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"By combining our proven diagnostic AI technology with Ikonopedia's powerful reporting software, we are strengthening and enhancing the tools available for the diagnosis of breast cancer," said Qlarity Imaging Chief Executive Officer Jon DeVries. "Creating a streamlined workflow that delivers more accurate diagnoses, reduces the risk of reporting errors, and saves time can help radiologists overcome challenges associated with ever growing exam volume and data complexity—which are intensifying in today's environment—to improve patient care."
A key partnership component is the seamless integration of data-driven analysis from QuantX into Ikonopedia's closed-loop structured breast reporting system. Instead of typing or dictating results into the reporting application, the location, size, kinetics, and QuantX score are automatically transferred into Ikonopedia. The auto-population of lesion-specific details helps increase accuracy by reducing the risk of errors caused by manual entry and boosts productivity. While integrating the diagnostic and reporting workflow can yield efficiency gains and cost savings for radiologists and health systems, the most critical benefit is felt by patients where increased accuracy can lead to earlier detection of breast cancer.
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"Our partnership with Qlarity Imaging is a natural progression as we are both leading technology innovators in the breast imaging space," said Ikonopedia Chief Executive Officer Emily Crane. "We also share the ultimate goal of improving patient care to help more women become breast cancer survivors; a goal we are one step closer to achieving."
To explore the Qlarity Imaging and Ikonopedia partnership, including a short demo video of the software integration, click here.
Ikonopedia is the first and only secure, cloud-based breast reporting and MQSA management system designed to track individual lesions in all categories of care to significantly improve patient safety. This closed-loop system increases reporting efficiencies and radiologist awareness with helpful clinical warnings and timely alerts for pertinent patient and family history. Ikonopedia was founded by three expert breast imaging radiologists: László Tabár, MD, is a world renowned educator and the author of six books in 10 languages on mammography; A. Thomas Stavros, MD is the author of one of the most popular reference books in the field of breast ultrasound; and Michael J. Vendrell, MD is an expert in breast MRI and CAD design. For more information, please visit www.ikonopedia.com.
About Qlarity Imaging
Qlarity Imaging improves patient care by building AI-driven breast imaging solutions that enhance diagnostic insights. The company's vision is to transform women's imaging with AI technologies that advance the detection and diagnosis of breast cancer. Qlarity's award-winning initial product, QuantX, is the first computer-aided diagnosis software to be cleared by the FDA for breast MRI evaluation. Qlarity Imaging is a portfolio company of Paragon Biosciences, a life science innovator that creates, invests in and builds life science companies in artificial intelligence, cell and gene therapy, synthetic biology and biopharmaceuticals. For more information, please visit www.qlarityimaging.com.
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Indication: QuantX is indicated for evaluation of the assessment and characterization of breast abnormalities from MRI data in patients presenting for high-risk screening, diagnostic imaging workup, or evaluation of extent of known disease. QuantX is not intended for primary interpretation of digital mammography images.
Important Safety Statement: QuantX is not intended for primary interpretation of digital mammography images. Warnings and cautions related to the potential device failure or low performance are included in the User Manual including comments on image quality, patient population, and segmentation accuracy. Warnings and cautions related to the device are included in the User Manual. Information about the Similar Case Database and cases used in the MRMC study provided in labeling also provide information to users about potential limitations of the device related to specific subpopulations.
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