Development of a Monte Carlo model for treatment planning dose verification of the Leksell Gamma Knife Perfexion radiosurgery system.

Detailed Monte Carlo (MC) modeling of the Leksell Gamma Knife (GK) Perfexion (PFX) collimator system is the only accurate ab initio approach appearing in the literature. As a different approach, in this work, we present a MC model based on film measurement. By adjusting the model parameters and fine-tuning the derived fluence map for each individual source to match the manufacturer's ring output factors, we created a reasonable virtual source model for MC simulations to verify treatment planning dose for the GK PFX radiosurgery system. The MC simulation model was commissioned by simple single shots. Dose profiles and both ring and collimator output factors were compared with the treatment planning system (TPS). Good agreement was achieved for dose profiles especially for the region of plateau (< 2%), while larger difference (< 5%) came from the penumbra region. The maximum difference of the calculated output factor was within 0.7%. The model was further validated by a clinical test case. Good agreement was obtained. The DVHs for brainstem and the skull were almost identical and, for the target, the volume covered by the prescription (12.5 Gy to 50% isodose line) was 95.6% from MC calculation versus 100% from the TPS.

A virtual source model for Monte Carlo simulation of helical tomotherapy.

The purpose of this study was to present a Monte Carlo (MC) simulation method based on a virtual source, jaw, and MLC model to calculate dose in patient for helical tomotherapy without the need of calculating phase-space files (PSFs). Current studies on the tomotherapy MC simulation adopt a full MC model, which includes extensive modeling of radiation source, primary and secondary jaws, and multileaf collimator (MLC). In the full MC model, PSFs need to be created at different scoring planes to facilitate the patient dose calculations. In the present work, the virtual source model (VSM) we established was based on the gold standard beam data of a tomotherapy unit, which can be exported from the treatment planning station (TPS). The TPS-generated sinograms were extracted from the archived patient XML (eXtensible Markup Language) files. The fluence map for the MC sampling was created by incorporating the percentage leaf open time (LOT) with leaf filter, jaw penumbra, and leaf latency contained from sinogram files. The VSM was validated for various geometry setups and clinical situations involving heterogeneous media and delivery quality assurance (DQA) cases. An agreement of < 1% was obtained between the measured and simulated results for percent depth doses (PDDs) and open beam profiles for all three jaw settings in the VSM commissioning. The accuracy of the VSM leaf filter model was verified in comparing the measured and simulated results for a Picket Fence pattern. An agreement of < 2% was achieved between the presented VSM and a published full MC model for heterogeneous phantoms. For complex clinical head and neck (HN) cases, the VSM-based MC simulation of DQA plans agreed with the film measurement with 98% of planar dose pixels passing on the 2%/2 mm gamma criteria. For patient treatment plans, results showed comparable dose-volume histograms (DVHs) for planning target volumes (PTVs) and organs at risk (OARs). Deviations observed in this study were consistent with literature. The VSM-based MC simulation approach can be feasibly built from the gold standard beam model of a tomotherapy unit. The accuracy of the VSM was validated against measurements in homogeneous media, as well as published full MC model in heterogeneous media.

Using a deep learning approach for implanted seed detection on fluoroscopy images in prostate brachytherapy.

Purpose: To apply a deep learning approach to automatically detect implanted seeds on a fluoroscopy image in prostate brachytherapy. Material and methods: Forty-eight fluoroscopy images of patients, who underwent permanent seed implant (PSI) were used for this study after our Institutional Review Boards approval. Pre-processing procedures that were used to prepare for the training data, included encapsulating each seed in a bounding box, re-normalizing seed dimension, cropping to a region of prostate, and converting fluoroscopy image to PNG format. We employed a pre-trained faster region convolutional neural network (R-CNN) from PyTorch library for automatic seed detection, and leave-one-out cross-validation (LOOCV) procedure was applied to evaluate the performance of the model. Results: Almost all cases had mean average precision (mAP) greater than 0.91, with most cases (83.3%) having a mean average recall (mAR) above 0.9. All cases achieved F1-scores exceeding 0.91. The averaged results for all the cases were 0.979, 0.937, and 0.957 for mAP, mAR, and F1-score, respectively. Conclusions: Although there are limitations shown in interpreting overlapping seeds, our model is reasonably accurate and shows potential for further applications.

