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Ultrasonic pulsed echo imaging, measurement, color Doppler, and color velocity imaging for Fetal, Abdominal, Pediatric, Small Organ, and Peripheral Vascular.

Apoqee 800 PLUS transmits ultrasound waves. receives the echoes, and generates images based on information contained in the echoes. The format in which the information is displayed depends on the imaging mode or modes that you select. The system is capable of real-time two-dimensional (2D) imaging, motion mode (M-mode) imaging, Doppler imaging, Power imaging, and color imaging. The system supports application and exam type presets, which means that the system is automatically optimized for the scanhead and application you have selected. Additionally, analysis protocols are made available so that you can store measurements in the patient's report. Physically the system consists of the monitor module, the control module, the main chassis, and transducers.

Here's an analysis of the provided text regarding the acceptance criteria and study information for the SIUI Apogee 800 PLUS Ultrasound Imaging System, structured according to your request.

Please note: The provided document is a 510(k) Premarket Notification Summary from 1999. These types of documents are primarily concerned with demonstrating "substantial equivalence" to a predicate device, rather than providing detailed clinical study results and statistically derived acceptance criteria as might be expected for novel AI/ML-driven devices today. Therefore, much of the requested information (like specific sample sizes for test and training sets, expert qualifications, and adjudication methods for AI performance studies) is not present in this document. The "acceptance criteria" here are essentially the features and performance specifications of the device being compared directly to a predicate.

Acceptance Criteria and Device Performance for SIUI Apogee 800 PLUS Ultrasound Imaging System

1. Table of Acceptance Criteria and Reported Device Performance

For a 510(k) submission, "acceptance criteria" are effectively whether the new device's specifications and performance fall within a comparable range to the predicate device, demonstrating substantial equivalence. The document doesn't provide explicit statistical acceptance criteria for performance metrics in the way a clinical trial for a new diagnostic might. Instead, it presents a direct comparison of features and specifications.

Study Details:

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

• Not Applicable. This document pre-dates modern AI/ML device evaluations. The "test set" in this context is the physical device and its performance against technical specifications and clinical uses, primarily through comparison to a predicate device. There is no mention of a separate "test set" of diagnostic images or patient data to evaluate algorithmic performance.
• Data Provenance: The manufacturer is Shantou Institute of Ultrasonic Instruments, China. The device and its specifications are presented by the manufacturer for FDA review.

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

• Not Applicable. No explicit "ground truth" establishment by experts for a test set of data is described. The comparison is based on the declared technical specifications and intended uses, which are implicitly validated by general medical consensus and the established performance of the predicate device.

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

• Not Applicable. No adjudication method for a test set is described.

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. This document does not describe an MRMC study, nor does the device involve AI assistance for human readers. It is a standalone ultrasound imaging system.

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

• Yes, in concept, but not as an "algorithm." The "standalone performance" is the performance of the ultrasound system itself, as described by its technical specifications and capabilities, independent of a specific human operator’s interpretive skill. This is the core of what the comparison tables are trying to establish – that the system on its own can perform the stated functions. However, it's not an "algorithm-only" performance study in the modern sense of AI/ML evaluation.

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

• Not explicitly stated in terms of a study. The "ground truth" for this submission is an implicit one: the established performance and safety of the predicate devices (ATL Ultramark 9 HDI system, K903603 and Interspec Inc Apogee RX 400, K924231) and the general understanding of what constitutes a safe and effective ultrasound imaging system for the stated intended uses. The clinical applications and modes of operation are standard for these devices and are understood to provide diagnostically useful information.

8. The sample size for the training set:

• Not Applicable. This is not a submission for an AI/ML device that requires a training set of data. The device is hardware-based.

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

• Not Applicable. As above, no training set is relevant for this type of device submission.

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