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At least 613 records · Page 34

TH-E-BRF-05: Comparison of Survival-Time Prediction Models After Radiotherapy for High-Grade Glioma Patients Based On Clinical and DVH Features

Purpose: Although many outcome prediction models based on dose-volume information have been proposed, it is well known that the prognosis may be affected also by multiple clinical factors. The purpose of this study is to predict the survival time after radiotherapy for high-grade glioma patients based on features including clinical and dose-volume histogram (DVH) information. Methods: A total of 35 patients with high-grade glioma (oligodendroglioma: 2, anaplastic astrocytoma: 3, glioblastoma: 30) were selected in this study. All patients were treated with prescribed dose of 30–80 Gy after surgical resection or biopsy from 2006 to 2013 at The University of Tokyo Hospital. All cases were randomly separated into training dataset (30 cases) and test dataset (5 cases). The survival time after radiotherapy was predicted based on a multiple linear regression analysis and artificial neural network (ANN) by using 204 candidate features. The candidate features included the 12 clinical features (tumor location, extent of surgical resection, treatment duration of radiotherapy, etc.), and the 192 DVH features (maximum dose, minimum dose, D95, V60, etc.). The effective features for the prediction were selected according to a step-wise method by using 30 training cases. The prediction accuracy was evaluated by a coefficient of determination (R{sup 2}) between the predicted and actual survival time for the training and test dataset. Results: In the multiple regression analysis, the value of R{sup 2} between the predicted and actual survival time was 0.460 for the training dataset and 0.375 for the test dataset. On the other hand, in the ANN analysis, the value of R{sup 2} was 0.806 for the training dataset and 0.811 for the test dataset. Conclusion: Although a large number of patients would be needed for more accurate and robust prediction, our preliminary Result showed the potential to predict the outcome in the patients with high-grade glioma. This work was partly supported by the JSPS Core-to-Core Program(No. 23003) and Grant-in-aid from the JSPS Fellows.

60 APPLIED LIFE SCIENCES↗

SU-C-17A-01: MRI-Based Radiotherapy Treatment Planning In Pelvis

Purpose: To support radiotherapy dose calculation, synthetic CT (MRCT) image volumes need to represent the electron density of tissues with sufficient accuracy. This study compares CT and MRCT for pelvic radiotherapy. Methods: CT and multi-contrast MRI acquired using T1- based Dixon, T2 TSE, and PETRA sequences were acquired on an IRBapproved protocol patient. A previously published method was used to create a MRCT image volume by applying fuzzy classification on T1- weighted and calculated water image volumes (air and fluid voxels were excluded using thresholds applied to PETRA and T2-weighted images). The correlation of pelvic bone intensity between CT and MRCT was investigated. Two treatment plans, based on CT and MRCT, were performed to mimic treatment for: (a) pelvic bone metastasis with a 16MV parallel beam arrangement, and (b) gynecological cancer with 6MV volumetric modulated arc therapy (VMAT) using two full arcs. The CT-calculated fluence maps were used to recalculate doses using the MRCT-derived density grid. The dose-volume histograms and dose distributions were compared. Results: Bone intensities in the MRCT volume correlated linearly with CT intensities up to 800 HU (containing 96% of the bone volume), and then decreased with CT intensity increase (4% volume). There was no significant difference in dose distributions between CT- and MRCTbased plans, except for the rectum and bladder, for which the V45 differed by 15% and 9%, respectively. These differences may be attributed to normal and visualized organ movement and volume variations between CT and MR scans. Conclusion: While MRCT had lower bone intensity in highly-dense bone, this did not cause significant dose deviations from CT due to its small percentage of volume. These results indicate that treatment planning using MRCT could generate comparable dose distributions to that using CT, and further demonstrate the feasibility of using MRI-alone to support Radiation Oncology workflow. NIH R01EB016079.

60 APPLIED LIFE SCIENCES↗

Independent dosimetric assessment of the model EP917 episcleral brachytherapy plaque

