Novel Breast Cancer Screening Technology Could Offer Superior Alternative to Mammogram
By MedImaging International staff writers Posted on 24 Oct 2024 |

Breast cancer represents 15.5% of new cancer cases and 7% of cancer-related deaths in the United States. Approximately 13.1% of women will be diagnosed with breast cancer during their lifetime. A significant number of women of screening age who do not undergo regular screenings cite the discomfort associated with compression as a reason for avoiding mammograms. This highlights the importance of advancements in screening technology. Researchers are now testing a novel imaging technique for breast cancer detection that they hope will eventually serve as a better alternative to the traditional mammogram.
Researchers at the University of Arizona Health Sciences (Tucson, AZ, USA) are exploring non-compression computed tomography (CT) technology that could potentially detect more breast cancers while improving comfort and reducing radiation exposure. Their advanced breast CT system eliminates the need for physical compression of the breast and addresses tissue overlap issues. Instead, it generates high-resolution 3-D images using detailed CT scans. The researchers believe this method could significantly improve early cancer detection and diagnosis, particularly for the subset of women with dense breast tissue, which contains more fibrous and glandular components that can obscure tumors.
The research team plans to refine their non-compression CT scanner prototype, which has already been tested with 92 women. They will concentrate on advanced image reconstruction techniques and recruit an additional 600 volunteers to further evaluate the breast CT system, comparing its effectiveness with 3-D mammography, the current standard for breast cancer detection. The implications of the team’s research extend beyond breast imaging and may eventually be applied to enhance radiation therapy, surgical planning, and detailed imaging of other major organ systems.
“With our technology, there is a hole on the table and the woman lies prone with the breast through the hole. The tube spins around 360 degrees,” said Srinivasan Vedantham, PhD, a professor in the U of A College of Medicine – Tucson’s Department of Medical Imaging and member of the U of A Cancer Center. “There is nothing in contact with the breast — no compression, nothing. You lie face down, and it takes 10 seconds to image each breast. The advantage of breast CT is we have a whole 3-D image. It would have better sensitivity in detecting breast cancer, particularly for women with dense breasts. Our goal is to enhance breast cancer screening technology to improve early detection and outcomes for patients.”
Related Links:
University of Arizona Health Sciences
Latest General/Advanced Imaging News
- AI-Powered Imaging System Improves Lung Cancer Diagnosis
- AI Model Significantly Enhances Low-Dose CT Capabilities
- Ultra-Low Dose CT Aids Pneumonia Diagnosis in Immunocompromised Patients
- AI Reduces CT Lung Cancer Screening Workload by Almost 80%
- Cutting-Edge Technology Combines Light and Sound for Real-Time Stroke Monitoring
- AI System Detects Subtle Changes in Series of Medical Images Over Time
- New CT Scan Technique to Improve Prognosis and Treatments for Head and Neck Cancers
- World’s First Mobile Whole-Body CT Scanner to Provide Diagnostics at POC
- Comprehensive CT Scans Could Identify Atherosclerosis Among Lung Cancer Patients
- AI Improves Detection of Colorectal Cancer on Routine Abdominopelvic CT Scans
- Super-Resolution Technology Enhances Clinical Bone Imaging to Predict Osteoporotic Fracture Risk
- AI-Powered Abdomen Map Enables Early Cancer Detection
- Deep Learning Model Detects Lung Tumors on CT
- AI Predicts Cardiovascular Risk from CT Scans
- Deep Learning Based Algorithms Improve Tumor Detection in PET/CT Scans
- New Technology Provides Coronary Artery Calcification Scoring on Ungated Chest CT Scans
Channels
MRI
view channel
AI Tool Predicts Relapse of Pediatric Brain Cancer from Brain MRI Scans
Many pediatric gliomas are treatable with surgery alone, but relapses can be catastrophic. Predicting which patients are at risk for recurrence remains challenging, leading to frequent follow-ups with... Read more
AI Tool Tracks Effectiveness of Multiple Sclerosis Treatments Using Brain MRI Scans
Multiple sclerosis (MS) is a condition in which the immune system attacks the brain and spinal cord, leading to impairments in movement, sensation, and cognition. Magnetic Resonance Imaging (MRI) markers... Read more
Ultra-Powerful MRI Scans Enable Life-Changing Surgery in Treatment-Resistant Epileptic Patients
Approximately 360,000 individuals in the UK suffer from focal epilepsy, a condition in which seizures spread from one part of the brain. Around a third of these patients experience persistent seizures... Read moreUltrasound
view channel.jpeg)
AI-Powered Lung Ultrasound Outperforms Human Experts in Tuberculosis Diagnosis
Despite global declines in tuberculosis (TB) rates in previous years, the incidence of TB rose by 4.6% from 2020 to 2023. Early screening and rapid diagnosis are essential elements of the World Health... Read more
AI Identifies Heart Valve Disease from Common Imaging Test
Tricuspid regurgitation is a condition where the heart's tricuspid valve does not close completely during contraction, leading to backward blood flow, which can result in heart failure. A new artificial... Read moreNuclear Medicine
view channel
Novel Radiolabeled Antibody Improves Diagnosis and Treatment of Solid Tumors
Interleukin-13 receptor α-2 (IL13Rα2) is a cell surface receptor commonly found in solid tumors such as glioblastoma, melanoma, and breast cancer. It is minimally expressed in normal tissues, making it... Read more
Novel PET Imaging Approach Offers Never-Before-Seen View of Neuroinflammation
COX-2, an enzyme that plays a key role in brain inflammation, can be significantly upregulated by inflammatory stimuli and neuroexcitation. Researchers suggest that COX-2 density in the brain could serve... Read moreGeneral/Advanced Imaging
view channel
AI-Powered Imaging System Improves Lung Cancer Diagnosis
Given the need to detect lung cancer at earlier stages, there is an increasing need for a definitive diagnostic pathway for patients with suspicious pulmonary nodules. However, obtaining tissue samples... Read more
AI Model Significantly Enhances Low-Dose CT Capabilities
Lung cancer remains one of the most challenging diseases, making early diagnosis vital for effective treatment. Fortunately, advancements in artificial intelligence (AI) are revolutionizing lung cancer... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read moreIndustry News
view channel
GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
GE HealthCare (Chicago, IL, USA) has entered into a collaboration with NVIDIA (Santa Clara, CA, USA), expanding the existing relationship between the two companies to focus on pioneering innovation in... Read more
Patient-Specific 3D-Printed Phantoms Transform CT Imaging
New research has highlighted how anatomically precise, patient-specific 3D-printed phantoms are proving to be scalable, cost-effective, and efficient tools in the development of new CT scan algorithms... Read more
Siemens and Sectra Collaborate on Enhancing Radiology Workflows
Siemens Healthineers (Forchheim, Germany) and Sectra (Linköping, Sweden) have entered into a collaboration aimed at enhancing radiologists' diagnostic capabilities and, in turn, improving patient care... Read more