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Purpose: To investigate the optimal use of XR-RV3 GafChromic® films to assess patient skin dose in interventional radiology while addressing the means to reduce uncertainties in dose assessment. Methods: XR-Type R GafChromic films have been shown to represent the most efficient and suitable solution to determine patient skin dose in interventional procedures. As film dosimetry can be associated with high uncertainty, this paper presents the EURADOS WG 12 initiative to carry out a comprehensive study of film characteristics with a multisite approach. The considered sources of uncertainties include scanner, film, and fitting-related errors. The work focused on studying film behavior with clinical high-dose-rate pulsed beams (previously unavailable in the literature) together with reference standard laboratory beams. Results: First, the performance analysis of six different scanner models has shown that scan uniformity perpendicular to the lamp motion axis and that long term stability are the main sources of scanner-related uncertainties. These could induce errors of up to 7% on the film readings unless regularly checked and corrected. Typically, scan uniformity correction matrices and reading normalization to the scanner-specific and daily background reading should be done. In addition, the analysis on multiple film batches has shown that XR-RV3 films have generally good uniformity within one batch (

Purpose: Exit 2D detectors are widely used in clinics as a tool for pre‐ treatment field verification. It is desired to have accurate modeling of the detector dose for each IMRT plan with patient geometry for in‐vivo delivery verification. We propose a novel hybrid of model and measurement based methods to estimate the detector dose using the information from TPS and plan/verification CT. Methods: Our approach is based on the generalized equivalent field size (GEFS) method. It requires two commissioning tables for various square fields (l×l, 2×2, …40×40): the percent depth dose (PDD) table and the detector correction factor (DDCF) table. PDDs are retrieved from the treatment planning system (TPS), and DDCFs are reconstructed from measurement with various field sizes and air gaps (from 5 cm to 50 cm). GEFS models the detector point dose as the superposition of annular contribution of the fluence map, which is retrieved from the TPS. Correction on the radiological path length is calculated through ray‐tracing the patient CT. Corrections on the air gap between the couch and detector and detector response are applied via table lookup on PDD and DDCF. Results: We validated the proposed method using TPS with extended geometry and direct clinic measurements for both regular and IMRT fields, various phantom and patient geometry. For all calculations, more than 98% of pixels pass the gamma index with criteria of 3%, 3mm. Each calculation took only a few seconds on a single PC. Conclusions: We proposed a novel detector dose calculation method that can be applied for arbitrary IMRT field and arbitrary patient geometry. The calculation is simple and fast and when compared with detector measurement during IMRT treatment, makes in‐ vivo delivery verification and dose reconstruction feasible.

Purpose: Every year, new radiotherapy techniques including stereotactic radiosurgery using linear accelerators give rise to new applications of Monte Carlo(MC) modeling. Accurate modeling requires knowing the size of the electron spot, one of the few parameters to tune in MC models. The resolution of integrated megavoltage imaging systems, such as the tomotherapy system, strongly depends on the photon spot size which is closely related to the electron spot. The aim of this article is to clarify the relationship between the electron spot size and the photon spot size (i.e., thefocal spot size) for typical incident electron beam energies and target thicknesses. Methods: Three electron energies (3, 5.5, and 18 MeV), four electron spot sizes ( FWHM = 0 , 0.5, 1, and 1.5 mm), and two tungsten target thicknesses (0.15 and 1 cm) were considered. The formation of the photon beam within the target was analyzed through electron energy deposition with depth, as well as photon production at several phase-space planes placed perpendicular to the beam axis, where only photons recorded for the first time were accounted for. Photon production was considered for “newborn” photons intersecting a 45 × 45 cm 2 plane at the isocenter (85 cm from source). Finally, virtual source position and “effective” focal spot size were computed by backprojecting all the photons from the bottom of the target intersecting a 45 × 45 cm 2 plane. The virtual source position and focal spot size were estimated at the plane position where the latter is minimal. Results: In the relevant case of considering only photons intersecting the 45 × 45 cm 2 plane, the results unambiguously showed that the effective photon spot is created within the first 0.25 mm of the target and that electron and focal spots may be assumed to be equal within 3–4%. Conclusions: In a good approximation photon spot size equals electron spot size for high energy X-ray treatments delivered by linear accelerators.

The reliability of the convolution/superposition (C/S) algorithm of the Hi-Art tomotherapy system is evaluated by using the Monte Carlo model TomoPen, which has been already validated for homogeneous phantoms. The study was performed in three stages. First, measurements with EBT Gafchromic film for a 1.25 x 2.5 cm2 field in a heterogeneous phantom consisting of two slabs of polystyrene separated with Styrofoam were compared to simulation results from TomoPen. The excellent agreement found in this comparison justifies the use of TomoPen as the reference for the remaining parts of this work. Second, to allow analysis and interpretation of the results in clinical cases, dose distributions calculated with TomoPen and C/S were compared for a similar phantom geometry, with multiple slabs of various densities. Even in conditions of lack of lateral electronic equilibrium, overall good agreement was obtained between C/S and TomoPen results, with deviations within 3%/2 mm, showing that the C/S algorithm accounts for modifications in secondary electron transport due to the presence of a low density medium. Finally, calculations were performed with TomoPen and C/S of dose distributions in various clinical cases, from large bilateral head and neck tumors to small lung tumors with diameter of < 3 cm. To ensure a "fair" comparison, identical dose calculation grid and dose-volume histogram calculator were used. Very good agreement was obtained for most of the cases, with no significant differences between the DVHs obtained from both calculations. However, deviations of up to 4% for the dose received by 95% of the target volume were found for the small lung tumors. Therefore, the approximations in the C/S algorithm slightly influence the accuracy in small lung tumors even though the C/S algorithm of the tomotherapy system shows very good overall behavior.

