Artificial intelligence has become one of the most discussed topics in medical imaging. For QView Medical, however, AI for automated breast ultrasound is not a new concept or an emerging product category. It is a field we have helped build.
QView Medical developed QVCAD®, an FDA-approved artificial intelligence system for concurrent reading of automated breast ultrasound exams. The system is designed to assist radiologists as they review three-dimensional ABUS images and search for mammographically occult lesions in women with dense breast tissue.
That distinction matters. Effective clinical AI requires more than an algorithm. It requires carefully developed technology, regulatory review, clinical validation, workflow integration, reader training, and experience across real-world breast imaging environments.
QView has spent years bringing those elements together.
Why AI for Automated Breast Ultrasound Matters
Automated breast ultrasound, commonly called ABUS, creates three-dimensional image volumes of the breast. It is used as an adjunct to mammography for screening certain women with dense breast tissue.
Dense tissue presents an important imaging challenge because both dense breast tissue and many cancers can appear white on a mammogram. This masking effect can make some cancers more difficult to see. Since September 2024, facilities operating under the Mammography Quality Standards Act have been required to include breast-density information in patient mammography communications, bringing greater national attention to breast density and conversations about supplemental screening.
ABUS gives the interpreting physician another way to evaluate dense breast tissue. Unlike handheld ultrasound, automated breast ultrasound acquires standardized volumetric datasets that can be reviewed after the examination. A typical ABUS study can contain a substantial number of images across multiple views and planes.
That volume of information can create a practical challenge: radiologists must review the entire examination carefully without allowing the complexity of the dataset to slow adoption or disrupt workflow.
This is where purpose-built ABUS AI can help.
What Is QVCAD?
QVCAD is QView Medical’s FDA-approved computer-aided detection system for automated breast ultrasound. It is intended to aid the reader during screening procedures by searching ABUS images for mammographically occult lesions in regions not already known to contain suspicious findings.
QVCAD processes the three-dimensional ABUS dataset and presents its output concurrently with the original images. The system can highlight areas that may warrant the radiologist’s attention and provide navigation support during review.
The radiologist remains responsible for interpreting the complete examination and making the final assessment. QVCAD does not replace the physician, and its indicators are not intended to provide independent diagnostic characterization of a suspicious finding.
This human-plus-AI model has guided QView’s work from the beginning: use artificial intelligence to support the radiologist’s search and navigation while preserving clinical judgment at the center of care.
How QVCAD Supports ABUS Interpretation
QVCAD was developed specifically for the structure and demands of automated breast ultrasound—not retrofitted from a general-purpose imaging application.
The system analyzes ABUS image data for patterns associated with suspicious breast lesions. Its output includes navigation images and computer-generated marks that help direct the reader to corresponding locations in the original ABUS images.
1. Navigating a large three-dimensional examination
An ABUS exam contains far more information than a small set of static images. QVCAD provides a visual roadmap that helps the radiologist move between its AI-generated output and the source ABUS images.
2. Drawing attention to potential areas of interest
The software identifies and marks certain regions with characteristics that may be associated with breast lesions. These marks function as decision support—not as a diagnosis—and must be evaluated by the radiologist in the context of the complete examination.
3. Supporting an efficient reading workflow
Workflow is essential to the successful adoption of supplemental screening. Peer-reviewed reader studies have evaluated computer-aided detection for ABUS and found improvements in reading efficiency while preserving reader performance. The precise results depend on the study design, readers, and system configuration, but the broader lesson is consistent: AI has the greatest value when it is designed around the radiologist’s actual workflow.
4. Helping programs build experience with ABUS
ABUS requires readers to become comfortable with volumetric breast ultrasound, multiplanar review, and the coronal plane. AI-supported navigation can be one component of a broader implementation program that also includes education, case review, training, and quality assurance.
The Difference Between AI Assistance and Autonomous Diagnosis
As interest in medical AI grows, precise language is important.
QVCAD is a physician-support tool. It does not independently screen a patient, interpret an examination, or issue a final diagnosis. Its role is to assist a qualified reader in reviewing ABUS images within the product’s approved indications.
Responsible implementation therefore includes:
- Appropriate patient selection
- High-quality ABUS acquisition
- Review by a trained interpreting physician
- Use of QVCAD according to its approved labeling
- Clear clinical pathways for follow-up when additional evaluation is recommended
- Ongoing attention to reader performance and program quality
AI should strengthen a clinical system, not become a substitute for one.
