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The UltraGuide USG 2000sa system is indicated for enhancing the ultrasonic image of an interventional needle or needle-like rigid device, such as a biopsy needle or an aspiration needle, and for predicting its future path. The enhancement and prediction are presented on a computer monitor screen which also shows the image of a B-scan (or similar display) of a medical ultrasound imaging system.

The device is intended to be used in clinical applications and for anatomical structures where ultrasound is currently used for visualizing such procedures.

The UltraGuide USG 2000sa provides visual enhancement of the interventional needle by overlaying the image of the insertion device and its predicted future path on the ultrasound scan image of the internal organs, all displayed on the monitor of a personal computer.

The device uses magnetic transmitters and receivers, sold under the trade name "PC Birds," to determine the location and orientation of the interventional needle. These devices have been used on medical devices cleared by the FDA. The positions and orientations of the interventional device and the video of the US image, are transmitted to a Personal Computer, which makes the necessary calculations to provide the overlay of the video image and the interventional device.

Here's an analysis of the provided text regarding the acceptance criteria and study for the UltraGuide USG 2000sa device:

1. Table of Acceptance Criteria and Reported Device Performance

Important Note: The provided document is a 510(k) summary for a medical device cleared in 2002. At that time, explicit quantifiable acceptance criteria (e.g., specific accuracy metrics, sensitivity, specificity) for device performance as we often see in modern submissions were not always explicitly stated or required in the same way for "substantial equivalence" claims. The focus here is on demonstrating equivalence to a legally marketed predicate device.

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

No specific test set or sample size for a clinical study is mentioned. The submission states, "Since this system uses the same technology as the predicate device, a clinical test is not necessary." This indicates that no new clinical data was generated for the USG 2000sa for its 510(k) clearance.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

Not applicable, as no new clinical test set was used for the submission.

4. Adjudication Method for the Test Set

Not applicable, as no new clinical test set was used.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The submission explicitly states "a clinical test is not necessary."

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The device is described as enhancing the ultrasonic image and predicting the needle path for display on a computer monitor. This implies a human-in-the-loop interaction, where the user interprets the enhanced image. A standalone (algorithm-only) performance evaluation, separate from human interaction, is not indicated or discussed for this type of device. The clearance is based on the technology being equivalent to a predicate, not on a new standalone performance claim.

7. The Type of Ground Truth Used

No new ground truth from clinical data was established for the USG 2000sa's 510(k) clearance. The basis for safety and efficacy was the substantial equivalence to the predicate device, UltraGuide 1000. For the bench tests, the "ground truth" would have been established by engineering standards for electrical safety and electromagnetic compatibility rather than medical ground truth.

8. The Sample Size for the Training Set

Not applicable. This device is not an AI/ML algorithm that typically requires a large training set in the modern sense. Its function relies on established physical principles of magnetic tracking and visual overlay, rather than learning from a large dataset.

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

Not applicable, as there is no mention or implication of a training set for an AI/ML model.

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This modification has no effect on intended use of the HP ultrasound systems.

The modification addressed in this submission is a change from analog to digital circuit technology for the front end of the HP ultrasound imaging systems listed above.

This document is a 510(k) summary for a modification to an existing ultrasound imaging system. It focuses on demonstrating substantial equivalence to predicate devices for a change from analog to digital circuit technology in the front end. Therefore, it does not contain the detailed performance study information typically found in submissions for novel devices or those requiring clinical efficacy studies with specific acceptance criteria.

Based on the provided text, here's what can be extracted and what cannot:

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

The document does not provide a table of acceptance criteria and reported device performance in the way typically expected for a new device's clinical performance. Since this is a modification to an existing device, the "acceptance criteria" discussed are primarily related to safety, compliance with medical device standards, and functional equivalence to predicate devices.

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

Not applicable. This submission is for a technological modification and primarily relies on engineering validation, safety testing, and comparison to predicate devices, not a clinical "test set" with a specific sample size of patient data. There is no mention of patient data being used for this specific filing.

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 a clinical test set is not discussed as this is a technological modification submission.

4. Adjudication method for the test set

Not applicable. There is no mention of a clinical test set or 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

Not applicable. This document pertains to an ultrasound imaging system and does not mention AI or MRMC studies.

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

Not applicable. This is not an algorithm-only device; it's a hardware modification to an imaging system.

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

Not applicable. Ground truth in the context of clinical data is not discussed. For this submission, the "ground truth" for the claims of safety and equivalence would be the established safety standards, the validated performance specifications of the device, and the characteristics of the predicate devices.

8. The sample size for the training set

Not applicable. There is no mention of a training set as this is not a machine learning or AI-driven device.

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

Not applicable (as above).

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This modification expands the intended use statement for the HP SONOS 100CF Ultrasound Imaging System to include obstetrics and gynecology applications.

This 510(k) submission is to add an endovaginal transducer and a new EV(EndoVaginal)/Pelvic study type to the HP SONOS 100CF Ultrasound Imaging System.

This document is a 510(k) summary for a modification to an ultrasound imaging system. It focuses on demonstrating substantial equivalence to predicate devices for regulatory approval, rather than providing a detailed study that proves the device meets specific acceptance criteria in the manner typically seen for novel AI/software devices. Therefore, much of the requested information cannot be found in this summary.

Here's a breakdown of what can and cannot be extracted:

• Acceptance Criteria and Reported Device Performance: This document does not present specific quantitative acceptance criteria or reported device performance in the form of a table for clinical effectiveness. The acceptance is based on compliance to general safety standards and substantial equivalence to predicate devices.
• Sample size used for the test set and the data provenance: Not applicable. There is no mention of a clinical test set with specific data provenance for performance evaluation.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for clinical performance evaluation is not discussed.
• Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
• 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 summary predates common AI integration in medical devices and does not describe such a study. The device is an ultrasound imaging system, not an AI-powered diagnostic tool.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI algorithm.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable for clinical performance. The "ground truth" here is compliance with safety standards and functional equivalence to predicate devices.
• The sample size for the training set: Not applicable. This is not a machine learning device that requires a training set.
• How the ground truth for the training set was established: Not applicable.

Based on the provided 510(k) summary, here's what can be stated:

1. Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicit and revolve around:

2. Sample size used for the test set and the data provenance: Not applicable as this submission relies on compliance to standards, predicate device comparison, and internal validation, not a clinical performance test set with retrospective/prospective data or specific data provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.

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: No, an MRMC comparative effectiveness study was not done. The device is an ultrasound imaging system, and this submission predates the widespread use of AI in medical imaging.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This device is an imaging system, not a standalone algorithm.

7. The type of ground truth used:
* Safety: Compliance with established medical device safety standards (IEC 601, UL 544).
* Functionality/Effectiveness: Verification that performance specifications are met through software validation, and comparison to the known performance of predicate devices.
* Acoustic Output: Measured acoustic output data.

8. The sample size for the training set: Not applicable. This is not a machine learning device that requires a training set.

9. How the ground truth for the training set was established: Not applicable.

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