Search Results

The NeuralBot when used with Lucid M1 System is a medical ultrasound device which assists the user in the setup and acquisition of cerebral blood flow velocity via the patient's temporal windows. It is intended for use as an adjunct to standard clinical practices for measuring and displaying cerebral blood flow velocity and the occurrence of transient emboli within the blood stream.

The NeuralBot is intended to be used by healthcare professionals qualified by training in its safe and effective use. The device is not intended to replace other means of evaluating vital patient physiological processes, is not intended to be used in fetal applications, and is not intended to be used inside the sterile field.

The NeuralBot System is a cart mounted. robotic transcranial Doppler (TCD) probe positioning accessory for the previously cleared Lucid M1 System (K160442) which assists the user in the acquisition of cerebral blood flow velocity (CBFV) data via the patient's temporal acoustic windows.

The NeuralBot System consists of the following three subsystems mounted on a cart

• 1. Accessory Control Unit (ACU)
  • The main accessory software including the, TCD signal search algorithm, and a. graphical user interface are installed on this subsystem.
• 2. Robotic Control Unit (RCU)
  • Contains the electronics and embedded software that control the robotic actuators of a. the patient headmount unit.
• 3. Patient Headmount Unit (PHU)
  • Comprised of the patient head interface, 2 MHz transducers, and the robotic probe a. positioning mechanism.

The NeuralBot System guides the operator in positioning the transducers in the PHU, one on each side of a patient's head, at their temporal regions. The 2 MHz transducers used in the NeuralBot System are the same transducers previously cleared for use with the Lucid M1 System (K160442). The NeuralBot System's probe positioning is accomplished using robotic actuators that adjust the translational and angular position of each transducer independently using TCD signal search algorithms. The accessory is designed to locate TCD signals at depths between 45 and 60 mm allowing the operator to monitor the CBFV of the vessels via the patient's temporal acoustic windows. The NeuralBot System identifies several candidate TCD signals and displays multiple signals from each side of the patient's head. At the end of the search, the NeuralBot System will then retrieve and track the best located signal.

The NeuralBot System is a robotic transcranial Doppler (TCD) probe positioning accessory that works with the existing Lucid M1 System. It assists users in acquiring cerebral blood flow velocity (CBFV) data by guiding the positioning of transducers at the patient's temporal acoustic windows.

Here's an analysis of the acceptance criteria and supporting studies as described in the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not contain a specific table detailing acceptance criteria for performance metrics (e.g., sensitivity, specificity, accuracy) related to the device's primary function of assisting in TCD signal acquisition and tracking. Instead, it focuses on general safety, effectiveness, and substantial equivalence to predicate devices, adhering to recognized standards.

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

The document does not specify a sample size for a "test set" in the context of clinical performance or algorithm evaluation. The non-clinical testing mentioned focuses on engineering verification and validation against recognized standards for safety and electrical performance. There is no mention of data provenance (e.g., country of origin, retrospective/prospective) for a performance test set.

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

Not applicable. The provided document does not describe a study involving expert-established ground truth for a test set related to diagnostic performance. The document focuses on the device's ability to assist in TCD signal acquisition and tracking, rather than providing a diagnostic interpretation.

4. Adjudication Method for the Test Set

Not applicable. There is no mention of a clinical test set requiring ground truth adjudication.

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, a multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance is not described in the provided document. The NeuralBot System is presented as an accessory that assists in probe positioning and TCD signal acquisition, not as an AI interpretation tool.

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

The document describes the NeuralBot System as having a "TCD signal search algorithm" and "robotic actuators that adjust the translational and angular position of each transducer independently using TCD signal search algorithms." While an algorithm is at the core of its functionality, the device is explicitly designed as an accessory that "assists the user." Therefore, its performance is inherently tied to a human-in-the-loop interaction for TCD data acquisition, and a standalone algorithm-only performance study (in the sense of diagnostic interpretation without human input) is not discussed. The "device performance" relies on its ability to guide the operator and retrieve and track the best located signal.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

The document does not describe a clinical study where ground truth of the type "expert consensus, pathology, or outcomes data" would be used. The "ground truth" implied for the device's functionality would be objective measures of its ability to locate and track TCD signals effectively, likely against established TCD methodologies or physical phantoms, but this level of detail is not provided.

