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

Publication ,  Journal Article
Selvakumaran, V; Hou, R; Baker, JA; Yoon, SC; Ghate, SV; Walsh, R; Litton, TP; Lu, LX; Devalapalli, A; Kim, C; Soo, MS; Hwang, ES; Lo, JY; Grimm, LJ
Published in: Acad Radiol
November 2020

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 (<2 cm) and after the exclusion of microinvasive disease.

Duke Scholars

Published In

Acad Radiol

DOI

EISSN

1878-4046

Publication Date

November 2020

Volume

27

Issue

11

Start / End Page

1580 / 1585

Location

United States

Related Subject Headings

  • Retrospective Studies
  • Radiologists
  • Nuclear Medicine & Medical Imaging
  • Neoplasm Invasiveness
  • Mammography
  • Humans
  • Carcinoma, Intraductal, Noninfiltrating
  • Carcinoma, Ductal, Breast
  • Breast Neoplasms
  • 3202 Clinical sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Selvakumaran, V., Hou, R., Baker, J. A., Yoon, S. C., Ghate, S. V., Walsh, R., … Grimm, L. J. (2020). Predicting Upstaging of DCIS to Invasive Disease: Radiologists's Predictive Performance. Acad Radiol, 27(11), 1580–1585. https://doi.org/10.1016/j.acra.2019.12.009
Selvakumaran, Vignesh, Rui Hou, Jay A. Baker, Sora C. Yoon, Sujata V. Ghate, Ruth Walsh, Tyler P. Litton, et al. “Predicting Upstaging of DCIS to Invasive Disease: Radiologists's Predictive Performance.Acad Radiol 27, no. 11 (November 2020): 1580–85. https://doi.org/10.1016/j.acra.2019.12.009.
Selvakumaran V, Hou R, Baker JA, Yoon SC, Ghate SV, Walsh R, et al. Predicting Upstaging of DCIS to Invasive Disease: Radiologists's Predictive Performance. Acad Radiol. 2020 Nov;27(11):1580–5.
Selvakumaran, Vignesh, et al. “Predicting Upstaging of DCIS to Invasive Disease: Radiologists's Predictive Performance.Acad Radiol, vol. 27, no. 11, Nov. 2020, pp. 1580–85. Pubmed, doi:10.1016/j.acra.2019.12.009.
Selvakumaran V, Hou R, Baker JA, Yoon SC, Ghate SV, Walsh R, Litton TP, Lu LX, Devalapalli A, Kim C, Soo MS, Hwang ES, Lo JY, Grimm LJ. Predicting Upstaging of DCIS to Invasive Disease: Radiologists's Predictive Performance. Acad Radiol. 2020 Nov;27(11):1580–1585.

Published In

Acad Radiol

DOI

EISSN

1878-4046

Publication Date

November 2020

Volume

27

Issue

11

Start / End Page

1580 / 1585

Location

United States

Related Subject Headings

  • Retrospective Studies
  • Radiologists
  • Nuclear Medicine & Medical Imaging
  • Neoplasm Invasiveness
  • Mammography
  • Humans
  • Carcinoma, Intraductal, Noninfiltrating
  • Carcinoma, Ductal, Breast
  • Breast Neoplasms
  • 3202 Clinical sciences