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Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis

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Characterizing Breast Lesions Using Quantitative Parametric 3D Subharmonic Imaging: A Multicenter Study.

Anush Sridharan¹, John R Eisenbrey², Maria Stanczak²

¹Department of Radiology, Thomas Jefferson University, 763H Main Building, 132 South 10th Street, Philadelphia, PA 19107; Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania.

Academic Radiology

|December 21, 2019

Summary

This summary is machine-generated.

Three-dimensional contrast-enhanced ultrasound imaging shows promise for characterizing breast lesions. Quantitative vascular metrics derived from 3D subharmonic imaging (SHI) can accurately assess breast cancer vascularity.

Keywords:

Breast cancer Contrast-enhanced ultrasound Subharmonic imaging Ultrasound contrast agents

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Area of Science:

Medical imaging
Oncology
Radiology

Background:

Breast cancer is the most common cancer in women.
Accurate characterization of breast lesions is crucial for diagnosis and treatment.
Vascularity plays a key role in tumor development and progression.

Purpose of the Study:

To evaluate the use of 3D contrast-enhanced ultrasound imaging for visualizing and characterizing breast lesions based on vascularity kinetics.
To assess the diagnostic accuracy of quantitative vascular parameters derived from 3D imaging techniques.

Main Methods:

A clinical study involving 219 breast lesions.
Imaging modalities included power Doppler imaging (PDI), 3D contrast-enhanced harmonic imaging (HI), and 3D contrast-enhanced subharmonic imaging (SHI).
Quantitative metrics of vascularity (PER and AUC) were derived from 3D parametric volumes and analyzed offline. Diagnostic accuracy was compared to biopsy results.

Main Results:

3D SHI successfully detected contrast agent flow in breast lesions.
Diagnostic accuracy for vascular heterogeneity, PER, and AUC ranged from 0.52 to 0.75.
A logistic regression model incorporating vascular heterogeneity ratio, central PER, and central AUC achieved 0.90 accuracy.

Conclusions:

3D SHI is effective in detecting contrast agent flow in breast lesions.
Characterizing breast lesions using quantitative measures of vascular heterogeneity and 3D parametric volumes shows significant promise.
This imaging approach offers a potential tool for improved breast cancer diagnosis.