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The VPan (View Panoramic) Module is being added to the Technos™ ultrasound imaging system to provide panoramic, wide field-of-view images for easier orientation of anatomy and pathology.

The Technos™ ultrasound imaging system is intended to be used by a physician for diagnostic imaging in cardiac, abdominal, peripheral vascular, fetal, pediatric, small organ, neonatal cephalic, transrectal, transvaginal, intraoperative abdominal, intraoperative peripheral vascular, laparoscopic, adult cephalic, other-urological and musculoskeletal applications.

The VPan (View Panoramic) Module is being added to the Technos™ ultrasound imaging system to provide panoramic, wide field-of-view images for easier orientation of anatomy and pathology.

The provided 510(k) summary for the VPan Module to the TechnosMP Ultrasound Imaging System does not contain a detailed study proving the device meets specific acceptance criteria in the manner of a clinical trial with performance metrics. Instead, the submission focuses on demonstrating substantial equivalence to a previously cleared predicate device.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state acceptance criteria in terms of performance metrics (e.g., sensitivity, specificity, accuracy, or quantitative image quality scores). It relies on a comparison to a predicate device.

The "Comparison Chart for Substantial Equivalence" serves as the primary "acceptance criteria" by showing the new device functions similarly to the predicate.

Reported Device Performance: The document states that the VPan Module (the subject device) "provides panoramic, wide field-of-view images for easier orientation of anatomy and pathology." The implicit performance is that it performs these functions equivalently to the predicate device. No quantitative performance metrics are provided.

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

The document does not describe a test set or data provenance for a performance study. Clinical data is not typically required for 510(k) submissions that demonstrate substantial equivalence through comparison to predicate devices, especially for devices like this that are modifications or additions to existing ultrasound systems. The focus is on technical characteristics and intended use.

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

Not applicable. No ground truth establishment for a test set is described as there isn't a performance study evaluating diagnostic capabilities against a reference standard.

4. Adjudication Method for the Test Set

Not applicable. No test set or independent adjudication is described.

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 device is an ultrasound imaging module, not an AI or CAD (Computer-Aided Detection) system. Therefore, an MRMC study comparing human reader performance with and without AI assistance is not relevant to this submission.

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

Not applicable. This is an imaging module, not an algorithm, so standalone performance is not relevant in this context.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

Not applicable. There is no performance study described that would require establishing a ground truth. The submission relies on demonstrating the new module's technical similarity and equivalent intended use to the predicate device.

8. The Sample Size for the Training Set

Not applicable. This is an ultrasound imaging module, not a machine learning algorithm. Therefore, there is no "training set" in the context of AI/ML.

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

Not applicable, as there is no training set mentioned or implied.

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The AU6 (Technos/TechnosMP) ultrasound imaging system is intended to be used by a physician for diagnostic imaging in pediatric, small organ, neonatal cephalic, transrectal, transvaginal, intraoperative abdominal, intraoperative peripheral vascular, laparoscopic, adult cephalic and musculoskeletal applications.

Not Found

This is a 510(k) premarket notification for an ultrasound imaging system. Such notifications typically focus on establishing substantial equivalence to a legally marketed predicate device rather than presenting detailed standalone performance studies with specific acceptance criteria and outcome metrics like accuracy, sensitivity, or specificity.

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

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state quantitative acceptance criteria for image quality or diagnostic accuracy/performance. The "reported device performance" is essentially that it is substantially equivalent to the predicate devices and supports the specified imaging modes and clinical applications.

The tables within the document (e.g., "Comparison Chart for Substantial Equivalence", and tables for individual transducers) indicate capabilities and modes of operation for various clinical applications, rather than quantifiable performance metrics against acceptance criteria.

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

The document does not provide any information about a specific "test set" in the context of an accuracy study. This submission is a 510(k) for an ultrasound imaging system, which primarily demonstrates substantial equivalence through technical comparison and compliance with performance standards (e.g., electrical safety, acoustic output), rather than clinical performance studies against a gold standard for specific diagnostic tasks. The "data provenance" for a clinical test set is therefore unstated.

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

This information is not provided as there is no mention of a clinical performance study with a test set requiring expert-established ground truth.

4. Adjudication Method for the Test Set:

This information is not provided as there is no mention of a clinical performance study with a test set requiring adjudication.

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

The document does not report on an MRMC comparative effectiveness study, nor does it mention any effect size of human readers improving with AI vs. without AI assistance. This device is an ultrasound imaging system, not an AI-powered diagnostic aide in the context of this submission.

6. Standalone (Algorithm Only) Performance Study:

The document does not report on a standalone performance study. The device is an ultrasound imaging system, where its "performance" for 510(k) purposes is largely demonstrated through technical specifications and adherence to safety and performance standards.

7. Type of Ground Truth Used:

As no clinical performance study with a "test set" is described, there is no mention of the type of ground truth used (e.g., expert consensus, pathology, outcomes data).

8. Sample Size for the Training Set:

The document does not provide any information about a training set. This is not an AI/machine learning device in the context of this 510(k) submission.

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

This information is not provided as no training set is mentioned.

Summary of the Study (Based on the 510(k) provided):

The "study" presented in this 510(k) is a substantial equivalence comparison. The manufacturer, Biosound Esaote, sought clearance for the AU6 (Technos/Technos MP) Ultrasound Imaging System with the addition of 3D Imaging Mode and Musculoskeletal Indication.