Case Report: Role of an Iodinated Rectal Hydrogel Spacer, SpaceOAR Vue™, in the Context of Low-Dose-Rate Prostate Brachytherapy, for Enhanced Post-Operative Contouring to Aid in Accurate Implant Evaluation and Dosimetry.

We present a case series of 13 consecutive patients with prostate cancer treated with low-dose-rate (LDR) brachytherapy, utilizing SpaceOAR Vue™, the recent iodinated iteration of the SpaceOAR™ hydrogel rectal spacer. Low- and favorable intermediate-risk patients receiving monotherapy and unfavorable intermediate- and high-risk patients undergoing a brachytherapy boost were included. Permanent brachytherapy can result in subacute and late rectal toxicity, and precise contouring of the anterior rectal wall and posterior aspect of the prostate is essential for accurate dosimetry to confirm a safe implant. Clearly visible on non-contrast CT imaging, SpaceOAR Vue™ can substantially aid in post-implant contouring and analysis. Not previously described in the literature in the context of LDR brachytherapy, we demonstrate the added clinical benefit of placing a well-visualized rectal spacer.

Monte Carlo Dose Calculation Using MRI Based Synthetic CT Generated by Fully Convolutional Neural Network for Gamma Knife Radiosurgery.

The aim of this work is to study the dosimetric effect from generated synthetic computed tomography (sCT) from magnetic resonance (MR) images using a deep learning algorithm for Gamma Knife (GK) stereotactic radiosurgery (SRS). The Monte Carlo (MC) method is used for dose calculations. Thirty patients were retrospectively selected with our institution IRB's approval. All patients were treated with GK SRS based on T1-weighted MR images and also underwent conventional external beam treatment with a CT scan. Image datasets were preprocessed with registration and were normalized to obtain similar intensity for the pairs of MR and CT images. A deep convolutional neural network arranged in an encoder-decoder fashion was used to learn the direct mapping from MR to the corresponding CT. A number of metrics including the voxel-wise mean error (ME) and mean absolute error (MAE) were used for evaluating the difference between generated sCT and the true CT. To study the dosimetric accuracy, MC simulations were performed based on the true CT and sCT using the same treatment parameters. The method produced an MAE of 86.6 ± 34.1 Hundsfield units (HU) and a mean squared error (MSE) of 160.9 ± 32.8. The mean Dice similarity coefficient was 0.82 ± 0.05 for HU > 200. The difference for dose-volume parameter D95 between the ground true dose and the dose calculated with sCT was 1.1% if a synthetic CT-to-density table was used, and 4.9% compared with the calculations based on the water-brain phantom.

A gamma dose distribution evaluation technique using the k-d tree for nearest neighbor searching.

PURPOSE: The authors propose an algorithm based on the k-d tree for nearest neighbor searching to improve the gamma calculation time for 2D and 3D dose distributions. METHODS: The gamma calculation method has been widely used for comparisons of dose distributions in clinical treatment plans and quality assurances. By specifying the acceptable dose and distance-to-agreement criteria, the method provides quantitative measurement of the agreement between the reference and evaluation dose distributions. The gamma value indicates the acceptability. In regions where gamma < or = 1, the predefined criterion is satisfied and thus the agreement is acceptable; otherwise, the agreement fails. Although the concept of the method is not complicated and a quick naïve implementation is straightforward, an efficient and robust implementation is not trivial. Recent algorithms based on exhaustive searching within a maximum radius, the geometric Euclidean distance, and the table lookup method have been proposed to improve the computational time for multidimensional dose distributions. Motivated by the fact that the least searching time for finding a nearest neighbor can be an O (log N) operation with a k-d tree, where N is the total number of the dose points, the authors propose an algorithm based on the k-d tree for the gamma evaluation in this work. RESULTS: In the experiment, the authors found that the average k-d tree construction time per reference point is O (log N), while the nearest neighbor searching time per evaluation point is proportional to O (N(1/k), where k is between 2 and 3 for two-dimensional and three-dimensional dose distributions, respectively. CONCLUSIONS: Comparing with other algorithms such as exhaustive search and sorted list O (N), the k-d tree algorithm for gamma evaluation is much more efficient.

