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Detection and analysis of vascular disease in peripheral vessels. Evaluation of degree and site of a stenosis. Detection of occlusions and flow disturbances. Determination of vessel type and location. Measurement of relative flow velocity. Not intended for fetal use.

Stenodoc is a mains independent portable continuous wave Doppler ultrasound device with two pen-shaped split-D transducers operating at 4 MHz and 8 MHz. A 512 point fast Fourier transform (FFT) is performed on the returned signal. The spectral distribution of blood flow is represented as a frequency over time diagram with intensities represented by different shades of gray. The diagram is displayed on a liquid crystal display (LCD). Measurements can be annotated with the patient's name, vessel name and a diagnosis and can be stored on a built-in harddisk for later evaluation. Size: 3" x 13.5" x 10" (Height/Width/Depth) Weight: 9 lbs.

Please note: The provided text is a 510(k) summary for a medical device (Stenodoc Bidirectional Vascular Doppler with Spectral Analysis) from 1995. Medical device regulation and the types of studies required for market clearance have evolved significantly since then. The information available in this summary is consistent with the regulatory landscape of its time, which did not typically include the detailed statistical performance metrics, extensive clinical trial data, or specific ground truth methodologies that are common in modern AI/ML device submissions.

Based on the provided text, here is an analysis of the acceptance criteria and study information:

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not explicitly state "acceptance criteria" in the modern sense of quantifiable performance targets for a clinical study (e.g., sensitivity, specificity, AUC thresholds). Instead, the "acceptance criteria" are implied by the demonstration of substantial equivalence to a predicate device. The performance is assessed by comparing technical characteristics to the predicate.

Interpretation: The "acceptance" is that the new device's characteristics are either equivalent or have technological differences that do not raise new questions of safety or effectiveness when compared to the predicate. For example, some values are slightly different (e.g., ISPTA, max frequency detection, FFT calculation speed), and some are enhanced (e.g., AD-Converter resolution, additional calculations). These differences would have been reviewed by the FDA to ensure they did not negatively impact performance as defined by the predicate.

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

The document does not explicitly describe a "test set" or any clinical study with a specific sample size for evaluating performance in the way modern AI/ML devices do. The primary mechanism for clearance is demonstrating substantial equivalence based on technological characteristics and intended use to a predicate device.

The provenance of data (e.g., country of origin, retrospective/prospective) is not mentioned because a clinical data-based performance study is not detailed.

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

This information is not applicable to this 510(k) submission. A formal "ground truth" establishment by experts for a specific test set, as is common in AI/ML validation, is not described or required based on the provided text for this device's 1995 submission. The "ground truth" for showing effectiveness relies on the established effectiveness of the predicate device.

4. Adjudication method for the test set

This information is not applicable. Since no specific "test set" and expert ground truth establishment are described, there is no adjudication method detailed.

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 was not done, and therefore no effect size regarding human reader improvement with AI assistance is reported. This device is a diagnostic ultrasound system (Doppler with spectral analysis), not an AI-powered diagnostic aid in the modern sense. Its function is to provide physiological measurements (blood flow velocity and characteristics) for clinicians to interpret.

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

The concept of a "standalone" algorithmic performance, as understood for AI/ML devices, is not applicable here. The device itself (Stenodoc) performs the spectral analysis (FFT) and calculations. Its performance is inherent to its technical specifications and comparison to the predicate, rather than being an algorithm that makes a diagnostic "call" independent of a human. The device generates data (spectral traces, calculated indices) that a clinician then interprets.

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

The document does not specify an explicit type of "ground truth" used for clinical performance evaluation. For a 510(k) submission, the "ground truth" for the device's functionality and effectiveness is implicitly established by the predicate device's known performance and intended use. The new device is deemed safe and effective because its technological characteristics are substantially equivalent to a device already on the market with a history of safe and effective use.

8. The sample size for the training set

This information is not applicable. The device is not an AI/ML algorithm that is "trained" on a dataset in the modern sense.

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

This information is not applicable, as there is no "training set" for an AI/ML algorithm involved in this 1995 device submission.

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