The study primarily involves a technical comparison of the proposed device (AU6 Technos/Technos MP with 3D/Musculoskeletal additions) against predicate devices: the Esaote AU5 3D (K000931) for 3D capabilities and the Esaote AU6 Digital (Technos K990360) for general ultrasound capabilities.

The "acceptance criteria" are implicitly met if the new device demonstrates similar technological characteristics and performance specifications for the modes and applications it claims, and meets relevant electrical and ultrasound safety standards (IEC 60601-1 and Track 3 for Ultrasound safety). The performance is "reported" by affirming the device's capabilities match or are comparable to the predicates for the cleared indications and modes, while explicitly highlighting the new applications (Musculoskeletal Conventional, Musculoskeletal Superficial, and 3D imaging in certain contexts) as additions with these capabilities. The FDA's letter of clearance confirms that the device is "substantially equivalent" for the stated indications for use.

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The AU6 ultrasound imaging system is intended to be used by a physician for diagnostic imaging in cardiac, abdominal, peripheral vessel and fetal applications.
Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows:
Fetal, Abdominal, Intraoperative (specify) Abdominal, Intraoperative (specify) Peripheral vascular, Intraoperative Neurological, Pediatric, Small Organ (specify), Neonatal Cephalic, Adult Cephalic, Cardiac, Tranesophageal, Transrectal, Transvaginal, Transurethral, Intravascular, Peripheral Vascular, Laparoscopic, Musculo-skeletal Conventional, Musculo-skeletal Superficial, Other - Urological.
Small organs (specifically, thyroid, testicles and breast; Peripheral vascular to include Vein Mapping & Scierotherapy

Ultrasound Imaging System

The Biosound Esaote AU6 Diagnostic Ultrasound System is not an AI/ML device therefore the questions related to acceptance criteria and studies which are relevant to AI/ML devices are not applicable. But, it is a medical device and it has its own set of acceptance criteria and the methods used for the study. I have summarized this information below from the provided text.

Acceptance Criteria and Device Performance:

The device's performance is gauged by whether it can provide diagnostic ultrasound imaging or fluid flow analysis for various clinical applications, either as a "new indication" (N), "previously cleared by FDA" (P), or "added under Appendix E" (E). The specific modes of operation (A, B, M, PWD, CWD, Color Doppler CFM, Amplitude Doppler PD, Color Velocity Imaging) are listed for each clinical application.

Note: 'A' refers to Annular Array, but in the tables provided for indications, 'A' seems to represent an imaging mode, similar to B, M, PWD, CWD. Given the context of a diagnostic ultrasound system, 'A' likely refers to A-mode imaging, although it's not explicitly defined as such in the provided text. The tables use 'P' for previously cleared by FDA, 'N' for new indication, and 'E' for added under Appendix E.

Study Information (Based on a Traditional Medical Device Clearance):

1. Sample size used for the test set and the data provenance: Not applicable. For a traditional medical device like an ultrasound system, the "test set" in the AI/ML sense (where a predefined dataset is used to evaluate algorithm performance) isn't directly relevant. The evaluation of substantial equivalence typically involves engineering tests, phantom studies, and possibly clinical studies. The document does not specify particular clinical trial data or patient sample sizes. The data provenance is implied to be from the manufacturer (Biosound Esaote) based on their submission to the FDA. The nature of the submission (510(k)) indicates a comparison to a legally marketed predicate device, rather than a de novo submission requiring extensive clinical studies from scratch.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth as understood in AI/ML (e.g., expert annotations on images) is not the primary method for evaluating a medical imaging device for 510(k) clearance. The "ground truth" for a device like this would be established through performance specifications, adherence to standards, and comparison to the predicate device's established efficacy and safety.

3. Adjudication method for the test set: Not applicable. Adjudication methods are typically used in clinical trials or for complex image interpretation tasks, which are not detailed in this 510(k) summary for an ultrasound system.

4. If a multi-reader, multi-case (MRMC) comparative effectiveness study was done: Not applicable. MRMC studies are specific to evaluating the diagnostic accuracy of imaging interpretations, often when comparing new AI-assisted workflows to traditional human reading. This document describes a medical imaging device itself, not an AI/ML algorithm that assists human readers.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. The Biosound Esaote AU6 is a diagnostic ultrasound system, not an AI/ML algorithm, and as such, it operates with a human operator. Its performance is inherent to the system's ability to generate images, not as a standalone interpretive algorithm.

6. The type of ground truth used: For a traditional ultrasound system 510(k), the "ground truth" is established through:

   • Predicate Device Comparison: The primary method for 510(k) clearance is demonstrating substantial equivalence to a legally marketed predicate device (Esaote AU5, K980468 in this case). This means showing the new device is as safe and effective as the predicate.
   • Performance Specifications: The device must meet documented performance specifications for imaging modes, frequencies, transducer types, acoustic output, and other technical characteristics.
   • Safety Standards: Compliance with relevant electrical safety and biocompatibility standards.
   • Clinical Utility (Implied): The intended uses (cardiac, abdominal, peripheral vessel, fetal) are established categories for which ultrasound is a recognized diagnostic tool. The device is expected to perform within the established clinical utility of such systems.

7. The sample size for the training set: Not applicable. This is not an AI/ML device, so there is no "training set."

8. How the ground truth for the training set was established: Not applicable, as there is no training set for this type of device.

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