Oblique incidence for broad monoenergetic proton beams.

PURPOSE: The depth dose of a monoenergetic broad parallel proton beam has been modeled in a number of ways, but evidently not yet for oblique incidence. The purpose of this investigation is to find an accurate analytic formula for this case, which can then be used to model the depth dose of a broad beam with an initial Gaussian angular distribution. METHODS: The Bortfeld model of depth dose in a broad normally incident proton beam has been extended to the case of oblique incidence. This extension uses an empirically determined Gaussian parameter sigma(x) which (roughly) characterizes the off-axis dose of a proton pencil beam. As with Bortfeld's work, the modeling is done in terms of parabolic cylinder functions. To obtain the depth dose for an initial angular distribution, the result is integrated over the angle of incidence, weighted by a Gaussian probability function. The predictions of the theory have been compared to MCNPX Monte Carlo calculations for four phantom materials (water, bone, aluminum, and copper) and for initial proton energies of 50, 100, 150, 200, and 250 MeV. RESULTS: Comparisons of the depth dose predicted by this theory with Monte Carlo calculations have established that with very good accuracy, sigma(x) can be taken to be independent both of the depth and of the angle of incidence. As a function of initial proton range or of initial proton energy, sigma(x) has been found to obey a power law to very high accuracy. Good fits to Monte Carlo calculations have also been found for an initial Gaussian angular distribution. CONCLUSIONS: This investigation is the first step in the accurate modeling of a proton pencil beam with initial Gaussian angular distribution. It provides the longitudinal factor, with its Bragg peak buildup and sharp distal falloff. A transverse factor must still be incorporated into this theory and this will give the lateral penumbra of a collimated proton beam. Also, it will be necessary to model the dose of product particles from nuclear interactions of the proton beam. With the accurate modeling of a pencil beam, it will be possible to accurately take into account the effect of localized tissue inhomogeneities.

An Integrated Framework Based on Full Monte Carlo Simulations for Double-Scattering Proton Therapy.

PURPOSE: We developed an integrated framework that employs a full Monte Carlo (MC) model for treatment-plan simulations of a passive double-scattering proton system. MATERIALS AND METHODS: We have previously validated a virtual machine source model for full MC proton-dose calculations by comparing the percentage of depth-dose curves, spread-out Bragg peaks, and lateral profiles against measured commissioning data. This study further expanded our previous work by developing an integrate framework that facilitates its clinical use. Specifically, we have (1) constructed patient-specific applicator and compensator numerically from the plan data and incorporated them into the beamline, (2) created the patient anatomy from the computed tomography image and established the transformation between patient and machine coordinate systems, and (3) developed a graphical user interface to ease the whole process from importing the treatment plan in the Digital Imaging and Communications in Medicine format to parallelization of the MC calculations. End-to-end tests were performed to validate the functionality, and 3 clinical cases were used to demonstrate clinical utility of the framework. RESULTS: The end-to-end tests demonstrated that the framework functioned correctly for all tested functionality. Comparisons between the treatment planning system calculations and MC results in 3 clinical cases revealed large dose difference up to 17%, especially in the beam penumbra and near the end of beam range. The discrepancy likely originates from a variety of sources, such as the dose algorithms, modeling of the beamline, and the dose metric. The agreement for other regions was acceptable. CONCLUSION: An integrated framework was developed for full MC simulations of double-scattering proton therapy. It can be a valuable tool for dose verification and plan evaluation.