Purpose: To investigate the influence of slot design on dose distributions and dose-volume histograms (DVHs) for the model EP917 plaque for episcleral brachytherapy. Methods: Dimensions and orientations of the slots were measured for three model EP917 plaques and compared to data in the Plaque Simulator (PS) treatment planning software (version 5.7.6). These independently determined coordinates were incorporated into the MCNP Monte Carlo simulation environment to obtain dose from the plaques in a water environment and in a clinical environment with ocular structures. A tumor volume was simulated as 5 mm in apical height and 11 mm in basal diameter. Variations in plaque mass density and composition; slot length, width, and depth; seed positioning; and Ag-marker rod positioning were simulated to examine their influence on plaque central axis (CAX) and planar dose distributions, and DVHs. Results: Seed shifts in a single slot toward the eye and shifts of the{sup 125}I-coated Ag rod within the capsule had the greatest impact on CAX dose distribution. A shift of 0.0994 mm toward the eye increased dose by 14%, 9%, 4.3%, and 2.7% at 1, 2, 5, and 10 mm, respectively, from the inner sclera. When examining the fully-modeled plaque in the ocular geometry, the largest dose variations were caused by shifting the Ag rods toward the sclera and shifting the seeds away from the globe when the slots were made 0.51 mm deeper, causing +34.3% and −69.4% dose changes to the outer sclera, respectively. At points along the CAX, dose from the full plaque geometry using the measured slot design was 2.4% ± 1.1% higher than the manufacturer-provided slot design and 2.2% ± 2.3% higher than the homogeneous calculation of PS treatment planning results. The ratio of D{sub 10} values for the measured slot design to the D{sub 10} values for the manufacturer-provided slot design was higher by 9%, 10%, and 19% for the tumor, inner sclera, and outer sclera, respectively. In comparison to the measured slot design, a theoretical plaque having narrower and deeper slots delivered 30%, 37%, and 62% lower D{sub 10} doses to the tumor, inner sclera, and outer sclera, respectively. Conclusions: While the measured positions of the slots on the model EP917 plaque were in close agreement (<0.7 mm) with the PS values, small differences in the slot shape caused substantial differences in dose distributions and DVH metrics. Increasing slot depth by 0.1 mm decreased outer scleral dose by 20%, yet shifting the Ag rods in the seeds toward the globe by 0.1 mm increased outer scleral dose by 35%. The clinical medical physicist is advised to measure these types of plaques upon acceptance testing before clinical use to inspect slot shape and position for comparison with data used for treatment planning purposes.

60 APPLIED LIFE SCIENCES↗

Comparison of internal dose estimates obtained using organ-level, voxel S value, and Monte Carlo techniques

Purpose: The authors’ objective was to compare internal dose estimates obtained using the Organ Level Dose Assessment with Exponential Modeling (OLINDA/EXM) software, the voxel S value technique, and Monte Carlo simulation. Monte Carlo dose estimates were used as the reference standard to assess the impact of patient-specific anatomy on the final dose estimate. Methods: Six patients injected with{sup 99m}Tc-hydrazinonicotinamide-Tyr{sup 3}-octreotide were included in this study. A hybrid planar/SPECT imaging protocol was used to estimate {sup 99m}Tc time-integrated activity coefficients (TIACs) for kidneys, liver, spleen, and tumors. Additionally, TIACs were predicted for {sup 131}I, {sup 177}Lu, and {sup 90}Y assuming the same biological half-lives as the {sup 99m}Tc labeled tracer. The TIACs were used as input for OLINDA/EXM for organ-level dose calculation and voxel level dosimetry was performed using the voxel S value method and Monte Carlo simulation. Dose estimates for {sup 99m}Tc, {sup 131}I, {sup 177}Lu, and {sup 90}Y distributions were evaluated by comparing (i) organ-level S values corresponding to each method, (ii) total tumor and organ doses, (iii) differences in right and left kidney doses, and (iv) voxelized dose distributions calculated by Monte Carlo and the voxel S value technique. Results: The S values for all investigated radionuclides used by OLINDA/EXM and the corresponding patient-specific S values calculated by Monte Carlo agreed within 2.3% on average for self-irradiation, and differed by as much as 105% for cross-organ irradiation. Total organ doses calculated by OLINDA/EXM and the voxel S value technique agreed with Monte Carlo results within approximately ±7%. Differences between right and left kidney doses determined by Monte Carlo were as high as 73%. Comparison of the Monte Carlo and voxel S value dose distributions showed that each method produced similar dose volume histograms with a minimum dose covering 90% of the volume (D90) agreeing within ±3%, on average. Conclusions: Several aspects of OLINDA/EXM dose calculation were compared with patient-specific dose estimates obtained using Monte Carlo. Differences in patient anatomy led to large differences in cross-organ doses. However, total organ doses were still in good agreement since most of the deposited dose is due to self-irradiation. Comparison of voxelized doses calculated by Monte Carlo and the voxel S value technique showed that the 3D dose distributions produced by the respective methods are nearly identical.

