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Title: MO-G-BRF-06: Radiotherapy and Prompt Oxygen Dynamics

Abstract

Purpose: Adaptive radiotherapy requires a knowledge of the changing local tumor oxygen concentrations for times on the order of the treatment time, a time scale far shorter than cell death and proliferation. This knowledge will be needed to guide hypofractionated radiotherapy. Methods: A diffuse optical probe system was developed to spatially average over the whole interior of athymic Sprague Dawley nude mouse xenografts of human head and neck cancers. The blood volume and hemoglobin saturation was measured in real time. The quantities were measured with spectral fitting before and after 10 Gy of radiation is applied. An MRI BOLD scan is acquired before and after 10 Gy that measures regional changes in R2* which is inversely proportional to oxygen availability. Simulations were performed to fit the blood oxygen dynamics and infer changes in hypoxia within the tumor. Results: The optical probe measured nearly constant blood volume and a significant drop in hemoglobin saturation of about 30% after 10 Gy over the time scale of less than 30 minutes. The averaged R2* within the tumor volume increased by 15% after the 10 Gy dose, which is consistent with the optical results. The simulations and experiments support likely dynamic metabolic changes and/ormore » fast vasoconstrictive signals are occurring that change the oxygen concentrations significantly, but not cell death or proliferation. Conclusion: Significant oxygen changes were observed to occur within 30 minutes, coinciding with the treatment time scale. This dynamic is very important for patient specific adaptive therapy. For hypofractionated therapy, the local instantaneous oxygen content is likely the most important variable to control. The invention of a bedside device for the purpose of measuring the instantaneous response to large radiation doses would be an important step to future improvements in outcome.« less

Authors:
; ; ; ; ; ; ; ;  [1];  [2]
  1. University of Wisconsin - Madison, Madison, WI (United States)
  2. Oregon Health ' Science University, Portland, OR (United States)
Publication Date:
OSTI Identifier:
22409616
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 41; Journal Issue: 6; Other Information: (c) 2014 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; APOPTOSIS; BLOOD; HEAD; HEMOGLOBIN; MICE; NECK; NEOPLASMS; NMR IMAGING; OXYGEN; RADIATION DOSES; RADIOTHERAPY

