Neelam Tyagi

Photon beam relative dose validation of the DPM Monte Carlo code in lung-equivalent media.

Validation experiments have been conducted using 6 and 15 MV photons in inhomogeneous (water/lung/water) media to benchmark the accuracy of the DPM Monte Carlo code for photon beam dose calculations. Small field sizes (down to 2 x 2 cm2) and low-density media were chosen for this investigation because the intent was to test the DPM code under conditions where lateral electronic disequilibrium effects are emphasized. The treatment head components of a Varian 21EX linear accelerator, including the jaws (defining field sizes of 2 x 2, 3 x 3 and 10 x 10 cm2), were simulated using the BEAMnrc code. The phase space files were integrated within the DPM code system, and central axis depth dose and profile calculations were compared against diode measurements in a homogeneous water phantom in order to validate the phase space. Results of the homogeneous phantom study indicated that the relative differences between DPM calculations and measurements were within +/- 1% (based on the rms deviation) for the depth dose curves; relative profile dose differences were on average within +/- 1%/1 mm. Depth dose and profile measurements were carried out using an ion-chamber and film, within an inhomogeneous phantom consisting of a 6 cm slab of lung-equivalent material embedded within solid water. For the inhomogeneous phantom experiment, DPM depth dose calculations were within +/- 1% (based on the rms deviation) of measurements; relative profile differences at depths within and beyond the lung were, on average, within +/- 2% in the inner and outer beam regions, and within 1-2 mm distance-to-agreement within the penumbral region. Relative point differences on the order of 2-3% were within the estimated experimental uncertainties. This work demonstrates that the DPM Monte Carlo code is capable of accurate photon beam dose calculations in situations where lateral electron disequilibrium effects are pronounced.

A fluence convolution method to account for respiratory motion in three-dimensional dose calculations of the liver: A Monte Carlo study

We describe the implementation of a fluence convolution method to account for the influence of superior-inferior (SI) respiratory induced motion on a Monte Carlo-based dose calculation of a tumor located in the liver. This method involves convolving the static fluence map with a function describing the SI motion of the liver-the motion function has been previously derived from measurements of diaphragm movement observed under fluoroscopy. Significant differences are noted between fluence-convolved and static dose distributions in an example clinical treatment plan; hot and cold spots (on the order of 25%) are observed in the fluence-convolved plan at the superior and inferior borders of the liver, respectively. This study illustrates that the fluence convolution method can be incorporated into Monte Carlo dose calculation algorithms to account for some of the effects of patient breathing during radiotherapy treatment planning, thus leading to more accurate dose calculations.

Synchronized dynamic dose reconstruction

Variations in target volume position between and during treatment fractions can lead to measurable differences in the dose distribution delivered to each patient. Current methods to estimate the ongoing cumulative delivered dose distribution make idealized assumptions about individual patient motion based on average motions observed in a population of patients. In the delivery of intensity modulated radiation therapy (IMRT) with a multi-leaf collimator (MLC), errors are introduced in both the implementation and delivery processes. In addition, target motion and MLC motion can lead to dosimetric errors from interplay effects. All of these effects may be of clinical importance. Here we present a method to compute delivered dose distributions for each treatment beam and fraction, which explicitly incorporates synchronized real-time patient motion data and real-time fluence and machine configuration data. This synchronized dynamic dose reconstruction method properly accounts for the two primary classes of errors that arise from delivering IMRT with an MLC: (a) Interplay errors between target volume motion and MLC motion, and (b) Implementation errors, such as dropped segments, dose over/under shoot, faulty leaf motors, tongue-and-groove effect, rounded leaf ends, and communications delays. These reconstructed dose fractions can then be combined to produce high-quality determinations of the dose distribution actually received to date, from which individualized adaptive treatment strategies can be determined.

Implementation of the DPM Monte Carlo code on a parallel architecture for treatment planning applications.