60 APPLIED LIFE SCIENCES↗

Poster — Thur Eve — 32: Stereotactic Body Radiation Therapy for Peripheral Lung Lesion: Treatment Planning and Quality Assurance

Stereotactic body radiation therapy (SBRT), due to its high precision for target localizing, has become widely used to treat tumours at various locations, including the lungs. Lung SBRT program was started at our institution a year ago. Eighteen patients with peripheral lesions up to 3 cm diameter have been treated with 48 Gy in 4 fractions. Based on four-dimensional computed tomography (4DCT) simulation, internal target volume (ITV) was delineated to encompass the respiratory motion of the lesion. A margin of 5 mm was then added to create the planning target volume (PTV) for setup uncertainties. There was no expansion from gross tumour volume (GTV) to clinical target volume (CTV). Pinnacle 9.6 was used as the primary treatment planning system. Volumetric modulated arc therapy (VMAT) technique, with one or two coplanar arcs, generally worked well. For quality assurance (QA), each plan was exported to Eclipse 10 and dose calculation was repeated. Dose volume histograms (DVHs) of the targets and organs at risk (OARs) were then compared between the two treatment planning systems. Winston-Lutz tests were carried out as routine machine QA. Patient-specific QA included ArcCheck measurement with an insert, where an ionization chamber was placed at the centre to measure dose at the isocenter. For the first several patients, and subsequently for the plans with extremely strong modulation, Gafchromic film dosimetry was also employed. For each patient, a mock setup was scheduled prior to treatments. Daily pre- and post-CBCT were acquired for setup and assessment of intra-fractional motion, respectively.

60 APPLIED LIFE SCIENCES↗

Poster — Thur Eve — 35: The impact of intensity- and energy-modulated photon radiotherapy (XMRT) optimization on a variety of organ geometries

We previously reported on a novel, modulated in both energy and intensity; photon radiotherapy (XMRT) optimization technique. The purpose of this investigation was to test this XMRT optimization against conventional intensity modulated radiotherapy (IMRT) optimization on four different organ test geometries. All geometries mimicked clinically relevant scenarios. Both IMRT and XMRT were based on a linear programming approach where the objective function was the mean dose to healthy organs and organ-specific linear dose-point constraints were used. For IMRT, the beam energy was fixed to 6 MV while XMRT optimized in terms of both 6 and 18 MV beams. All plans consisted of a seven beam coplanar arrangement. All organ geometries were contoured on a 25cm diameter cylindrical water phantom in open source radiotherapy research software known as CERR. Solutions for both IMRT and XMRT were obtained for each geometry using a numerical solver Gurobi. Analyzing the quality of the solutions was done by comparing dose distributions and dose volume histograms calculated using CERR. For all four geometries, IMRT and XMRT solutions were comparable in terms of target coverage. For two of the geometries, IMRT provided an advantage in terms of reduced dose to the healthy structures. XMRT showed improved dose reduction to healthy organs for one geometry and a comparable dose distribution to IMRT for the remaining geometry. The inability to exploit the benefits of using multiple energies may be attributed to limited water phantom diameter and having the majority of the organs in close proximity to the transverse axis.

60 APPLIED LIFE SCIENCES↗

Sci—Thur AM: YIS - 11: Estimation of Bladder-Wall Cumulative Dose in Multi-Fraction Image-Based Gynaecological Brachytherapy Using Deformable Point Set Registration

Dosimetric parameters based on dose-volume histograms (DVH) of contoured structures are routinely used to evaluate dose delivered to target structures and organs at risk. However, the DVH provides no information on the spatial distribution of the dose in situations of repeated fractions with changes in organ shape or size. The aim of this research was to develop methods to more accurately determine geometrically localized, cumulative dose to the bladder wall in intracavitary brachytherapy for cervical cancer. The CT scans and treatment plans of 20 cervical cancer patients were used. Each patient was treated with five high-dose-rate (HDR) brachytherapy fractions of 600cGy prescribed dose. The bladder inner and outer surfaces were delineated using MIM Maestro software (MIM Software Inc.) and were imported into MATLAB (MathWorks) as 3-dimensional point clouds constituting the “bladder wall”. A point-set registration toolbox for MATLAB, Coherent Point Drift (CPD), was used to non-rigidly transform the bladder-wall points from four of the fractions to the coordinate system of the remaining (reference) fraction, which was chosen to be the emptiest bladder for each patient. The doses were accumulated on the reference fraction and new cumulative dosimetric parameters were calculated. The LENT-SOMA toxicity scores of these patients were studied against the cumulative dose parameters. Based on this study, there was no significant correlation between the toxicity scores and the determined cumulative dose parameters.

