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The ACUSON Sequoia ultrasound imaging system is intended to provide images of, or signals from, inside the body by an appropriately trained healthcare professional in a clinical setting for the following applications: Fetal, Abdominal, Pediatric, Neonatal Cephalic, Small Parts, OB/GYN (useful for visualization of the ovaries, follicles, uterus and other pelvic structures), Cardiac, Pelvic, Vascular, Adult Cephalic, Musculoskeletal and Peripheral Vascular applications.

The system also provides the ability to measure anatomical structures for fetal, abdominal, pediatric, small organ, cardiac, transvaginal, peripheral vessel, musculoskeletal and calculation packages that provide information to the clinician that may be used adjunctively with other medical data obtained by a physician for clinical diagnosis purposes.

The ACUSON Sequoia Diagnostic Ultrasound System is a multi-purpose mobile, software controlled, diagnostic ultrasound system with an on-screen display of thermal and mechanical indices related to potential bio-effect mechanisms. Its function is to transmit and receive ultrasound echo data and display it in B-Mode, Pulsed (PW) Doppler Mode, Continuous (CW) Doppler Mode, Color Doppler Mode, Color M Mode, Doppler Tissue Mode, Amplitude Doppler Mode, a combination of modes. Panoramic Imaging, Contrast agent Imaging, Virtual Touch Strain Imaging, Virtual Touch - pSWE Imaging, Virtual Touch - SWE Imaging, syngo Velocity Vector Imaging, Custom Tissue Imaging, 3D/4D Volume Imaging and Harmonic Imaging on a Display.

The provided document is a 510(k) premarket notification for the Siemens ACUSON Sequoia Diagnostic Ultrasound System. It describes the device, its intended use, and its substantial equivalence to previously cleared predicate devices.

However, the document explicitly states in section 8: "Since the ACUSON Sequoia Diagnostic Ultrasound System uses the same technology and principles as existing devices, clinical studies were not required to support substantial equivalence."

This means that no clinical study was conducted to prove the device meets specific acceptance criteria based on human-in-the-loop performance or an AI’s standalone performance as would be the case for AI/ML-driven devices. Therefore, I cannot provide information on:

• A table of acceptance criteria and reported device performance related to AI/ML.
• Sample sizes, data provenance, number of experts, adjudication methods for a test set.
• MRMC comparative effectiveness studies or standalone AI performance.
• Ground truth establishment for test sets.
• Training set sample size or ground truth establishment relevant to AI/ML.

The provided information focuses on the device's technical specifications, safety standards compliance (acoustic output, biocompatibility, cleaning/disinfection, thermal, electrical, electromagnetic, mechanical safety), and engineering verification and validation, rather than clinical performance metrics for an AI/ML component.

The "acceptance criteria" presented in this document are primarily related to general device safety and performance based on engineering principles and comparison to predicate devices, rather than the kind of AI/ML performance metrics typically seen in studies demonstrating clinical efficacy or diagnostic accuracy for an AI-powered device.

Key takeaway: The document asserts substantial equivalence based on technological similarity to existing devices and compliance with safety standards, eliminating the need for new clinical performance studies for this specific submission.

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