Citation Formats

Kissick, M, Campos, D, Adamson, E, Niles, D, Torres, A, L, Che Fru, Kimple, R, Fain, S, Kogel, A van der, and Jacques, S. MO-G-BRF-06: Radiotherapy and Prompt Oxygen Dynamics. United States: N. p., 2014. Web. doi:10.1118/1.4889198.
Kissick, M, Campos, D, Adamson, E, Niles, D, Torres, A, L, Che Fru, Kimple, R, Fain, S, Kogel, A van der, & Jacques, S. MO-G-BRF-06: Radiotherapy and Prompt Oxygen Dynamics. United States. doi:10.1118/1.4889198.
Kissick, M, Campos, D, Adamson, E, Niles, D, Torres, A, L, Che Fru, Kimple, R, Fain, S, Kogel, A van der, and Jacques, S. Sun . "MO-G-BRF-06: Radiotherapy and Prompt Oxygen Dynamics". United States. doi:10.1118/1.4889198.
@article{osti_22409616,
title = {MO-G-BRF-06: Radiotherapy and Prompt Oxygen Dynamics},
author = {Kissick, M and Campos, D and Adamson, E and Niles, D and Torres, A and L, Che Fru and Kimple, R and Fain, S and Kogel, A van der and Jacques, S},
abstractNote = {Purpose: Adaptive radiotherapy requires a knowledge of the changing local tumor oxygen concentrations for times on the order of the treatment time, a time scale far shorter than cell death and proliferation. This knowledge will be needed to guide hypofractionated radiotherapy. Methods: A diffuse optical probe system was developed to spatially average over the whole interior of athymic Sprague Dawley nude mouse xenografts of human head and neck cancers. The blood volume and hemoglobin saturation was measured in real time. The quantities were measured with spectral fitting before and after 10 Gy of radiation is applied. An MRI BOLD scan is acquired before and after 10 Gy that measures regional changes in R2* which is inversely proportional to oxygen availability. Simulations were performed to fit the blood oxygen dynamics and infer changes in hypoxia within the tumor. Results: The optical probe measured nearly constant blood volume and a significant drop in hemoglobin saturation of about 30% after 10 Gy over the time scale of less than 30 minutes. The averaged R2* within the tumor volume increased by 15% after the 10 Gy dose, which is consistent with the optical results. The simulations and experiments support likely dynamic metabolic changes and/or fast vasoconstrictive signals are occurring that change the oxygen concentrations significantly, but not cell death or proliferation. Conclusion: Significant oxygen changes were observed to occur within 30 minutes, coinciding with the treatment time scale. This dynamic is very important for patient specific adaptive therapy. For hypofractionated therapy, the local instantaneous oxygen content is likely the most important variable to control. The invention of a bedside device for the purpose of measuring the instantaneous response to large radiation doses would be an important step to future improvements in outcome.},
doi = {10.1118/1.4889198},
journal = {Medical Physics},
number = 6,
volume = 41,
place = {United States},
year = {Sun Jun 15 00:00:00 EDT 2014},
month = {Sun Jun 15 00:00:00 EDT 2014}
}
  • Purpose: PET-guided dynamic tumor tracking is a novel concept of biologically targeted image guidance for radiotherapy. A dynamic tumor tracking algorithm based on list-mode PET data has been developed and previously tested on dynamic phantom data. In this study, we investigate if dynamic tumor tracking is clinically feasible by applying the method to lung cancer patient PET data. Methods: PET-guided tumor tracking estimates the target position of a segmented volume in PET images reconstructed continuously from accumulated coincidence events correlated with external respiratory motion, simulating real-time applications, i.e., only data up to the current time point is used to estimatemore » the target position. A target volume is segmented with a 50% threshold, consistently, of the maximum intensity in the predetermined volume of interest. Through this algorithm, the PET-estimated trajectories are quantified from four lung cancer patients who have distinct tumor location and size. The accuracy of the PET-estimated trajectories is evaluated by comparing to external respiratory motion because the ground-truth of tumor motion is not known in patients; however, previous phantom studies demonstrated sub-2mm accuracy using clinically derived 3D tumor motion. Results: The overall similarity of motion patterns between the PET-estimated trajectories and the external respiratory traces implies that the PET-guided tracking algorithm can provide an acceptable level of targeting accuracy. However, there are variations in the tracking accuracy between tumors due to the quality of the segmentation which depends on target-to-background ratio, tumor location and size. Conclusion: For the first time, a dynamic tumor tracking algorithm has been applied to lung cancer patient PET data, demonstrating clinical feasibility of real-time tumor tracking for integrated PET-linacs. The target-to-background ratio is a significant factor determining accuracy: screening during treatment planning would enable appropriate patient selection for PET-guided dynamic tumor tracking in radiotherapy.« less
  • Purpose: Accurate calibration of radiobiological parameters is crucial to predicting radiation treatment response. Modeling differences may have a significant impact on calibrated parameters. In this study, we have integrated two existing models with kinetic differential equations to formulate a new tumor regression model for calibrating radiobiological parameters for individual patients. Methods: A system of differential equations that characterizes the birth-and-death process of tumor cells in radiation treatment was analytically solved. The solution of this system was used to construct an iterative model (Z-model). The model consists of three parameters: tumor doubling time Td, half-life of dying cells Tr and cellmore » survival fraction SFD under dose D. The Jacobian determinant of this model was proposed as a constraint to optimize the three parameters for six head and neck cancer patients. The derived parameters were compared with those generated from the two existing models, Chvetsov model (C-model) and Lim model (L-model). The C-model and L-model were optimized with the parameter Td fixed. Results: With the Jacobian-constrained Z-model, the mean of the optimized cell survival fractions is 0.43±0.08, and the half-life of dying cells averaged over the six patients is 17.5±3.2 days. The parameters Tr and SFD optimized with the Z-model differ by 1.2% and 20.3% from those optimized with the Td-fixed C-model, and by 32.1% and 112.3% from those optimized with the Td-fixed L-model, respectively. Conclusion: The Z-model was analytically constructed from the cellpopulation differential equations to describe changes in the number of different tumor cells during the course of fractionated radiation treatment. The Jacobian constraints were proposed to optimize the three radiobiological parameters. The developed modeling and optimization methods may help develop high-quality treatment regimens for individual patients.« less