Inversion of deformation fields is applied frequently to map images, dose, and contours between the reference frame and the study frame. A prevailing approach that takes the negative of the forward deformation as the inverse deformation is oversimplified and can cause large errors for large deformations or deformations that are composites of several deformations. Other approaches, including Newton's method and scatter data interpolation, either require the first derivative or are very inefficient. Here we propose an iterative approach that is easy to implement, converges quickly to the inverse when it does, and works for a majority of cases in practice. Our approach is rooted in fixed-point theory. We build a sequence to approximate the inverse deformation through iterative evaluation of the forward deformation. A sufficient but not necessary convergence condition (Lipschitz condition) and its proof are also given. Though this condition guarantees the convergence, it may not be met for an arbitrary deformation field. One should always check whether the inverse exists for the given forward deformation field by calculating its Jacobian. If nonpositive values of the Jacobian occur only for few voxels, this method will usually converge to a pseudoinverse. In case the iteration fails to converge, one should switch to other means of finding the inverse. We tested the proposed method on simulated 2D data and real 3D computed tomography data of a lung patient and compared our method with two implementations in the Insight Segmentation and Registration Toolkit (ITK). Typically less than ten iterations are needed for our method to get an inverse deformation field with clinically relevant accuracy. Based on the test results, our method is about ten times faster and yet ten times more accurate than ITK's iterative method for the same number of iterations. Simulations and real data tests demonstrated the efficacy and the accuracy of the proposed algorithm.

Radiographic image guidance has emerged as the new paradigm for patient positioning, target localization, and external beam alignment in radiotherapy. Although widely varied in modality and method, all radiographic guidance techniques have one thing in common—they can give a significant radiation dose to the patient. As with all medical uses of ionizing radiation, the general view is that this exposure should be carefully managed. The philosophy for dose management adopted by the diagnostic imaging community is summarized by the acronym ALARA, i.e., as low as reasonably achievable. But unlike the general situation with diagnostic imaging and image-guided surgery, image-guided radiotherapy (IGRT) adds the imaging dose to an already high level of therapeutic radiation. There is furthermore an interplay between increased imaging and improved therapeutic dose conformity that suggests the possibility of optimizing rather than simply minimizing the imaging dose. For this reason, the management of imaging dose during radiotherapy is a different problem than its management during routine diagnostic or image-guided surgical procedures. The imaging dose received as part of a radiotherapy treatment has long been regarded as negligible and thus has been quantified in a fairly loose manner. On the other hand, radiation oncologists examine the therapy dose distribution in minute detail. The introduction of more intensive imaging procedures for IGRT now obligates the clinician to evaluate therapeutic and imaging doses in a more balanced manner. This task group is charged with addressing the issue of radiation dose delivered via image guidance techniques during radiotherapy. The group has developed this charge into three objectives: (1) Compile an overview of image-guidance techniques and their associated radiation dose levels, to provide the clinician using a particular set of image guidance techniques with enough data to estimate the total diagnostic dose for a specific treatment scenario, (2) identify ways to reduce the total imaging dose without sacrificing essential imaging information, and (3) recommend optimization strategies to trade off imaging dose with improvements in therapeutic dose delivery. The end goal is to enable the design of image guidance regimens that are as effective and efficient as possible.

A helical tomotherapy system is used in our clinic to deliver intensity-modulated radiation therapy (IMRT) treatments. Since this machine is designed to deliver IMRT treatments, the traditional field flatness requirements are no longer applicable. This allows the unit to operate without a field flatness filter and consequently the 400 mm wide fan beam is highly inhomogeneous in intensity. The shape of this beam profile is mapped during machine commissioning and for quality assurance purposes the shape of the beam profile needs to be monitored. The use of a commercial diode array for quality assurance measurements is investigated. Central axis beam profiles were acquired at different depths using solid water built-up material. These profiles were compared with ion chamber scans taken in a water tank to test the accuracy of the diode array measurements. The sensitivity of the diode array to variations in the beam profile was checked. Over a seven week period, beam profiles were repeatedly measured. The observed variations are compared with those observed with an on-board beam profile monitor. The diode measurements were in agreement with the ion chamber scans. In the high dose, low gradient region the average ratio between the diode and ion chamber readings was 1.000 +/- 0.005 (+/- 1 standard deviation). In the penumbra region the agreement was poorer but all diodes passed the distance to agreement (DTA) requirement of 2 mm. The trend in the beam profile variations that was measured with the diode array device was in agreement with the on-board monitor. While the calculated amount of variation differs between the devices, both were sensitive to subtle variations in the beam profile. The diode array is a valuable tool to quickly and accurately monitor the beam profile on a helical tomotherapy unit.

