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The British journal of radiology · 2014

How does semi-automated computer-derived CT measure of breast density compare with subjective assessments to assess mean glandular breast density, in patients with breast cancer?

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Bansal G J, Kotugodella S

Аннотация

OBJECTIVES: (a) To compare radiologists' breast mammographic density readings with CT subjective measures. (b) To correlate computer-derived measurement of CT density with subjective assessments. (c) To evaluate density distributions in this cohort of patients with breast cancer.

METHODS: A retrospective review of mammograms and CT scans in 77 patients with breast cancer obtained within 1 year of each other was performed. Two radiologists independently reviewed both CT and mammograms and classified each case into four categories as defined by the breast imaging-reporting and data system of the American College of Radiology. Inter-reader agreements were obtained for both mammographic and CT density subjective evaluations by using the Cohen-weighted kappa statistic and Spearman correlation. The semi-automated computer-derived measurement of breast density was correlated with visual measurements.

RESULTS: Inter-reader agreements were lower for subjective CT density grades than those for mammographic readings 0.428 [confidence interval (CI), 0.24-0.89] vs 0.571 (CI, 0.35-0.76). There was moderately good correlation between subjective CT density grades and the mammographic density grades for both readers (0.760 for Reader 1 and 0.913 for Reader 2). The semi-automated CT density measurement correlated well with the subjective assessments, with complete agreement of the density grades in 84.9% of patients and only one level difference in the rest.

CONCLUSIONS: Semi-automated CT density measurements in the evaluation of breast density correlated well with subjective mammographic density measurement.

ADVANCES IN KNOWLEDGE: There is good correlation between CT and mammographic density, but further studies are needed on how to incorporate semi-automated CT breast density measurement in the risk stratification of patients.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты