Volpara Imaging Software

Volpara Imaging Software utilizes raw digital mammography and tomosynthesis data to automatically perform a volumetric analysis, generating quantitative metrics of breast composition, including volumetric breast density and BI-RADS categorization. The system's methodology involves creating density maps to calculate fibroglandular tissue volume relative to total breast volume, providing adjunctive information and quality assurance data to aid healthcare professionals in breast assessment.

Volpara Imaging Software is an application designed to work with raw data from digital breast x-ray systems, including tomosynthesis, to provide a quantitative assessment of breast composition. The software automatically analyzes these images using a volumetric approach, calculating and quantifying a density map where each pixel represents the thickness of fibroglandular tissue. From this density map, it determines volumetric breast density by calculating the ratio of fibroglandular tissue volume to total breast volume estimates, processing standard mammographic views (CC and MLO) from both digital mammography and digital breast tomosynthesis (DBT) examinations. The software outputs several key metrics, including the volume of fibroglandular tissue, total breast volume, volumetric breast density percentage, average and maximum thickness of dense tissue, and the maximum volume of dense tissue over any 1 cm² region. Additionally, it provides image quality assurance metrics, with version 3.2 specifically including dose and pressure values. These numerical values, along with an automatically assigned BI-RADS breast density category (4th or 5th Edition) and the density maps themselves (marked with maxima), are presented via a Volpara scorecard (DICOM Secondary Capture Image) or a DICOM Mammography CAD Structured Report. The software, intended to aid healthcare professionals as adjunctive information for breast composition assessment and not as a standalone diagnostic tool, operates on server environments, with version 3.2 specifically deployable on a Microsoft Azure-connected virtual appliance.

AI Regulatory Concerns

Powered by

Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. How does the algorithm differentiate between fibroglandular tissue and other breast tissues from raw x-ray data, especially across different vendor equipment and acquisition protocols?; What is the variability or margin of error in the calculated volumetric breast density and BI-RADS categorization compared to expert radiologist consensus, particularly in borderline cases?; How do the quality assurance metrics, such as dose and pressure (specifically mentioned for version 3.2), correlate with image quality and the accuracy of the density assessment?; What specific improvements in 'density sanity checking' were implemented in version 3.2, and how do these affect the reliability of results in challenging cases (e.g., implants, very dense or very fatty breasts)?; Could the quantitative density metrics provided by Volpara Imaging Software be used to longitudinally track changes in breast density over time, and what is the reproducibility of these measurements?