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Full text release has been delayed at the author's request until May 19, 2025

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Developing Generalizable Radiomics Features for Risk Stratification and Pathologic Phenotyping in Crohn’s Disease via Imaging

Chirra, Prathyush Venkata
http://rave.ohiolink.edu/etdc/view?acc_num=case1680690057850258

Abstract Details

2023, Doctor of Philosophy, Case Western Reserve University, Biomedical Engineering.
Current non-invasive cross-sectional imaging such as MRI and CT provide clinicians with a powerful tool for the diagnosis, monitoring, and treatment planning of patients. The advancements in this field are especially noticeable in chronic diseases like Crohn’s, which benefits from early identification but lacks a long term cure and thus requires life time monitoring. However, the current application of imaging is predominantly qualitative, allowing for inter-reader variability and an incomplete view of the diseased regions. Additionally, many patients show significant variation in response to specific therapies with standard radiological and clinical assessment being unable to predict or prognosticate the response for each patient. This variation in response maybe due to underlying phenotypic differences in disease like extent of fibrosis and inflammation, but at present there are no methods to assess this at time of diagnosis with non-invasive imaging. However, the computer-extraction of advanced features from radiographic images (radiomics), has enabled superior disease characterization especially in concert with radiological reading and clinical markers. While, studies have shown the potential for radiomics in the context of treatment response prognostication in cancers there is a lack of similar work in the field of Crohn’s. These initial studies have also shown that radiomic features vary as a function of the scanner and the settings. It is therefore important to identify a stable set of radiomic features which are correlated with Crohn’s disease treatment outcomes and phenotype. In this dissertation, we provide a comprehensive evaluation of radiomic features in which, we identify pools of radiomic features which are consistent across image variations in both MRI and CT. We leverage these features to construct a prognostic radiomics model for risk stratifying patients with Crohn’s based on need for early surgical interventions. Finally, we identify and validate radiomic features and models for the characterization of degree of inflammation and fibrosis in Crohn’s disease strictures.
David Wilson (Committee Chair)
Satish Viswanath (Advisor)
Anant Madabhushi (Committee Member)
Shuo Li (Committee Member)
Erick Remer (Committee Member)
138 p.
Biomedical Engineering; Biomedical Research
MRI,CT, Radiomics, AI, Crohn's, Strictures, Phenotyping, MRE, CTE, Reproducibility

Recommended Citations

Citations

  • Chirra, P. V. (2023). Developing Generalizable Radiomics Features for Risk Stratification and Pathologic Phenotyping in Crohn’s Disease via Imaging [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1680690057850258

    APA Style (7th edition)

  • Chirra, Prathyush. Developing Generalizable Radiomics Features for Risk Stratification and Pathologic Phenotyping in Crohn’s Disease via Imaging. 2023. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1680690057850258.

    MLA Style (8th edition)

  • Chirra, Prathyush. "Developing Generalizable Radiomics Features for Risk Stratification and Pathologic Phenotyping in Crohn’s Disease via Imaging." Doctoral dissertation, Case Western Reserve University, 2023. http://rave.ohiolink.edu/etdc/view?acc_num=case1680690057850258

    Chicago Manual of Style (17th edition)

case1680690057850258
© 2023, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.