News | Ultrasound Women's Health | November 19, 2018

QView Medical Showcases QVCAD for ABUS Exams at RSNA 2018

Completes first joint installation of AI-based system for concurrent reading with Invenia ABUS from GE Healthcare

QView Medical Showcases QVCAD for ABUS Exams at RSNA 2018

November 19, 2018 – QView Medical will showcase QVCAD, the first U.S. Food and Drug Administration (FDA)-approved artificial intelligence (AI) computer-aided detection (CAD) system for concurrent reading of automated breast ultrasound (ABUS) exams, at the 104th Annual Radiological Society of North America (RSNA) meeting, Nov. 25-30, in Chicago. Being demonstrated for the first time since being approved, QVCAD reduces interpretation time of screening ABUS exams while maintaining diagnostic accuracy.  

In addition, QView successfully completed an installation of QVCAD at Northern Arizona Healthcare, the first joint installation with the Invenia ABUS system from GE Healthcare. Invenia ABUS is approved by the FDA for breast cancer screening as an adjunct to mammography for asymptomatic women with dense breasts. “We are excited to add the capability to offer ABUS as part of our comprehensive breast cancer screening program, which will help improve cancer detection for women with dense breasts. However, it was important that we implement with concurrent decision support from QVCAD to improve reading times while maintaining workflow and diagnostic confidence,” said Liz Palomino, MHA, RT, Northern Arizona Healthcare director of medical imaging, Flagstaff Medical Center, Sedona Medical Center, Verde Valley Medical Center and Verde Valley Medical Imaging Center.

Results from several clinical studies have shown that the addition of ABUS to screening mammography results in a significant increase in cancer detection in women with dense breasts. However, the interpretation of ABUS exams, with up to 2,000 images per case, is complex and time consuming, particularly for new users. According to results of a reader study published recently in the American Journal of Radiology, QVCAD reduced reader interpretation time by 33 percent while maintaining diagnostic accuracy.

Based on deep learning algorithms, the AI system is designed to detect suspicious areas of breast tissue with characteristics similar to breast lesions, and highlight suspicious area to distinguish potentially malignant lesions from normal breast tissue.  QVCAD is FDA-approved for use with ABUS systems and has received the CE mark for use with ABUS/ABVS systems.

To improve reader productivity, QVCAD provides synthetic 2-D images of all six volumetric datasets in a standard ABUS exam to provide an immediately visual overview of the case. The C-thru images, which are minimum intensity projections (MinIP), summarize each 3-D ABUS volume in a 2-D image. They bring attention to specific areas of interest by enhancement of radial spiculations and retraction patterns in coronal reconstructions, which are highly suggestive of breast cancer in ABUS. Users may select any CAD mark or area of interest on the C-thru image and the corresponding original ABUS images will be displayed, enabling users to efficiently review the entire ABUS case.

For more information: www.qviewmedical.com

Related Content

A 3-D ultrasound system provides an effective, noninvasive way to estimate blood flow that retains its accuracy across different equipment, operators and facilities, according to a study published in the journal Radiology.

Volume flow as a function of color flow gain (at a single testing site). For each row the color flow c-plane and the computed volume flow are shown as a function of color flow gain. The c-plane is shown for four representative gain levels, whereas the computed volume flow is shown for 12–17 steps across the available gain settings. Flow was computed with (solid circles on the graphs) and without (hollow circles on the graphs) partial volume correction. Partial volume correction accounts for pixels that are only partially inside the lumen. Therefore, high gain (ie, blooming) does not result in overestimation of flow. Systems 1 and 2 converge to true flow after the lumen is filled with color pixel. System 3 is nearly constant regarding gain and underestimates the flow by approximately 17%. Shown are mean flow estimated from 20 volumes, and the error bars show standard deviation. Image courtesy of the journal Radiology

News | Ultrasound Imaging | July 01, 2020
July 1, 2020 — A 3-D ultrasound
R2* maps of healthy control participants and participants with Alzheimer disease. R2* maps are windowed between 10 and 50 sec21. Differences in iron concentration in basal ganglia are too small to allow visual separation between patients with Alzheimer disease and control participants, and iron levels strongly depend on anatomic structure and subject age. Image courtesy of Radiological Society of North America

R2* maps of healthy control participants and participants with Alzheimer disease. R2* maps are windowed between 10 and 50 sec21. Differences in iron concentration in basal ganglia are too small to allow visual separation between patients with Alzheimer disease and control participants, and iron levels strongly depend on anatomic structure and subject age. Image courtesy of Radiological Society of North America

News | Magnetic Resonance Imaging (MRI) | July 01, 2020
July 1, 2020 — Researchers using magnetic...
Imaging Artificial Intelligence (AI) provider Qure.ai announced its first US FDA 510(k) clearance for its head CT scan product qER. The US Food and Drug Administration's decision covers four critical abnormalities identified by Qure.ai's emergency room product.
News | Artificial Intelligence | June 30, 2020
June 30, 2020 — Imaging Artificial Intelligence (AI) provider Qure.ai announced its first US FDA 510(k) clearance for
Sponsored Content | Videos | PACS | June 29, 2020
Kevin Borden, Vice President of Product, Healthcare IT for Konica Minolta, talks about Improving Access and Aiding Wo
Thoracic findings in a 15-year-old girl with Multisystem Inflammatory Syndrome in Children (MIS-C). (a) Chest radiograph on admission shows mild perihilar bronchial wall cuffing. (b) Chest radiograph on the third day of admission demonstrates extensive airspace opacification with a mid and lower zone predominance. (c, d) Contrast-enhanced axial CT chest of the thorax at day 3 shows areas of ground-glass opacification (GGO) and dense airspace consolidation with air bronchograms. (c) This conformed to a mosai

Thoracic findings in a 15-year-old girl with Multisystem Inflammatory Syndrome in Children (MIS-C). (a) Chest radiograph on admission shows mild perihilar bronchial wall cuffing. (b) Chest radiograph on the third day of admission demonstrates extensive airspace opacification with a mid and lower zone predominance. (c, d) Contrast-enhanced axial CT chest of the thorax at day 3 shows areas of ground-glass opacification (GGO) and dense airspace consolidation with air bronchograms. (c) This conformed to a mosaic pattern with a bronchocentric distribution to the GGO (white arrow, d) involving both central and peripheral lung parenchyma with pleural effusions (black small arrow, d). image courtesy of Radiological Society of North America

News | Coronavirus (COVID-19) | June 26, 2020
June 26, 2020 — In recent weeks, a multisystem hyperinflammatory condition has emerged in children in association wit
Universal digital operating system for surgery enables health tech companies and start-ups to accelerate, scale and grow

Stefan Vilsmeier, President and CEO of Brainlab Photo courtesy of Brainlab

News | Artificial Intelligence | June 26, 2020
June 26, 2020 — ...
n support of Mayo Clinic’s digital health and practice transformation initiatives, the Mayo Clinic Department of Laboratory Medicine and Pathology has initiated an enterprise-wide digital pathology implementation of the Sectra digital slide review and image storage and management system to enable digital pathology. 
News | Enterprise Imaging | June 26, 2020
June 26, 2020 —  In support of Mayo Clinic’s digital health