Total body radiation (TBI) has been used for many years as a preconditioning agent before bone marrow transplantation. Many side effects still plague its use. We investigated the planning and delivery of total body irradiation (TBI) and selective total marrow irradiation (TMI) and a reduced radiation dose to sensitive structures using image-guided helical tomotherapy. To assess the feasibility of using helical tomotherapy, (A) we studied variations in pitch, field width, and modulation factor on total body and total marrow helical tomotherapy treatments. We varied these parameters to provide a uniform dose along with a treatment times similar to conventional TBI (15-30 min). (B) We also investigated limited (head, chest, and pelvis) megavoltage CT (MVCT) scanning for the dimensional pretreatment setup verification rather than total body MVCT scanning to shorten the overall treatment time per treatment fraction. (C) We placed thermoluminescent detectors (TLDs) inside a Rando phantom to measure the dose at seven anatomical sites, including the lungs. A simulated TBI treatment showed homogeneous dose coverage (+/-10%) to the whole body. Doses to the sensitive organs were reduced by 35%-70% of the target dose. TLD measurements on Rando showed an accurate dose delivery (+/-7%) to the target and critical organs. In the TMI study, the dose was delivered conformally to the bone marrow only. The TBI and TMI treatment delivery time was reduced (by 50%) by increasing the field width from 2.5 to 5.0 cm in the inferior-superior direction. A limited MVCT reduced the target localization time 60% compared to whole body MVCT. MVCT image-guided helical tomotherapy offers a novel method to deliver a precise, homogeneous radiation dose to the whole body target while reducing the dose significantly to all critical organs. A judicious selection of pitch, modulation factor, and field size is required to produce a homogeneous dose distribution along with an acceptable treatment time. In addition, conformal radiation to the bone marrow appears feasible in an external radiation treatment using image-guided helical tomotherapy.

An accurate means of determining and correcting for daily patient setup errors is important to the cancer outcome in radiotherapy. While many tools have been developed to detect setup errors, difficulty may arise in accurately adjusting the patient to account for the rotational error components. A novel, automated method to correct for rotational patient setup errors in helical tomotherapy is proposed for a treatment couch that is restricted to motion along translational axes. In tomotherapy, only a narrow superior/inferior section of the target receives a dose at any instant, thus rotations in the sagittal and coronal planes may be approximately corrected for by very slow continuous couch motion in a direction perpendicular to the scanning direction. Results from proof-of-principle tests indicate that the method improves the accuracy of treatment delivery, especially for long and narrow targets. Rotational corrections about an axis perpendicular to the transverse plane continue to be implemented easily in tomotherapy by adjustment of the initial gantry angle.

Inherent to helical tomotherapy is a dose variation pattern that manifests as a "ripple" (peak-to-trough relative to the average). This ripple is the result of helical beam junctioning, completely unique to helical tomotherapy. Pitch is defined as in helical CT, the couch travel distance for a complete gantry rotation relative to the axial beam width at the axis of rotation. Without scattering or beam divergence, an analytical posing of the problem as a simple integral predicts minima near a pitch of 1/n where n is an integer. A convolution-superposition dose calculator (TomoTherapy, Inc.) included all the physics needed to explore the ripple magnitude versus pitch and beam width. The results of the dose calculator and some benchmark measurements demonstrate that the ripple has sharp minima near p=0.86(1/n). The 0.86 factor is empirical and caused by a beam junctioning of the off-axis dose profiles which differ from the axial profiles as well as a long scatter tail of the profiles at depth. For very strong intensity modulation, the 0.86 factor may vary. The authors propose choosing particular minima pitches or using a second delivery that starts 180 deg off-phase from the first to reduce these ripples: "Double threading." For current typical pitches and beam widths, however, this effect is small and not clinically important for most situations. Certain extremely large field or high pitch cases, however, may benefit from mitigation of this effect.

Current dosimetric protocols based on the absorbed dose (AAPM TG-51 and IAEA TRS-398 protocols) require calibration measurements under reference conditions. For some radiotherapy systems, this requirement cannot be met, and calibration has to be performed under nonreference experimental conditions. In order to solve this problem, both protocols can be extended by inclusion of the measured-to-reference conversion factor, k(mr). In order to determine this factor, basic dosimetric quantities, like stopping power ratios, mass attenuation coefficients and chamber correction factors have to be calculated. If measurements are not feasible, accurate Monte Carlo modeling is required. The extension of the protocols is illustrated using the case of the helical tomotherapy radiation unit, where the typical calibration measurement conditions are the 10 x 5 cm2 field size and the 85 cm surface source distance, limited by the system design. It was calculated that the k(mr) factor for this conditions is close to unity (0.997+/-0.001). In addition, the deviation of the measurement conditions from the reference conditions results in the change of the quality conversion factor (approximately 0.995-0.998, depending on the ionization chamber used). This change is the same regardless of the used calibration protocol. For smaller field sizes the corrections become more significant, resulting in the total correction factor compared to the reference conditions of up to 1.5% for the smallest considered field size of 2 x 2 cm2.

Conventional radiotherapy treatment planning systems rely on a static computed tomography (CT) image for planning and evaluation. Intra/inter-fraction patient motions may result in significant differences between the planned and the delivered dose. In this paper, we develop a method to incorporate the knowledge of intra/inter-fraction patient motion directly into the dose calculation. By decomposing the motion into a parallel (to beam direction) component and perpendicular (to beam direction) component, we show that the motion effects can be accounted for by simply modifying the fluence distribution (sinogram). After such modification, dose calculation is the same as those based on a static planning image. This method is superior to the “dose-convolution” method because it is not based on “shift invariant” assumption. Therefore, it deals with material heterogeneity and surface curvature very well. We test our method using extensive simulations, which include four phantoms, four motion patterns, and three plan beams. We compare our method with the “dose-convolution” and the “stochastic simulation” methods (gold standard). As for the homogeneous flat surface phantom, our method has similar accuracy as the “dose-convolution” method. As for all other phantoms, our method outperforms the “dose-convolution.” The maximum motion encoded dose calculation error using our method is within 4% of the gold standard. It is shown that a treatment planning system that is based on “motion-encoded dose calculation” can incorporate random and systematic motion errors in a very simple fashion. Under this approximation, in principle, a planning target volume definition is not required, since it already accounts for the intra/inter-fraction motion variations and it automatically optimizes the cumulative dose rather than the single fraction dose. © 2005 American Association of Physicists in Medicine . [DOI: 10.1118/1.1829402]