From FDA Approval to Real-World ABUS Programs
The FDA approved the original QVCAD System in 2016. QView technology has since been deployed across more than 100 locations, including hospital systems, breast imaging programs, and emerging screening models. These installations demonstrate how AI for dense breast screening can support different clinical environments when paired with appropriate technology, trained readers, and follow-up infrastructure.
One important installation is Eve Wellness, QView Medical’s direct-to-patient screening partner. Eve uses automated breast ultrasound with QVCAD AI and physician interpretation to make supplemental breast screening more accessible in a patient-centered environment.
The partnership demonstrates a larger point: innovation in breast imaging is not only about developing better technology. It is also about finding responsible ways to bring that technology closer to the people who may benefit from it.
Eve’s model does not change QVCAD’s intended role or eliminate the need for clinical oversight. It shows how an established ABUS platform, FDA-approved AI, trained acquisition personnel, physician interpretation, and defined follow-up pathways can be brought together in a new care setting.
QView Medical’s Experience in Breast Imaging AI
QView’s leadership is grounded in more than a single product.
The QView team brings decades of experience spanning computer-aided detection for mammography, the development and adoption of automated breast ultrasound, and artificial intelligence for ABUS interpretation. This continuity gives QView a practical understanding of the entire imaging pathway—from acquisition and image quality to interpretation, workflow, and clinical adoption.
It also shapes how we think about AI.
The best medical-imaging technology is not necessarily the system with the loudest launch. It is the system that has been clinically evaluated, integrated into practice, and designed to help physicians work confidently and efficiently.
QView has been advancing that work for years.
What Imaging Leaders Should Consider When Evaluating ABUS AI
Hospitals and imaging centers considering an AI-supported automated breast ultrasound program should look beyond the phrase “powered by AI.” Important questions include:
- Is the technology authorized for the intended clinical use? Review the exact FDA indication rather than relying on a broad marketing description.
- Was the AI designed specifically for ABUS? Three-dimensional automated breast ultrasound has different workflow and image-review requirements than handheld ultrasound or mammography.
- How does the output fit into the reader’s workflow? Useful AI should help the radiologist navigate the examination without creating unnecessary complexity.
- What clinical evidence supports the system? Evaluate peer-reviewed studies, regulatory documentation, and reader-performance data.
- What training and implementation support are available? Technology alone does not build a successful screening program.
- How will positive or indeterminate findings be managed? Every supplemental screening model needs a reliable clinical follow-up pathway.
These questions help separate meaningful clinical decision support from generic AI positioning.
The Future of AI and Automated Breast Ultrasound
Awareness of breast density is increasing. Demand for more personalized screening options is growing. At the same time, imaging organizations face continuing pressure to improve access, maintain quality, and use radiologist time effectively.
Automated breast ultrasound with AI will play an important role in that future—but leadership in this space will require more than entering the market at the right moment.
It will require regulatory discipline, clinical evidence, technical expertise, strong partnerships, and sustained experience in real-world care.
QView Medical helped establish AI for automated breast ultrasound before breast-imaging AI became a crowded conversation. We continue to advance the field by supporting radiologists, imaging providers, and innovative screening partners with technology built specifically for ABUS.
Interested in bringing AI-supported ABUS to your organization? Contact QView Medical to discuss QVCAD, clinical workflow, and implementation.
Frequently Asked Questions
What is AI for automated breast ultrasound?
AI for automated breast ultrasound analyzes three-dimensional ABUS images and provides decision support to a qualified interpreting physician. Depending on the authorized product, this may include marks or navigation tools that call attention to areas for review.
What is QVCAD?
QVCAD is QView Medical’s FDA-approved computer-aided detection system. It assists radiologists during screening procedures by searching ABUS images for mammographically occult lesions within its approved indication.
Does QVCAD replace a radiologist?
No. QVCAD is an aid to the reader. A qualified physician reviews the complete ABUS examination and makes the final clinical assessment.
How can an imaging center implement ABUS with AI?
Implementation typically requires an appropriate ABUS acquisition system, trained personnel, qualified interpreting physicians, workflow integration, AI used according to its approved labeling, and established pathways for diagnostic follow-up.