Leaf Open Time Research Articles

MO‐FF‐A2‐04: Pulsed Reduced Dose‐Rate Radiotherapy On a Helical Tomotherapy Unit

Purpose/Background: Pulsed reduced dose‐rate radiotherapy (PRDR) re‐irradiation has the potential to reduce late normal tissue toxicity while yielding nearly identical tumoricidal effect. A typical method using a conventional linac is to deliver a series of 20cGy pulses separated by 3‐minute intervals to give an average dose‐rate of 6.67cGy/min. Dissimilarly, PRDR done via helical tomotherapy would not require an interlude if the sub‐fraction time is approximately 3 minutes, since the top of the PTV will have had a 3‐minute “rest” by the time the bottom is finished. However, intrinsic MLC leaf open time (LOT) limitations in tomotherapy deteriorate plan quality and deliverability when attempting to deliver very low doses (<40cGy). We investigated various means to overcome this limitation to deliver PRDR with a helical tomotherapy device. Method and Materials: Two different cases (central and non‐central targets) were studied. Plans were generated with different combinations of jaw‐width (1.05cm and 2.5cm), pitch (0.43 and 0.86), and modulation factor (MF) (1.5 and 2.5) to administer eight 25cGy sub‐fractions as part of 2Gy to PTV for 20 fractions, giving a total of 40Gy dose. Plans were compared using dose‐volume histogram (DVH), homogeneity indexes (HI), conformation number (CN), and treatment time. DQA for each plan was performed to assess deliverability. Results: Clinically acceptable DVHs with a ∼3 minute treatment duration are achievable with several combinations of jaw width and pitch. However, dose discrepancies were >3% in those plans where average LOT is <70msec, which falls into the high‐error region in the MLC latency curve. The combination of small jaw‐width (1cm), low MF (1.5) and large pitch (0.86), as well as using directional blocks gives clinically acceptable results in dose distribution, beam‐on time, and delivery accuracy (<3%). Conclusion: With a careful selection of planning parameters, PRDR re‐irradiation is deliverable in an efficient fashion on a tomotherapy unit.

SU-FF-T-209: Implementation of 2D Arrays for TomoTherapy Patient-Specific QA

Purpose: 2D arrays were not designed for rotational delivery modalities such as TomoTherapy. This study explores their clinical use and develops a methodology for minimizing their limitations. Method and Materials: The MatriXX ion chamber array (MULTICube phantom) and the MapCHECK diode array (MapPHAN phantom) were calibrated using a TomoTherapy plan with a contour enclosing the center diode/ion chamber and an adjacent ion chamber in solid water for absolute dose calibration. Eight prototype TomoTherapy treatment plans were created with various directional blocks to restrict beam delivery angles. Delivery verification plans for these prototype plans and for multiple clinical patient plans were created using MVCT images of each array in its respective phantom and then delivered. For comparison, film and ion chamber measurements were made with the cylindrical TomoTherapy cheese phantom. Results: Clinically, less than 5% of more than 100 patient treatment plans verified with these 2D arrays had pass rates less than 95% for a 3%/3-mm DTA criterion. Relative dose comparisons for the failing plans all had pass rates above 95%, indicating a calibration/scaling error. DQAs for a prototype plan that restricted beams to a 45 degree lateral arc had pass rates of ∼40% (absolute error > 5%) for both devices, indicating a problem with lateral beams. Similar arc restrictions in the AP/PA plane produced plans with pass rates > 95% for both devices. To minimize these effects, two approaches were explored. Histograms of MLC leaf opening times as a function of projection angle were used to either determine the optimal device orientation or to determine a calibration procedure that more closely matched the angular distribution of delivery beams. Conclusion: Both devices can be used with TomoTherapy satisfactorily, but care must be taken to orient and calibrate the 2D array under delivery conditions that more closely match the treatment delivery conditions.

Treatment Planning to Improve Delivery Accuracy and Patient Throughput in Helical Tomotherapy