We have parallelized the Dose Planning Method (DPM), a Monte Carlo code optimized for radiotherapy class problems, on distributed-memory processor architectures using the Message Passing Interface (MPI). Parallelization has been investigated on a variety of parallel computing architectures at the University of Michigan-Center for Advanced Computing, with respect to efficiency and speedup as a function of the number of processors. We have integrated the parallel pseudo random number generator from the Scalable Parallel Pseudo-Random Number Generator (SPRNG) library to run with the parallel DPM. The Intel cluster consisting of 800 MHz Intel Pentium III processor shows an almost linear speedup up to 32 processors for simulating 1 x 10(8) or more particles. The speedup results are nearly linear on an Athlon cluster (up to 24 processors based on availability) which consists of 1.8 GHz+ Advanced Micro Devices (AMD) Athlon processors on increasing the problem size up to 8 x 10(8) histories. For a smaller number of histories (1 x 10(8)) the reduction of efficiency with the Athlon cluster (down to 83.9% with 24 processors) occurs because the processing time required to simulate 1 x 10(8) histories is less than the time associated with interprocessor communication. A similar trend was seen with the Opteron Cluster (consisting of 1400 MHz, 64-bit AMD Opteron processors) on increasing the problem size. Because of the 64-bit architecture Opteron processors are capable of storing and processing instructions at a faster rate and hence are faster as compared to the 32-bit Athlon processors. We have validated our implementation with an in-phantom dose calculation study using a parallel pencil monoenergetic electron beam of 20 MeV energy. The phantom consists of layers of water, lung, bone, aluminum, and titanium. The agreement in the central axis depth dose curves and profiles at different depths shows that the serial and parallel codes are equivalent in accuracy.

Experimental verification of a Monte Carlo-based MLC simulation model for IMRT dose calculations in heterogeneous media

Inter- and intra-leaf transmission and head scatter can play significant roles in intensity modulated radiation therapy (IMRT)-based treatment deliveries. In order to accurately calculate the dose in the IMRT planning process, it is therefore important that the detailed geometry of the multi-leaf collimator (MLC), in addition to other components in the accelerator treatment head, be accurately modeled. In this paper, we have used the Monte Carlo method (MC) to develop a comprehensive model of the Varian 120 leaf MLC and have compared it against measurements in homogeneous phantom geometries under different IMRT delivery circumstances. We have developed a geometry module within the DPM MC code to simulate the detailed MLC design and the collimating jaws. Tests consisting of leakage, leaf positioning and static MLC shapes were performed to verify the accuracy of transport within the MLC model. The calculations show agreement within 2% in the high dose region for both film and ion-chamber measurements for these static shapes. Clinical IMRT treatment plans for the breast [both segmental MLC (SMLC) and dynamic MLC (DMLC)], prostate (SMLC) and head and neck split fields (SMLC) were also calculated and compared with film measurements. Such a range of cases were chosen to investigate the accuracy of the model as a function of modulation in the beamlet pattern, beamlet width, and field size. The overall agreement is within 2% /2 mm of the film data for all IMRT beams except the head and neck split field, which showed differences up to 5% in the high dose regions. Various sources of uncertainties in these comparisons are discussed.

SU‐EE‐A1‐02: Experimental Evaluation and Verification of the Deliverability Aspects of IMRT Beams Optimized with Adaptive Diffusion Smoothing

