Intrinsic radiomics phenotypes of DCI from breast DCE-MRI: Demonstrating feasibility in interim analysis of the ECOG-ACRIN E4112 trial

Vivian Belenky, Rhea Chitalia, Nickolas Lewis, Debosmita Biswas, Constantine Gatsonis, Jennifer Xiao, Michael Hirano, Sunil Badve, Joseph A. Sparano, Seema Khan, Kathy D. Miller, Constance Lehman, Justin Romanoff, Antonio C. Wolff, Christopher Comstock, Savannah C. Partridge, Habib Rahbar, Despina Kontos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Ductal in-situ carcinoma (DCIS) is a non-invasive proliferation that lacks the ability to metastasize. Over the past four decades, DCIS diagnoses have increased ten-fold, with treatments nearly as aggressive as those for small low-grade invasive breast cancer. In this study, we evaluate the potential of identifying intrinsic imaging phenotype of DCIS using radiomic signatures from breast DCE-MRI. The rationale is that such phenotypes may capture aspects of the heterogeneity of DCIS that can aid in identifying indolent from aggressive disease to better stratify patients for improved disease management. An initial analysis was performed on eighty- two DCIS cases from the ECOG-ACRIN E4112 trial. The Cancer Phenomics Toolkit (CapTK) was used to extract a total of 95 3-D radiomic features from each primary lesion volume in pre-treatment, pre-operative breast DCE-MRI images. Features were first filtered for robustness across the heterogeneous clinical sites of DCE-MRI acquisition and features deemed non-robust (59) were discarded. Dimensionality reduction was performed with the remaining thirty-six features via principle component analysis (PCA). Unsupervised hierarchical clustering of the resulting five principal components (PCs) capturing 85% of the original feature variance was applied. Two significant intrinsic DCIS radiomic phenotypes were identified (p<0.001). Our hypothesis is that DCIS imaging biomarkers could improve prognostic ability more reliably than biopsy alone. These findings will be further explored in the expanded analysis of ECOG-ACRIN E4112 trial.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2021
Subtitle of host publicationComputer-Aided Diagnosis
EditorsMaciej A. Mazurowski, Karen Drukker
PublisherSPIE
ISBN (Electronic)9781510640238
DOIs
StatePublished - 2021
EventMedical Imaging 2021: Computer-Aided Diagnosis - Virtual, Online, United States
Duration: Feb 15 2021Feb 19 2021

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume11597
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2021: Computer-Aided Diagnosis
Country/TerritoryUnited States
CityVirtual, Online
Period2/15/212/19/21

Keywords

  • Breast DCE-MRI
  • DCIS
  • Imaging phenotypes
  • Radiomics

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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