TY  - GEN
N2  - Radiomics is an emerging field that focuses on expanding the role of human image interpretation to incorporate computer vision, artificial intelligence and machine learning. The goal is to gather statistical relationships of tumors as derived from various imaging modalities, including computed tomography (CT), and provide a deeper understanding of the properties that define a tumor in contrast with normal tissue. This could explain diagnostic and prognostic attributes of disease and predict an individual's unique response to treatment. The overall aim of this work was to develop a workflow for radiomic analysis and identify variables during biopsy procedures that could provide insight into the composition of a patient's tumor burden and predict response to treatment. The study found that several variables, including kurtosis, gray level variance, volume, sedation time, and procedure complications could play a role in determining prognosis.
DO  - 10.6083/h415pb25z
DO  - DOI
AB  - Radiomics is an emerging field that focuses on expanding the role of human image interpretation to incorporate computer vision, artificial intelligence and machine learning. The goal is to gather statistical relationships of tumors as derived from various imaging modalities, including computed tomography (CT), and provide a deeper understanding of the properties that define a tumor in contrast with normal tissue. This could explain diagnostic and prognostic attributes of disease and predict an individual's unique response to treatment. The overall aim of this work was to develop a workflow for radiomic analysis and identify variables during biopsy procedures that could provide insight into the composition of a patient's tumor burden and predict response to treatment. The study found that several variables, including kurtosis, gray level variance, volume, sedation time, and procedure complications could play a role in determining prognosis.
AD  - Oregon Health and Science University
T1  - Radiomics and the future of precision oncology: the relationship between solid tumor imaging properties and biopsy data
ED  - Guimaraes, Alexander
ED  - Johnson, Brett
ED  - Gray, Joe
ED  - Mentor
ED  - Co-PI
ED  - Co-PI
DA  - 2023
AU  - Nacharaju, Deepthi
L1  - https://digitalcollections.ohsu.edu/record/10096/files/Nacharaju.Deepthi.2023.pdf
PB  - Oregon Health and Science University
PY  - 2023
ID  - 10096
L4  - https://digitalcollections.ohsu.edu/record/10096/files/Nacharaju.Deepthi.2023.pdf
KW  - Prognosis
KW  - Biopsy
KW  - Oncology Service, Hospital
KW  - Masks
KW  - Radiomics
KW  - kurtosis
TI  - Radiomics and the future of precision oncology: the relationship between solid tumor imaging properties and biopsy data
Y1  - 2023
L2  - https://digitalcollections.ohsu.edu/record/10096/files/Nacharaju.Deepthi.2023.pdf
LK  - https://digitalcollections.ohsu.edu/record/10096/files/Nacharaju.Deepthi.2023.pdf
UR  - https://digitalcollections.ohsu.edu/record/10096/files/Nacharaju.Deepthi.2023.pdf
ER  -