Engineering topics

Herman, Michael G.

Publications and source records attributed to Herman, Michael G..

8 records

DOE OSTI2016

Exploratory Study of 4D versus 3D Robust Optimization in Intensity Modulated Proton Therapy for Lung Cancer

Purpose: The purpose of this study was to compare the impact of uncertainties and interplay on 3-dimensional (3D) and 4D robustly optimized intensity modulated proton therapy (IMPT) plans for lung cancer in an exploratory methodology study. Methods and Materials: IMPT plans were created for 11 nonrandomly selected non-small cell lung cancer (NSCLC) cases: 3D robustly optimized plans on average CTs with internal gross tumor volume density overridden to irradiate internal target volume, and 4D robustly optimized plans on 4D computed tomography (CT) to irradiate clinical target volume (CTV). Regular fractionation (66 Gy [relative biological effectiveness; RBE] in 33 fractions) was considered. In 4D optimization, the CTV of individual phases received nonuniform doses to achieve a uniform cumulative dose. The root-mean-square dose-volume histograms (RVH) measured the sensitivity of the dose to uncertainties, and the areas under the RVH curve (AUCs) were used to evaluate plan robustness. Dose evaluation software modeled time-dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Dose-volume histogram (DVH) indices comparing CTV coverage, homogeneity, and normal tissue sparing were evaluated using Wilcoxon signed rank test. Results: 4D robust optimization plans led to smaller AUC for CTV (14.26 vs 18.61, respectively; P=.001), better CTV coverage (Gy [RBE]) (D{sub 95%} CTV: 60.6 vs 55.2, respectively; P=.001), and better CTV homogeneity (D{sub 5%}-D{sub 95%} CTV: 10.3 vs 17.7, resspectively; P=.002) in the face of uncertainties. With interplay effect considered, 4D robust optimization produced plans with better target coverage (D{sub 95%} CTV: 64.5 vs 63.8, respectively; P=.0068), comparable target homogeneity, and comparable normal tissue protection. The benefits from 4D robust optimization were most obvious for the 2 typical stage III lung cancer patients. Conclusions: Our exploratory methodology study showed that, compared to 3D robust optimization, 4D robust optimization produced significantly more robust and interplay-effect-resistant plans for targets with comparable dose distributions for normal tissues. A further study with a larger and more realistic patient population is warranted to generalize the conclusions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

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

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

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

Effects of minimum monitor unit threshold on spot scanning proton plan quality

Purpose: To investigate the influence of the minimum monitor unit (MU) on the quality of clinical treatment plans for scanned proton therapy. Methods: Delivery system characteristics limit the minimum number of protons that can be delivered per spot, resulting in a min-MU limit. Plan quality can be impacted by the min-MU limit. Two sites were used to investigate the impact of min-MU on treatment plans: pediatric brain tumor at a depth of 5–10 cm; a head and neck tumor at a depth of 1–20 cm. Three-field, intensity modulated spot scanning proton plans were created for each site with the following parameter variations: min-MU limit range of 0.0000–0.0060; and spot spacing range of 2–8 mm. Comparisons were based on target homogeneity and normal tissue sparing. For the pediatric brain, two versions of the treatment planning system were also compared to judge the effects of the min-MU limit based on when it is accounted for in the optimization process (Eclipse v.10 and v.13, Varian Medical Systems, Palo Alto, CA). Results: The increase of the min-MU limit with a fixed spot spacing decreases plan quality both in homogeneous target coverage and in the avoidance of critical structures. Both head and neck and pediatric brain plans show a 20% increase in relative dose for the hot spot in the CTV and 10% increase in key critical structures when comparing min-MU limits of 0.0000 and 0.0060 with a fixed spot spacing of 4 mm. The DVHs of CTVs show min-MU limits of 0.0000 and 0.0010 produce similar plan quality and quality decreases as the min-MU limit increases beyond 0.0020. As spot spacing approaches 8 mm, degradation in plan quality is observed when no min-MU limit is imposed. Conclusions: Given a fixed spot spacing of ≤4 mm, plan quality decreases as min-MU increased beyond 0.0020. The effect of min-MU needs to be taken into consideration while planning proton therapy treatments.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Implication of spot position error on plan quality and patient safety in pencil-beam-scanning proton therapy

