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The SONOACE X4 system is intended for the following applications: General, OB, Gynecology, Abdomen, Fetal Heart, Renal, Neonatal, Pediatric, Vascular, Cardiac, Urology, Breast, Small Parts, Vascular, Musculoskeletal applications.

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

The SONOACE X4 is a general purpose, mobile, software controlled, diagnostic ultrasound system with on-screen display for themal and mechanical indices related to potential bioeffect mechanisms.. Its function is to acquire ultrasound data and to display the data as 2D (B) mode, M mode, Power Doppler imaging, Harmonic imaging, or 3D imaging on the CRT display.

This appears to be a 510(k) premarket notification for a diagnostic ultrasound system (SONOACE X4) and its associated transducers. The document focuses on demonstrating substantial equivalence to previously cleared predicate devices, rather than establishing de novo performance criteria through a clinical study with acceptance criteria.

Therefore, the requested information regarding acceptance criteria, study details, expert involvement, and ground truth establishment does not apply in the context of this specific regulatory submission.

Here's why and what can be inferred:

Why the requested information doesn't apply to this document:

• Substantial Equivalence (510(k)) Process: The 510(k) pathway is for devices that are "substantially equivalent" to a legally marketed predicate device. This means the new device has the same intended use and technological characteristics as the predicate, or has different technological characteristics but does not raise different questions of safety and effectiveness.
• Focus on Comparison, Not De Novo Performance: This document primarily identifies predicate devices (K012887, K043455) and asserts that the SONOACE X4 and its transducers are substantially equivalent. It lists safety standards (UL, CSA, IEC, NEMA, ISO) that the device meets, but these are general safety and performance standards for ultrasound equipment, not specific diagnostic acceptance criteria for a particular clinical task.
• Absence of Clinical Study Data for Acceptance Criteria: There is no mention of a clinical study designed to test the diagnostic performance of the SONOACE X4 against specific acceptance criteria (e.g., sensitivity, specificity for detecting a certain condition). The "Mode of Operation" tables simply indicate what modes (B, M, PWD, etc.) are available for each clinical application, and whether they are new ("N") or previously cleared ("P") based on predicate devices.

What can be extracted/inferred from the document given the request:

Since the document doesn't contain a study proving the device meets acceptance criteria in the way you've described for a diagnostic AI model, most of your requested fields will be "Not Applicable" or "Not Provided." However, here's an attempt to address each point based on the nature of this 510(k) submission:

Acceptance Criteria and Device Performance for SONOACE X4 Diagnostic Ultrasound System

This submission is a 510(k) premarket notification for the SONOACE X4 Diagnostic Ultrasound System, which aims to demonstrate "substantial equivalence" to previously cleared predicate devices, rather than establishing de novo performance acceptance criteria through a specific clinical study for diagnostic accuracy. Therefore, the concept of a "table of acceptance criteria and reported device performance" as typically associated with a diagnostic AI model study is not applicable here.

The device's "performance" is implicitly deemed acceptable by its substantial equivalence to predicate devices which have already been cleared for marketing. The acceptance criteria met are primarily related to safety and general device performance standards for diagnostic ultrasound equipment.

1. Table of Acceptance Criteria and Reported Device Performance

¹ Note: The tables provided in the document (from {5} to {14}) list clinical applications and modes of operation for the main system and each transducer. "N" indicates a new indication (compared to the specific predicate mentioned in the footer for that table), while "P" indicates previously cleared. This is a demonstration of equivalence for intended uses, not a performance study.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: Not applicable. This document does not describe a clinical study with a specific test set for diagnostic accuracy. The substantial equivalence argument relies on prior clearances of predicate devices and adherence to recognized standards.
• Data Provenance: Not applicable. No patient data (retrospective or prospective) from a specific test set is discussed in the context of diagnostic performance evaluation.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• Number of Experts: Not applicable. No ground truth establishment for a diagnostic test set is described.
• Qualifications of Experts: Not applicable.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. No test set requiring ground truth adjudication 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

• MRMC Study: Not applicable. This document is for a diagnostic ultrasound system, not an AI-assisted diagnostic tool.

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

• Standalone Study: Not applicable. This document is for a diagnostic ultrasound system, which inherently involves human operation and interpretation.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

• Type of Ground Truth: Not applicable. This document does not present a study requiring clinical ground truth for diagnostic accuracy.

8. The Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. As an ultrasound imaging system (not an AI model within the scope of this submission), there is no "training set" in the context of machine learning.

9. How the Ground Truth for the Training Set was Established

• Ground Truth Establishment for Training Set: Not applicable.

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