Novel Functional Radiomics for Prediction of Cardiac Positron Emission Tomography Avidity in Lung Cancer Radiotherapy.
Publication/Presentation Date
3-1-2024
Abstract
PURPOSE: Traditional methods of evaluating cardiotoxicity focus on radiation doses to the heart. Functional imaging has the potential to provide improved prediction for cardiotoxicity for patients with lung cancer. Fluorine-18 (
METHODS: Pretreatment
RESULTS: From 202 of 209 scans, cardiac FDG uptake was scored as no uptake (39.6%), diffuse uptake (25.3%), and focal uptake (35.1%), respectively. Sixty-two independent radiomics features were reduced to nine clinically pertinent features. The best model showed 93% predictive accuracy in the training data set and 80% and 92% predictive accuracy in two external validation data sets.
CONCLUSION: This work used an extensive patient data set to develop a functional cardiac radiomic model from standard-of-care
Volume
8
First Page
2300241
Last Page
2300241
ISSN
2473-4276
Published In/Presented At
Choi, W., Jia, Y., Kwak, J., Werner-Wasik, M., Dicker, A. P., Simone, N. L., Storozynsky, E., Jain, V., & Vinogradskiy, Y. (2024). Novel Functional Radiomics for Prediction of Cardiac Positron Emission Tomography Avidity in Lung Cancer Radiotherapy. JCO clinical cancer informatics, 8, e2300241. https://doi.org/10.1200/CCI.23.00241
Disciplines
Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods
PubMedID
38452302
Department(s)
Administration and Leadership
Document Type
Article