Similar to conventional conformal radiotherapy, during lung tomotherapy, a motion margin has to be set for respiratory motion. Consequently, large volume of normal tissue is irradiated by intensive radiation. To solve this problem, we have developed a new motion mitigation method by incorporating target motion into treatment optimization. In this method, the delivery-breathing correlation is determined prior to treatment plan optimization. Beamlets are calculated by using the CT images at the corresponding breathing phases from a dynamic (four-dimensional) image sequence. With the displacement vector fields at different breathing phases, a set of deformed beamlets is obtained by mapping the dose to the primary phase. Optimization incorporating motion is then performed by using the deformed beamlets obtained by dose mapping. During treatment delivery, the same breathing-delivery correlation can be reproduced by instructing the patient to breathe following a visually displayed guiding cycle. This method was tested using a computer-simulated deformable phantom and a real lung case. Results show that treatment optimization incorporating motion achieved similar high dose conformality on a mobile target compared with static delivery. The residual motion effects due to imperfect breathing tracking were also analyzed.

The imaging characteristics of an arc-shaped xenon gas ionization chamber for the purpose of megavoltage CT imaging were investigated. The detector consists of several hundred 320 microm thick gas cavities separated by thin tungsten plates of the same thickness. Dose response, efficiency and resolution parameters were calculated using Monte Carlo simulations. The calculations were compared to measurements taken in a 4 MV photon beam, assuming that the measured signal in the chambers corresponds to the therein absorbed dose. The measured response profiles for narrow and broad incident photon beams could be well reproduced with the Monte Carlo calculations. They show, that the quantum efficiency is 29.2% and the detective quantum efficiency at zero frequency DQE(0) is 20.4% for the detector arc placed in focus with the photon source. For a detector placed out of focus, these numbers even increase. The efficiency of this kind of radiation detector for megavoltage radiation therefore surpasses the reported efficiency of existing detector technologies. The resolution of the detector is quantified with calculated and measured line spread functions. The corresponding modulation transfer functions were determined for different thicknesses of the tungsten plates. They show that the resolution is only slightly dependent on the plate thickness but is predominantly determined by the cell size of the detector. The optimal plate thickness is determined by a tradeoff between quantum efficiency, total signal generation and resolution. Thicker plates are more efficient but the total signal and the resolution decrease with plate thickness. In conclusion, a gas ionization chamber of the described type is a highly efficient megavoltage radiation detector, allowing to obtain CT images with very little dose for a sufficient image quality for anatomy verification. This kind of detector might serve as a model for a future generation of highly efficient radiation detectors.

Delivery verification is the process in which the energy fluence delivered during a treatment is verified. This verified energy fluence can be used in conjunction with an image in the treatment position to reconstruct the full three-dimensional dose deposited. A method for delivery verification that utilizes a measured database of detector signal is described in this work. This database is a function of two parameters, radiological path-length and detector-to-phantom distance, both of which are computed from a CT image taken at the time of delivery. Such a database was generated and used to perform delivery verification and dose reconstruction. Two experiments were conducted: a simulated prostate delivery on an inhomogeneous abdominal phantom, and a nasopharyngeal delivery on a dog cadaver. For both cases, it was found that the verified fluence and dose results using the database approach agreed very well with those using previously developed and proven techniques. Delivery verification with a measured database and CT image at the time of treatment is an accurate procedure for tomotherapy. The database eliminates the need for any patient-specific, pre- or post-treatment measurements. Moreover, such an approach creates an opportunity for accurate, real-time delivery verification and dose reconstruction given fast image reconstruction and dose computation tools.

Convolution/superposition software has been used to produce a library of photon pencil beam dose matrices. This library of pencil beams is designed to serve as a tool for both education and investigation in the field of radiotherapy optimization. The elegance of this pencil beam model stems from its cylindrical symmetry. Because of the symmetry, the dose distribution for a pencil beam from any arbitrary angle can be determined through a simple rotation of a pre-computed dose matrix. Rapid dose calculations can thus be performed while maintaining the accuracy of a convolution/superposition based dose computation. The pencil beam data sets have been made publicly available. It is hoped that the data sets will facilitate a comparison of a variety of optimization and delivery approaches. This paper will present a number of studies designed to demonstrate the usefulness of the pencil beam data sets. These studies include an examination of the extent to which a treatment plan can be improved through either an increase in the number of beam angles and/or a decrease in the collimator size. A few insights into the significance of heterogeneity corrections for treatment planning for intensity modulated radiotherapy will also be presented.