To investigate delivery quality assurance (DQA) discrepancies observed for a subset of helical tomotherapy patients. Six tomotherapy patient plans were selected for analysis. Three had passing DQA ion chamber (IC) measurements, whereas 3 had measurements deviating from the expected dose by more than 3.0%. All plans used similar parameters, including: 2.5 cm field-width, 15-s gantry period, and pitch values ranging from 0.143 to 0.215. Preliminary analysis suggested discrepancies were associated with plans having predominantly small leaf open times (LOTs). To test this, patients with failing DQA measurements were replanned using an increased pitch of 0.287. New DQA plans were generated and IC measurements performed. Exit fluence data were also collected during DQA delivery for dose reconstruction purposes. Sinogram analysis showed increases in mean LOTs ranging from 29.8% to 83.1% for the increased pitch replans. IC measurements for these plans showed a reduction in dose discrepancies, bringing all measurements within +/-3.0%. The replans were also more efficient to deliver, resulting in reduced treatment times. Dose reconstruction results were in excellent agreement with IC measurements, illustrating the impact of leaf-timing inaccuracies on plans having predominantly small LOTs. The impact of leaf-timing inaccuracies on plans with small mean LOTs can be considerable. These inaccuracies result from deviations in multileaf collimator latency from the linear approximation used by the treatment planning system and can be important for plans having a 15-s gantry period. The ability to reduce this effect while improving delivery efficiency by increasing the pitch is demonstrated.

Independent calculation of dose from a helical TomoTherapy unit

A new calculation algorithm has been developed for independently verifying doses calculated by the TomoTherapy® Hi·Art® treatment planning system (TPS). The algorithm is designed to confi rm the dose to a point in a high dose, low dose‐gradient region. Patient data used by the algorithm include the radiological depth to the point for each projection angle and the treatment sinogram file controlling the leaf opening time for each projection. The algorithm uses common dosimetric functions [tissue phantom ratio (TPR) and output factor (Scp)] for the central axis combined with lateral and longitudinal beam profile data to quantify the off‐axis dose dependence. Machine data for the dosimetric functions were measured on the Hi·Art machine and simulated using the TPS. Point dose calculations were made for several test phantoms and for 97 patient treatment plans using the simulated machine data. Comparisons with TPS‐predicted point doses for the phantom treatment plans demonstrated agreement within 2% for both on‐axis and off‐axis planning target volumes (PTVs). Comparisons with TPS‐predicted point doses for the patient treatment plans also showed good agreement. For calculations at sites other than lung and superficial PTVs, agreement between the calculations was within 2% for 94% of the patient calculations (64 of 68). Calculations within lung and superficial PTVs overestimated the dose by an average of 3.1% (σ=2.4%) and 3.2% (σ=2.2%), respectively. Systematic errors within lung are probably due to the weakness of the algorithm in correcting for missing tissue and/or tissue density heterogeneities. Errors encountered within superficial PTVs probably result from the algorithm overestimating the scatter dose within the patient. Our results demonstrate that for the majority of cases, the algorithm could be used without further refinement to independently verify patient treatment plans.PACS number(s): 87.53.Bn, 87.53.Dq, 87.53.Xd

Real-time motion-adaptive delivery (MAD) using binary MLC: II. Rotational beam (tomotherapy) delivery

TomoTherapy delivery is controlled by a planned, projection-wised leaf sequence (sinogram) that is optimized during treatment planning. In this paper, we developed a software solution for real-time motion compensation that delivers helical TomoTherapy plans without modifying the hardware and workflow of the TomoTherapy delivery system. Unlike the dynamic MLC-based method, our technique only requires instantaneous tumor positions, which greatly simplifies its implementation. This technique re-uses the planned sinogram by shuffling its projections and leaf sequences. In order to compensate for longitudinal tumor motion in real-time, instead of sequential execution of the planned sinogram, the projections are executed out of order. That is, we may choose a past or future projection of the planned sinogram rather than the current projection depending on tumor motion, so that the planned radiation source position of the chosen projection is the same as the radiation source position at the current delivery time in the tumor reference frame. The transverse tumor motion is further compensated for by shifting and scaling the leaf open time of the chosen projection. We tested different planned sinograms that were optimized using various synthetic tumor/OAR configurations, as well as planned sinogram of a lung cancer patient, all with zero motion margins. Various TomoTherapy machine parameters and both regular and irregular respiratory traces were used in calculations. By applying the motion-adaptive delivery (MAD) technique, the delivered dose matched the planned dose very well in both DVH and dose profiles. As for the regular and minor irregular respiration, the dose errors were well below 3 mm and 3% criteria. No hot and cold spots were noticeable. For irregular respiration with some missing breathing cycles, this method demonstrates the capability for motion margin reduction.

