Radiomics of NSCLC: Quantitative CT Image Feature Characterization and Tumor Shrinkage Prediction

Radiomics is the high-throughput extraction and analysis of quantitative image features. For non-small cell lung cancer (NSCLC) patients, radiomics can be applied to standard of care computed tomography (CT) images to improve tumor diagnosis, staging, and response assessment. The first objective of this work was to show that CT image features extracted from pre-treatment NSCLC tumors could be used to predict tumor shrinkage in response to therapy. This is important since tumor shrinkage is an important cancer treatment endpoint that is correlated with probability of disease progression and overall survival. Accurate prediction of tumor shrinkage could also lead to individually customized treatment plans. To accomplish this objective, 64 stage NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. Quantitative image features were extracted and principal component regression with simulated annealing subset selection was used to predict shrinkage. Cross validation and permutation tests were used to validate the results. The optimal model gave a strong correlation between the observed and predicted shrinkages with . The second objective of this work was to identify sets of NSCLC CT image features that are reproducible, non-redundant, and informative across multiple machines. Feature sets with these qualities are needed for NSCLC radiomics models to be robust to machine variation and spurious correlation. To accomplish this objective, test-retest CT image pairs were obtained from 56 NSCLC patients imaged on three CT machines from two institutions. For each machine, quantitative image features with concordance correlation coefficient values greater than 0.90 were considered reproducible. Multi-machine reproducible feature sets were created by taking the intersection of individual machine reproducible feature sets. Redundant features were removed through hierarchical clustering. The findings showed that image feature reproducibility and redundancy depended on both the CT machine and the CT image type (average cine 4D-CT imaging vs. end-exhale cine 4D-CT imaging vs. helical inspiratory breath-hold 3D CT). For each image type, a set of cross-machine reproducible, non-redundant, and informative image features was identified. Compared to end-exhale 4D-CT and breath-hold 3D-CT, average 4D-CT derived image features showed superior multi-machine reproducibility and are the best candidates for clinical correlation.

Development and implementation of a dynamic heterogeneous proton equivalent anthropomorphic thorax phantom for the assessment of scanned proton beam therapy

DEVELOPMENT AND IMPLEMENTATION OF A DYNAMIC HETEROGENEOUS PROTON EQUIVALENT ANTHROPOMORPHIC THORAX PHANTOM FOR THE ASSESSMENT OF SCANNED PROTON BEAM THERAPY by James Leroy Neihart, B.S. APPROVED: ______________________________David Followill, Ph.D. ______________________________Peter Balter, Ph.D. ______________________________Narayan Sahoo, Ph.D. ______________________________Kenneth Hess, Ph.D. ______________________________Paige Summers, M.S. APPROVED: ____________________________ Dean, The University of Texas Graduate School of Biomedical Sciences at Houston DEVELOPMENT AND IMPLEMENTATION OF A DYNAMIC HETEROGENEOUS PROTON EQUIVALENT ANTHROPOMORPHIC THORAX PHANTOM FOR THE ASSESSMENT OF SCANNED PROTON BEAM THERAPY A THESIS Presented to the Faculty of The University of Texas Health Science Center at Houston andThe University of TexasMD Anderson Cancer CenterGraduate School of Biomedical Sciences in Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE by James Leroy Neihart, B.S. Houston, Texas Date of Graduation August, 2013 Acknowledgments I would like to acknowledge my advisory committee members, chair David Followill, Ph.D., Peter Balter, Ph.D, Narayan Sahoo, Ph.D., Kenneth Hess, Ph.D., Paige Summers M.S. and, for their time and effort contributed to this project. I would additionally like to thank the faculty and staff at the PTC-H and the RPC who assisted in many aspects of this project. Falk Pӧnisch, Ph.D. for his breath hold proton therapy treatment expertise, Matt Palmer and Jaques Bluett for proton dosimetry assistance, Matt Kerr for verification plan assistance, Carrie Amador, Nadia Hernandez, Trang Nguyen, Andrea Molineu, Lynda McDonald for TLD and film dosimetry assistance. Finally, I would like to thank my wife and family for their support and encouragement during my research and studies. Development and implementation of a dynamic heterogeneous proton equivalent anthropomorphic thorax phantom for the assessment of scanned proton beam therapy By: James Leroy Neihart, B.S. Chair of Advisory Committee: David Followill, Ph.D Proton therapy has been gaining ground recently in radiation oncology. To date, the most successful utilization of proton therapy is in head and neck cases as well as prostate cases. These tumor locations do not suffer from the resulting difficulties of treatment delivery as a result of respiratory motion. Lung tumors require either breath hold or motion tracking, neither of which have been assessed with an end-to-end phantom for proton treatments. Currently, the RPC does not have a dynamic thoracic phantom for proton therapy procedure assessment. Additionally, such a phantom could be an excellent means of assessing quality assurance of the procedures of proton therapy centers wishing to participate in clinical trials. An eventual goal of this phantom is to have a means of evaluating and auditing institutions for the ability to start clinical trials utilizing proton therapy procedures for lung cancers. Therefore, the hypothesis of this study is that a dynamic anthropomorphic thoracic phantom can be created to evaluate end-to-end proton therapy treatment procedures for lung cancer to assure agreement between the measured and calculated dose within 5% / 5 mm with a reproducibility of 2%. Multiple materials were assessed for thoracic heterogeneity equivalency. The phantom was designed from the materials found to be in greatest agreement. The phantom was treated in an end-to-end treatment four times, which included simulation, treatment planning and treatment delivery. Each treatment plan was delivered three times to assess reproducibility. The dose measured within the phantom was compared to that of the treatment plan. The hypothesis was fully supported for three of the treatment plans, but failed the reproducibility requirement for the most aggressive treatment plan.