Every year, new radiotherapy techniques including stereotactic radiosurgery using linear accelerators give rise to new applications of Monte Carlo (MC) modeling. Accurate modeling requires knowing the size of the electron spot, one of the few parameters to tune in MC models. The resolution of integrated megavoltage imaging systems, such as the tomotherapy system, strongly depends on the photon spot size which is closely related to the electron spot. The aim of this article is to clarify the relationship between the electron spot size and the photon spot size (i.e., the focal spot size) for typical incident electron beam energies and target thicknesses.Three electron energies (3, 5.5, and 18 MeV), four electron spot sizes (FWHM = 0, 0.5, 1, and 1.5 mm), and two tungsten target thicknesses (0.15 and 1 cm) were considered. The formation of the photon beam within the target was analyzed through electron energy deposition with depth, as well as photon production at several phase-space planes placed perpendicular to the beam axis, where only photons recorded for the first time were accounted for. Photon production was considered for "newborn" photons intersecting a 45 x 45 cm2 plane at the isocenter (85 cm from source). Finally, virtual source position and "effective" focal spot size were computed by back-projecting all the photons from the bottom of the target intersecting a 45 x 45 cm2 plane. The virtual source position and focal spot size were estimated at the plane position where the latter is minimal.In the relevant case of considering only photons intersecting the 45 x 45 cm2 plane, the results unambiguously showed that the effective photon spot is created within the first 0.25 mm of the target and that electron and focal spots may be assumed to be equal within 3-4%.In a good approximation photon spot size equals electron spot size for high energy X-ray treatments delivered by linear accelerators.

Purpose: An accurate leaf fluence model can be used in applications such as patient specific delivery QA and in-vivo dosimetry for TomoTherapy systems. It is known that the total fluence is not a linear combination of individual leaf fluence due to leakage-transmission, tongue-and-groove, and source occlusion effect. Here we propose a method to model the nonlinear effects as linear terms thus making the MLC-detector system a linear system. Methods: A leaf pattern basis (LPB) consisting of no-leaf-open, single-leaf-open, double-leaf-open and triple-leaf-open patterns are chosen to represent linear and major nonlinear effects of leaf fluence as a linear system. An arbitrary leaf pattern can be expressed as (or decomposed to) a linear combination of the LPB either pulse by pulse or weighted by dwelling time. The exit detector responses to the LPB are obtained by processing returned detector signals resulting from the predefined leaf patterns for each jaw setting. Through forward transformation, detector signal can be predicted given a delivery plan. An equivalent leaf open time (LOT) sinogram containing output variation information can also be inversely calculated from the measured detector signals. Twelve patient plans were delivered in air. The equivalent LOT sinograms were compared with their planned sinograms. Results: The whole calibration process was done in 20 minutes. For two randomly generated leaf patterns, 98.5% of the active channels showed differences within 0.5% of the local maximum between the predicted and measured signals. Averaged over the twelve plans, 90% of LOT errors were within +/−10 ms. The LOT systematic error increases and shows an oscillating pattern when LOT is shorter than 50 ms. Conclusion: The LPB method models the MLC-detector response accurately, which improves patient specific delivery QA and in-vivo dosimetry for TomoTherapy systems. It is sensitive enough to detect systematic LOT errors as small as 10 ms.

Purpose: Test and validation of analytical models predicting leakage neutron exposure in passively scattered proton therapy. Methods: Taking inspiration from the literature, this work attempts to build an analytical model predicting neutron ambient dose equivalents, H*(10), within the local 75 MeV ocular proton therapy facility. MC simulations were first used to model H*(10) in the beam axis plane while considering a closed final collimator and pristine Bragg peak delivery. Next, MC-based analytical model was tested against simulation results and experimental measurements. The model was also expended in the vertical direction to enable a full 3D mapping of H*(10) inside the treatment room. Finally, the work focused on upgrading the literature model to clinically relevant configurations considering modulated beams, open collimators, patient-induced neutron fluctuations, etc. Results: The MC-based analytical model efficiently reproduced simulated H*(10) values with a maximum difference below 10%. In addition, it succeeded in predicting measured H*(10) values with differences

Helical tomotherapy is a relatively new modality with integrated treatment planning and delivery hardware for radiation therapy treatments. In view of the uniqueness of the hardware design of the helical tomotherapy unit and its implications in routine quality assurance, the Therapy Physics Committee of the American Association of Physicists in Medicine commissioned Task Group 148 to review this modality and make recommendations for quality assurance related methodologies. The specific objectives of this Task Group are: (a) To discuss quality assurance techniques, frequencies, and tolerances and (b) discuss dosimetric verification techniques applicable to this unit. This report summarizes the findings of the Task Group and aims to provide the practicing clinical medical physicist with the insight into the technology that is necessary to establish an independent and comprehensive quality assurance program for a helical tomotherapy unit. The emphasis of the report is to describe the rationale for the proposed QA program and to provide example tests that can be performed, drawing from the collective experience of the task group members and the published literature. It is expected that as technology continues to evolve, so will the test procedures that may be used in the future to perform comprehensive quality assurance for helical tomotherapy units.

