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Title: SU-F-T-685: Evaluation of Tumor Hypoxic Fraction Using Serial Volumetric Imaging During Radiation Therapy

Abstract

Purpose: To develop a tumor response model which could be uses to compute tumor hypoxic fraction using serial volumetric tumor imaging. This algorithm may be used for treatment response assessment and also for guidance of more expensive PET imaging of hypoxia. Methods: Previously developed two-level cell population tumor response model was modified to include a third cell level describing hypoxic and necrotic cells. This third level was considered constant value during radiotherapy treatment; therefore, inclusion additional parameter did not compromise stability of model fitting to imaging data. Fitting the model to serial volumetric imaging data was performed using a least squares objective function and simulated annealing algorithm. The problem of reconstruction of radiobiological parameters from serial imaging data was considered as inverse ill-posed problem described by the Fredholm integral equation of the first kind. Variational regularization was used to stabilize solutions. Results: To evaluate performance of the algorithm, we used a set of serial CT imaging data on tumor-volume for 14 head and neck cancer patients. The hypoxic fractions were reconstructed for each patient and the distribution of hypoxic fractions was compared to the distribution of initial hypoxic fractions previously measured using histograph. The measured and reconstructed from imaging datamore » distributions of hypoxic fractions are in good agreement. The reconstructed distribution of cell surviving fraction was also in better agreement with in vitro data than previously obtained using the two-level cell population model. Conclusion: Our results indicate that it is possible to evaluate the initial hypoxic tumor fraction using serial volumetric imaging and a tumor response model. This algorithm can be used for treatment response assessment and guidance of more expensive PET imaging.« less

Authors:
 [1]
  1. University of Washington, Seattle, WA (United States)
Publication Date:
OSTI Identifier:
22649240
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 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; 61 RADIATION PROTECTION AND DOSIMETRY; ALGORITHMS; BIOMEDICAL RADIOGRAPHY; DISTRIBUTION; FREDHOLM EQUATION; LEAST SQUARE FIT; NEOPLASMS; POSITRON COMPUTED TOMOGRAPHY; RADIOTHERAPY; SIMULATION

