Evaluation of PRESAGE® dosimeters for brachytherapy sources and the 3D dosimetry and characterization of the new AgX100 125I seed model

With continuous new improvements in brachytherapy source designs and techniques, method of 3D dosimetry for treatment dose verifications would better ensure accurate patient radiotherapy treatment. This study was aimed to first evaluate the 3D dose distributions of the low-dose rate (LDR) Amersham 6711 OncoseedTM using PRESAGE® dosimeters to establish PRESAGE® as a suitable brachytherapy dosimeter. The new AgX100 125I seed model (Theragenics Corporation) was then characterized using PRESAGE® following the TG-43 protocol. PRESAGE® dosimeters are solid, polyurethane-based, 3D dosimeters doped with radiochromic leuco dyes that produce a linear optical density response to radiation dose. For this project, the radiochromic response in PRESAGE® was captured using optical-CT scanning (632 nm) and the final 3D dose matrix was reconstructed using the MATLAB software. An Amersham 6711 seed with an air-kerma strength of approximately 9 U was used to irradiate two dosimeters to 2 Gy and 11 Gy at 1 cm to evaluate dose rates in the r=1 cm to r=5 cm region. The dosimetry parameters were compared to the values published in the updated AAPM Report No. 51 (TG-43U1). An AgX100 seed with an air-kerma strength of about 6 U was used to irradiate two dosimeters to 3.6 Gy and 12.5 Gy at 1 cm. The dosimetry parameters for the AgX100 were compared to the values measured from previous Monte-Carlo and experimental studies. In general, the measured dose rate constant, anisotropy function, and radial dose function for the Amersham 6711 showed agreements better than 5% compared to consensus values in the r=1 to r=3 cm region. The dose rates and radial dose functions measured for the AgX100 agreed with the MCNPX and TLD-measured values within 3% in the r=1 to r=3 cm region. The measured anisotropy function in PRESAGE® showed relative differences of up to 9% with the MCNPX calculated values. It was determined that post-irradiation optical density change over several days was non-linear in different dose regions, and therefore the dose values in the r=4 to r=5 cm regions had higher uncertainty due to this effect. This study demonstrated that within the radial distance of 3 cm, brachytherapy dosimetry in PRESAGE® can be accurate within 5% as long as irradiation times are within 48 hours.

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.