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Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows: Fetal, Abdominal, Intra-operative (Abdominal organs and vascular), Pediatric, Small Organ (breast, thyroid, testicles.), Neonatal Cephalic, Trans-rectal, Trans-vaginal, Musculo-skel. (Convent.), Cardiac Adult, Cardiac Pediatric, Peripheral vessel.

The SonoHeart™ Hand-Carried Echocardiography System is a general purpose, highly portable, software-controlled, diagnostic ultrasound system. Its function is to acquire ultrasound data and display it on a monitor in 2D, Color Power Doppler, and 2D PowerMap™ Directional Color Power Doppler or in a combination of modes. The SonoHeart™ Hand-Carried Echocardiography System also gives the operator the ability to measure anatomical structures and offers analysis packages that provide information used for clinical diagnostic purposes.

This is a 510(k) summary for the SonoHeart™ Hand-Carried Echocardiography System, submitted to the FDA on December 3, 1999. As such, it is a declaration of substantial equivalence to predicate devices and does not contain detailed primary study data or explicit acceptance criteria for device performance as a modern AI/ML device submission would. The document focuses on technological characteristics, intended use, and equivalence to existing devices rather than a standalone performance study.

Therefore, many of the requested details, such as sample size for test sets, data provenance, number and qualifications of experts, adjudication methods, MRMC studies, specific ground truth types, training set sizes, and how training ground truth was established, are not provided in this 510(k) summary. This type of information is typical for new medical device submissions involving novel algorithms or AI components, which was not the case for this device from 1999.

Here's an analysis based on the provided text, highlighting what is available:

1. Table of acceptance criteria and the reported device performance

The document does not present explicit acceptance criteria for device performance in terms of diagnostic accuracy, sensitivity, specificity, or similar metrics. Instead, the "acceptance criteria" are implied by compliance with established medical device standards and demonstrating substantial equivalence to predicate devices. The "reported device performance" is primarily in terms of acoustic output limits, intended uses, and modes of operation, which are compared to predicate devices.

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

• Not provided. This document does not concern a clinical study with a test set of patient data to evaluate algorithmic performance. It is a submission for substantial equivalence based on technological similarity and compliance with safety standards.

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/Not provided. As there is no "test set" of images requiring ground truth establishment, this information is not relevant to this 510(k) submission.

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

• Not applicable/Not provided. No adjudication method is mentioned as there's no clinical performance evaluation on a test set.

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/Not provided. This device is a diagnostic ultrasound system, not an AI-powered diagnostic aide. MRMC studies are not relevant to this submission.

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

• Not applicable/Not provided. This is a hardware and software system, not a standalone algorithm in the modern AI sense.

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

• Not applicable/Not provided. No specific "ground truth" for diagnostic accuracy or performance is described in the context of a clinical study, as the submission focuses on safety and technological equivalence.

8. The sample size for the training set

• Not applicable/Not provided. The device is a traditional ultrasound system, not an AI/ML system trained on a dataset.

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

• Not applicable/Not provided. There is no "training set" in the context of an AI/ML algorithm for this device.

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