Search Results

The Breast Volume Navigator (BVN) is an add-on accessory for existing ultrasound imaging systems, and is intended to control position and movement of ultrasound transducers for the systematic acquisition of 2 dimensional image slices throughout a volume of interest. The BVN is intended to acquire, and retrieve digital ultrasound images for computerized 3-dimensional image processing.

The BVN will allow exporting to any third party application that has the appropriate level of DICOM compliance.

The BVN is intended as a general purpose digital 3D breast ultrasound image processing tool for radiology and surgery.

The BVN is indicated for use as an adjunct to mammography for B-mode ultrasonic imaging of a patient's breast when used with an automatic scanning linear array transducer.

The device is not intended to be used as a replacement for screening mammography.

The Breast Volume Navigator (BVN) System comprises hardware components and a software element, including the following components: a magnetic position tracking device, sensor attaching pieces used to attach the magnetic sensors to the skin and ultrasound probe, a central control unit, and software for controlling the system, collecting and processing images and positional data, and performing automated annotation.

The Breast Volume Navigator (BVN) has a touch-screen user interface and a push-button for power on the system. The User Interface can be placed on a stand next to the examination table for ease of use and ergonomic adaptation.

The BVN has a USB port available for transferring data files via USB Memory Stick. The BVN has an Ethernet port for connection to a PACS system, using DICOM. The BVN has a VGA/DVI Input Ports for capturing images from an ultrasound imaging scanner.

The Breast Volume Navigator (BVN) System receives ultrasound DICOM images from the US machine via the network connection and telemetry data from a position tracking system.

The BVN automatically detects when the image is being frozen on the US machine and takes a snapshot of the telemetry data at that time. Later, when the BVN receives the DICOM image, it associates the telemetry data to the image from the time when the image was frozen on the US machine.

The customer's existing ultrasound probe securely attaches to the BVN probe sensor. During a scan, the operator applies constant pressure to the transducer against the patient's breast tissue and can rotate the transducer (pitch and roll) to accommodate for the physical characteristics of the breast.

Exam data is subsequently reviewed on standard radiological viewing stations. Any lesions or anomalies discovered during the review process can be evaluated using the localization and measurement tools included in the software.

The document provides information on the Breast Volume Navigator (BVN), a device intended to assist with 3D breast ultrasound image processing.

Here's an analysis of the acceptance criteria and the study data provided:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance for Test Set

• Sample Size for Test Set: The document explicitly states "9 test locations in 4 layers" for the design validation tests. This refers to 36 distinct points (9 locations x 4 layers) on a test phantom where measurements were taken.
• Data Provenance: The testing was conducted "in-house by trained personnel in a simulated work-environment using phantoms." This indicates a prospective and controlled laboratory setting using simulated data (phantoms) rather than human patient data. There is no mention of country of origin as it was a simulated environment.

3. Number of Experts and Qualifications for Ground Truth (Test Set)

The document does not explicitly state the number of experts or their qualifications for establishing the ground truth for the test set. Given that the testing was performed on a phantom in a simulated environment, the "ground truth" for distance and angle measurements would likely be derived from the known physical specifications of the phantom and the calibrated measurement tools used, rather than expert consensus on medical images.

4. Adjudication Method (Test Set)

The document does not specify an adjudication method. Since the testing was conducted on a phantom with known physical properties, the ground truth would be objectively verifiable through the phantom's design and measurement instruments, not through clinical adjudication.

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

There is no indication of a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, or any comparison of human readers with vs. without AI assistance. The study focuses purely on the device's technical performance with phantoms.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone performance study was conducted. The "Performance, Verification and Validation testing" and "DESIGN VALIDATION TESTS - NON-CLINICAL TESTING" sections describe tests performed on the device (Breast Volume Navigator system) in a simulated environment using phantoms, without human intervention for interpretation of the results from the device itself. The device is assessed for its ability to accurately measure distances and angles of targets on the phantom.

7. Type of Ground Truth Used (Test Set)

The ground truth used for the test set was based on the known physical dimensions and configurations of a test phantom. This is a form of engineered or objective ground truth, as opposed to expert consensus, pathology, or outcomes data from human subjects.

8. Sample Size for Training Set

The document does not provide any information regarding a training set sample size. The tests described are purely performance verification and validation against design specifications using simulated data, not an AI or machine learning model that would require a training set.

9. How Ground Truth for Training Set Was Established

Since no training set is mentioned or implied by the type of device and testing described, there is no information on how ground truth for a training set was established. The BVN appears to be a hardware/software system for navigation and 3D data acquisition/processing, not a diagnostic AI algorithm that learns from data.

Ask a specific question about this device