Citation Formats

Chvetsov, A. SU-F-T-685: Evaluation of Tumor Hypoxic Fraction Using Serial Volumetric Imaging During Radiation Therapy. United States: N. p., 2016. Web. doi:10.1118/1.4956871.
Chvetsov, A. SU-F-T-685: Evaluation of Tumor Hypoxic Fraction Using Serial Volumetric Imaging During Radiation Therapy. United States. doi:10.1118/1.4956871.
Chvetsov, A. 2016. "SU-F-T-685: Evaluation of Tumor Hypoxic Fraction Using Serial Volumetric Imaging During Radiation Therapy". United States. doi:10.1118/1.4956871.
@article{osti_22649240,
title = {SU-F-T-685: Evaluation of Tumor Hypoxic Fraction Using Serial Volumetric Imaging During Radiation Therapy},
author = {Chvetsov, A},
abstractNote = {Purpose: To develop a tumor response model which could be uses to compute tumor hypoxic fraction using serial volumetric tumor imaging. This algorithm may be used for treatment response assessment and also for guidance of more expensive PET imaging of hypoxia. Methods: Previously developed two-level cell population tumor response model was modified to include a third cell level describing hypoxic and necrotic cells. This third level was considered constant value during radiotherapy treatment; therefore, inclusion additional parameter did not compromise stability of model fitting to imaging data. Fitting the model to serial volumetric imaging data was performed using a least squares objective function and simulated annealing algorithm. The problem of reconstruction of radiobiological parameters from serial imaging data was considered as inverse ill-posed problem described by the Fredholm integral equation of the first kind. Variational regularization was used to stabilize solutions. Results: To evaluate performance of the algorithm, we used a set of serial CT imaging data on tumor-volume for 14 head and neck cancer patients. The hypoxic fractions were reconstructed for each patient and the distribution of hypoxic fractions was compared to the distribution of initial hypoxic fractions previously measured using histograph. The measured and reconstructed from imaging data distributions of hypoxic fractions are in good agreement. The reconstructed distribution of cell surviving fraction was also in better agreement with in vitro data than previously obtained using the two-level cell population model. Conclusion: Our results indicate that it is possible to evaluate the initial hypoxic tumor fraction using serial volumetric imaging and a tumor response model. This algorithm can be used for treatment response assessment and guidance of more expensive PET imaging.},
doi = {10.1118/1.4956871},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: Combination of serial tumor imaging with radiobiological modeling can provide more accurate information on the nature of treatment response and what underlies resistance. The purpose of this article is to improve the algorithms related to imaging-based radiobilogical modeling of tumor response. Methods: Serial imaging of tumor response to radiation therapy represents a sum of tumor cell sensitivity, tumor growth rates, and the rate of cell loss which are not separated explicitly. Accurate treatment response assessment would require separation of these radiobiological determinants of treatment response because they define tumor control probability. We show that the problem of reconstruction ofmore » radiobiological parameters from serial imaging data can be considered as inverse ill-posed problem described by the Fredholm integral equation of the first kind because it is governed by a sum of several exponential processes. Therefore, the parameter reconstruction can be solved using regularization methods. Results: To study the reconstruction problem, we used a set of serial CT imaging data for the head and neck cancer and a two-level cell population model of tumor response which separates the entire tumor cell population in two subpopulations of viable and lethally damage cells. The reconstruction was done using a least squared objective function and a simulated annealing algorithm. Using in vitro data for radiobiological parameters as reference data, we shown that the reconstructed values of cell surviving fractions and potential doubling time exhibit non-physical fluctuations if no stabilization algorithms are applied. The variational regularization allowed us to obtain statistical distribution for cell surviving fractions and cell number doubling times comparable to in vitro data. Conclusion: Our results indicate that using variational regularization can increase the number of free parameters in the model and open the way to development of more advanced algorithms which take into account tumor heterogeneity, for example, related to hypoxia.« less
  • Variations of the hypoxic fraction (HF) after single dose (13 Gy or 4 Gy) and during fractionated (5 fractions of 4 Gy, 1 or 2 fractions per day) radiation therapy were studied in SCC VII tumors implanted subcutaneously in the hind legs of C3H/He/Jms mice using the paired survival curve method. Whole-body irradiation was delivered to tumor-bearing mice without anesthesia or physical restraint, because both are known to increase the HF artificially. The HF decreased after a single 13 Gy dose in a biphasic fashion: extremely rapidly within 1 hr and comparatively slowly during the following 12-72 hr. On themore » other hand, nearly no fall of HF was observed in 24 hr following a single 4 Gy dose. Also, reoxygenation was found to occur more rapidly in the interfraction period as the number of fractions of 4 Gy increased irrespective of differences of interfraction time. However, the HF just before each radiation fraction was significantly higher than the pretreatment level for both fractionated regimens. Thus, the reoxygenation patterns observed after single low and high doses of irradiation were different from each other, and reoxygenation in each interfraction period did not always proceed in a similar manner to that after single low dose irradiation. Reoxygenation was facilitated as fractionated radiation therapy proceeded, but it was not sufficient for the HF to remain at a level comparable to that before irradiation.« less
