AI-Based Mammography Triage Software Helps Dramatically Improve Interpretation Process
By MedImaging International staff writers Posted on 11 Oct 2021 |

An artificial intelligence (AI)-based mammography triage software is helping dramatically improve the interpretation process for healthcare providers.
In a new study, researchers at the Scripps Green Hospital (La Jolla, CA, USA) showed how the use of an AI-based computer-aided detection (CAD) and triage software suite improved the mammographic interpretation process at an imaging center and its partners. Mammographic results can be delayed for many reasons, including physician shortages. Many women experience anxiety waiting for their mammographic results, with 97% of women in one study reporting that immediate results would lower anxiety.
The AI software that aids in detection and triage of clinical concerns was first implemented in June 2019 at a single outpatient site utilizing 2D digital mammography. The AI software evaluated all imaging exams as soon as they were completed, triaging any suspicious findings into a sortable worklist and notifying the physicians. While integrating the AI tool into the imaging centers’ picture archiving and communication system was “unproblematic”, radiologist buy-in proved to be a challenge as physicians experienced fears of being replaced, distrust and hesitancy in learning the new approach.
The study showed that post the implementation of the AI tool, the average turnaround times declined from around 9.6 days based on 2019 data to 3.9 days in 2021. Among BI-RADS (Breast Imaging-Reporting and Data System) category 0 patients, the average turnaround times fell from 9.4 days (with a range of 1-33) to 4.7 days (0-22). Exams with suspicious findings were usually interpreted within one day, with fewer left for outside comparisons. There was also a decline of 71% in flags per examination when using AI from 2.26 per exam to 0.65, marking a “comparable and significant” reduction for both masses (down 72%) and calcifications (70%).
“Despite initial skepticism, a verbal survey of the interpreting radiologists performed two years after implementation showed universal preference for the AI-[computer-aided detection] compared with traditional CAD, the value of which has been questioned,” the researchers wrote. “Furthermore, the use of triage is now seen as the preferred way to manage their work lists,” indicating the “perception of greater ease” when reading batched mammograms.
Related Links:
Scripps Green Hospital
Latest Imaging IT News
- New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
- Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
- Artificial Intelligence (AI) Program Accurately Predicts Lung Cancer Risk from CT Images
- Image Management Platform Streamlines Treatment Plans
- AI-Based Technology for Ultrasound Image Analysis Receives FDA Approval
- AI Technology for Detecting Breast Cancer Receives CE Mark Approval
- Digital Pathology Software Improves Workflow Efficiency
- Patient-Centric Portal Facilitates Direct Imaging Access
- New Workstation Supports Customer-Driven Imaging Workflow
Channels
Radiography
view channel
World's Largest Class Single Crystal Diamond Radiation Detector Opens New Possibilities for Diagnostic Imaging
Diamonds possess ideal physical properties for radiation detection, such as exceptional thermal and chemical stability along with a quick response time. Made of carbon with an atomic number of six, diamonds... Read more
AI-Powered Imaging Technique Shows Promise in Evaluating Patients for PCI
Percutaneous coronary intervention (PCI), also known as coronary angioplasty, is a minimally invasive procedure where small metal tubes called stents are inserted into partially blocked coronary arteries... Read moreMRI
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 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