Monte Carlo calculation of helical tomotherapy dose delivery

Helical tomotherapy delivers intensity modulated radiation therapy using a binary multileaf collimator (MLC) to modulate a fan beam of radiation. This delivery occurs while the linac gantry and treatment couch are both in constant motion, so the beam describes, from a patient/phantom perspective, a spiral or helix of dose. The planning system models this continuous delivery as a large number (51) of discrete gantry positions per rotation, and given the small jaw/fan width setting typically used (1 or 2.5 cm) and the number of overlapping rotations used to cover the target (pitch often <0.5), the treatment planning system (TPS) potentially employs a very large number of static beam directions and leaf opening configurations to model the modulated fields. All dose calculations performed by the system employ a convolution/superposition model. In this work the authors perform a full Monte Carlo (MC) dose calculation of tomotherapy deliveries to phantom computed tomography (CT) data sets to verify the TPS calculations. All MC calculations are performed with the EGSnrc-based MC simulation codes, BEAMnrc and DOSXYZnrc. Simulations are performed by taking the sinogram (leaf opening versus time) of the treatment plan and decomposing it into 51 different projections per rotation, as does the TPS, each of which is segmented further into multiple MLC opening configurations, each with different weights that correspond to leaf opening times. Then the projection is simulated by the summing of all of the opening configurations, and the overall rotational treatment is simulated by the summing of all of the projection simulations. Commissioning of the source model was verified by comparing measured and simulated values for the percent depth dose and beam profiles shapes for various jaw settings. The accuracy of the MLC leaf width and tongue and groove spacing were verified by comparing measured and simulated values for the MLC leakage and a picket fence pattern. The validated source and MLC configuration were then used to simulate a complex modulated delivery from fixed gantry angle. Further, a preliminary rotational treatment plan to a delivery quality assurance phantom (the "cheese" phantom) CT data set was simulated. Simulations were compared with measured results taken with an A1SL ionization chamber or EDR2 film measurements in a water tank or in a solid water phantom, respectively. The source and MLC MC simulations agree with the film measurements, with an acceptable number of pixels passing the 2%/1 mm gamma criterion. 99.8% of voxels of the MC calculation in the planning target volume (PTV) of the preliminary plan passed the 2%/2 mm gamma value test. 87.0% and 66.2% of the voxels in two organs at risk (OARs) passed the 2%/2 mm tests. For a 3%/3 mm criterion, the PTV and OARs show 100%, 93.2%, and 86.6% agreement, respectively. All voxels passed the gamma value test with a criterion of 5%/3 mm. The Tomo-Therapy TPS showed comparable results.

WE-D-AUD B-04: Dosimetric Evaluation of a Delivery Verification and Dose Reconstruction Method for Helical Tomotherapy

Purpose: To determine the dosimetric accuracy of a dose reconstruction method used for verification of helical tomotherapy delivery for four different clinical sites. Method and Materials: A delivery verification and dose reconstruction method has been applied to helical tomotherapy treatment plans of four different treatment sites (prostate, head and neck, lung and total scalp). Treatment plans were generated on a cylindrical measurement phantom (TomoPhantom) using contours, prescriptions and planning objectives taken from clinical patient plans from the four sites. Several film and ion chambermeasurements were made for each plan to simulate the dose variation with multiple deliveries. Additional measurements mere made with intentional changes made to the machine output and leaf open times. A TomoTherapy delivery verification tool uses pulse‐by‐pulse machine CT detector and transmission ion chamber data, extracted at the conclusion of each delivery, to determine the incident energy fluence delivered for each projection. Dose reconstruction with the delivered energy fluence was calculated on the planning CT and compared with both the measured dose distributions and those calculated from the original treatment plan. Differences were compared using dose difference plots. Results:Measured(ion chamber) dose variations in the center of the PTV for repeated daily deliveries of a given treatment plan were small, typically within 2%. Greatest differences in the measured doses occurred with intentional changes in leaf open times. The measured dose variations were well predicted by the dose reconstruction method, which demonstrated agreement with the measured dose within 2%. The dose reconstruction method also demonstrated acceptable agreement with the film dose measurements, for each of the clinical plans. Conclusion: Variations in treatment delivery due to machine output or leaf opening time changes can be determined using the investigated method. Conflict of Interest: Supported in part by a research agreement with TomoTherapy, Inc.