The reliability of the convolution/superposition (C/S) algorithm of the Hi-Art tomotherapy system is evaluated by using the Monte Carlo model TomoPen, which has been already validated for homogeneous phantoms. The study was performed in three stages. First, measurements with EBT Gafchromic film for a 1.25 x 2.5 cm2 field in a heterogeneous phantom consisting of two slabs of polystyrene separated with Styrofoam were compared to simulation results from TomoPen. The excellent agreement found in this comparison justifies the use of TomoPen as the reference for the remaining parts of this work. Second, to allow analysis and interpretation of the results in clinical cases, dose distributions calculated with TomoPen and C/S were compared for a similar phantom geometry, with multiple slabs of various densities. Even in conditions of lack of lateral electronic equilibrium, overall good agreement was obtained between C/S and TomoPen results, with deviations within 3%/2 mm, showing that the C/S algorithm accounts for modifications in secondary electron transport due to the presence of a low density medium. Finally, calculations were performed with TomoPen and C/S of dose distributions in various clinical cases, from large bilateral head and neck tumors to small lung tumors with diameter of3 cm. To ensure a "fair" comparison, identical dose calculation grid and dose-volume histogram calculator were used. Very good agreement was obtained for most of the cases, with no significant differences between the DVHs obtained from both calculations. However, deviations of up to 4% for the dose received by 95% of the target volume were found for the small lung tumors. Therefore, the approximations in the C/S algorithm slightly influence the accuracy in small lung tumors even though the C/S algorithm of the tomotherapy system shows very good overall behavior.

Inversion of deformation fields is applied frequently to map images, dose, and contours between the reference frame and the study frame. A prevailing approach that takes the negative of the forward deformation as the inverse deformation is oversimplified and can cause large errors for large deformations or deformations that are composites of several deformations. Other approaches, including Newton's method and scatter data interpolation, either require the first derivative or are very inefficient. Here we propose an iterative approach that is easy to implement, converges quickly to the inverse when it does, and works for a majority of cases in practice. Our approach is rooted in fixed-point theory. We build a sequence to approximate the inverse deformation through iterative evaluation of the forward deformation. A sufficient but not necessary convergence condition (Lipschitz condition) and its proof are also given. Though this condition guarantees the convergence, it may not be met for an arbitrary deformation field. One should always check whether the inverse exists for the given forward deformation field by calculating its Jacobian. If nonpositive values of the Jacobian occur only for few voxels, this method will usually converge to a pseudoinverse. In case the iteration fails to converge, one should switch to other means of finding the inverse. We tested the proposed method on simulated 2D data and real 3D computed tomography data of a lung patient and compared our method with two implementations in the Insight Segmentation and Registration Toolkit (ITK). Typically less than ten iterations are needed for our method to get an inverse deformation field with clinically relevant accuracy. Based on the test results, our method is about ten times faster and yet ten times more accurate than ITK's iterative method for the same number of iterations. Simulations and real data tests demonstrated the efficacy and the accuracy of the proposed algorithm.

Radiographic image guidance has emerged as the new paradigm for patient positioning, target localization, and external beam alignment in radiotherapy. Although widely varied in modality and method, all radiographic guidance techniques have one thing in common--they can give a significant radiation dose to the patient. As with all medical uses of ionizing radiation, the general view is that this exposure should be carefully managed. The philosophy for dose management adopted by the diagnostic imaging community is summarized by the acronym ALARA, i.e., as low as reasonably achievable. But unlike the general situation with diagnostic imaging and image-guided surgery, image-guided radiotherapy (IGRT) adds the imaging dose to an already high level of therapeutic radiation. There is furthermore an interplay between increased imaging and improved therapeutic dose conformity that suggests the possibility of optimizing rather than simply minimizing the imaging dose. For this reason, the management of imaging dose during radiotherapy is a different problem than its management during routine diagnostic or image-guided surgical procedures. The imaging dose received as part of a radiotherapy treatment has long been regarded as negligible and thus has been quantified in a fairly loose manner. On the other hand, radiation oncologists examine the therapy dose distribution in minute detail. The introduction of more intensive imaging procedures for IGRT now obligates the clinician to evaluate therapeutic and imaging doses in a more balanced manner. This task group is charged with addressing the issue of radiation dose delivered via image guidance techniques during radiotherapy. The group has developed this charge into three objectives: (1) Compile an overview of image-guidance techniques and their associated radiation dose levels, to provide the clinician using a particular set of image guidance techniques with enough data to estimate the total diagnostic dose for a specific treatment scenario, (2) identify ways to reduce the total imaging dose without sacrificing essential imaging information, and (3) recommend optimization strategies to trade off imaging dose with improvements in therapeutic dose delivery. The end goal is to enable the design of image guidance regimens that are as effective and efficient as possible.

A helical tomotherapy system is used in our clinic to deliver intensity-modulated radiation therapy (IMRT) treatments. Since this machine is designed to deliver IMRT treatments, the traditional field flatness requirements are no longer applicable. This allows the unit to operate without a field flatness filter and consequently the 400 mm wide fan beam is highly inhomogeneous in intensity. The shape of this beam profile is mapped during machine commissioning and for quality assurance purposes the shape of the beam profile needs to be monitored. The use of a commercial diode array for quality assurance measurements is investigated. Central axis beam profiles were acquired at different depths using solid water built-up material. These profiles were compared with ion chamber scans taken in a water tank to test the accuracy of the diode array measurements. The sensitivity of the diode array to variations in the beam profile was checked. Over a seven week period, beam profiles were repeatedly measured. The observed variations are compared with those observed with an on-board beam profile monitor. The diode measurements were in agreement with the ion chamber scans. In the high dose, low gradient region the average ratio between the diode and ion chamber readings was 1.000 +/- 0.005 (+/- 1 standard deviation). In the penumbra region the agreement was poorer but all diodes passed the distance to agreement (DTA) requirement of 2 mm. The trend in the beam profile variations that was measured with the diode array device was in agreement with the on-board monitor. While the calculated amount of variation differs between the devices, both were sensitive to subtle variations in the beam profile. The diode array is a valuable tool to quickly and accurately monitor the beam profile on a helical tomotherapy unit.

