MRI-based Radiomic Features for Risk Stratification of Ductal Carcinoma in Situ in a Multicenter Setting (ECOG-ACRIN E4112 Trial)

Kalina P. Slavkova; Ruya Kang; Anum S. Kazerouni; Debosmita Biswas; Vivian Belenky; Rhea Chitalia; Hannah Horng; Michael Hirano; Jennifer Xiao; Ralph L. Corsetti; Sara H. Javid; Derrick W. Spell; Antonio C. Wolff; Joseph A. Sparano; Seema A. Khan; Christopher Comstock; Justin Romanoff; Constantine Gatsonis; Constance D. Lehman; Savannah C. Partridge; Jon A. Steingrimsson; Despina Kontos; Habib Rahbar

doi:10.1148/radiol.241628

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Models using clinical and MRI-based radiomic features identified from ductal carcinoma in situ lesions improved prediction of disease upstaging at surgery compared with standard clinical information alone.

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Slavkova et al. (2025) studied this question.

synapsesocial.com/papers/6a1bc54c69a4af5b15a8f85f https://doi.org/10.1148/radiol.241628

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MRI-based Radiomic Features for Risk Stratification of Ductal Carcinoma in Situ in a Multicenter Setting (ECOG-ACRIN E4112 Trial)

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MRI-based Radiomic Features for Risk Stratification of Ductal Carcinoma in Situ in a Multicenter Setting (ECOG-ACRIN E4112 Trial)

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