Download Mobile App

Breast Imaging Reporting Tools and Management System Selected for Telemedicine Services

By MedImaging International staff writers
Posted on 17 May 2015

Image: Ikonopedia Reporting Tool (Photo courtesy of Ikonopedia).

BelleBridge (Shelton, CT, USA) has selected Ikonopedia (Dallas, TX, USA) to provide breast imaging reporting tools, and a new US Mammography Quality Standards Act (MQSA) management system, for interpretations of breast screening and diagnostic examinations.

BelleBridge provides remote telemedicine diagnostic and interpretation services for screening and diagnostic mammography, breast ultrasound and Magnetic Resonance Imaging (MRI). The Ikonopedia software tool enables image-based breast-study interpretation and reporting, and can interface with various Radiology Picture Archiving and Communication System (PACS), and Information Systems. Ikonopedia also includes screening MRI, diagnostic MRI, diagnostic ultrasound, and biopsy functionality.

The Ikonopedia tool is designed to optimize the breast imaging workflow, and will enable BelleBridge radiologists to provide more accurate structured reports to their clients, faster than before. The reports are fully BI-RADS language compliant. The new management system is MQSA compliant, and can manage all patient tracking and communications, such as calls, letters, and mail, based on user-defined protocols.

Elmar A. Davé, MBA, COO, BelleBridge, said, "While breast imaging technology has made tremendous advances over the past several years with digital mammography, tomosynthesis and automated breast ultrasound, the true lynchpin to quality breast care is access to dedicated breast imagers. Ikonopedia is a perfect partner for improving breast care, offering breast specific reporting tools, risk assessment software and MQSA tracking capabilities that provide tremendous workflow and efficiency benefits that enable us to drive access to high quality breast imaging through the industry's first true breast telehealth service."

Related Links:
Ikonopedia
BelleBridge

Visit expo >

Digital Radiography System (Ceiling Free)

Digix CF Series

MRI System

nanoScan MRI 3T/7T

Pocket Fetal Doppler

CONTEC10C/CL

Ultrasound Table

Women’s Ultrasound EA Table

Latest Imaging IT News

Channels

Radiography

view channel

Images in a 75-year-old woman who underwent routine screening mammography in 2022. Left mediolateral oblique views shown from prior screening mammograms: (A) 2015, (B) 2018, (C) 2019, and (D) 2021. In (E) 2022, a new mass developed in the left breast at the 6-o’clock position (arrow), with a (F) corresponding irregular mass at US (arrow). Subsequent US-guided core needle biopsy yielded invasive ductal carcinoma, grade 2. The deep learning 5-year risk scores gradually increased from 2.0 (2015) to 2.1 (2018), 3.4 (2019), 3.6 (2021), and 15.3 (2022). CMFN = centimeters from nipple, LT = left, TRANS = transverse (Photo courtesy of Radiological Society of North America)

AI Tool Predicts Five-Year Breast Cancer Risk from Mammograms

Breast cancer risk assessment during routine screening is difficult because many women who develop the disease have no known genetic mutations or family history. Static risk tools provide limited discrimination... Read more

Image: Screening mammograms and artificial intelligence (AI) score changes over time in two individuals with screen-detected cancer. Full-field digital mammograms show craniocaudal (top) and mediolateral (bottom) views of the left and right breast (Photo courtesy of Radiological Society of North America)

AI Mammography Tools Detect Early Breast Cancer Signs Years Before Diagnosis

Breast cancer screening aims to detect tumors before symptoms develop, but subtle mammographic changes can appear years before diagnosis and may be missed during routine reads. Delayed detection can lead... Read more

$Image: Kyushu University researchers use Dynamic Chest Radiography (DCR) to evaluate the severity of Pulmonary Regurgitation (PR), a common complication after treatment of the congenital heart disease Tetralogy of Fallot. The analysis only requires the patient to hold their breath for seven seconds for a sequence of images of their heart to be taken. The images are then analyzed and extracted into a waveform that can show the severity of PR. The new technique\\\'s detection accuracy of severe PR is 93%, with a sensitivity of 93% and a specificity of 94%. (Photo courtesty of Kyushu University/Yuzo Yamasaki)$

Rapid X-Ray Test Quantifies Pulmonary Regurgitation After Tetralogy of Fallot Repair

Tetralogy of Fallot is the most common cyanotic congenital heart defect and can leave patients with pulmonary valve regurgitation, a backward flow of blood into the right ventricle after repair.... Read more

Image credit: Shu-Han Chen / St. Paul’s Hospital / National Taiwan University

AI Tool Flags Osteoporosis Risk from Routine Chest X-Rays

Osteoporosis is a progressive loss of bone density that is often silent until a fracture occurs. Current screening frameworks concentrate on older women and select high-risk groups. Many men, younger adults,... Read more

MRI

view channel

Image: Video and scientific image caption: Demonstration of ELITE results in two patients — a technology that provides high temporal and spatial resolution, reduces noise, and enhances the visualization of breast tumor (marked in yellow) and blood vessels morphology (Photo courtesy of Dr. Eddy Solomon/Technion - Israel Institute of Technology)

AI Reconstruction Tool Speeds Dynamic Breast MRI and Improves Cancer Detection

Breast cancer affects about 2.3 million people each year, creating sustained demand for precise imaging. Dynamic magnetic resonance imaging (MRI) is highly sensitive, yet slow acquisitions hinder real-time... Read more

International Study Assesses AI for Prostate Cancer MRI Interpretation

Prostate cancer is a leading cause of cancer morbidity in men, and accurate early diagnosis hinges on expert interpretation of prostate magnetic resonance imaging (MRI). Rapid adoption of MRI-first pathways... Read more

$Image: By training the AI with simulations, researchers can reconstruct brain images with high precision using only one-tenth of the data typically required in magnetic resonance imaging. The image shows a metric known as “fractional anisotropy”—an index of myelination—obtained using conventional methods and with the new approach (Photo courtesy of Instituto de Neurociencias UMH CSIC)$