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Velacur is intended to provide estimates of tissue stiffness generated from shear wave speed measurements (40-70 Hz) and coefficient of attenuation. The device is indicated to non-invasively determine liver tissue stiffness and attenuation. These are meant to be used in conjunction with other clinical indicators in order to assist in clinical management of patients with liver disease. The device is intended to be used in a clinical setting and by appropriately trained medical professionals.

Velacur is a portable device intended to non-invasively measure the stiffness and attenuation of the liver via measurement of liver tissue shear modulus and ultrasound attenuation. This is done by measuring the wavelength or wave speed of mechanically created shear waves within the organ of the patient. Attenuation is measured directly via the loss in power of the ultrasound beam. The device is designed to be used at the point of care, in clinics and hospitals. The device is used by a medical profession, an employee of the clinic/hospital. The activation unit is placed under the patient, while lying supine on an exam bed. The activation unit vibrates at frequencies 40, 50, and 60 Hz causing shear waves within the liver of the patient. The ultrasound transducer is placed on the patient's skin, over the intercostal space, and is used to take volumetric scans of the liver while shear waves are occurring. The device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue. From the scan data, the device calculates tissue stiffness and attenuation.

The provided document is a 510(k) premarket notification summary for the Velacur device, which is an ultrasound elastography system. The document focuses on demonstrating substantial equivalence to a predicate device, specifically regarding algorithmic changes for elasticity and attenuation calculations.

Here's an analysis based on the provided text, addressing your questions:

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

Note: The document states for elasticity that "Bland-Altman plots show that no value falls outside the 1.96STD lines." This is a common method for assessing agreement and implies good performance, but specific numerical criteria for the 1.96STD ranges are not provided as "acceptance criteria." The explicit acceptance criteria listed are for bias and precision.

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

The testing described is non-clinical bench testing performed on phantoms (materials with known physical properties simulating tissue).

• Sample Size:
  • Elasticity: "4 phantoms of various elasticities" were used for homogeneous elasticity testing. For the "boundary-less" phantom, it implies a single phantom of that type.
  • Attenuation: "three attenuation phantoms" were used.
• Data Provenance: The data is from bench testing in a lab setting, not from human subjects. The location of the testing is not specified beyond "Sonic Incytes" (which is based in Vancouver, Canada), but this is not human data with geographical or retrospective/prospective distinctions.

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 section is not applicable as the ground truth was established using physical phantoms with known properties. The "Magnetic Resonance Elasticity (MRE)" measurements are referred to for elasticity validation, but this refers to a different measurement technique for phantom properties, not human expert consensus.

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

This is not applicable as the ground truth was established by phantom specifications and MRE measurements, not by human expert review that would require adjudication.

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

No, an MRMC comparative effectiveness study was not conducted. The document explicitly states: "No animal or clinical performance was performed." This submission focuses on validating algorithmic changes through bench testing against phantoms, not through human-in-the-loop clinical studies.

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

Yes, in a sense. The "performance data" presented is the algorithm's performance when processing data from phantoms, validated against the known physical properties of those phantoms or readings from alternative methods (like MRE). While the device still has human operation (e.g., placing the transducer), the validation itself pertains to the accuracy of the algorithm's output (stiffness and attenuation values) from the acquired phantom data.

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

The ground truth used was phantom specifications and measurements from other established physical measurement techniques (Magnetic Resonance Elasticity - MRE).

8. The sample size for the training set

The document does not provide information on the training set sample size. This submission focuses on the validation of algorithmic changes, implying the algorithms were already developed. Furthermore, as this is a 510(k) for an updated algorithm in an existing device, details of the original training data (if any was used for the initial algorithm development) are not typically required for this type of submission unless new machine learning models are being introduced for new functionalities that would require it.

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

The document does not provide information on how the ground truth for the training set (if any) was established. As noted in point 8, the focus is on the validation of algorithmic changes, not on the developmental process of the original algorithms.

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