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510(k) Data Aggregation
(247 days)
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.
| Feature/Characteristic | Acceptance Criteria (Inferred from Predicate Equivalence) | Reported Lucid M1 System Performance |
|---|---|---|
| Indications for Use | Equivalent to Spencer TCD 100 M | "adjunct to the standard clinical practices for measuring and displaying cerebral blood flow velocity...and measures the occurrence of transient emboli signals." (Equivalent) |
| Product Code, Class | IYN, ITX; Class II | IYN, ITX; Class II (Equivalent) |
| Energy Used/Delivered | Ultrasound Energy | Ultrasound Energy (Equivalent) |
| Sample Volume | Similar to predicate | 2 to 12mm in 1mm steps |
| Depth | Similar to predicate | 23 to 151mm |
| Acoustic Output (ISPTA) | Global maximum derated ISPTA < 720 mW/cm² (as predicate) | < 720 mW/cm² (specifically 675mW/cm²) |
| Acoustic Output (MI) | Global maximum MI < 1.0 (as predicate) | < 1.0 |
| Acoustic Output (TIC) | Max TIC (as predicate) | Max TIC of 2.5 (user informed on display) |
| Clinical Measurements | Equivalent to predicate (e.g., Peak, Diastolic velocity, Mean, PI, Embolus Count) | Maximum Velocity, Mean Velocity, Minimum Velocity, Pulsatility Index, Cerebrovascular Reactivity, Embolus Count |
| Rechargeable Battery | Not present on predicate (user convenience feature) | Lithium Ion (TCD Driver), Lithium Polymer (Tablet). Compliant with IEC 62133 and UL 2054. |
| M-Mode | Traditional M-Mode (as predicate) | Traditional M-Mode + Modified M-Mode |
| Cerebrovascular Reactivity Calculations | Manual calculations (as predicate) | Automated CVR calculations |
| Safety and Electrical | Meet applicable safety requirements (IEC standards) | Complies with IEC 60601-1, 60601-1-2, 60601-2-37, etc. (Equivalent) |
| Biocompatibility | Pass biocompatibility evaluation | Evaluated per ISO 10993-1 |
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.
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