Purpose: To quantitatively and systematically assess dosimetric effects induced by spot positioning error as a function of spot spacing (SS) on intensity-modulated proton therapy (IMPT) plan quality and to facilitate evaluation of safety tolerance limits on spot position. Methods: Spot position errors (PE) ranging from 1 to 2 mm were simulated. Simple plans were created on a water phantom, and IMPT plans were calculated on two pediatric patients with a brain tumor of 28 and 3 cc, respectively, using a commercial planning system. For the phantom, a uniform dose was delivered to targets located at different depths from 10 to 20 cm with various field sizes from 2{sup 2} to 15{sup 2} cm{sup 2}. Two nominal spot sizes, 4.0 and 6.6 mm of 1 σ in water at isocenter, were used for treatment planning. The SS ranged from 0.5 σ to 1.5 σ, which is 2–6 mm for the small spot size and 3.3–9.9 mm for the large spot size. Various perturbation scenarios of a single spot error and systematic and random multiple spot errors were studied. To quantify the dosimetric effects, percent dose error (PDE) depth profiles and the value of percent dose error at the maximum dose difference (PDE [ΔDmax]) were used for evaluation. Results: A pair of hot and cold spots was created per spot shift. PDE[ΔDmax] is found to be a complex function of PE, SS, spot size, depth, and global spot distribution that can be well defined in simple models. For volumetric targets, the PDE [ΔDmax] is not noticeably affected by the change of field size or target volume within the studied ranges. In general, reducing SS decreased the dose error. For the facility studied, given a single spot error with a PE of 1.2 mm and for both spot sizes, a SS of 1σ resulted in a 2% maximum dose error; a SS larger than 1.25 σ substantially increased the dose error and its sensitivity to PE. A similar trend was observed in multiple spot errors (both systematic and random errors). Systematic PE can lead to noticeable hot spots along the field edges, which may be near critical structures. However, random PE showed minimal dose error. Conclusions: Dose error dependence for PE was quantitatively and systematically characterized and an analytic tool was built to simulate systematic and random errors for patient-specific IMPT. This information facilitates the determination of facility specific spot position error thresholds.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Comparison of two methods for minimizing the effect of delayed charge on the dose delivered with a synchrotron based discrete spot scanning proton beam

Purpose: Delayed charge is a small amount of charge that is delivered to the patient after the planned irradiation is halted, which may degrade the quality of the treatment by delivering unwarranted dose to the patient. This study compares two methods for minimizing the effect of delayed charge on the dose delivered with a synchrotron based discrete spot scanning proton beam. Methods: The delivery of several treatment plans was simulated by applying a normally distributed value of delayed charge, with a mean of 0.001(SD 0.00025) MU, to each spot. Two correction methods were used to account for the delayed charge. Method one (CM1), which is in active clinical use, accounts for the delayed charge by adjusting the MU of the current spot based on the cumulative MU. Method two (CM2) in addition reduces the planned MU by a predicted value. Every fraction of a treatment was simulated using each method and then recomputed in the treatment planning system. The dose difference between the original plan and the sum of the simulated fractions was evaluated. Both methods were tested in a water phantom with a single beam and simple target geometry. Two separate phantom tests were performed. In one test the dose per fraction was varied from 0.5 to 2 Gy using 25 fractions per plan. In the other test the number fractions were varied from 1 to 25, using 2 Gy per fraction. Three patient plans were used to determine the effect of delayed charge on the delivered dose under realistic clinical conditions. The order of spot delivery using CM1 was investigated by randomly selecting the starting spot for each layer, and by alternating per layer the starting spot from first to last. Only discrete spot scanning was considered in this study. Results: Using the phantom setup and varying the dose per fraction, the maximum dose difference for each plan of 25 fractions was 0.37–0.39 Gy and 0.03–0.05 Gy for CM1 and CM2, respectively. While varying the total number of fractions, the maximum dose difference increased at a rate of 0.015 Gy and 0.0018 Gy per fraction for CM1 and CM2, respectively. For CM1, the largest dose difference was found at the location of the first spot in each energy layer, whereas for CM2 the difference in dose was small and showed no dependence on location. For CM1, all of the fields in the patient plans had an area where their excess dose overlapped. No such correlation was found when using CM2. Randomly selecting the starting spot reduces the maximum dose difference from 0.708 to 0.15 Gy. Alternating between first and last spot reduces the maximum dose difference from 0.708 to 0.37 Gy. In the patient plans the excess dose scaled linearly at 0.014 Gy per field per fraction for CM1 and standard delivery order. Conclusions: The predictive model CM2 is superior to a cumulative irradiation model CM1 for minimizing the effects of delayed charge, particularly when considering maximal dose discrepancies and the potential for unplanned hot-spots. This study shows that the dose discrepancy potentially scales at 0.014 Gy per field per fraction for CM1.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Optimizing mini-ridge filter thickness to reduce proton treatment times in a spot-scanning synchrotron system

