Comput Math Methods Med - Statistical evaluation of a fully automated mammographic breast density algorithm.


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Visual assessments of mammographic breast density by radiologists are used in clinical practice; however, these assessments have shown weaker associations with breast cancer risk than area-based, quantitative methods. The purpose of this study is to present a statistical evaluation of a fully automated, area-based mammographic density measurement algorithm. Five radiologists estimated density in 5% increments for 138 "For Presentation" single MLO views; the median of the radiologists' estimates was used as the reference standard. Agreement amongst radiologists was excellent, ICC = 0.884, 95% CI (0.854, 0.910). Similarly, the agreement between the algorithm and the reference standard was excellent, ICC = 0.862, falling within the 95% CI of the radiologists' estimates. The Bland-Altman plot showed that the reference standard was slightly positively biased (+1.86%) compared to the algorithm-generated densities. A scatter plot showed that the algorithm moderately overestimated low densities and underestimated high densities. A box plot showed that 95% of the algorithm-generated assessments fell within one BI-RADS category of the reference standard. This study demonstrates the effective use of several statistical techniques that collectively produce a comprehensive evaluation of the algorithm and its potential to provide mammographic density measures that can be used to inform clinical practice.

Resumo Limpo

visual assess mammograph breast densiti radiologist use clinic practic howev assess shown weaker associ breast cancer risk areabas quantit method purpos studi present statist evalu fulli autom areabas mammograph densiti measur algorithm five radiologist estim densiti increment present singl mlo view median radiologist estim use refer standard agreement amongst radiologist excel icc ci similar agreement algorithm refer standard excel icc fall within ci radiologist estim blandaltman plot show refer standard slight posit bias compar algorithmgener densiti scatter plot show algorithm moder overestim low densiti underestim high densiti box plot show algorithmgener assess fell within one birad categori refer standard studi demonstr effect use sever statist techniqu collect produc comprehens evalu algorithm potenti provid mammograph densiti measur can use inform clinic practic

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