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The Uscan is for non-invasive imaging of the human body and is intended for the following applications: Abdominal. Musculoskeletal, Pediatric, Small Organ, and Peripheral Vessel. Users must have ultrasound training for abdominal, musculoskeletal, pediatric, small organ, and peripheral vessel imaging.

The Uscan can also be used to obtain an image of the bladder that is used to automatically determine bladder volume.

The Uscan is a hand-held, diagnostic ultrasound system with an on-screen display. Its purpose is to acquire ultrasound echo data and display it in B-Mode on an off-the-shelf display. Automated bladder volume measurements are supported.

Here's an analysis of the provided text to extract information about the acceptance criteria and the supporting study for the Uscan device.

Note: The provided FDA 510(k) summary focuses primarily on establishing substantial equivalence based on technological characteristics and adherence to recognized standards. It does not present a detailed clinical study demonstrating the device "meets acceptance criteria" in terms of clinical performance metrics (e.g., sensitivity, specificity, accuracy against a gold standard in a human population) against specific acceptance thresholds. Instead, it emphasizes bench testing for imaging performance and measurement accuracy, and conformance to regulatory standards.

Therefore, "acceptance criteria" here largely refer to the requirements for safe and effective operation based on engineering and regulatory standards, rather than clinical performance metrics. The "study" refers to the non-clinical testing performed.

Acceptance Criteria and Reported Device Performance

Study Details (Based on the provided text)

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

   • Test Set Sample Size: Not specified in terms of clinical cases or patient data. The document refers to "bench testing" of imaging and measurement accuracy. This implies a test set of physical phantoms, simulated data, or lab-based scenarios, not a human patient cohort.
   • Data Provenance: Not applicable for a clinical test set from human subjects since the testing described is non-clinical/bench testing.

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

   • Not applicable as the testing described is non-clinical bench testing, not a clinical study involving human expert interpretation. Ground truth for bench testing would be established by the physical properties of the phantoms or known parameters of the simulated data.

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

   • Not applicable, as this refers to a clinical study interpretation process, which is not detailed here.

4. 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 MRMC comparative effectiveness study is described in this document. The focus is on the device itself and its equivalence to predicate devices, not on human-AI augmented performance.

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

   • The "bench testing for imaging performance and measurement accuracy" represents a form of standalone testing, as it evaluates the device's technical capabilities (image quality, automated measurements like bladder volume) without human interpretation in a clinical setting mentioned. However, specific metrics (e.g., accuracy, precision) are not provided beyond stating substantial equivalence to predicate devices.

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

   • For the bench testing, the ground truth would likely be physical measurements from phantoms or known parameters of simulated datasets used to evaluate imaging performance and measurement accuracy. No clinical ground truth (like pathology or expert consensus on patient data) is mentioned for the testing described.

7. The sample size for the training set:

   • Not applicable. This document does not describe the development or training of any AI/ML components in the Uscan, but rather its regulatory clearance as a diagnostic ultrasound system. While automated bladder volume determination might imply some underlying algorithm, the training data and its size are not disclosed here.

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

   • Not applicable, as the training set details are not provided.

Summary of what the document implies about "meeting acceptance criteria":

The provided 510(k) summary primarily demonstrates that the Uscan device meets regulatory acceptance criteria by:

• Conforming to a comprehensive list of FDA-recognized international and national standards for medical electrical equipment, software, usability, risk management, biological evaluation, and acoustic output.
• Undergoing bench testing that showed its imaging performance and measurement accuracy to be "substantially equivalent" to predicate devices.
• Having verified risk mitigation and functioning as intended per verification and validation reports.

It does not provide details about specific clinical performance acceptance criteria (e.g., diagnostic accuracy thresholds like sensitivity/specificity for detecting certain conditions) or a clinical study demonstrating the device's ability to meet such criteria in a human population. The approval is based on substantial equivalence and compliance with engineering and safety standards.

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