  • Purpose: Real-time tracking of implanted fiducials in cine megavoltage (MV) imaging during volumetric modulated arc therapy (VMAT) delivery is complicated due to the inherent low contrast of MV images and potential blockage of dynamic leaves configurations. The purpose of this work is to develop a clinically practical autodetection algorithm for motion management during VMAT. Methods: The expected field-specific segments and the planned fiducial position from the Eclipse (Varian Medical Systems, Palo Alto, CA) treatment planning system were projected onto the MV images. The fiducials were enhanced by applying a Laplacian of Gaussian filter in the spatial domain for each image,more » with a blob-shaped object as the impulse response. The search of implanted fiducials was then performed on a region of interest centered on the projection of the fiducial when it was within an open field including the case when it was close to the field edge or partially occluded by the leaves. A universal template formula was proposed for template matching and normalized cross correlation was employed for its simplicity and computational efficiency. The search region for every image was adaptively updated through a prediction model that employed the 3D position of the fiducial estimated from the localized positions in previous images. This prediction model allowed the actual fiducial position to be tracked dynamically and was used to initialize the search region. The artifacts caused by electronic interference during the acquisition were effectively removed. A score map was computed by combining both morphological information and image intensity. The pixel location with the highest score was selected as the detected fiducial position. The sets of cine MV images taken during treatment were analyzed with in-house developed software written in MATLAB (The Mathworks, Inc., Natick, MA). Five prostate patients were analyzed to assess the algorithm performance by measuring their positioning accuracy during treatment. Results: The algorithm was able to accurately localize the fiducial position on MV images with success rates of more than 90% per case. The percentage of images in which each fiducial was localized in the studied cases varied between 23% and 65%, with at least one fiducial having been localized between 40% and 95% of the images. This depended mainly on the modulation of the plan and fiducial blockage. The prostate movement in the presented cases varied between 0.8 and 3.5 mm (mean values). The maximum displacement detected among all patients was of 5.7 mm. Conclusions: An algorithm for automatic detection of fiducial markers in cine MV images has been developed and tested with five clinical cases. Despite the challenges posed by complex beam aperture shapes, fiducial localization close to the field edge, partial occlusion of fiducials, fast leaf and gantry movement, and inherently low MV image quality, good localization results were achieved in patient images. This work provides a technique for enabling real-time accurate fiducial detection and tumor tracking during VMAT treatments without the use of extra imaging dose.« less
  • The purpose of this study was to present the findings of the irradiated noncritical soft tissues of the female pelvis at magnetic resonance (MR) imaging within 18 months after radiation therapy (RT). The soft tissues of the pelvis of 24 women with advanced cervical carcinoma were studied in 240 MR examinations scheduled before, three times during, and 7 weeks and 3, 6, 9, 12, and 18 months after RT. Two radiologists visually evaluated the signal intensity (SI) of the subcutaneous fat, muscles, and presacral space (PS) on T1- and T2-weighted and short inversion time inversion-recovery images. SI compatible with edemamore » appeared in the PS, pelvic muscles, and subcutaneous fat within 3 months after the end of RT and was observed in 23 (96%) of the 24 patients. During the observation period, the edema subsided. Eighteen months after treatment, edema in the PS was seen in 12 (50%) of the 24 patients. The soft tissues of the female pelvis showed a characteristic pattern of varying edema after irradiation. 27 refs., 12 figs.« less
  • Purpose: To report findings from an in vivo dosimetry program implemented for all stereotactic body radiation therapy patients over a 31-month period and discuss the value and challenges of utilizing in vivo electronic portal imaging device (EPID) dosimetry clinically. Methods and Materials: From December 2013 to July 2016, 117 stereotactic body radiation therapy–volumetric modulated arc therapy patients (100 lung, 15 spine, and 2 liver) underwent 602 EPID-based in vivo dose verification events. A developed model-based dose reconstruction algorithm calculates the 3-dimensional dose distribution to the patient by back-projecting the primary fluence measured by the EPID during treatment. The EPID frame-averaging was optimized in Junemore » 2015. For each treatment, a 3%/3-mm γ comparison between our EPID-derived dose and the Eclipse AcurosXB–predicted dose to the planning target volume (PTV) and the ≥20% isodose volume were performed. Alert levels were defined as γ pass rates <85% (lung and liver) and <80% (spine). Investigations were carried out for all fractions exceeding the alert level and were classified as follows: EPID-related, algorithmic, patient setup, anatomic change, or unknown/unidentified errors. Results: The percentages of fractions exceeding the alert levels were 22.6% for lung before frame-average optimization and 8.0% for lung, 20.0% for spine, and 10.0% for liver after frame-average optimization. Overall, mean (± standard deviation) planning target volume γ pass rates were 90.7% ± 9.2%, 87.0% ± 9.3%, and 91.2% ± 3.4% for the lung, spine, and liver patients, respectively. Conclusions: Results from the clinical implementation of our model-based in vivo dose verification method using on-treatment EPID images is reported. The method is demonstrated to be valuable for routine clinical use for verifying delivered dose as well as for detecting errors.« less