Jefferson investigates the relationship between Artificial Intelligence and Heart Disease in “The Nexus”.
Tag Archives: Lung
Shining a Light: Unveiling Cardiac Risks Using PET Imaging in Lung Cancer Radiotherapy
A study on cardiac toxicity in lung cancer treatment is highlighted in a JCO CCI editorial. The findings could significantly impact patient care. The study focuses on using Positron Emission Tomography Imaging in lung cancer radiotherapy to reveal cardiac risks. #CardiacToxicity #LungCancer #Innovation
Exploring published and novel pre-treatment CT and PET radiomics to stratify risk of progression among early-stage non-small cell lung cancer patients treated with stereotactic radiation
Maria Thor 1,4, Kelly Fitzgerald 2,4, Aditya Apte 1, Jung Hun Oh 1, Aditi Iyer 1, Otasowie Odiase 2, Saad Nadeem 1, Ellen D. Yorke 1, Jamie Chaft 3, Abraham J. Wu 2, Michael Offin 3, Charles B Simone II 2, Isabel Preeshagul 3, Daphna Y. Gelblum 2, Daniel Gomez 2, Joseph O. Deasy 1,Continue reading “Exploring published and novel pre-treatment CT and PET radiomics to stratify risk of progression among early-stage non-small cell lung cancer patients treated with stereotactic radiation”
Novel Functional Radiomics for Predicting Cardiotoxicity in Lung Cancer Radiotherapy using Cardiac FDG-PET Uptake
The provided content discusses functional Delta-Radiomics and its application in predicting overall survival, showcased through a Slideshare presentation. Additionally, there is mention of a study on the classification of cardiac uptake patterns, also presented on Slideshare, using functional Radiomics.
2023 Accepted/Invited Annual Meeting abstracts
Longitudinal CBCT radiomics in Lung Cancer supported by Varian Medical Systems Inc.
Jefferson Whole Lung CBCT radiomics
Clinically-Interpretable Radiomics
MICCAI’22 Paper | CMPB’21 Paper | CIRDataset This library serves as a one-stop solution for analyzing datasets using clinically-interpretable radiomics (CIR) in cancer imaging (https://github.com/choilab-jefferson/CIR). The primary motivation for this comes from our collaborators in radiology and radiation oncology inquiring about the importance of clinically-reported features in state-of-the-art deep learning malignancy/recurrence/treatment response prediction algorithms. PreviousContinue reading “Clinically-Interpretable Radiomics”
Lung Cancer Screening Radiomics
A comprehensive framework for lung cancer screening radiomics using LIDC-IDRI and LUNGx dataset. Data preprocessing – download data, conversion, etc. Radiomics feature extraction including spiculation features AutoML model building and validation Source code https://github.com/choilab-jefferson/LungCancerScreeningRadiomics Publications Wookjin Choi, Jung Hun Oh, Sadegh Riyahi, Chia-Ju Liu, Feng Jiang, Wengen Chen, Charles White, Andreas Rimner, James G. Mechalakos,Continue reading “Lung Cancer Screening Radiomics”