Total body radiation (TBI) has been used for many years as a preconditioning agent before bone marrow transplantation. Many side effects still plague its use. We investigated the planning and delivery of total body irradiation (TBI) and selective total marrow irradiation (TMI) and a reduced radiation dose to sensitive structures using image-guided helical tomotherapy. To assess the feasibility of using helical tomotherapy, (A) we studied variations in pitch, field width, and modulation factor on total body and total marrow helical tomotherapy treatments. We varied these parameters to provide a uniform dose along with a treatment times similar to conventional TBI (15-30 min). (B) We also investigated limited (head, chest, and pelvis) megavoltage CT (MVCT) scanning for the dimensional pretreatment setup verification rather than total body MVCT scanning to shorten the overall treatment time per treatment fraction. (C) We placed thermoluminescent detectors (TLDs) inside a Rando phantom to measure the dose at seven anatomical sites, including the lungs. A simulated TBI treatment showed homogeneous dose coverage (+/-10%) to the whole body. Doses to the sensitive organs were reduced by 35%-70% of the target dose. TLD measurements on Rando showed an accurate dose delivery (+/-7%) to the target and critical organs. In the TMI study, the dose was delivered conformally to the bone marrow only. The TBI and TMI treatment delivery time was reduced (by 50%) by increasing the field width from 2.5 to 5.0 cm in the inferior-superior direction. A limited MVCT reduced the target localization time 60% compared to whole body MVCT. MVCT image-guided helical tomotherapy offers a novel method to deliver a precise, homogeneous radiation dose to the whole body target while reducing the dose significantly to all critical organs. A judicious selection of pitch, modulation factor, and field size is required to produce a homogeneous dose distribution along with an acceptable treatment time. In addition, conformal radiation to the bone marrow appears feasible in an external radiation treatment using image-guided helical tomotherapy.

An accurate means of determining and correcting for daily patient setup errors is important to the cancer outcome in radiotherapy. While many tools have been developed to detect setup errors, difficulty may arise in accurately adjusting the patient to account for the rotational error components. A novel, automated method to correct for rotational patient setup errors in helical tomotherapy is proposed for a treatment couch that is restricted to motion along translational axes. In tomotherapy, only a narrow superior/inferior section of the target receives a dose at any instant, thus rotations in the sagittal and coronal planes may be approximately corrected for by very slow continuous couch motion in a direction perpendicular to the scanning direction. Results from proof-of-principle tests indicate that the method improves the accuracy of treatment delivery, especially for long and narrow targets. Rotational corrections about an axis perpendicular to the transverse plane continue to be implemented easily in tomotherapy by adjustment of the initial gantry angle.

Inherent to helical tomotherapy is a dose variation pattern that manifests as a "ripple" (peak-to-trough relative to the average). This ripple is the result of helical beam junctioning, completely unique to helical tomotherapy. Pitch is defined as in helical CT, the couch travel distance for a complete gantry rotation relative to the axial beam width at the axis of rotation. Without scattering or beam divergence, an analytical posing of the problem as a simple integral predicts minima near a pitch of 1/n where n is an integer. A convolution-superposition dose calculator (TomoTherapy, Inc.) included all the physics needed to explore the ripple magnitude versus pitch and beam width. The results of the dose calculator and some benchmark measurements demonstrate that the ripple has sharp minima near p=0.86(1/n). The 0.86 factor is empirical and caused by a beam junctioning of the off-axis dose profiles which differ from the axial profiles as well as a long scatter tail of the profiles at depth. For very strong intensity modulation, the 0.86 factor may vary. The authors propose choosing particular minima pitches or using a second delivery that starts 180 deg off-phase from the first to reduce these ripples: "Double threading." For current typical pitches and beam widths, however, this effect is small and not clinically important for most situations. Certain extremely large field or high pitch cases, however, may benefit from mitigation of this effect.

Current dosimetric protocols based on the absorbed dose (AAPM TG-51 and IAEA TRS-398 protocols) require calibration measurements under reference conditions. For some radiotherapy systems, this requirement cannot be met, and calibration has to be performed under nonreference experimental conditions. In order to solve this problem, both protocols can be extended by inclusion of the measured-to-reference conversion factor, k(mr). In order to determine this factor, basic dosimetric quantities, like stopping power ratios, mass attenuation coefficients and chamber correction factors have to be calculated. If measurements are not feasible, accurate Monte Carlo modeling is required. The extension of the protocols is illustrated using the case of the helical tomotherapy radiation unit, where the typical calibration measurement conditions are the 10 x 5 cm2 field size and the 85 cm surface source distance, limited by the system design. It was calculated that the k(mr) factor for this conditions is close to unity (0.997+/-0.001). In addition, the deviation of the measurement conditions from the reference conditions results in the change of the quality conversion factor (approximately 0.995-0.998, depending on the ionization chamber used). This change is the same regardless of the used calibration protocol. For smaller field sizes the corrections become more significant, resulting in the total correction factor compared to the reference conditions of up to 1.5% for the smallest considered field size of 2 x 2 cm2.