60 APPLIED LIFE SCIENCES↗

Poster — Thur Eve — 15: Improvements in the stability of the tomotherapy imaging beam

Use of helical TomoTherapy based MVCT imaging for adaptive planning requires the image values (HU) to remain stable over the course of treatment. In the past, the image value stability was suboptimal, which required frequent change to the image value to density calibration curve to avoid dose errors on the order of 2–4%. The stability of the image values at our center was recently improved by stabilizing the dose rate of the machine (dose control servo) and performing daily MVCT calibration corrections. In this work, we quantify the stability of the image values over treatment time by comparing patient treatment image density derived using MVCT and KVCT. The analysis includes 1) MVCT - KVCT density difference histogram, 2) MVCT vs KVCT density spectrum, 3) multiple average profile density comparison and 4) density difference in homogeneous locations. Over two months, the imaging beam stability was compromised several times due to a combination of target wobbling, spectral calibration, target change and magnetron issues. The stability of the image values were analyzed over the same period. Results show that the impact on the patient dose calculation is 0.7% +− 0.6%.

60 APPLIED LIFE SCIENCES↗

Dosimetric feasibility of real-time MRI-guided proton therapy

Purpose: Magnetic resonance imaging (MRI) is a prime candidate for image-guided radiotherapy. This study was designed to assess the feasibility of real-time MRI-guided proton therapy by quantifying the dosimetric effects induced by the magnetic field in patients’ plans and identifying the associated clinical consequences. Methods: Monte Carlo dose calculation was performed for nine patients of various treatment sites (lung, liver, prostate, brain, skull-base, and spine) and tissue homogeneities, in the presence of 0.5 and 1.5 T magnetic fields. Dose volume histogram (DVH) parameters such as D{sub 95}, D{sub 5}, and V{sub 20} as well as equivalent uniform dose were compared for the target and organs at risk, before and after applying the magnetic field. The authors further assessed whether the plans affected by clinically relevant dose distortions could be corrected independent of the planning system. Results: By comparing the resulting dose distributions and analyzing the respective DVHs, it was determined that despite the observed lateral beam deflection, for magnetic fields of up to 0.5 T, neither was the target coverage jeopardized nor was the dose to the nearby organs increased in all cases except for prostate. However, for a 1.5 T magnetic field, the dose distortions were more pronounced and of clinical concern in all cases except for spine. In such circumstances, the target was severely underdosed, as indicated by a decrease in D{sub 95} of up to 41% of the prescribed dose compared to the nominal situation (no magnetic field). Sites such as liver and spine were less affected due to higher tissue homogeneity, typically smaller beam range, and the choice of beam directions. Simulations revealed that small modifications to certain plan parameters such as beam isocenter (up to 19 mm) and gantry angle (up to 10°) are sufficient to compensate for the magnetic field-induced dose disturbances. The authors’ observations indicate that the degree of required corrections strongly depends on the beam range and direction relative to the magnetic field. This method was also applicable to more heterogeneous scenarios such as skull-base tumors. Conclusions: This study confirmed the dosimetric feasibility of real-time MRI-guided proton therapy and delivering a clinically acceptable dose to patients with various tumor locations within magnetic fields of up to 1.5 T. This work could serve as a guide and encouragement for further efforts toward clinical implementation of hybrid MRI–proton gantry systems.

60 APPLIED LIFE SCIENCES↗

A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system

Purpose: Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. Methods: An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. Results: For relatively large and complex three-field head and neck cases, i.e., >100 000 spots with a target volume of ∼1000 cm{sup 3} and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. Conclusions: A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45 000 dollars. The fast calculation and optimization make the system easily expandable to robust and multicriteria optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Segmentation-free empirical beam hardening correction for CT

