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The SQNOACE X8 system and transducers are intended for diagnostic ultrasound imaging and fluid analysis of the human body. The clinical applications include: General, abdomen, obstetrics, gynecology, vascular, extremity, pediatric, cardiac, breast, urology, neonatal cephalic, trans-esophageal. and etc.

The SONOACE X8 is a general purpose, mobile, software controlled, diagnostic ultrasound system. Its function is to acquire ultrasound data and to display the data as 2D mode, M mode, Color Doppler mode, Power Doppler mode, PW Spectral Doppler, CW Spectral Doppler mode, and Tissue Doppler Image mode on the LCD display. It also provides the 3D/4D imaging mode using the 3D/4D probe in the Mechanical scan mode. The SONOACE X8 has real time acoustic output display with two basic indices, a mechanical index and a thermal index, which are both automatically displayed. The system also provides for the measurement of anatomical structures and for analysis packages that provide information used for clinical diagnostic purposes by competent health care professionals.

The provided submission (K093714) for the SONOACE X8 Diagnostic Ultrasound System is a 510(k) Premarket Notification. This type of submission focuses on demonstrating "substantial equivalence" to a legally marketed predicate device, rather than proving safety and effectiveness through clinical trials with specific acceptance criteria and performance metrics against ground truth.

Therefore, the document does not contain the information requested in questions 1-9 directly. The submission establishes equivalence based on technological characteristics and intended uses being similar to previously cleared devices (K0635580 and K092159). There are no specific acceptance criteria for performance metrics (like sensitivity, specificity, or similar quantitative measures for an AI-enabled device) or a study proving the device meets such criteria as would be found in a de novo or PMA submission.

The document discusses compliance with recognized safety and performance standards for diagnostic ultrasound systems as part of establishing substantial equivalence. These standards are general for the device type, not specific acceptance criteria for a novel AI capability's performance.

Here's what can be inferred or stated from the document, with explanations why other information is not present:

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

• Acceptance Criteria: Not explicitly stated as performance metrics (e.g., sensitivity, specificity, accuracy) for a specific clinical task. The "acceptance criteria" for a 510(k) submission like this are implicitly demonstrating substantial equivalence to predicate devices and adherence to relevant industry standards for safety and fundamental operational characteristics. The device is assessed against safety standards such as UL 60601-1, CSA C22.2 No. 601.1, IEC60601-2-37, EN/IEC60601-1, EN/IEC60601-1-2, NEMA UD-2, NEMA UD-3, IEC 61157, and ISO10993-1 (biocompatibility).
• Reported Device Performance: No specific quantitative performance metrics (like sensitivity, specificity, etc.) are reported in the summary that would be tied to clinical acceptance criteria. The performance is deemed substantially equivalent to the predicate devices for the listed clinical applications (General, abdomen, obstetrics, gynecology, vascular, extremity, pediatric, cardiac, breast, urology, neonatal cephalic, trans-esophageal, etc.) and modes of operation (2D, M-mode, Color Doppler, Power Doppler, PW Spectral Doppler, CW Spectral Doppler, Tissue Doppler Image, 3D/4D).

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

This information is not provided in the 510(k) summary. For ultrasound systems seeking substantial equivalence, performance is typically confirmed through engineering testing, comparison to predicate devices, and adherence to performance standards, rather than extensive clinical efficacy studies with specific test sets in the same manner as a novel AI algorithm.

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)

This information is not provided. Ground truth establishment by experts for specific clinical tasks is generally not required for this type of 510(k) submission, as it's not evaluating the diagnostic performance of a novel AI algorithm against a reference standard.

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

This information is not provided. Clinical study design details such as adjudication methods are not typically part of a 510(k) summary for a general diagnostic ultrasound system.

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

This information is not applicable/provided. The SONOACE X8 is a diagnostic ultrasound system, not explicitly described as having AI assistance for human readers in this submission. Therefore, an MRMC comparative effectiveness study regarding AI assistance would not be relevant to this submission.

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

This information is not applicable/provided. The SONOACE X8 is a hardware and software system for generating ultrasound images and data, not a standalone algorithm.

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

This information is not provided. As explained above, specific ground truth for performance evaluation of a novel diagnostic claim is not presented in this substantial equivalence summary. The "ground truth" for a general ultrasound system is its ability to accurately produce images and measurements in accordance with its intended use and technical specifications, which would be verified through engineering and phantom testing, and comparison to predicate devices.

8. The sample size for the training set

This information is not applicable/provided. This submission does not pertain to an AI algorithm that would have a training set.

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

This information is not applicable/provided. This submission does not pertain to an AI algorithm that would have a training set with established ground truth.

In summary: The K093714 document is a 510(k) summary for a diagnostic ultrasound system. Its purpose is to demonstrate substantial equivalence to existing devices and compliance with safety and performance standards for ultrasound technology. It does not provide the kind of performance data (e.g., accuracy, sensitivity, specificity) and study details (sample sizes, ground truth establishment, expert qualifications, adjudication methods) that would be expected for a novel AI-enabled device with specific diagnostic claims requiring clinical validation.

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