Purpose: Study the contributors to treatment time as a function of Mini-Ridge Filter (MRF) thickness to determine the optimal choice for breath-hold treatment of lung tumors in a synchrotron-based spot-scanning proton machine. Methods: Five different spot-scanning nozzles were simulated in TOPAS: four with MRFs of varying maximal thicknesses (6.15–24.6 mm) and one with no MRF. The MRFs were designed with ridges aligned along orthogonal directions transverse to the beam, with the number of ridges (4–16) increasing with MRF thickness. The material thickness given by these ridges approximately followed a Gaussian distribution. Using these simulations, Monte Carlo data were generated for treatment planning commissioning. For each nozzle, standard and stereotactic (SR) lung phantom treatment plans were created and assessed for delivery time and plan quality. Results: Use of a MRF resulted in a reduction of the number of energy layers needed in treatment plans, decreasing the number of synchrotron spills needed and hence the treatment time. For standard plans, the treatment time per field without a MRF was 67.0 ± 0.1 s, whereas three of the four MRF plans had treatment times of less than 20 s per field; considered sufficiently low for a single breath-hold. For SR plans, the shortest treatment time achieved was 57.7 ± 1.9 s per field, compared to 95.5 ± 0.5 s without a MRF. There were diminishing gains in time reduction as the MRF thickness increased. Dose uniformity of the PTV was comparable across all plans; however, when the plans were normalized to have the same coverage, dose conformality decreased with MRF thickness, as measured by the lung V20%. Conclusions: Single breath-hold treatment times for plans with standard fractionation can be achieved through the use of a MRF, making this a viable option for motion mitigation in lung tumors. For stereotactic plans, while a MRF can reduce treatment times, multiple breath-holds would still be necessary due to the limit imposed by the proton extraction time. To balance treatment time and normal tissue dose, the ideal MRF choice was shown to be the thinnest option that is able to achieve the desired breath-hold timing.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2011

An accelerated threshold-based back-projection algorithm for Compton camera image reconstruction

Purpose: Compton camera imaging (CCI) systems are currently under investigation for radiotherapy dose reconstruction and verification. The ability of such a system to provide real-time images during dose delivery will be limited by the computational speed of the image reconstruction algorithm. In this work, the authors present a fast and simple method by which to generate an initial back-projected image from acquired CCI data, suitable for use in a filtered back-projection algorithm or as a starting point for iterative reconstruction algorithms, and compare its performance to the current state of the art. Methods: Each detector event in a CCI system describes a conical surface that includes the true point of origin of the detected photon. Numerical image reconstruction algorithms require, as a first step, the back-projection of each of these conical surfaces into an image space. The algorithm presented here first generates a solution matrix for each slice of the image space by solving the intersection of the conical surface with the image plane. Each element of the solution matrix is proportional to the distance of the corresponding voxel from the true intersection curve. A threshold function was developed to extract those pixels sufficiently close to the true intersection to generate a binary intersection curve. This process is repeated for each image plane for each CCI detector event, resulting in a three-dimensional back-projection image. The performance of this algorithm was tested against a marching algorithm known for speed and accuracy. Results: The threshold-based algorithm was found to be approximately four times faster than the current state of the art with minimal deficit to image quality, arising from the fact that a generically applicable threshold function cannot provide perfect results in all situations. The algorithm fails to extract a complete intersection curve in image slices near the detector surface for detector event cones having axes nearly parallel to the image plane. This effect decreases the sum of the image, thereby also affecting the mean, standard deviation, and SNR of the image. All back-projected events associated with a simulated point source intersected the voxel containing the source and the FWHM of the back-projected image was similar to that obtained from the marching method. Conclusions: The slight deficit to image quality observed with the threshold-based back-projection algorithm described here is outweighed by the 75% reduction in computation time. The implementation of this method requires the development of an optimum threshold function, which determines the overall accuracy of the method. This makes the algorithm well-suited to applications involving the reconstruction of many large images, where the time invested in threshold development is offset by the decreased image reconstruction time. Implemented in a parallel-computing environment, the threshold-based algorithm has the potential to provide real-time dose verification for radiation therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2011

Improving patient safety in radiation oncology

Beginning in the 1990s, and emphasized in 2000 with the release of an Institute of Medicine report, healthcare providers and institutions have dedicated time and resources to reducing errors that impact the safety and well-being of patients. But in January 2010 the first of a series of articles appeared in the New York Times that described errors in radiation oncology that grievously impacted patients. In response, the American Association of Physicists in Medicine and the American Society of Radiation Oncology sponsored a working meeting entitled ''Safety in Radiation Therapy: A Call to Action''. The meeting attracted 400 attendees, including medical physicists, radiation oncologists, medical dosimetrists, radiation therapists, hospital administrators, regulators, and representatives of equipment manufacturers. The meeting was cohosted by 14 organizations in the United States and Canada. The meeting yielded 20 recommendations that provide a pathway to reducing errors and improving patient safety in radiation therapy facilities everywhere.

60 APPLIED LIFE SCIENCES↗