The overall aim of this project is to investigate and better understand the repeatability and robustness of radiomics in breast cancer imaging. Radiomics from medical images can provide information about lesion features such as size, irregularity, and texture, which can be used to produce quantitative image-based phenotypes that can assist in diagnosis of cancer and assessment of treatment. Using previously acquired radiomics measurements of breast cancer imaged by full-field digital mammography (FFDM) and magnetic resonance (MR), Aim 1 of this study is to assess their repeatability using three classifiers (linear discriminant analysis, support vector machines, and Bayesian neural network methods), bootstrapping for variability assessment, and receiver operating characteristics (ROC) methods. By doing so, we will be able to evaluate how radiomics may be expected to vary in their output and performance on FFDM and MR.
In Aim 2, we endeavor to understand the cross-modality performance of radiomics measurements of lesion cases imaged by both FFDM and MR. This work will provide a new understanding of the robustness of radiomics tumor descriptors compared across two modalities and fulfill a currently unmet need ? thus being both novel and significant. Statistical analysis will be conducted using superiority and non-inferiority testing. These studies will provide a better understanding of the repeatability and robustness of radiomics of breast lesion images, an important step in establishing their utility in disease diagnosis and treatment assessment.

Public Health Relevance

Breast cancer is a significant public health concern; it is estimated that one in eight women will be diagnosed with breast cancer in their lifetime. Radiomics makes use of quantitative image-based phenotypes, also called features, to provide information about the presence of cancer and its response to treatment, which can aid physicians in medical decision making. The overall objective of this study, addresses a currently unmet need and aims to assess the repeatability of radiomics made from mammography and magnetic resonance images of breast cancer and to determine the robustness of radiomics for lesions imaged across two modalities, mammography and magnetic resonance; the aims of this study are designed to contribute to better understanding of the utility and generalizability of the role of radiomics in cancer patient management and precision medicine.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Academic Research Enhancement Awards (AREA) (R15)
Project #
1R15CA227948-01A1
Application #
9654299
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Redmond, George O
Project Start
2019-01-16
Project End
2021-12-31
Budget Start
2019-01-16
Budget End
2021-12-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Wheaton College
Department
Physics
Type
Schools of Arts and Sciences
DUNS #
068605054
City
Wheaton
State
IL
Country
United States
Zip Code
60187