Editorial Comment
Breast Imaging
December 21, 2022

Editorial Comment: The Value of Decision Support in Breast Ultrasound

Ultrasound is widely used in breast imaging as both a screening tool and a diagnostic tool to complement mammography. It not only provides precise shape, margin, orientation, and echo-genicity information on masses through use of gray-scale imaging but also reveals real-time information through use of color imaging. Optoacoustic imaging is a novel technique that quantifies additional functional information about tumor biology, including neoangiogenesis and oxygen extraction from hemoglobin. This information parallels the dynamic data obtained with breast MRI, contrast-enhanced mammography, and molecular breast imaging, though without the cost of MRI system time, ionizing radiation, or risk of allergic reactions from gadolinium-based or iodinated contrast material.
Advances in digital breast tomosynthesis and high-resolution ultrasound allow breast imagers to visualize more subtle findings and a larger number of findings overall. However, this greater visualization inevitably leads to increased frequency of false-positive results. For example, in a review of screening breast ultrasound of women with dense breasts, the increase in incremental cancer detection rates (from 2.0 to 2.7 per 1000) came at a cost of an increase in recall and biopsy rates [1]. False-positives can increase patient anxiety and are a strain on health care costs.
The Pioneer-01 study showed that optoacoustic imaging, when fused with conventional ultrasound, can help radiologists categorize sonographic masses as benign, probably benign, or suspicious while increasing the specificity of breast cancer detection [2]. The current study goes beyond the original Pioneer-01 study, introducing a machine learning–based decision support tool to generate a probability of malignancy that would objectively justify such management. Integrated into the screening or diagnostic breast imaging workflow, such tools could decrease the rates of false-positive results and unnecessary biopsy. These outcomes are particularly useful in a time when artificial intelligence and decision support tools should be integrated into everyday practice to help manage complex cases and ever-increasing volumes.

Footnote

Provenance and review: Solicited; not externally peer reviewed.

References

1.
Berg WA, Vourtsis A. Screening breast ultrasound using handheld or automated technique in women with dense breasts. J Breast Imaging 2019; 1:283–296
2.
Neuschler EI, Butler R, Young CA, et al. A pivotal study of optoacoustic imaging to diagnose benign and malignant breast masses: a new evaluation tool for radiologists. Radiology 2018; 287:398–412

Information & Authors

Information

Published In

American Journal of Roentgenology
Pages: 659
PubMed: 36541596

History

Version of record online: December 21, 2022

Authors

Affiliations

Babita Panigrahi, MD
Johns Hopkins Medicine, Baltimore, MD
[email protected]

Notes

Version of record: Mar 22, 2023
The author declares that there are no disclosures relevant to the subject matter of this article.

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