Purpose: The polychromatic nature of the x-ray beams and their effects on the reconstructed image are often disregarded during standard image reconstruction. This leads to cupping and beam hardening artifacts inside the reconstructed volume. To correct for a general cupping, methods like water precorrection exist. They correct the hardening of the spectrum during the penetration of the measured object only for the major tissue class. In contrast, more complex artifacts like streaks between dense objects need other techniques of correction. If using only the information of one single energy scan, there are two types of corrections. The first one is a physical approach. Thereby, artifacts can be reproduced and corrected within the original reconstruction by using assumptions in a polychromatic forward projector. These assumptions could be the used spectrum, the detector response, the physical attenuation and scatter properties of the intersected materials. A second method is an empirical approach, which does not rely on much prior knowledge. This so-called empirical beam hardening correction (EBHC) and the previously mentioned physical-based technique are both relying on a segmentation of the present tissues inside the patient. The difficulty thereby is that beam hardening by itself, scatter, and other effects, which diminish the image quality also disturb the correct tissue classification and thereby reduce the accuracy of the two known classes of correction techniques. The herein proposed method works similar to the empirical beam hardening correction but does not require a tissue segmentation and therefore shows improvements on image data, which are highly degraded by noise and artifacts. Furthermore, the new algorithm is designed in a way that no additional calibration or parameter fitting is needed. Methods: To overcome the segmentation of tissues, the authors propose a histogram deformation of their primary reconstructed CT image. This step is essential for the proposed algorithm to be segmentation-free (sf). This deformation leads to a nonlinear accentuation of higher CT-values. The original volume and the gray value deformed volume are monochromatically forward projected. The two projection sets are then monomially combined and reconstructed to generate sets of basis volumes which are used for correction. This is done by maximization of the image flatness due to adding additionally a weighted sum of these basis images. sfEBHC is evaluated on polychromatic simulations, phantom measurements, and patient data. The raw data sets were acquired by a dual source spiral CT scanner, a digital volume tomograph, and a dual source micro CT. Different phantom and patient data were used to illustrate the performance and wide range of usability of sfEBHC across different scanning scenarios. The artifact correction capabilities are compared to EBHC. Results: All investigated cases show equal or improved image quality compared to the standard EBHC approach. The artifact correction is capable of correcting beam hardening artifacts for different scan parameters and scan scenarios. Conclusions: sfEBHC generates beam hardening-reduced images and is furthermore capable of dealing with images which are affected by high noise and strong artifacts. The algorithm can be used to recover structures which are hardly visible inside the beam hardening-affected regions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Validation of a deformable image registration technique for cone beam CT-based dose verification

Purpose: As radiation therapy evolves toward more adaptive techniques, image guidance plays an increasingly important role, not only in patient setup but also in monitoring the delivered dose and adapting the treatment to patient changes. This study aimed to validate a method for evaluation of delivered intensity modulated radiotherapy (IMRT) dose based on multimodal deformable image registration (DIR) for prostate treatments. Methods: A pelvic phantom was scanned with CT and cone-beam computed tomography (CBCT). Both images were digitally deformed using two realistic patient-based deformation fields. The original CT was then registered to the deformed CBCT resulting in a secondary deformed CT. The registration quality was assessed as the ability of the DIR method to recover the artificially induced deformations. The primary and secondary deformed CT images as well as vector fields were compared to evaluate the efficacy of the registration method and it’s suitability to be used for dose calculation. PLASTIMATCH, a free and open source software was used for deformable image registration. A B-spline algorithm with optimized parameters was used to achieve the best registration quality. Geometric image evaluation was performed through voxel-based Hounsfield unit (HU) and vector field comparison. For dosimetric evaluation, IMRT treatment plans were created and optimized on the original CT image and recomputed on the two warped images to be compared. The dose volume histograms were compared for the warped structures that were identical in both warped images. This procedure was repeated for the phantom with full, half full, and empty bladder. Results: The results indicated mean HU differences of up to 120 between registered and ground-truth deformed CT images. However, when the CBCT intensities were calibrated using a region of interest (ROI)-based calibration curve, these differences were reduced by up to 60%. Similarly, the mean differences in average vector field lengths decreased from 10.1 to 2.5 mm when CBCT was calibrated prior to registration. The results showed no dependence on the level of bladder filling. In comparison with the dose calculated on the primary deformed CT, differences in mean dose averaged over all organs were 0.2% and 3.9% for dose calculated on the secondary deformed CT with and without CBCT calibration, respectively, and 0.5% for dose calculated directly on the calibrated CBCT, for the full-bladder scenario. Gamma analysis for the distance to agreement of 2 mm and 2% of prescribed dose indicated a pass rate of 100% for both cases involving calibrated CBCT and on average 86% without CBCT calibration. Conclusions: Using deformable registration on the planning CT images to evaluate the IMRT dose based on daily CBCTs was found feasible. The proposed method will provide an accurate dose distribution using planning CT and pretreatment CBCT data, avoiding the additional uncertainties introduced by CBCT inhomogeneity and artifacts. This is a necessary initial step toward future image-guided adaptive radiotherapy of the prostate.