8. The Sample Size for the Training Set

The document does not specify a sample size for a training set. If the "TCD signal search algorithm" utilizes machine learning, the details of its training are not included in this summary.

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

The document does not provide information on how ground truth for any potential training set was established.

Ask a specific question about this device

The Lucid M1 System is a medical ultrasound system intended for use as an adjunct to the standard clinical practices for measuring and displaying cerebral blood flow velocity within the major conducting arteries and veins of the head and neck. Additionally, The Lucid M1 System measures the occurrence of transient emboli signals within the blood stream.

The device is not intended to replace other means of evaluating vital patient physiological processes, is not intended to be used in fetal applications, and is not intended to be used inside the sterile field.

The Lucid M1 System is an adjunctive, portable, non-invasive, non-ionizing radiation, point-of-care transcranial Doppler (TCD) diagnostic ultrasound system. It is designed to non-invasively measure and display cerebral blood flow velocity over the head and neck with a reusable, non-sterile 2-MHz hand-held probe. It can also be used bilaterally to monitor the blood flow velocity of the vessels insonated via the temporal window of the head with a headset with two reusable, non-sterile 2-MHz monitoring transducers. The system can also provide an emboli count for emboli detection.

The provided text does not contain detailed acceptance criteria or a study proving the device meets specific performance criteria beyond general statements of substantial equivalence to a predicate device. The information focuses on design, safety, and functional equivalence rather than quantitative performance metrics and clinical study results.

However, based on the provided text, here's what can be extracted and inferred:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly list "acceptance criteria" for performance metrics in a quantitative manner. Instead, it demonstrates "substantial equivalence" to a predicate device (Spencer Technologies TCD 100 M). The "reported device performance" is largely described in terms of functional equivalence and compliance with general safety standards.

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

The document explicitly states: "The Lucid M1 System does not require clinical testing to show substantial equivalence to its predicate device in safety and effectiveness." Therefore, no test set of patient data was used for clinical performance evaluation. The evaluation appears to be based on non-clinical testing and comparison of technical characteristics to the predicate device.

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

Not applicable, as no clinical test set was used for performance evaluation that required expert ground truth.

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

Not applicable, as no clinical test set was used.

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 device is an ultrasound system, not an AI-assisted diagnostic tool that would typically involve human readers interpreting images. Its "algorithm" refers to internal processing, not necessarily AI for interpretation.

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

The device is a medical ultrasound system that outputs measurements and displays. Its "algorithm" is responsible for processing the raw ultrasound signals into interpretable data (e.g., velocity, emboli count, CVR calculation). The document implies that the algorithms perform these analyses without direct human intervention in the calculation process itself, though a human operates the device and interprets the results. The non-clinical testing would have verified the accuracy and functionality of these internal algorithms and their outputs.

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

For the non-clinical testing, the "ground truth" would have been established through engineering benchmarks, calibrated measurement equipment, and compliance with recognized standards (e.g., for acoustic output, electrical safety). For example, acoustic output measurements against the NEMA UD 2-2004 standard would serve as the ground truth for acoustic performance. There's no mention of a clinical ground truth (like pathology or outcomes data) being used for this submission.

8. The sample size for the training set:

Not applicable, as this is a traditional 510(k) submission for an ultrasound system, not a machine learning or AI-driven device requiring a "training set" in the conventional sense. The "algorithm" mentioned refers to signal processing and calculation logic, not an algorithm trained on a dataset.

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

Not applicable.

Ask a specific question about this device