Search Results

This device is intended for use in surgical procedures to assist in locating and mapping motor nerves through the use of mechanomyographic (MMG) signals and electrical stimulus of nerves. This device is indicated for locating and identifying spinal nerve roots and peripheral motor nerves originating from spinal levels C3-T1 and L2-S2.

The Sentio MMG® system is a multichannel intraoperative monitor for use during surgeries in which a motor nerve is at risk. The Sentio MMG® system records mechanomyographic (MMG) signals from muscles innervated by the affected nerve, which may originate from operator applied electrical stimulus or from direct mechanical stimulus occurring during the course of surgery. The monitor will assist early nerve identification by providing the surgeon with a tool to help locate and identify the particular nerve at risk to minimize trauma by alerting the surgeon when a particular nerve has been activated.

The Sentio MMG® system consists of a reusable Control Unit comprised of a touch-screen PC and Patient Module, a reusable Sensor Connector Module and an assortment of disposable conductive probes, stimulators, sensors, electrodes and electrode leads.

Here's a breakdown of the acceptance criteria and the study details for the Sentio MMG® Neurosurgical Nerve Locator, based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary states that a "comparative performance evaluation was conducted to assess statistical agreement between the subject device and the predicate." It then concludes that "Results for positive, and overall percent agreement have established that 1) the principle functions of the Sentio MMG® system are effective, such that spinal nerve status and location may be ascertained and monitored, and 2) the data processed by the subject device following surgical use correlate well with those acquired by the predicate device."

However, specific numerical acceptance criteria (e.g., minimum percentage agreement, sensitivity, specificity, or specific statistical thresholds) are not explicitly provided in the document for the new device. The acceptance is based on demonstrating "substantial equivalence" to the predicate device (K100992 NeuralMAS™). This implies that the performance of Sentio MMG® must be comparable to or better than the predicate's established performance without raising new safety or effectiveness concerns.

2. Sample Size and Data Provenance

The document does not explicitly state the sample size used for the comparative performance evaluation or the data provenance (e.g., country of origin, retrospective/prospective). It only refers to "market data evaluation" and "non-clinical testing." This often implies internal testing or possibly data collected from the predicate device's use in the market.

3. Number of Experts and Their Qualifications

The document does not mention the involvement of experts for establishing ground truth or evaluating the test results. The assessment relied on statistical agreement between the subject device and the predicate device.

4. Adjudication Method

No adjudication method is mentioned in the document. The comparative evaluation appears to be a direct comparison of the subject device's output against the predicate device's output.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC study was done, as this is a device that directly measures physiological signals rather than an imaging device requiring human interpretation of images. The device assists in locating and mapping motor nerves, and its performance is evaluated based on its signal output compared to a predicate device.

6. Standalone (Algorithm Only) Performance

A standalone performance evaluation was conducted in the sense that the device's output was statistically compared to the predicate device's output. This is not an "algorithm only" in the context of AI, but rather the device's functional performance in isolation of human decision-making based on the output. The conclusion states: "The conclusions drawn from our non-clinical testing (to include our market data evaluation) of the subject device demonstrates that the subject device is as safe, as effective and performs better than the legally marketed predicate device."

7. Type of Ground Truth Used

The "ground truth" for the comparative study appears to be the performance and data acquired by the predicate device (ISS NeuralMAS #K100992). The study assessed the "statistical agreement" between the subject device's output and the predicate device's output. This is a comparison to a previously cleared device's performance, not an independent clinical ground truth like pathology or expert consensus on nerve presence.

8. Sample Size for the Training Set

The document does not mention a "training set" as this device is not described as an AI/machine learning product in the traditional sense that requires complex algorithm training. The comparison is against an existing predicate device's functionality.

9. How the Ground Truth for the Training Set Was Established

Not applicable, as no training set (in the AI/ML sense) is mentioned or implied for this non-clinical testing. The "ground truth" for the comparison was the predicate device's established performance.