Conventional radiotherapy treatment planning systems rely on a static computed tomography (CT) image for planning and evaluation. Intra/inter-fraction patient motions may result in significant differences between the planned and the delivered dose. In this paper, we develop a method to incorporate the knowledge of intra/inter-fraction patient motion directly into the dose calculation. By decomposing the motion into a parallel (to beam direction) component and perpendicular (to beam direction) component, we show that the motion effects can be accounted for by simply modifying the fluence distribution (sinogram). After such modification, dose calculation is the same as those based on a static planning image. This method is superior to the "dose-convolution" method because it is not based on "shift invariant" assumption. Therefore, it deals with material heterogeneity and surface curvature very well. We test our method using extensive simulations, which include four phantoms, four motion patterns, and three plan beams. We compare our method with the "dose-convolution" and the "stochastic simulation" methods (gold standard). As for the homogeneous flat surface phantom, our method has similar accuracy as the "dose-convolution" method. As for all other phantoms, our method outperforms the "dose-convolution." The maximum motion encoded dose calculation error using our method is within 4% of the gold standard. It is shown that a treatment planning system that is based on "motion-encoded dose calculation" can incorporate random and systematic motion errors in a very simple fashion. Under this approximation, in principle, a planning target volume definition is not required, since it already accounts for the intra/inter-fraction motion variations and it automatically optimizes the cumulative dose rather than the single fraction dose.

Helical tomotherapy is a dedicated intensity modulated radiation therapy (IMRT) system with on-board imaging capability (MVCT) and therefore differs from conventional treatment units. Different design goals resulted in some distinctive radiation field characteristics. The most significant differences in the design are the lack of flattening filter, increased shielding of the collimators, treatment and imaging operation modes and narrow fan beam delivery. Radiation characteristics of the helical tomotherapy system, sensitivity studies of various incident electron beam parameters and radiation safety analyses are presented here. It was determined that the photon beam energy spectrum of helical tomotherapy is similar to that of more conventional radiation treatment units. The two operational modes of the system result in different nominal energies of the incident electron beam with approximately 6 MeV and 3.5 MeV in the treatment and imaging modes, respectively. The off-axis mean energy dependence is much lower than in conventional radiotherapy units with less than 5% variation across the field, which is the consequence of the absent flattening filter. For the same reason the transverse profile exhibits the characteristic conical shape resulting in a 2-fold increase of the beam intensity in the center. The radiation leakage outside the field was found to be negligible at less than 0.05% because of the increased shielding of the collimators. At this level the in-field scattering is a dominant source of the radiation outside the field and thus a narrow field treatment does not result in the increased leakage. The sensitivity studies showed increased sensitivity on the incident electron position because of the narrow fan beam delivery and high sensitivity on the incident electron energy, as common to other treatment systems. All in all, it was determined that helical tomotherapy is a system with some unique radiation characteristics, which have been to a large extent optimized for intensity modulated delivery.

Helical tomotherapy presented many unique dosimetric challenges and solutions during the initial commissioning process, and some of them are presented. The dose calculation algorithm is convolution/superposition based. This requires that the energy fluence spectrum and magnitude be quantified. The methodology for doing so is described. Aspects of the energy fluence characterization that are unique to tomotherapy are highlighted. Many beam characteristics can be measured automatically by an included megavoltage computed tomography imaging system. This greatly improves data collection efficiency.

There are many benefits to having an online CT imaging system for radiotherapy, as it helps identify changes in the patient's position and anatomy between the time of planning and treatment. However, many current online CT systems suffer from a limited field-of-view (LFOV) in that collected data do not encompass the patient's complete cross section. Reconstruction of these data sets can quantitatively distort the image values and introduce artifacts. This work explores the use of planning CT data as a priori information for improving these reconstructions. Methods are presented to incorporate this data by aligning the LFOV with the planning images and then merging the data sets in sinogram space. One alignment option is explicit fusion, producing fusion-aligned reprojection (FAR) images. For cases where explicit fusion is not viable, FAR can be implemented using the implicit fusion of normal setup error, referred to as normal-error-aligned reprojection (NEAR). These methods are evaluated for multiday patient images showing both internal and skin-surface anatomical variation. The iterative use of NEAR and FAR is also investigated, as are applications of NEAR and FAR to dose calculations and the compensation of LFOV online MVCT images with kVCT planning images. Results indicate that NEAR and FAR can utilize planning CT data as imperfect a priori information to reduce artifacts and quantitatively improve images. These benefits can also increase the accuracy of dose calculations and be used for augmenting CT images (e.g., MVCT) acquired at different energies than the planning CT.

Purpose: To efficiently calculate the head scatter fluence for an arbitrary intensity-modulated field with any source distribution using the source occlusion model. Method: The source occlusion model with focal and extra focal radiation (Jaffray et al, 1993) can be used to account for LINAC head scatter. In the model, the fluence map of any field shape at any point can be calculated via integration of the source distribution within the visible range, as confined by each segment, using the detector eye's view. A 2D integration would be required for each segment and each fluence plane point, which is time-consuming, as an intensity-modulated field contains typically tens to hundreds of segments. In this work, we prove that the superposition of the segmental integrations is equivalent to a simple convolution regardless of what the source distribution is. In fact, for each point, the detector eye's view of the field shape can be represented as a function with the origin defined at the point's pinhole reflection through the center of the collimator plane. We were thus able to reduce hundreds of source plane integration to one convolution. We calculated the fluence map for various 3D and IMRT beams and various extra-focal source distributionsmore » using both the segmental integration approach and the convolution approach and compared the computation time and fluence map results of both approaches. Results: The fluence maps calculated using the convolution approach were the same as those calculated using the segmental approach, except for rounding errors (