Automated breast density measurement to support personalized breast cancer screening

This technology is an automated software platform that segments and analyzes digital breast tomosynthesis (DBT) images to provide objective and reproducible breast density assessments for cancer screening, risk stratification, and monitoring.

Unmet Need: Standardized and reliable breast density measurement for risk assessment

Breast density is an important predictor of breast cancer risk and is used to guide patient monitoring and screening decisions. Current breast density assessment relies heavily on the Breast Imagining Reporting and Data System (BI-RADS), which is based on radiologist interpretation and can vary with experience, training, and subjective judgment. In addition, breast density measurements from digital breast tomosynthesis (DBT) can be influenced by variations in imaging hardware, reconstruction algorithms, and post-processing techniques. These variabilities can limit consistency of longitudinal monitoring and breast cancer risk assessment. There is a need for standardized, reproducible methods to accurately quantify breast density across imagining platforms.

The Technology: Automated breast density measurement from digital breast tomosynthesis

This technology is an automated platform that analyzes digital breast tomosynthesis (DBT) images to estimate volumetric breast density. Using image segmentation and tissue classification methods, it distinguishes dense breast tissue from fatty tissue and generates an objective measurement of breast density. The software incorporates image standardization and refinement steps to reduce variability caused by differences in imaging systems and processing workflows, enabling more consistent density assessment over time and across sites.

Preliminary validation cohorts demonstrated strong within-patient correlation of volumetric breast density measurements over time, with slightly reduced consistency across vendors, and strong agreement with BI-RADS categories.

Applications:

  • Breast cancer screening and breast density assessment
  • Longitudinal monitoring of breast density changes
  • Multi-vendor imaging studies
  • Decision-support tool for radiologists
  • Developing other imaging-based cancer risk assessment tools
  • Automated tissue characterization and segmentation methods
  • Pregnancy and pre-term birth monitoring

Advantages:

  • Provides objective and reproducible breast density measurements
  • Reduces variability associated with differences in imaging hardware and image processing
  • Reduces inter-operator variability
  • Demonstrates agreement with clinically used BI-RADS density classification
  • Potentially less time consuming that traditional screening processes
  • Enables reliable monitoring of breast density changes over time
  • Easily implementable at multiple different sites
  • Easily integrates with current clinical workflow

Lead Inventor:

Despina Kontos, Ph.D.

Tech Ventures Reference:

Quick Facts:
Tags
Adipose tissueBreast cancerBreast cancer screeningCancerDigital image processingImage segmentationRadiologyRisk assessmentStratified samplingWorkflow
Inventors
Anne Marie McCarthyDespina KontosEric A. CohenNehal DoiphodeSarah EhsanWalter C. Mankowski
Manager
Joan Martinez
Departments
Biomedical EngineeringBiostatistics, Epidemiology & InformaticsRadiology
Divisions
Columbia University Medical Center (CUMC)Fu Foundation School of Engineering and Applied Science (SEAS)Perelman School of Medicine
Reference Number
CU26309
Release Date
2026-07-22