Hypofractionation regimens for stereotactic radiotherapy for large brain tumors.

PURPOSE: To investigate equivalent regimens for hypofractionated stereotactic radiotherapy (HSRT) for brain tumor treatment and to provide dose-escalation guidance to maximize the tumor control within the normal brain tolerance. METHODS AND MATERIALS: The linear-quadratic model, including the effect of nonuniform dose distributions, was used to evaluate the HSRT regimens. The alpha/beta ratio was estimated using the Gammaknife stereotactic radiosurgery (GKSRS) and whole-brain radiotherapy experience for large brain tumors. The HSRT regimens were derived using two methods: (1) an equivalent tumor control approach, which matches the whole-brain radiotherapy experience for many fractions and merges it with the GKSRS data for few fractions; and (2) a normal-tissue tolerance approach, which takes advantages of the dose conformity and fractionation of HSRT to approach the maximal dose tolerance of the normal brain. RESULTS: A plausible alpha/beta ratio of 12 Gy for brain tumor and a volume parameter n of 0.23 for normal brain were derived from the GKSRS and whole-brain radiotherapy data. The HSRT prescription regimens for the isoeffect of tumor irradiation were calculated. The normal-brain equivalent uniform dose decreased as the number of fractions increased, because of the advantage of fractionation. The regimens for potential dose escalation of HSRT within the limits of normal-brain tolerance were derived. CONCLUSIONS: The designed hypofractionated regimens could be used as a preliminary guide for HSRT dose prescription for large brain tumors to mimic the GKSRS experience and for dose escalation trials. Clinical studies are necessary to further tune the model parameters and validate these regimens.

Fractionated grid therapy in treating cervical cancers: conventional fractionation or hypofractionation?

PURPOSE: To evaluate the conventionally fractionated and hypofractionated grid therapy in debulking cervical cancers using the linear quadratic (LQ) model. METHODS AND MATERIALS: A Monte Carlo technique was used to calculate the dose distribution of a commercially available grid in a 6-MV photon beam. The LQ model was used to evaluate the therapeutic outcome of both the conventionally fractionated (2 Gy/fraction) and hypofractionated (15 Gy/fraction) grid therapy regimens to debulk cervical cancers with different LQ parameters. The equivalent open-field dose (EOD) to the cancer cells and therapeutic ratio (TR) were defined by comparing grid therapy with the open debulking field. The clinical outcomes from 114 patients were used to verify our theoretical model. RESULTS: The cervical cancer and normal tissue cell survival statistics for grid therapy in two regimens were calculated. The EODs and TRs were derived. The EOD was only a fraction of the prescribed dose. The TR was dependent on the prescribed dose and the LQ parameters of both the tumor and normal tissue cells. The grid therapy favors the acutely responding tumors inside radiosensitive normal tissues. Theoretical model predictions were consistent with the clinical outcomes. CONCLUSIONS: Grid therapy provided a pronounced therapeutic advantage in both the hypofractionated and conventionally fractionated regimens compared with that seen with single fraction, open debulking field regimens, but the true therapeutic advantage exists only in the hypofractionated grid therapy. The clinical outcomes and our study indicated that a course of open-field radiotherapy is necessary to control tumor growth fully after a grid therapy.

Deterministic photon kerma distribution based on the Boltzmann equation for external beam radiation therapy.

A photon transport algorithm for fully three-dimensional radiotherapy treatment planning has been developed based on the discrete ordinates (SN) solution of the Boltzmann equation. The algorithm is characterized by orthogonal adaptive meshes, which place additional points where large gradients occur and a procedure to evaluate the collided flux using the representation of spherical harmonic expansion instead of the summation of the volume-weighted contribution from discrete angles. The Boltzmann equation was solved in the form of SN spatial, energy, and angular discretization with mitigation of ray effects by the first-collision source method. Unlike existing SN codes, which were designed for general purpose for multiparticle transport in areas such as nuclear engineering, our code is optimized for medical radiation transport. To validate the algorithm, several examples were employed to calculate the photon flux distribution. Numerical results show good agreement with the Monte Carlo calculations using EGSnrc.

