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The S2000 ultrasound imaging system is intended for the following applications: General Radiology, Abdominal, Fetal, Small Parts, Transcranial, OB/GYN, Cardiac, Pelvic, Neonatal/Adult Cephalic, Pediatric, Urology, Vascular, Musculoskeletal, Superficial Musculoskeletal, and Peripheral Vascular applications.

The system aiso provides for the measurement of anatomical structures and for analysis packages that provide information that is used for clinical diagnosis purposes.

The Acuson S2000™ Ultrasound System is a new multi-purpose mobile, software controlled diagnostic ultrasound system with and on-screen display for thermal and mechanical indices related to potential bio-effect mechanisms. Its function is to acquire primary or secondary harmonic ultrasound echo data and display it in B-Mode, Pulsed (PW) Doppler Mode, Continuous (CW) Doppler Mode, Color Doppler Mode, Amplitude Doppler Mode, a combination of modes, or Harmonic Imaging and 3D/4D Imaging on a Flat Panel Display.

This is a 510(k) premarket notification for the Siemens Acuson S2000™ Diagnostic Ultrasound System. It primarily focuses on demonstrating substantial equivalence to predicate devices and detailing the intended uses and supported transducers. As such, it does not contain the type of performance study data and acceptance criteria typically found for AI/ML-driven devices.

Therefore, the requested information elements related to specific performance metrics, sample sizes for test/training sets, expert qualifications, and comparative effectiveness studies are not present in this document.

Summary of Available Information:

1. A table of acceptance criteria and the reported device performance:

This document is a 510(k) submission for a diagnostic ultrasound system. It primarily focuses on demonstrating substantial equivalence to predicate devices and lists the safety standards it meets (e.g., UL 60601-1, CSA C22.2 No. 601-1, AIUM/NEMA UD-3, AIUM/NEMA UD-2, 93/42/EEC Medical Devices Directive, EN 60601-1, EN 60601-1-1, EN 60601-1-2, EN 60601-2-37, IEC 61157, ISO 10993).

It does not include specific performance acceptance criteria or reported device performance metrics in the way an AI/ML study would (e.g., sensitivity, specificity, AUC). The "performance" assessment is based on demonstrating that the device functions as intended and is safe, aligning with its 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 applicable. This document does not describe a performance study with a test set.

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. This document does not describe a performance study with a test set requiring ground truth establishment by experts.

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

Not applicable. This document does not describe a performance study with a test set requiring 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:

Not applicable. This document does not describe a multi-reader, multi-case comparative effectiveness study or involve AI assistance for human readers. It focuses on the capabilities of the ultrasound system itself.

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

Not applicable. This device is a diagnostic ultrasound system, not an algorithm being tested in a standalone fashion. Its performance is inherent in its operation as a medical imaging device.

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

Not applicable. There is no performance study where ground truth would be established for the device's diagnostic capabilities in this 510(k). The regulatory submission is for the device's safety and effectiveness based on its intended use and comparison to legally marketed predicate devices, not for a novel diagnostic algorithm requiring independent ground truth validation.

8. The sample size for the training set:

Not applicable. This document does not pertain to an AI/ML algorithm that would have a training set.

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

Not applicable. This document does not pertain to an AI/ML algorithm that would have a training set.

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