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MX7/ MX7T/ Vaus7/ Zeus/ ME7/ Anesus ME7/ Anesus ME7T/ MX8/ MX8T/ Vaus8/ ME8 Diagnostic Ultrasound System is applicable for adults, pregnant women, pediatric patients and neonates. It is intended for use in ophthalmic, fetal, abdominal, pediatric, small organ(breast, thyroid, testes), neonatal cephalic, trans-rectal, transvaginal, musculo-skeletal(conventional), musculo- skeletal(superficial), thoracic/pleural, cardiac pediatric, peripheral vessel and urology exams.

Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows:
Ophthalmic, Fetal, Abdominal, Intra-operative (Specify*), Intra-operative (Neuro), Laparoscopic, Pediatric, Small Organ (Specify**), Neonatal Cephalic, Adult Cephalic, Trans-rectal, Trans-vaginal, Trans-urethral, Trans-esoph. (non-Card.), Musculo-skeletal (Conventional), Musculo-skeletal (Superficial), Intravascular, Thoracic/Pleural (Specify****), Cardiac Adult, Cardiac Pediatric, Intravascular (Cardiac), Trans-esoph. (Cardiac), Intra-cardiac, Peripheral vessel, Other (Specify***)

*Intraoperative includes abdominal, thoracic, and vascular etc.
**Small organ-breast, thyroid, testes.
***Other use includes Urology.
****For detection of fluid and pleural motion/sliding.

MX7/ MX7T/ Vaus7/ Zeus/ ME7/ Anesus ME7/ Anesus ME7T/ MX8/ MX8T/ Vaus8/ ME8 Diagnostic Ultrasound System is a general purpose, mobile, software controlled, ultrasound diagnostic system. Its function is to acquire and display ultrasound images in B-mode, M-mode, PW-mode, CW mode, Color-mode, Color M-mode, Power/Dirpower mode, TDI mode, THI, iScape, Biopsy Guidance, eSpacial Navi, Smart 3D mode, Strain Elastography, Contrast imaging (Contrast agent for Liver and LVO) or the combined mode (i.e. B/M-Mode).This system is a Track 3 device that employs an array of probes that include linear array, convex array and phased array.

This document is a 510(k) Premarket Notification summary for a diagnostic ultrasound system. It does not describe an AI/ML-driven device, therefore, a detailed acceptance criteria table and study results for such a device are not present. However, I can extract the information related to the device's general performance and safety evaluations as presented in the document, which serves as a form of acceptance criteria for a medical device cleared via the 510(k) pathway.

The provided document describes the MX7/MX7T/Vaus7/Zeus/ME7/Anesus ME7/Anesus ME7T/MX8/MX8T/Vaus8/ME8 Diagnostic Ultrasound System. This is a general-purpose ultrasound system and not an AI/ML device in the sense of providing automated diagnoses or assisting human readers with AI. The "acceptance criteria" for such a device primarily revolve around safety, effectiveness, and substantial equivalence to legally marketed predicate devices, rather than AI performance metrics like sensitivity, specificity, or AUC.

Here's an analysis of the provided information concerning the device's acceptance criteria and the studies performed:

1. Acceptance Criteria and Reported Device Performance:

The document doesn't present a table with specific quantitative performance metrics as one would expect for an AI/ML device (e.g., accuracy, sensitivity, specificity). Instead, the acceptance criteria are met by demonstrating compliance with recognized medical device standards and showing substantial equivalence to predicate devices in terms of technology, intended use, and safety/effectiveness.

The reported "performance" is qualitative, focusing on whether the device meets regulatory and safety standards:

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

The document explicitly states "7. Clinical Tests: Not Applicable." This indicates that no clinical study involving human subjects or real patient data (test sets) was performed for this 510(k) submission to demonstrate performance in a clinical setting. The evaluation relied entirely on non-clinical tests (bench testing, engineering validation, adherence to standards).

Therefore, there is no sample size for a test set, nor specific data provenance (country of origin, retrospective/prospective) related to patient data. The "tests" mentioned are primarily engineering and compliance tests.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

Since no clinical tests or human reader studies were conducted as part of this submission, there is no information provided regarding experts establishing ground truth for a test set.

4. Adjudication Method for the Test Set:

Not applicable, as no clinical test set was used for performance evaluation that would require adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

Not applicable. The device is a diagnostic ultrasound system (hardware and general software features), not an AI-assisted diagnostic tool that would typically undergo MRMC studies to evaluate human reader improvement. The document does not mention any AI capabilities that assist human readers.

6. Standalone (Algorithm Only) Performance:

Not applicable. This is a medical device, not a standalone algorithm. The "performance" is inherent to the system's ability to acquire and display ultrasound images and perform basic measurements, which is evaluated through engineering and safety standards.

7. Type of Ground Truth Used:

For the evaluation described, the "ground truth" is established by:

• Compliance with recognized standards: The device's technical specifications and safety features are compared against established industry and regulatory standards (e.g., IEC, ISO).
• Substantial equivalence to predicate devices: The functionality, safety, and performance characteristics are determined to be similar enough to already-cleared devices, implying that if the predicate is safe and effective, so is the new device.
• Engineering validation and bench testing: Physical measurements and tests demonstrating that the device operates within specified parameters and does not pose undue risks (e.g., acoustic output, temperature, electrical safety).

8. Sample Size for the Training Set:

Not applicable. This is not an AI/ML device, so there is no training set in the machine learning sense. The device's "training" and validation are part of its design, manufacturing, and quality control processes to ensure it meets its specifications and regulatory requirements.

9. How the Ground Truth for the Training Set Was Established:

Not applicable, as there is no training set for an AI/ML model. The "ground truth" for the device's development and validation relies on engineering principles, scientific understanding of ultrasound physics, and established medical device safety and performance standards.

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