Lesion spiculation may hinder breast cancer detection, according to a study published in the May issue of Academic Radiology. The study, which identified mammographic features that reduce detection, offers insights for radiology training programs and CAD algorithm development.
Mohammad A. Rawashdeh, MSc, from the University of Sydney in Australia, and colleagues devised the study to determine if features such as mass size, shape, texture, contrast and density reduced detection.
They developed a set of 60 mammograms, comprised of 16 positive cases with single masses and four cases with multicentric masses, and presented the exams to 129 breast imagers. The radiologists were asked to identify and locate lesions and indicate their confidence on a scale of 1 to 5.
“Lesions were then ranked according to the detectability rating and correlated with the following quantities,” wrote Rawashdeh and colleagues. These are: breast density; mean lesion size and lesion shape; texture and signal-to-noise ratio.
The researchers observed negative and positive correlations between lesion detection and breast density, as well as significant correlations between the probability of detection and area, lesion elongation and lesion nonspiculation.
“The results here demonstrate that breast density, lesion size, and lesion shape are the key features that affect detection of breast masses.”
Lesion elongation and lesion nonspiculation also were linked to higher detection, prompting the researchers to suggest that masses with irregular margins or greater levels of spiculation have a lower detectability index.
The researchers plan to further examine this finding with eye-position analysis research. In the interim, they recommended that their findings should be applied in the development of radiology training programs and CAD algorithm design.