densitas densityai
Overview
Densitas densityai™ is a deep learning algorithm that provides automated, standardized, and reproducible breast density assessments from mammograms. It is a core component of the broader intelliMammo™ platform by Densitas Inc., which offers comprehensive AI solutions for breast cancer screening.
The tool uniquely utilizes two distinct deep learning models to decouple breast density assessment into quantitative percent mammographic density (0%-100%) and qualitative descriptive categories (A, B, C, D), aligning with both the ACR BI-RADS® 4th and 5th Edition density scales. By eliminating the subjectivity and lack of reliability associated with visual assessment, densityai™ establishes standardization across entire health systems, supporting compliance with federal and regional breast density notification laws.
Densitas densityai™ seamlessly integrates into existing reporting and PACS workflows, boosting efficiency and facilitating retrospective analyses. It processes routinely archived ‘for presentation’ images and generates results that are available on-demand at the point of care for radiological technologists and radiologists, and retrospectively for clinic and health system administrators through an advanced analytics platform.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Automated and standardized breast density assessments
- Aligns with ACR BI-RADSu00ae Atlas 4th and 5th Edition density scales
- Eliminates subjectivity and improves reproducibility of breast density assessment
- Supports compliance with federal and regional breast density notification laws
- Integrates into existing reporting and PACS workflows
- Identifies higher-risk women for supplemental screening
- Utilizes deep learning models for analysis
- Processes routinely archived 'for presentation' mammograms
- Generates Secondary Capture (SC) and Structured Report (SR) objects
- Provides quantitative percent mammographic density and qualitative descriptive categories
Use Cases
- Standardized breast density classification at point-of-care
- Ensuring compliance with breast density reporting requirements
- Informing referral pathways for supplemental imaging
- Risk stratification of patients for tailored follow-up screening protocols
- Improving workflow efficiency and reducing unnecessary callbacks
- Supporting breast cancer screening trials and research
What Physicians Need to Know
Densitas densityai offers a robust solution for standardizing breast density assessment, which is crucial for consistent patient care and compliance with evolving notification laws. Leverage its automated, reproducible results to streamline reporting, reduce subjective variability, and inform personalized screening pathways, especially for high-risk patients. The seamless integration into existing workflows minimizes disruption, allowing radiologists to focus more on complex interpretive tasks. Remember it's an adjunctive tool, not a diagnostic aid, and should complement, not replace, comprehensive clinical evaluation.
Densitas densityai is designed for broad compatibility, integrating directly with PACS, RIS, and major reporting systems like Nuance PowerScribe. Its vendor-neutral approach and ability to process standard DICOM images facilitate straightforward integration into diverse imaging environments. Compatibility with AI marketplaces (e.g., Nuance, Blackford) further enhances its accessibility and interoperability within a broader AI ecosystem.
Details
| Category | Oncology AI, Radiology & Imaging AI |
| Pricing | Contact for pricing |
| Deployment | Hybrid (on-premise integration with PACS/reporting systems, cloud-based analytics platform) |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated Densitas densityai™ received FDA 510(k) clearance (K192973) on February 19, 2020, for providing breast density assessments in accordance with the American College of Radiology's BI-RADS 5th edition density classification scale. |
| Integrations | |
| EHR | Not specified |
| Specialties | Oncology, Radiology |
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