Ask a specific question about this device

This device is intended for use in surgical procedures to assist in locating and mapping motor nerves through the use of mechanomyographic (MMG) signals and electrical stimulus of nerves. This device is indicated for locating and identifying spinal nerve roots and peripheral motor nerves originating from spinal levels C3-T1 and L2-S2.

The NeuralMAS™ system is a multichannel intraoperative monitor for use during surgeries in which a motor nerve is at risk. The NeuralMAS™ system records mechanomyographic (MMG) signals from muscles innervated by the affected nerve, which may originate from operator applied electrical stimulus or from direct or indirect mechanical stimulus occurring during the course of surgery. The monitor will assist early nerve identification by providing the surgeon with a tool to help locate and identify the particular nerve at risk to minimize trauma by alerting the surgeon when a particular nerve has been activated.

The NeuralMAS™ system consists of a reusable Patient Module, a Control Unit comprised of a touch-screen PC and an assortment of disposable conductive probes, stimulators, sensors, electrodes and electrode leads.

Here's a breakdown of the acceptance criteria and the study details for the NeuralMAS™ device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state pre-defined acceptance criteria in terms of specific performance metrics (e.g., minimum sensitivity or specificity targets). Instead, the study's acceptance was based on demonstrating "statistical agreement" and "correlation" with a predicate device.

1. The NeuralMAS™ system's principle functions are effective for ascertaining and monitoring spinal nerve status and location.
2. Data acquired by NeuralMAS™ during simulated surgical use in an animal model correlate well with data acquired simultaneously by a predicate device. |
   | Effectiveness of principle functions | Demonstrated effectiveness in ascertaining and monitoring spinal nerve status and location. |
   | Correlation of acquired data with predicate device | Good correlation between data acquired by NeuralMAS™ and data acquired simultaneously by a predicate device in an animal model. |
   | Safety and effectiveness comparable to predicate device | Concluded to be "as safe, as effective and performs as well as the legally marketed predicate device." |
   | Substantial equivalence in function to predicate device | Concluded to be "substantially equivalent in function to the legally marketed predicate device." |

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: Not explicitly stated. The study mentions a "comparative performance evaluation was conducted in the sheep," implying a limited animal study, but the specific number of sheep or cases is not provided.
• Data Provenance: Prospective animal study conducted in "sheep" (animal model). The country of origin is not specified, but the submission is to the US FDA, so it's likely a US-based study or one adhering to US regulatory standards.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

Not applicable. The study was a comparative performance evaluation between the subject device and a predicate device in an animal model, not an assessment against human-established ground truth. The "ground truth" was essentially the synchronous readings from the predicate device and the physiological responses observed during the animal experiment.

4. Adjudication Method for the Test Set

Not applicable. There was no mention of human expert adjudication for the animal study. The comparison was statistical agreement and correlation between the two devices.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No. The study described is a non-clinical animal study comparing the device to a predicate, not an MRMC study involving human readers.

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

Yes, in essence. The "comparative performance evaluation" in the sheep assessed the device's ability to ascertain and monitor nerve status and location, and its data acquisition, in direct comparison to the predicate device. This is a standalone assessment of the device's functional performance in a simulated surgical environment. Human interpretation or intervention as part of the performance measurement itself (beyond setting up and operating the devices) is not indicated.

7. The Type of Ground Truth Used

The "ground truth" for the test set was the data simultaneously acquired by the predicate device and the directly observable physiological responses in the animal model. The study aimed to show correlation and agreement between the NeuralMAS™ and the predicate device's readings. It did not rely on a separate, independent "gold standard" or pathology.

8. The Sample Size for the Training Set

Not applicable. This is a 510(k) submission for a medical device that records mechanomyographic signals and uses electrical stimulation. The device itself is not described as involving a machine learning algorithm that requires a "training set" in the traditional sense. The "training" for the device would have involved engineering development and calibration, not a data-driven machine learning training set as would be found in AI/ML device submissions.

9. How the Ground Truth for the Training Set was Established

Not applicable, as there's no mention of a traditional machine learning training set for this device.

Ask a specific question about this device