  • Purpose: Intrafraction tumor deformation limits targeting accuracy in radiotherapy and cannot be adapted to by current motion management techniques. This study simulated intrafractional treatment adaptation to tumor deformations using a dynamic Multi-Leaf Collimator (DMLC) tracking system during Intensity-modulated radiation therapy (IMRT) treatment for the first time. Methods: The DMLC tracking system was developed to adapt to the intrafraction tumor deformation by warping the planned beam aperture guided by the calculated deformation vector field (DVF) obtained from deformable image registration (DIR) at the time of treatment delivery. Seven single phantom deformation images up to 10.4 mm deformation and eight tumor systemmore » phantom deformation images up to 21.5 mm deformation were acquired and used in tracking simulation. The intrafraction adaptation was simulated at the DMLC tracking software platform, which was able to communicate with the image registration software, reshape the instantaneous IMRT field aperture and log the delivered MLC fields.The deformation adaptation accuracy was evaluated by a geometric target coverage metric defined as the sum of the area incorrectly outside and inside the reference aperture. The incremental deformations were arbitrarily determined to take place equally over the delivery interval. The geometric target coverage of delivery with deformation adaptation was compared against the delivery without adaptation. Results: Intrafraction deformation adaptation during dynamic IMRT plan delivery was simulated for single and system deformable phantoms. For the two particular delivery situations, over the treatment course, deformation adaptation improved the target coverage by 89% for single target deformation and 79% for tumor system deformation compared with no-tracking delivery. Conclusion: This work demonstrated the principle of real-time tumor deformation tracking using a DMLC. This is the first step towards the development of an image-guided radiotherapy system to treat deforming tumors in real-time. The authors acknowledge funding support from the Australian NHMRC Australia Fellowship, Cure Cancer Australia Foundation, NHMRC Project Grant APP1042375 and US NIH/NCI R01CA93626.« less
  • Purpose: PET-based texture features are used to quantify tumor heterogeneity due to their predictive power in treatment outcome. We investigated the sensitivity of texture features to tumor motion by comparing whole body (3D) and respiratory-gated (4D) PET imaging. Methods: Twenty-six patients (34 lesions) received 3D and 4D [F-18]FDG-PET scans before chemo-radiotherapy. The acquired 4D data were retrospectively binned into five breathing phases to create the 4D image sequence. Four texture features (Coarseness, Contrast, Busyness, and Complexity) were computed within the the physician-defined tumor volume. The relative difference (δ) in each measure between the 3D- and 4D-PET imaging was calculated. Wilcoxonmore » signed-rank test (p<0.01) was used to determine if δ was significantly different from zero. Coefficient of variation (CV) was used to determine the variability in the texture features between all 4D-PET phases. Pearson correlation coefficient was used to investigate the impact of tumor size and motion amplitude on δ. Results: Significant differences (p<<0.01) between 3D and 4D imaging were found for Coarseness, Busyness, and Complexity. The difference for Contrast was not significant (p>0.24). 4D-PET increased Busyness (∼20%) and Complexity (∼20%), and decreased Coarseness (∼10%) and Contrast (∼5%) compared to 3D-PET. Nearly negligible variability (CV=3.9%) was found between the 4D phase bins for Coarseness and Complexity. Moderate variability was found for Contrast and Busyness (CV∼10%). Poor correlation was found between the tumor volume and δ for the texture features (R=−0.34−0.34). Motion amplitude had moderate impact on δ for Contrast and Busyness (R=−0.64− 0.54) and no impact for Coarseness and Complexity (R=−0.29−0.17). Conclusion: Substantial differences in textures were found between 3D and 4D-PET imaging. Moreover, the variability between phase bins for Coarseness and Complexity was negligible, suggesting that similar quantification can be obtained from all phases. Texture features, blurred out by respiratory motion during 3D-PET acquisition, can be better resolved by 4D-PET imaging with any phase.« less
  • Purpose: We have previously identified a prediction model of lung metastases at diagnosis of soft-tissue sarcomas (STS) that is composed of two textural features extracted from FDG-PET and T1-weighted (T1w) MRI scans. The goal of this study is to evaluate whether the optimization in FDGPET and MRI acquisition parameters would enhance the prediction performance of texture-based models. Methods: Ten FDG-PET and T1w- MRI digitized tumor models were generated from imaging data of STS patients who underwent pre-treatment clinical scans between 2005 and 2011. Five of ten patients eventually developed lung metastases. Numerically simulated MR images were produced using echo timesmore » (TE) of 2 and 4 times the nominal clinical parameter (TEc), and repetition times (TR) of 0.5, 0.67, 1.5 and 2 times the nominal clinical parameter (TRc) found in the DICOM headers (TEc range: 9–13 ms, TRc range: 410-667 ms). PET 2D images were simulated using Monte-Carlo and were reconstructed using an ordered-subsets expectation maximization (OSEM) algorithm with 1 to 32 iterations and a post-reconstruction Gaussian filter of 0, 2, 4 or 6 mm width. For all possible combinations of PET and MRI acquisition parameters, the prediction model was constructed using logistic regression with new coefficients, and its associated prediction performance for lung metastases was evaluated using the area under the ROC curve (AUC). Results: The prediction performance over all simulations yielded AUCs ranging from 0.7 to 1. Notably, TR values below or equal to TRc and higher PET post-reconstruction filter widths yielded higher prediction performance. The best results were obtained with a combination of 4*TEc, TRc, 30 OSEM iterations and 2mm filter width. Conclusion: This work indicates that texture-based metastasis prediction models could be improved using optimized choices of FDG-PET and MRI acquisition protocols. This principle could be generalized to other texture-based models.« less