60 APPLIED LIFE SCIENCES↗

A voxel-based multiscale model to simulate the radiation response of hypoxic tumors

Purpose: In radiotherapy, it is important to predict the response of tumors to irradiation prior to the treatment. This is especially important for hypoxic tumors, which are known to be highly radioresistant. Mathematical modeling based on the dose distribution, biological parameters, and medical images may help to improve this prediction and to optimize the treatment plan. Methods: A voxel-based multiscale tumor response model for simulating the radiation response of hypoxic tumors was developed. It considers viable and dead tumor cells, capillary and normal cells, as well as the most relevant biological processes such as (i) proliferation of tumor cells, (ii) hypoxia-induced angiogenesis, (iii) spatial exchange of cells leading to tumor growth, (iv) oxygen-dependent cell survival after irradiation, (v) resorption of dead cells, and (vi) spatial exchange of cells leading to tumor shrinkage. Oxygenation is described on a microscopic scale using a previously published tumor oxygenation model, which calculates the oxygen distribution for each voxel using the vascular fraction as the most important input parameter. To demonstrate the capabilities of the model, the dependence of the oxygen distribution on tumor growth and radiation-induced shrinkage is investigated. In addition, the impact of three different reoxygenation processes is compared and tumor control probability (TCP) curves for a squamous cells carcinoma of the head and neck (HNSSC) are simulated under normoxic and hypoxic conditions. Results: The model describes the spatiotemporal behavior of the tumor on three different scales: (i) on the macroscopic scale, it describes tumor growth and shrinkage during radiation treatment, (ii) on a mesoscopic scale, it provides the cell density and vascular fraction for each voxel, and (iii) on the microscopic scale, the oxygen distribution may be obtained in terms of oxygen histograms. With increasing tumor size, the simulated tumors develop a hypoxic core. Within the model, tumor shrinkage was found to be significantly more important for reoxygenation than angiogenesis or decreased oxygen consumption due to an increased fraction of dead cells. In the studied HNSSC-case, the TCD{sub 50} values (dose at 50% TCP) decreased from 71.0 Gy under hypoxic to 53.6 Gy under the oxic condition. Conclusions: The results obtained with the developed multiscale model are in accordance with expectations based on radiobiological principles and clinical experience. As the model is voxel-based, radiological imaging methods may help to provide the required 3D-characterization of the tumor prior to irradiation. For clinical application, the model has to be further validated with experimental and clinical data. If this is achieved, the model may be used to optimize fractionation schedules and dose distributions for the treatment of hypoxic tumors.

60 APPLIED LIFE SCIENCES↗

Novel tools for stepping source brachytherapy treatment planning: Enhanced geometrical optimization and interactive inverse planning

Purpose: Dose optimization for stepping source brachytherapy can nowadays be performed using automated inverse algorithms. Although much quicker than graphical optimization, an experienced treatment planner is required for both methods. With automated inverse algorithms, the procedure to achieve the desired dose distribution is often based on trial-and-error. Methods: A new approach for stepping source prostate brachytherapy treatment planning was developed as a quick and user-friendly alternative. This approach consists of the combined use of two novel tools: Enhanced geometrical optimization (EGO) and interactive inverse planning (IIP). EGO is an extended version of the common geometrical optimization method and is applied to create a dose distribution as homogeneous as possible. With the second tool, IIP, this dose distribution is tailored to a specific patient anatomy by interactively changing the highest and lowest dose on the contours. Results: The combined use of EGO–IIP was evaluated on 24 prostate cancer patients, by having an inexperienced user create treatment plans, compliant to clinical dose objectives. This user was able to create dose plans of 24 patients in an average time of 4.4 min/patient. An experienced treatment planner without extensive training in EGO–IIP also created 24 plans. The resulting dose-volume histogram parameters were comparable to the clinical plans and showed high conformance to clinical standards. Conclusions: Even for an inexperienced user, treatment planning with EGO–IIP for stepping source prostate brachytherapy is feasible as an alternative to current optimization algorithms, offering speed, simplicity for the user, and local control of the dose levels.