Purpose: To experimentally determine the impact of adaptive diffusion smoothing (ADS) on the delivery accuracy and efficiency of IMRT fields. Method and Materials:IMRToptimization was performed on several cases with and without the use of an ADS penalty applied within the objective function. The ADS penalty is based on diffusion principles and promotes smoothing in beam areas that are not essential to meeting the cost function objectives. Previous studies have shown that the use of the ADS penalty results in IMRT plans that are dosimetrically equivalent, less complex, and require fewer MU to deliver compared to standard IMRT. All plans were sequenced and delivered via step‐and‐shoot delivery. Film and ion‐chamber dosimetry were performed, and the total MU, delivery time, and differences between convolution/superposition calculations and film measurements for standard and ADS IMRT beams were evaluated. Results: Measurements verified that IMRT plans optimized using the ADS penalty were less likely to exhibit small regions of disagreement due to factors such as tongue‐and‐groove compared to standard IMRT plans. In particular, the in‐field agreement between calculations and measurements for the ADS plans was superior to the more modulated standard IMRT plans. The use of ADS resulted in the area outside a +/− 5 cGy criteria between calculations and film measurements decreasing from 3.7 to 1.8 % in a head/neck example and from 10.8 to 6.7 % in a prostate example. In addition, the total MU for SMLC delivery was reduced by 20 to 45 % in all cases with no loss in plan quality according to the DVHs and dose metrics. Conclusion: The use of the ADS penalty inside an inverse IMRT plan objective function reduces beam complexity without sacrificing dosimetric quality and results in significantly more efficient and accurate delivery of IMRT fields. Supported in part by NIH grant P01‐CA59827.

MO‐D‐224A‐09: Validation of Synchronized Dynamic Dose Reconstruction Using Film Dosimetry

Purpose: To validate a method of retrospective dose reconstruction that uses real‐time intra‐treatment patient motion data that is synchronized with MLC leaf positions during IMRT treatments. Method and Materials:IMRT fields from an IRB‐approved prostate protocol were delivered to a water‐equivalent phantom on a programmable translation stage. Kodak XV film was placed at 5 cm depth with an SSD of 95cm and marked to register it with the Monte Carlo (MC) calculation grid. Motion was synchronized with beam delivery by using the target signal to trigger motion. Film measurements were repeated for each beam while the phantom was stationary, and while moving with both idealized and clinically measured motion profiles. MLC leaf positions and fluence state for each beam were obtained from the Varian DynaLog files. MC dose accumulation was performed which incorporated the real‐time phantom motion, DynaLog files and beam state. Films were digitized and compared to the results of the MC calculations. Results: Film measurements in stationary phantoms were measured three times on two machines. The measured dose distributions were compared and showed an average difference of 0.38 +/− 1.53 cGy. The average difference between MC and film measurements of the moving phantom was 0.44 +/− 3.4 cGy and was independent of the motion profile. Measured dose patterns, for both stationary and moving phantoms, were generally well reproduced by MC dose accumulation, including tongue‐and‐groove and motion related features. Doses in moving and static phantoms were compared, for both films and simulations. The measured dose deviations due to motion were well‐characterized by the MC dose accumulation method and not significantly different when a static phantom was compared to MC calculation. Conclusion: Real‐time motion and machine data may be used to reconstruct the dose delivered to the target volume, and may serve as a basis for dynamic refinement of treatments.

SU‐FF‐T‐445: Use of the Monte Carlo Method as a Comprehensive Tool for SMLC and DMLC‐Based IMRT Delivery and Quality Assurance (QA)

Purpose: To report on use of a thoroughly benchmarked MC dose calculation algorithm as an accurate tool for IMRT delivery and QA, in patient‐like media, where direct measurements for routine QA are impractical. Methods and material: We have developed a source model to investigate dosimetric effects related to MLC based delivery techniques such as step‐and‐shoot and sliding window using the DPM MC code. The model incorporates details of the Varian, 120‐leaf MLC and has been comprehensively verified against measurements in homogeneous and heterogeneous phantoms. As part of this development, we have investigated an efficient algorithm, using adaptive kernel density estimation for sampling phase space files. Using this accurate source model, we have studied beams that were sequenced with 1% and 10% fluence intervals for prostate, brain, head and neck and breast IMRT beams. Dose differences between SMLC and DMLC delivery types were evaluated in homogeneous and heterogeneous media (bone, lung and low‐density slabs) using DPM. We have also investigated dosimetric differences between optimized planned leaf sequences and actual delivered sequences, using machine log (Dynalog) files, which capture the physical leaf positions during delivery. Results: Benchmarking of the source model showed average agreement with measurements within 1%/2 mm. For a given fluence interval, calculated dose differences between SMLC and DMLC delivery techniques are different in homogeneous and heterogeneous media. Dose differences of up to 10% were found between plans developed with 1% and 10% fluence intervals for either SMLC or DMLC delivered sequences. Calculated dose differences of up to ±3cGy were observed between planned and delivered sequences (computed using the Dynalog files) for a prostate beam; these differences were in good agreement with film measurements. Conclusions: A well commissioned MC‐based dose algorithm provides a useful tool to study dosimetric issues related to fluence modulation and static versus dynamic delivery in IMRT.