Technical Note: An approach to building a Monte Carlo simulation model for a double scattering proton beam system.

PURPOSE: The purpose of this study was to demonstrate and develop a Monte Carlo (MC) simulation model for a passive double scattering compact proton therapy system based on limited information of the mechanical components. METHOD: We built a virtual machine source model (VMSM) which included a detailed definition of each beam-modifying component in the nozzle. Conceptually, it is similar to the conventional virtual analytical source model (VASM), except that the numerical machine nozzle or beamline is constructed in the VMSM, whereas in the VASM analytical parameters characterizing the energy spectrum and source fluence distribution are sought. All major beam shaping components were included in the VMSM and the model simulates interactions of the beam with a rotating range modulation wheel (RMW) combined with the beam current modulation. The RMWs, the first and second scatterer in the system were generated and tuned to reproduce measurement data as closely as possible. To validate the model, we compared the percent depth dose curves, spread out Bragg peaks (SOBPs) and lateral profiles against measured commissioning beam data. RESULTS: The agreement of beam range between the MC calculation and measurement was within 1 mm for all beam options. The distal-falloff length was in good agreement as well (<1 mm for the large and deep groups, <1.5 mm for the small group). Agreement to within 2.5 mm of measured SOBP widths was obtained for all MC calculations. For lateral profiles, differences were found to be less than 2 mm. CONCLUSIONS: We demonstrated that with limited geometrical information it is possible to build an acceptable source model for MC simulations of a passive double scattering compact proton therapy system. The agreement between the measurements and the MC model provides validation for use of the model for further studies of the dosimetric effects in patient treatments.

A Monte Carlo model and its commissioning for the Leksell Gamma Knife Perfexion radiosurgery system.

PURPOSE: To develop and commission a Monte Carlo (MC) simulation model for the Leksell Gamma Knife (LGK) Perfexion (PFX) radiosurgery system. METHOD: We previously established a source model for MC simulations of the LGK PFX for the purpose of the treatment planning system (TPS) dose verification and plan evaluation. To make practical and effective use of the model in clinic, several issues need to be addressed. First, thorough commissioning procedures are needed to ensure the validity of the model parameters, such as the source-to-focus (STF) distance, the source solid angle. Second, an efficient source particle sampling method is required to facilitate dose calculations for multitarget and multishot configurations in patient treatment plans. Third, inseparably, it is interesting to know the dose difference between the two GK TPS algorithms (TMR and convolution) and the MC method in extreme heterogeneous cases resulting from the inhomogeneous effect. We report our recent development in addressing these issues. Phantoms with the frame fiducials were manually created in the format of DICOM CT image to eliminate the uncertainties associated with scanner artifacts and image registration. The created homogeneous phantom was used to calibrate the model parameters to match the output factors with the manufacturer provided data, and the heterogeneous phantom with multilayer materials was used to study the inhomogeneous effect. RESULTS: The agreement between the MC calculation and TPS was very good for the homogeneous spherical phantom. The difference of the full width at half maximum (FWHM) of the profiles was less than 1 mm except for the profile for 16 mm collimator along z-axis (less than 2 mm). For the extreme heterogeneous test case, it was shown that the TMR algorithm can overestimate the target dose by up to 22% using the measure of dose volume parameter D95. The agreement between the MC method and the TPS convolution method was better (within 3.6%) for the target near the center of phantom, however, discrepancy (up to 10.7%) existed for the target close to the skull. The difference between the two TPS dose algorithms was about 11%. CONCLUSIONS: Considerable dose difference may result from the effect of heterogeneity, such as in the regions of the air cavities and bones. As the MC method has been extensively used in conventional external beams, it is worthwhile for further investigation in applying the MC method to accurate dose planning in the new GK PFX radiosurgery platform.

Development and Validation of a Small Animal Immobilizer and Positioning System for the Study of Delivery of Intracranial and Extracranial Radiotherapy Using the Gamma Knife System.

