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The Acclarix LX8 Diagnostic Ultrasound System is intended for use by a qualified physician or sonographer for ultrasound evaluation. Clinical applications include: Abdominal, Gynecology (including endovaginal), Obstetic, Cardiac, Small parts (Breast, Testes, Thyroid, etc.), Urology, Musculoskeletal, and Peripheral vascular, and Intra-operative.

The Edan Acclarix LX8 Ultrasound system consists of a main system along with associated transducers. The system circuitry generates an electronic voltage pulse, which is transmitted to the transducer. In the transducer, a piezo electric array converts the electronic pulse into an ultrasonic pressure wave. When coupled to the body, the pressure wave transmits through body tissues. The waves are then reflected within the body and detected by the transducer, which then converts back to an electrical signal. The Acclarix LX8 system then analyzes the returned signal to generate an image or conduct Doppler processing. The Acclarix LX8 system gives the operator the ability to measure anatomical structures, and offers analysis packages that provide information used by competent health care professionals to make a diagnosis. The system provides both touch screen and hard buttons for the User Interface.

The provided document is a 510(k) summary for the EDAN INSTRUMENTS, INC. Acclarix LX8 Diagnostic Ultrasound System. It outlines the device's indications for use and compares it to predicate devices to establish substantial equivalence. However, the document explicitly states that clinical testing was not required for this submission (Page 15, "Clinical test: Clinical testing is not required."). Therefore, the detailed information requested regarding acceptance criteria and studies proving the device meets those criteria for clinical performance is not available within this document.

The document focuses on non-clinical testing and benchmarking against predicate devices to demonstrate safety and effectiveness.

Here's a breakdown of the available information based on your request:

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

Since no clinical studies were performed, there are no specific clinical performance acceptance criteria or reported clinical performance metrics in this document. The "acceptance criteria" appear to be compliance with relevant safety and performance standards for ultrasound devices, which are met through non-clinical testing.

2. Sample size used for the test set and the data provenance:

• Test set sample size: Not applicable, as no clinical test set was used.
• Data provenance: Not applicable, as no clinical data was generated for the purpose of this submission. The testing was non-clinical (electrical safety, electromagnetic compatibility, acoustic output, biocompatibility) and based on engineering validation.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

Not applicable, as no clinical test set with human-established ground truth was used.

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

Not applicable, as no clinical test set requiring adjudication was used.

5. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done, and if so, what was the effect size of how much human readers improve with AI vs without AI assistance:

Not applicable. The device is a diagnostic ultrasound system, not an AI-powered image interpretation device, and no MRMC study was performed or required for this 510(k) submission.

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

Not applicable. The device is a diagnostic imaging system, not a standalone algorithm.

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

Not applicable. For the non-clinical tests conducted, the "ground truth" would be established by reference standards or engineering specifications.

8. The sample size for the training set:

Not applicable, as this is not an AI/Machine Learning device requiring a training set.

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

Not applicable, as this is not an AI/Machine Learning device requiring a training set.

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