SU‐GG‐T‐136: Real Time Delivery Verification Using Exit Detector Data

Purpose: TomoTherapy® treatment systems have exit MV detectors that record the radiation fluence during treatment. This information can be used in real time to verify delivered dose. Method and Materials: We developed a method that can extract the MLC leaf open time from the detector data without relying on the patient CT or pre‐measured database proposed by previous researchers. Because each leaf has penumbra, an open leaf will contribute signals to the detectors that correspond to adjacent leaves. Therefore, a closed leaf could be reported as open if its adjacent leaf is open. To eliminate the impact of the penumbra, we model the penumbra with a point‐spread‐function and apply an iterative deconvolution procedure to remove the penumbra. The iterative method successfully removes the penumbra without introducing ringing artifacts. The MLC leaf open time is then extracted with a simple thresholding method. To verify the algorithm, we install optical sensor on each MLC leaf that reports the leaf position. The leaf open time extracted from exit detector is compared to the optical sensor report. Results: The leaf open time extracted from the exit detector showed good agreement with the optical sensor under a variety of conditions, such as different attenuation phantom and different delivery sinogram. The detector measured leaf open time agrees with the optical sensor within 0.2 ms and a standard deviation of 3.6 ms. The impact of these uncertainties to the dose calculation is estimated to be around 0.2%. The algorithm is optimized so that it can run on the onboard computer in the machine to process the detector data in real time. Conclusion: The exit detectors in TomoTherapy® treatment systems can provide us information of leaf behavior during delivery. Together with the monitor chambers of the linac, the actual delivered dose to patient can be calculated.

TU‐FF‐A1‐05: Treatment Planning to Reduce the Impact of Delivery Errors in Helical Tomotherapy

Purpose: To investigate the source of delivery quality assurance (DQA) errors observed for a subset of patients planned for treatment on Tomotherapy. Method and Materials: Six patients planned on Tomotherapy were selected for analysis. Three patients had passing DQA plans and three had DQA plans with ion‐chamber measurements that deviated from the expected dose by more than 3%. All patients were planned using similar parameters, including a 2.5 cm field width and pitch values ranging from 0.143–0.215. Machine output was determined not to be the problem so normalized leaf timing sinograms were analyzed to determine the mean leaf open time (LOT) for each plan. This analysis suggests the observed discrepancies are associated with plans having predominantly low LOTs. To test this, patients with failing DQA measurements were replanned using an increased pitch of 0.287. After replanning, new DQA plans were generated and ion‐chamber measurements performed. Exit fluence data was also collected during the DQA delivery using the onboard MVCT detectors for dose reconstruction purposes. Results: Sinogram analysis showed increases in mean LOTs of 30–85% for the higher pitch plans. In addition, ion‐chamber measurements showed a reduction in point dose errors of 1.9–4.4%, bringing all patient plans within the ±3% acceptance criteria. Dose reconstruction results were in excellent agreement with ion‐chamber measurements and clearly illustrate the impact of leaf timing errors on plans having predominantly small LOTs. Conclusion: The impact of leaf timing errors on plans with low mean LOTs can be significant. This becomes important for plans using low pitches, or potentially for hyper‐fractionated treatment schedules. The ability to reduce the impact of these errors by increasing the plan pitch is demonstrated. In addition, the efficacy of dose reconstruction in diagnosing delivery errors is established. Conflict of Interest: Some authors have a financial interest in TomoTherapy, Inc.

SU-FF-T-175: Dosimetric Effect of Rotational Variation On Helical Tomotherapy Treatment Plans

Purpose: Helical tomotherapy is subject to rotational output variation during treatment delivery. The purpose of this study is to evaluate the dosimetric effects of the rotational variation using recalculated treatment plans which include a rotational variation. Method and Materials: In order to assess the rotational output variation, the monitor chamber signal was extracted from delivered treatment data archives and analyzed. The rotational variation was then modeled and incorporated back into the treatment plan sinogram by adjusting the leaf opening times for each projection. The modified treatment plans were then calculated using a research version of the planned adaptive treatment planning software from TomoTherapy, Inc. Two treatment plans, one head and neck and one prostate, were evaluated in this study. Treatment plans were recalculated with an observed rotational variation of ±2 % and a hypothetical variation of ±10 % for comparison to the original calculated treatment plans. Results: The rotational variation from delivered treatments was found to follow a sinusoidal shape with a period equal to one gantry rotation and a magnitude of about ±2% on average. For a rotational variation of ±2%, the D95 for the target volumes and the D50 for critical structures were found to be different from the original plan by less than 0.26% for the recalculated treatment plans. For a hypothetical rotational variation of ±10%, the difference from the original was less than 0.5% for the D95 for target volumes and 1.4% for the D50 of critical structures. Conclusion: The rotational variation for delivered helical tomotherapy treatments was found to be on the order of ±2%. For this observed rotational variation, a negligible dosimetric effect on calculated helical tomotherapy treatment plans was found. Conflict of Interest: Our group holds a research grant from TomoTherapy, Inc.

