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Predicting Upstaging of DCIS to Invasive Disease: Radiologists's Predictive Performance

Authors :
Mary Scott Soo
Lucy Xiangxi Lu
E. Shelley Hwang
Connie Kim
Lars J. Grimm
Ruth Walsh
Sujata V. Ghate
Vignesh Selvakumaran
Tyler P. Litton
Rui Hou
Joseph Y. Lo
Sora C. Yoon
Jay A. Baker
Amrita Devalapalli
Source :
Acad Radiol
Publication Year :
2020
Publisher :
Elsevier BV, 2020.

Abstract

Rationale and Objectives The purpose of this study is to quantify breast radiologists’ performance at predicting occult invasive disease when ductal carcinoma in situ (DCIS) presents as calcifications on mammography and to identify imaging and histopathological features that are associated with radiologists’ performance. Materials and Methods Mammographically detected calcifications that were initially diagnosed as DCIS on core biopsy and underwent definitive surgical excision between 2010 and 2015 were identified. Thirty cases of suspicious calcifications upstaged to invasive ductal carcinoma and 120 cases of DCIS confirmed at the time of definitive surgery were randomly selected. Nuclear grade, estrogen and progesterone receptor status, patient age, calcification long axis length, and breast density were collected. Ten breast radiologists who were blinded to all clinical and pathology data independently reviewed all cases and estimated the likelihood that the DCIS would be upstaged to invasive disease at surgical excision. Subgroup analysis was performed based on nuclear grade, long axis length, breast density and after exclusion of microinvasive disease. Results Reader performance to predict upstaging ranged from an area under the receiver operating characteristic curve (AUC) of 0.541–0.684 with a mean AUC of 0.620 (95%CI: 0.489–0.751). Performances improved for lesions smaller than 2 cm (AUC: 0.676 vs 0.500; p = 0.002). The exclusion of microinvasive cases also improved performance (AUC: 0.651 vs 0.620; p = 0.005). There was no difference in performance based on breast density (p = 0.850) or nuclear grade (p = 0.270) Conclusion Radiologists were able to predict invasive disease better than chance, particularly for smaller DCIS lesions (

Details

ISSN :
10766332
Volume :
27
Database :
OpenAIRE
Journal :
Academic Radiology
Accession number :
edsair.doi.dedup.....a86cb95ed634e9957a570c65992499da
Full Text :
https://doi.org/10.1016/j.acra.2019.12.009