60 APPLIED LIFE SCIENCES↗

Automated planning of breast radiotherapy using cone beam CT imaging

Purpose: Develop and clinically validate a methodology for using cone beam computed tomography (CBCT) imaging in an automated treatment planning framework for breast IMRT. Methods: A technique for intensity correction of CBCT images was developed and evaluated. The technique is based on histogram matching of CBCT image sets, using information from “similar” planning CT image sets from a database of paired CBCT and CT image sets (n = 38). Automated treatment plans were generated for a testing subset (n = 15) on the planning CT and the corrected CBCT. The plans generated on the corrected CBCT were compared to the CT-based plans in terms of beam parameters, dosimetric indices, and dose distributions. Results: The corrected CBCT images showed considerable similarity to their corresponding planning CTs (average mutual information 1.0±0.1, average sum of absolute differences 185 ± 38). The automated CBCT-based plans were clinically acceptable, as well as equivalent to the CT-based plans with average gantry angle difference of 0.99°±1.1°, target volume overlap index (Dice) of 0.89±0.04 although with slightly higher maximum target doses (4482±90 vs 4560±84, P < 0.05). Gamma index analysis (3%, 3 mm) showed that the CBCT-based plans had the same dose distribution as plans calculated with the same beams on the registered planning CTs (average gamma index 0.12±0.04, gamma <1 in 99.4%±0.3%). Conclusions: The proposed method demonstrates the potential for a clinically feasible and efficient online adaptive breast IMRT planning method based on CBCT imaging, integrating automation.

60 APPLIED LIFE SCIENCES↗

Monte Carlo simulations of patient dose perturbations in rotational-type radiotherapy due to a transverse magnetic field: A tomotherapy investigation

Purpose: Several groups are exploring the integration of magnetic resonance (MR) image guidance with radiotherapy to reduce tumor position uncertainty during photon radiotherapy. The therapeutic gain from reducing tumor position uncertainty using intrafraction MR imaging during radiotherapy could be partially offset if the negative effects of magnetic field-induced dose perturbations are not appreciated or accounted for. The authors hypothesize that a more rotationally symmetric modality such as helical tomotherapy will permit a systematic mediation of these dose perturbations. This investigation offers a unique look at the dose perturbations due to homogeneous transverse magnetic field during the delivery of Tomotherapy{sup ®} Treatment System plans under varying degrees of rotational beamlet symmetry. Methods: The authors accurately reproduced treatment plan beamlet and patient configurations using the Monte Carlo code GEANT4. This code has a thoroughly benchmarked electromagnetic particle transport physics package well-suited for the radiotherapy energy regime. The three approved clinical treatment plans for this study were for a prostate, head and neck, and lung treatment. The dose heterogeneity index metric was used to quantify the effect of the dose perturbations to the target volumes. Results: The authors demonstrate the ability to reproduce the clinical dose–volume histograms (DVH) to within 4% dose agreement at each DVH point for the target volumes and most planning structures, and therefore, are able to confidently examine the effects of transverse magnetic fields on the plans. The authors investigated field strengths of 0.35, 0.7, 1, 1.5, and 3 T. Changes to the dose heterogeneity index of 0.1% were seen in the prostate and head and neck case, reflecting negligible dose perturbations to the target volumes, a change from 5.5% to 20.1% was observed with the lung case. Conclusions: This study demonstrated that the effect of external magnetic fields can be mitigated by exploiting a more rotationally symmetric treatment modality.

60 APPLIED LIFE SCIENCES↗

Knowledge-based prediction of plan quality metrics in intracranial stereotactic radiosurgery