TH-C-M100J-02: Real Time Motion Adaptive Delivery-I. Topotherapy

Purpose: Topotherapy is a new delivery technique that uses the binary MLC to implement static beam IMRT. We present a simple approach for real time motion adaptive delivery (MAD) of topotherapy plan using the current delivery system. Methods: Topotherapy uses fixed jaws and binary MLC for intensity modulation and its projection rate is a few Hz. Topotherapy delivery is controlled by a planned projection‐wised leaf sequence, which is optimized assuming stationary target. The couch proceeds in constant speed. To compensate longitudinal tumor motion in real time, instead of sequential execution of the planned leaf sequence, the projections are out of order executed. That is, a previous or future projection that with the same planned target position as the current status, is chosen instead. The transversal target motion is further compensated by shifting and scaling the MLC leaf open time at the chosen projection. Results: Extensive simulations with realistic topotherapy parameters and respiration motions validate MAD technique. The delivered dose conformed well to the target regardless how target moved during delivery. Significant margin reduction could be approached provided that real time tumor localization is achievable. Discussions and Conclusions: We present a novel technique for real time MAD in topotherapy. Unlike the dynamic MLC based tracking method, this technique requires neither the whole target motion trajectory nor the velocity of target motion. Instead, it only requires instantaneous target positions, which greatly simplifies the system implementation. This technique re‐uses the planned leaf sequence by re‐ordering its projection and leaf sequence. It does not involve time consuming re‐optimization. The simulations validated the presented technique. Experimental validation and extension to helical tomotherapy delivery is presented in another paper of this conference.

Po‐Thur Eve General‐08: Monte Carlo Simulation of Helical Tomotherapy

Helical tomotherapy represents the state of the art in intensity modulated radiation therapy (IMRT) and image guided adaptive radiotherapy (IGAR). This work is aimed at carrying out Monte Carlo (MC) dose calculations of tomotherapy deliveries to real phantom and virtual phantom/patient CT data. All MC calculations are performed with the EGSnrc‐based MC simulation codes, BEAMnrc and DOSXYZnrc. Various MC parameters and variance reduction techniques were investigated and optimized. Single projection simulations are carried out to get percent depth dose (PDD) and beam profiles at various depths and lateral field dimensions. Simulations are compared with measured results taken with an A1SL ionization chamber in a water tank. A complex delivery was simulated with the 64 leaf binary multileaf collimator (MLC) modulating at fixed radiation angle for a solid water phantom. Further, a rotational treatment plan to a cheese phantom CT data set was also simulated. Simulations are performed by taking the sinogram (leaf opening vs. time) of the treatment plan and decomposing it into different projections, each of which is segmented further into several opening configurations with different MLC settings and weights, which corresponded to leaf opening time. Then the projection is simulated with the result of sum of all of the opening configurations, and the overall rotational treatment is simulated with the result of sum of all of the projection simulations. Measured and simulated profiles and PDDs are found agree with each other well. Preliminary simulations of full treatment plans are also presented.

TH‐E‐ValA‐03: Topographic Leaf‐Sequencing Using a Genetic Algorithm

Purpose: To develop a leaf‐sequencing algorithm for fixed‐gantry (nonrotational) treatment delivery on a commercial helical tomotherapy system (HI‐ART, TomoTherapy, Inc., Madison, WI). Method and Materials: A genetic algorithm was used to determine the multileaf collimator (MLC) leaf open times for a series of fluence test maps generated from a tomotherapy machine with a fixed gantry angle of 0 degrees (IEC scale). A series of wedge shapes (15, 30, 45, and 60‐degree) were mathematically created to test the algorithm's ability to produce simple modulations, similar to those which would be encountered in breast radiation therapy. Results: In general, the topographic treatment delivery yielded reasonable dose distributions. The agreement for the wedge cases was within ±2%, or 2‐mm distance‐to‐agreement (DTA) in the high dose gradient regions. The central axis measured dose was between 3.6 and 4.2 percent higher than the expected dose for the wedge cases. For double peaks, the agreement was within ±2%, or 2‐mm DTA across the entire measured film. For quadruple peaks, the agreement was within ±2%, or 2‐mm DTA in the high dose gradient regions. At the first peak, calculated and measured agreed to within ±0.5%. The dose gradient between the first peak and the first valley was 5 percent per centimeter. The dose in the first valley agreed to within ±1.6% of the prescribed dose (at the first peak). The maximum error in the quadruple peaks occurred at the second peak, where the measured dose was 3.8% low (relative to the prescribed dose at the first peak). Conclusions: The developed algorithm produced calculated deliverable distributions that agreed well with the artificially constructed distributions. This delivery technique could be used for treatment of a whole intact breast. Additional work is needed to optimize the algorithm to improve agreement between the calculated doses and deliverable dose distributions.