnostic performance or clinical outcomes for an AI/algorithm-based medical device.

Therefore, many of the requested criteria regarding AI/ML device performance evaluation (e.g., sample sizes for training/test sets, expert adjudication methods, MRMC studies, standalone performance, ground truth types) are not applicable to this document.

However, I can extract the acceptance criteria and "performance" findings relevant to a medical device's physical and functional properties, as presented in this 510(k) submission.

Here's a breakdown of the relevant information provided in the document:

1. Table of Acceptance Criteria and Reported Device Performance (Non-Clinical/Engineering):

The document describes non-clinical testing performed to demonstrate that modifications to the NICO BrainPath still meet applicable design and performance requirements and support substantial equivalence to the predicate device. The "acceptance criteria" can be inferred as the expected "Pass" or "Non-cytotoxic," "Non-sensitizer," "Non-irritant" results for the respective tests.

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

• Sample Size: The document does not specify exact numerical sample sizes for each non-clinical test (e.g., number of devices tested for biocompatibility, number of packaging units, etc.). It generally states "All" devices/components were subjected to relevant tests.
• Data Provenance: The data provenance is internal to NICO Corporation's testing and validation processes. The document does not mention the country of origin of "data" in a patient/clinical sense, as this is laboratory/engineering testing. It is retrospective in the sense that the testing was conducted prior to the 510(k) submission to demonstrate compliance.

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

• This question is not applicable to the data presented. The document describes laboratory and engineering tests (e.g., biocompatibility, sterilization, simulated use, packaging). "Ground truth" in the context of expert consensus (like for image interpretation in AI) is not relevant here. Compliance with established standards (e.g., ASTM, ISO standards for biocompatibility) would be the "ground truth."

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

• This question is not applicable to the data presented. Adjudication methods are typically used for establishing ground truth in clinical or image-based studies where human interpretative variability exists. For engineering tests, results are typically objective Pass/Fail or numerical measurements against defined specifications.

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:

• This question is not applicable. This device is a physical surgical tool (self-retaining retractor), not an AI/ML-based diagnostic or assistive software that interacts with human "readers" or interpreters.

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

• This question is not applicable. This device is a physical surgical tool, not an algorithm or software.

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

• The "ground truth" for the non-clinical tests is adherence to established engineering specifications, validated test methodologies, and recognized industry standards (e.g., for biocompatibility, sterility, packaging integrity). For example, a "Pass" for sterility validation means the device met the acceptance criteria for a Sterility Assurance Level (SAL) of 10-6.

8. The sample size for the training set:

• This question is not applicable. There is no "training set" in the context of an AI/ML device. The device is a physical product, and its design is based on engineering principles and previous versions (predicate device).

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

• This question is not applicable. As there is no training set for an AI/ML algorithm, this concept does not apply. The "ground truth" for the device's design and manufacturing is established through defined product specifications, design control processes, and compliance with quality system regulations (e.g., 21 CFR Part 820).

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To provide for access and allow for visualization of the surgical field during brain and spinal surgery. Indications may include subcortical access to diseases such as the following:

• Primary/Secondary Brain Tumors
• Vascular Abnormalities/Malformations
• Intraventricular Tumors/Cysts

The NICO BrainPath and Accessories are designed to provide minimally invasive access to neurological tissues. The design specifically supports the creation of an atraumatic surgical corridor to access most areas of the brain. The BrainPath also facilitates the expanding neurosurgical armamentarium of trajectory planning software (e.g., Synaptive® Medical Inc. BrightMatter® Planning Software, K140337), navigation (e.g., Synaptive BrightMatter Navigation System, K142024), optics, corridor resection (e.g., NICO Myriad), and biopsy. To date, the BrainPath technology has been used to successfully access primary and secondary brain tumors, vascular abnormalities or malformations, and intraventricular tumors and cysts.

The BrainPath consists of multiple-sized reusable and re-sterilizable obturators with coordinating single patient use disposable sheaths. The obturator and sheath are assembled in the operating room immediately prior to use. After placement, the obturator is removed leaving behind the sheath which provides a 13.5 mm surgical corridor to the lesion or abnormality.

The BrainPath Accessories include a "manipulation tool," which is similar to a dental probe and is used for manipulating the position of the sheath after it has been placed. The accessories also include "shepherd's hooks" for attaching to various commercially available retractors, and a sterilization tray for the reusable components (i.e., obturators and manipulation tools).

This document is a 510(k) premarket notification for the NICO® BrainPath® and Accessories, a medical device for neurosurgery. It does not describe a study that proves the device meets specific acceptance criteria related to its clinical efficacy in the context of an AI/ML powered device. Instead, it focuses on demonstrating substantial equivalence to a predicate device (NICO Brain Port, K120691) through non-clinical testing.

Therefore, many of the requested elements for an AI/ML powered medical device study are not applicable or cannot be extracted from this document, as this is a traditional medical device submission.

Here's a breakdown of the available information based on your request, with an emphasis on what is present in the document and what is not:

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

The document provides a table of "Non-Clinical Testing" with "Result/Conclusion". These are the acceptance criteria and performance for a traditional medical device, not an AI/ML powered one.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not Applicable. This document describes non-clinical engineering and biocompatibility testing for a surgical device, not a study involving patient data or test sets in the context of AI/ML.

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 Applicable. Ground truth, in the context of diagnostic accuracy, is not established in this type of submission. The "ground truth" for the non-clinical tests is based on established engineering standards and validated methods (e.g., ISO standards for biocompatibility, cleaning validation protocols).

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

• Not Applicable. No adjudication method is described as this is not a study assessing diagnostic performance.

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

• No. An MRMC comparative effectiveness study was not done. This device is a surgical instrument, not an AI-powered diagnostic tool. The document states that the BrainPath "facilitates the expanding neurosurgical armamentarium of trajectory planning software (e.g., Synaptive® Medical Inc. BrightMatter® Planning Software, K140337), navigation (e.g., Synaptive BrightMatter Navigation System, K142024), optics, corridor resection (e.g., NICO Myriad), and biopsy." This indicates it can be used with other technologies, some of which may be software-based, but BrainPath itself is not an AI/ML device, and no MRMC study on its comparative effectiveness with AI assistance is mentioned.

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

• No. A standalone algorithm performance study was not done. The device is a physical surgical tool and does not operate as an algorithm.

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

• The "ground truth" for the non-clinical tests is based on established scientific and engineering principles, such as:
  • Biocompatibility standards: (e.g., ISO 10993 for Cytotoxicity, Sensitization, Irritation).
  • Sterilization validation methods: (e.g., for steam autoclaving, gas plasma, gamma irradiation).
  • Mechanical and functional specifications: (e.g., ability to interface with other instruments, packaging integrity).
  • These are not "expert consensus" or "pathology" in the clinical sense, but rather adherence to predefined and validated test methodologies and acceptance limits.

8. The sample size for the training set

• Not Applicable. There is no training set mentioned as this is not an AI/ML device.

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

• Not Applicable. As there is no training set, there is no ground truth establishment for it.

In summary: This document is a 510(k) submission for a physical surgical device, the NICO® BrainPath®, demonstrating substantial equivalence to a predicate device through non-clinical testing. It does not pertain to the development or validation of an AI/ML powered medical device, and thus, most of the requested information regarding AI/ML study design and criteria is not present.

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