Purpose: The objective of this work was to develop a comprehensive knowledge-based methodology for predicting achievable dose–volume histograms (DVHs) and highly precise DVH-based quality metrics (QMs) in stereotactic radiosurgery/radiotherapy (SRS/SRT) plans. Accurate QM estimation can identify suboptimal treatment plans and provide target optimization objectives to standardize and improve treatment planning. Methods: Correlating observed dose as it relates to the geometric relationship of organs-at-risk (OARs) to planning target volumes (PTVs) yields mathematical models to predict achievable DVHs. In SRS, DVH-based QMs such as brain V{sub 10Gy} (volume receiving 10 Gy or more), gradient measure (GM), and conformity index (CI) are used to evaluate plan quality. This study encompasses 223 linear accelerator-based SRS/SRT treatment plans (SRS plans) using volumetric-modulated arc therapy (VMAT), representing 95% of the institution’s VMAT radiosurgery load from the past four and a half years. Unfiltered models that use all available plans for the model training were built for each category with a stratification scheme based on target and OAR characteristics determined emergently through initial modeling process. Model predictive accuracy is measured by the mean and standard deviation of the difference between clinical and predicted QMs, δQM = QM{sub clin} − QM{sub pred}, and a coefficient of determination, R{sup 2}. For categories with a large number of plans, refined models are constructed by automatic elimination of suspected suboptimal plans from the training set. Using the refined model as a presumed achievable standard, potentially suboptimal plans are identified. Predictions of QM improvement are validated via standardized replanning of 20 suspected suboptimal plans based on dosimetric predictions. The significance of the QM improvement is evaluated using the Wilcoxon signed rank test. Results: The most accurate predictions are obtained when plans are stratified based on proximity to OARs and their PTV volume sizes. Volumes are categorized into small (V{sub PTV} < 2 cm{sup 3}), medium (2 cm{sup 3} < V{sub PTV} < 25 cm{sup 3}), and large (25 cm{sup 3} < V{sub PTV}). The unfiltered models demonstrate the ability to predict GMs to ∼1 mm and fractional brain V{sub 10Gy} to ∼25% for plans with large V{sub PTV} and critical OAR involvements. Increased accuracy and precision of QM predictions are obtained when high quality plans are selected for the model training. For the small and medium V{sub PTV} plans without critical OAR involvement, predictive ability was evaluated using the refined model. For training plans, the model predicted GM to an accuracy of 0.2 ± 0.3 mm and fractional brain V{sub 10Gy} to 0.04 ± 0.12, suggesting highly accurate predictive ability. For excluded plans, the average δGM was 1.1 mm and fractional brain V{sub 10Gy} was 0.20. These δQM are significantly greater than those of the model training plans (p < 0.001). For CI, predictions are close to clinical values and no significant difference was observed between the training and excluded plans (p = 0.19). Twenty outliers with δGM > 1.35 mm were identified as potentially suboptimal, and replanning these cases using predicted target objectives demonstrates significant improvements on QMs: on average, 1.1 mm reduction in GM (p < 0.001) and 23% reduction in brain V{sub 10Gy} (p < 0.001). After replanning, the difference of δGM distribution between the 20 replans and the refined model training plans was marginal. Conclusions: The results demonstrate the ability to predict SRS QMs precisely and to identify suboptimal plans. Furthermore, the knowledge-based DVH predictions were directly used as target optimization objectives and allowed a standardized planning process that bettered the clinically approved plans. Full clinical application of this methodology can improve consistency of SRS plan quality in a wide range of PTV volume and proximity to OARs and facilitate automated treatment planning for this critical treatment site.

60 APPLIED LIFE SCIENCES↗

Independent calculation of monitor units for VMAT and SPORT

Purpose: Dose and monitor units (MUs) represent two important facets of a radiation therapy treatment. In current practice, verification of a treatment plan is commonly done in dose domain, in which a phantom measurement or forward dose calculation is performed to examine the dosimetric accuracy and the MU settings of a given treatment plan. While it is desirable to verify directly the MU settings, a computational framework for obtaining the MU values from a known dose distribution has yet to be developed. This work presents a strategy to calculate independently the MUs from a given dose distribution of volumetric modulated arc therapy (VMAT) and station parameter optimized radiation therapy (SPORT). Methods: The dose at a point can be expressed as a sum of contributions from all the station points (or control points). This relationship forms the basis of the proposed MU verification technique. To proceed, the authors first obtain the matrix elements which characterize the dosimetric contribution of the involved station points by computing the doses at a series of voxels, typically on the prescription surface of the VMAT/SPORT treatment plan, with unit MU setting for all the station points. An in-house Monte Carlo (MC) software is used for the dose matrix calculation. The MUs of the station points are then derived by minimizing the least-squares difference between doses computed by the treatment planning system (TPS) and that of the MC for the selected set of voxels on the prescription surface. The technique is applied to 16 clinical cases with a variety of energies, disease sites, and TPS dose calculation algorithms. Results: For all plans except the lung cases with large tissue density inhomogeneity, the independently computed MUs agree with that of TPS to within 2.7% for all the station points. In the dose domain, no significant difference between the MC and Eclipse Anisotropic Analytical Algorithm (AAA) dose distribution is found in terms of isodose contours, dose profiles, gamma index, and dose volume histogram (DVH) for these cases. For the lung cases, the MC-calculated MUs differ significantly from that of the treatment plan computed using AAA. However, the discrepancies are reduced to within 3% when the TPS dose calculation algorithm is switched to a transport equation-based technique (Acuros™). Comparison in the dose domain between the MC and Eclipse AAA/Acuros calculation yields conclusion consistent with the MU calculation. Conclusions: A computational framework relating the MU and dose domains has been established. The framework does not only enable them to verify the MU values of the involved station points of a VMAT plan directly in the MU domain but also provide a much needed mechanism to adaptively modify the MU values of the station points in accordance to a specific change in the dose domain.

60 APPLIED LIFE SCIENCES↗