The purpose of this research is to establish a process of irradiating mice using the Gamma Knife as a versatile system for small animal irradiation and to validate accurate intracranial and extracranial dose delivery using this system. A stereotactic immobilization device was developed for small animals for the Gamma Knife head frame allowing for isocentric dose delivery. Intercranial positional reproducibility of a reference point from a primary reference animal was verified on an additional mouse. Extracranial positional reproducibility of the mouse aorta was verified using 3 mice. Accurate dose delivery was validated using film and thermoluminescent dosimeter measurements with a solid water phantom. Gamma Knife plans were developed to irradiate intracranial and extracranial targets. Mice were irradiated validating successful targeted radiation dose delivery. Intramouse positional variability of the right mandible reference point across 10 micro-computed tomography scans was 0.65 ± 0.48 mm. Intermouse positional reproducibility across 2 mice at the same reference point was 0.76 ± 0.46 mm. The accuracy of dose delivery was 0.67 ± 0.29 mm and 1.01 ± 0.43 mm in the coronal and sagittal planes, respectively. The planned dose delivered to a mouse phantom was 2 Gy at the 50% isodose with a measured thermoluminescent dosimeter dose of 2.9 ± 0.3 Gy. The phosphorylated form of member X of histone family H2A (γH2AX) staining of irradiated mouse brain and mouse aorta demonstrated adjacent tissue sparing. In conclusion, our system for preclinical studies of small animal irradiation using the Gamma Knife is able to accurately deliver intracranial and extracranial targeted focal radiation allowing for preclinical experiments studying focal radiation.

Experimental Validation of Monte Carlo Simulations Based on a Virtual Source Model for TomoTherapy in a RANDO Phantom.

A virtual source model for Monte Carlo simulations of helical TomoTherapy has been developed previously by the authors. The purpose of this work is to perform experiments in an anthropomorphic (RANDO) phantom with the same order of complexity as in clinical treatments to validate the virtual source model to be used for quality assurance secondary check on TomoTherapy patient planning dose. Helical TomoTherapy involves complex delivery pattern with irregular beam apertures and couch movement during irradiation. Monte Carlo simulation, as the most accurate dose algorithm, is desirable in radiation dosimetry. Current Monte Carlo simulations for helical TomoTherapy adopt the full Monte Carlo model, which includes detailed modeling of individual machine component, and thus, large phase space files are required at different scoring planes. As an alternative approach, we developed a virtual source model without using the large phase space files for the patient dose calculations previously. In this work, we apply the simulation system to recompute the patient doses, which were generated by the treatment planning system in an anthropomorphic phantom to mimic the real patient treatments. We performed thermoluminescence dosimeter point dose and film measurements to compare with Monte Carlo results. Thermoluminescence dosimeter measurements show that the relative difference in both Monte Carlo and treatment planning system is within 3%, with the largest difference less than 5% for both the test plans. The film measurements demonstrated 85.7% and 98.4% passing rate using the 3 mm/3% acceptance criterion for the head and neck and lung cases, respectively. Over 95% passing rate is achieved if 4 mm/4% criterion is applied. For the dose-volume histograms, very good agreement is obtained between the Monte Carlo and treatment planning system method for both cases. The experimental results demonstrate that the virtual source model Monte Carlo system can be a viable option for the accurate dose calculation of helical TomoTherapy.

Comparison of Ray Tracing and Monte Carlo Calculation Algorithms for Thoracic Spine Lesions Treated With CyberKnife-Based Stereotactic Body Radiation Therapy.

