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The X-CUBE 70 diagnostic ultrasound system is intended for use by, or by the order of, and under the supervision of, a licensed physician who is qualified for the evaluation of soft tissue and blood flow in the clinical applications of Fetal: Abdominal(renal & GYN/pelvic); Pediatric; Small Organ(breast, testes, thyroid); Neonatal Cephalic; Trans-rectal; Trans-vaginal; Musculo-skeletal(Conventional); Musculo-skeletal(Superficial); Cardiatric); Peripheral Vessel(PV); and Urology(including prostate).

And, in the imaging modes of 2D(B) mode; Harmonic mode(HAR); M mode; Anatomical M mode; Color Flow Doppler(CF) Mode; Power Doppler(PD) Mode; Directional PD mode; Pulsed Wave Doppler(PWD) Mode; Continuous Wave Doppler(CWD) Mode; High PRF Doppler mode; Tissue Doppler Imaging(TDI) Mode: 3D/4D mode. The X-CUBE 70 is intended to be used in a hospital or medical clinic.

X-CUBE 70 product is an ultrasound imaging system for medical diagnosis. This innovative system platform provides optimal patient diagnosis workflow with the wide flat panel display, ergonomic control panel with easy user interface, optimal image quality.

This document is an FDA 510(k) Premarket Notification stating that the Alpinion Medical Systems X-CUBE 70 ultrasound system is substantially equivalent to legally marketed predicate devices. It specifically outlines the indications for use, comparison to predicate devices, and a summary of non-clinical tests.

This document focuses on the substantial equivalence of the new device (X-CUBE 70) to existing predicate devices, primarily based on technical characteristics and compliance with safety standards, rather than proving performance against specific acceptance criteria through a clinical or algorithmic study.

Therefore, most of the requested information regarding acceptance criteria, study details, sample size, ground truth, and expert reconciliation cannot be extracted from this particular document, as it describes a regulatory submission for a medical imaging device, not a performance study of an AI/algorithm-driven device.

However, I can provide information based on what is available in the document:

Acceptance Criteria and Device Performance (Not directly addressing AI/algorithmic performance)

This section is interpreted in the context of the device's functional and safety characteristics, as the document details its equivalence to predicate ultrasound systems, not an AI component with specific performance metrics.

Since this document is a 510(k) submission for an ultrasound system, not an AI or algorithm-driven device that requires clinical performance studies to demonstrate accuracy in a diagnostic task, the following points are generally not applicable or stated as not required by the document:

2. Sample size used for the test set and the data provenance: Not mentioned as no specific performance test set (in the context of AI/algorithm accuracy) was required. The substantial equivalence relies on technical specifications and safety profile similarity to existing devices.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for diagnostic accuracy (e.g., presence/absence of disease based on expert consensus) is not part of this type of submission for an ultrasound machine.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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 is an ultrasound imaging system, not an AI-assisted diagnostic tool being evaluated for reader improvement.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is a medical device (ultrasound system), not a standalone algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. The "ground truth" here is the adherence to safety standards and performance characteristics comparable to predicate devices.
8. The sample size for the training set: Not applicable, as this is not an AI/ML device that requires a training set for a diagnostic algorithm.
9. How the ground truth for the training set was established: Not applicable.

Summary of Non-Clinical Tests (from document):
The device underwent non-clinical tests to assess biocompatibility, acoustic output, thermal, electrical, electromagnetic, and mechanical safety. It was found to conform to applicable medical device safety standards and voluntary standards (listed in the table above).

Summary of Clinical Tests (from document):
The document explicitly states: "The subject of this premarket submission, X-CUBE 70, did not require clinical studies to support substantial equivalence." This reinforces that the focus of this 510(k) submission is on technical and safety equivalence to predicate devices, not on a new clinical claim or an AI/algorithmic performance claim.

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