SU‐FF‐T‐402: Synchronized Dynamic Dose Reconstruction

Purpose: To present a dose accumulation method that explicitly incorporates real‐time target volume motion, and real‐time machine configuration, MLC motion and fluence state. Method and Materials: Effects of inter‐ and intra‐fraction motion on dose distributions delivered to a target volume are typically estimated by statistical methods that rely on idealized assumptions such as constant random and systematic errors, and constant offsets, periods and amplitudes of motion over the entire course of therapy. In addition, implementation and delivery related issues such as leaf sequencing limitations, spatial interplay between MLC leaf and target volume motion, and temporal interplay of the fluence state in IMRT, are assumed to average out during treatment. To include these effects, a dose accumulation technique is proposed which explicitly incorporates real‐time target volume motion data, and real‐time treatment machine data. Several technologies are becoming available to continuously monitor (10–30 Hz) the patient position, organs‐at‐risk, and the target volume during therapy. Likewise, real‐time (20 Hz) machine configuration, leaf position and fluence state data, is currently available in the Varian DynaLog files. These datasets are synchronized at the beginning of each beam; and the Monte Carlo method, which inherently accounts for time dependence, was used for dose calculations. Results: By synchronizing target volume position, machine configuration, leaf positions and fluence state, with sub‐second resolution, the dose delivered by each beam, may be accumulated. Such accumulated dose distributions reflect the interplay between target volume motion, MLC leaf motion and other machine‐related delivery effects based on real‐time, patient specific, measured data. The delivered dose distribution to date may then be compared to the planned dose distribution to provide input for dynamic refinement of treatment planning and delivery.Conclusion:Delivered target volume dose may be reconstructed using real‐time motion and machine data, and serve as a basis for dynamic refinement of treatments.

TU‐C‐T‐6E‐07: Monte Carlo Investigation of Dosimetric Differences Between SMLC and DMLC IMRT Delivery Techniques in Heterogeneous Media

Purpose: To investigate dosimetric differences between SMLC and DMLC IMRT delivery techniques in heterogeneous media using MC. We hypothesize that subtle differences in the energy spectra between SMLC and DMLC, which may not be detected in water, will be accentuated in inhomogeneous, patient-like tissues. With the ability to account for MLC design details and perform accurate transport in heterogeneous media, MC provides a powerful means to evaluate IMRT delivery methods and may be useful as a tool for IMRT QA. Method and Materials: The BEAMnrc code was used to simulate patient independent components of a Varian 21EX linac. The resultant Phase space file was then used as input for the DPM MC code which simulates the jaws, 120-leaf MLC geometry, and the patient or phantom. Transport through the jaws and MLC is accomplished using multiple scatter photon transport. Sampling algorithms have been developed for SMLC and DMLC by randomly sampling leaf segments based on the MU index. Accuracy of the simulations was assessed in a homogeneous media when compared to measurements in a solid water phantom. To assess the impact of MLC design and delivery technique in heterogeneous media, dose was calculated in a phantom consisting of material slabs ranging in density from lung to cortical bone using SMLC and DMLC leaf sequences. Results: Excellent agreement was seen between the Monte Carlo models for SMLC and DMLC sequencing when compared to the respective film measurements in homogenous media. Significant differences, up to 10%, were seen between the delivery techniques in lung equivalent media when calculated in heterogeneous slab geometry. Conclusion: This study provides evidence that heterogeneous tissue may exacerbate energy differences between SMLC and DMLC delivery methods. Such differences may be clinically important considering that they will not be detected during QA which is typically conducted using homogeneous phantoms.