Stereotactic body radiation therapy (SBRT) is an emerging technology for the treatment of spinal metastases, although the dosimetric impact of the calculation method on spinal dose distribution is unknown. This study attempts to determine whether CyberKnife (CK)-based SBRT using a Ray Tracing (RyTc) algorithm is comparable dosimetrically to that of Monte Carlo (MC) for thoracic spinal lesions. Our institutional CK-based SBRT database for thoracic spinal lesions was queried and a cohort was generated. Patients were planned using RyTc and MC algorithms using the same beam angles and monitor units. Dose-volume histograms of the planning target volume (PTV), spinal cord, esophagus, and skin were generated, and dosimetric parameters were compared. There were 37 patients in the cohort. The average percentage volume of PTV covered by the prescribed dose with RyTc and MC algorithms was 91.1% and 80.4%, respectively (P < .001). The difference in average maximum spinal cord dose between RyTc and MC plans was significant (1126 vs 1084 cGy, P = .004), with the MC dose ranging from 18.7% below to 13.8% above the corresponding RyTc dose. A small reduction in maximum skin dose was also noted (P = .017), although no difference was seen in maximum esophageal dose (P = .15). Only PTVs smaller than 27 cm(3) were found to correlate with large (>10%) changes in dose to 90% of the volume (P = .014), while no correlates with the average percentage volume of PTV covered by the prescribed dose were demonstrated. For thoracic spinal CK-based SBRT, RyTc computation may overestimate the MC calculated average percentage volume of PTV covered by the prescribed dose and have unpredictable effects on doses to organs at risk, particularly the spinal cord. In this setting, use of RyTc optimization should be limited and always verified with MC.

Application of positron emission tomography/computed tomography in radiation treatment planning for head and neck cancers.

18-fluorodeoxygluocose positron emission tomography/computed tomography ((18)FDG-PET/CT) provides significant information in multiple settings in the management of head and neck cancers (HNC). This article seeks to define the additional benefit of PET/CT as related to radiation treatment planning for squamous cell carcinomas (SCCs) of the head and neck through a review of relevant literature. By helping further define both primary and nodal volumes, radiation treatment planning can be improved using PET/CT. Special attention is paid to the independent benefit of PET/CT in targeting mucosal primaries as well as in detecting nodal metastases. The utility of PET/CT is also explored for treatment planning in the setting of SCC of unknown primary as PET/CT may help define a mucosal target volume by guiding biopsies for examination under anesthesia thus changing the treatment paradigm and limiting the extent of therapy. Implications of the use of PET/CT for proper target delineation in patients with artifact from dental procedures are discussed and the impact of dental artifact on CT-based PET attenuation correction is assessed. Finally, comment is made upon the role of PET/CT in the high-risk post-operative setting, particularly in the context of radiation dose escalation. Real case examples are used in these settings to elucidate the practical benefits of PET/CT as related to radiation treatment planning in HNCs.

Investigation of Nonuniform Dose Voxel Geometry in Monte Carlo Calculations.

The purpose of this work is to investigate the efficacy of using multi-resolution nonuniform dose voxel geometry in Monte Carlo (MC) simulations. An in-house MC code based on the dose planning method MC code was developed in C++ to accommodate the nonuniform dose voxel geometry package since general purpose MC codes use their own coupled geometry packages. We devised the package in a manner that the entire calculation volume was first divided into a coarse mesh and then the coarse mesh was subdivided into nonuniform voxels with variable voxel sizes based on density difference. We name this approach as multi-resolution subdivision (MRS). It generates larger voxels in small density gradient regions and smaller voxels in large density gradient regions. To take into account the large dose gradients due to the beam penumbra, the nonuniform voxels can be further split using ray tracing starting from the beam edges. The accuracy of the implementation of the algorithm was verified by comparing with the data published by Rogers and Mohan. The discrepancy was found to be 1% to 2%, with a maximum of 3% at the interfaces. Two clinical cases were used to investigate the efficacy of nonuniform voxel geometry in the MC code. Applying our MRS approach, we started with the initial voxel size of 5 × 5 × 3 mm(3), which was further divided into smaller voxels. The smallest voxel size was 1.25 × 1.25 × 3 mm(3). We found that the simulation time per history for the nonuniform voxels is about 30% to 40% faster than the uniform fine voxels (1.25 × 1.25 × 3 mm(3)) while maintaining similar accuracy.