Engineering topics

Unkelbach, J

Publications and source records attributed to Unkelbach, J.

8 records

DOE OSTI2016

SU-D-204-02: BED Consistent Extrapolation of Mean Dose Tolerances

Purpose: The safe use of radiotherapy requires the knowledge of tolerable organ doses. For experimental fractionation schemes (e.g. hypofractionation) these are typically extrapolated from traditional fractionation schedules using the Biologically Effective Dose (BED) model. This work demonstrates that using the mean dose in the standard BED equation may overestimate tolerances, potentially leading to unsafe treatments. Instead, extrapolation of mean dose tolerances should take the spatial dose distribution into account. Methods: A formula has been derived to extrapolate mean physical dose constraints such that they are mean BED equivalent. This formula constitutes a modified BED equation where the influence of the spatial dose distribution is summarized in a single parameter, the dose shape factor. To quantify effects we analyzed 14 liver cancer patients previously treated with proton therapy in 5 or 15 fractions, for whom also photon IMRT plans were available. Results: Our work has two main implications. First, in typical clinical plans the dose distribution can have significant effects. When mean dose tolerances are extrapolated from standard fractionation towards hypofractionation they can be overestimated by 10–15%. Second, the shape difference between photon and proton dose distributions can cause 30–40% differences in mean physical dose for plans having the same mean BED. The combined effect when extrapolating proton doses to mean BED equivalent photon doses in traditional 35 fraction regimens resulted in up to 7–8 Gy higher doses than when applying the standard BED formula. This can potentially lead to unsafe treatments (in 1 of the 14 analyzed plans the liver mean dose was above its 32 Gy tolerance). Conclusion: The shape effect should be accounted for to avoid unsafe overestimation of mean dose tolerances, particularly when estimating constraints for hypofractionated regimens. In addition, tolerances established for a given treatment modality cannot necessarily be applied to other modalities with drastically different dose distributions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-H-BRC-02: Biological Dose Escalation for Liver SBRT Through Spatiotemporal Fractionation

Purpose: Stereotactic body radiotherapy (SBRT) has become an established treatment option for liver cancer. For patients with large tumors, the prescription dose is often limited by constraints on the mean liver dose, leading to tumor recurrence. In this work, we demonstrate that spatiotemporal fractionation schemes, ie delivering distinct dose distributions in different fractions, may allow for a 10% increase in biologically effective dose (BED) in the tumor compared to current practice where each fraction delivers the same dose distribution. Methods: We consider rotation therapy delivered with x-ray beams. Treatment plan optimization is performed using objective functions evaluated for the cumulative BED delivered at the end of treatment. This allows for simultaneously optimizing multiple distinct treatment plans for different fractions. Results: The treatment that optimally exploits fractionation effects is designed such that each fraction delivers a similar dose bath to the uninvolved liver while delivering high single fraction doses to complementary parts of the target volume. Thereby, partial hypofractionation in the tumor is achieved along with near uniform fractionation in the surrounding liver - leading to an improvement in the therapeutic ratio. The benefit of such spatiotemporal fractionation schemes depends on tumor geometry and location as well as the number of fractions. For 5-fraction treatments (allowing for 5 distinct dose distributions) an improvement in the order of 10% is observed. Conclusion: Delivering distinct dose distributions in different fractions, purely motivated by fractionation effects rather than geometric changes, may improve the therapeutic ratio. For treatment sites where the prescriptions dose is limited by mean dose constraints in the surrounding organ, such as liver cancer, this approach may facilitate biological dose escalation and improved cure rates.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-CD-209-06: LET-Based Adjustment of IMPT Plans Using Prioritized Optimization

Purpose: In-vitro experiments suggest an increase in proton relative biological effectiveness (RBE) towards the end of range. However, proton treatment planning and dose reporting for clinical outcome assessment has been based on physical dose and constant RBE. Therefore, treatment planning for intensity-modulated proton therapy (IMPT) is unlikely to transition radically to pure RBE-based planning. We suggest a hybrid approach where treatment plans are initially created based on physical dose constraints and prescriptions, and are subsequently altered to avoid high linear energy transfer (LET) in critical structures while limiting the degradation of the physical dose distribution. Methods: To allow fast optimization based on dose and LET we extended a GPU-based Monte-Carlo code towards providing dose-averaged LET in addition to dose for all pencil beams. After optimizing an initial IMPT plan based on physical dose, a prioritized optimization scheme is used to modify the LET distribution while constraining the physical dose objectives to values close to the initial plan. The LET optimization step is performed based on objective functions evaluated for the product of physical dose and LET (LETxD). To first approximation, LETxD represents a measure of the additional biological dose that is caused by high LET. Regarding optimization techniques, LETxD has the advantage of being a linear function of the pencil beam intensities. Results: The method is applicable to treatments where serial critical structures with maximum dose constraint are located in or near the target. We studied intra-cranial tumors (high-grade meningiomas, base-of-skull chordomas) where the target (CTV) overlaps with the brainstem and optic structures. Often, high LETxD in critical structures can be avoided while minimally compromising physical dose planning objectives. Conclusion: LET-based re-optimization of IMPT plans represents a pragmatic approach to bridge the gap between purely physical dose-based and RBE-based planning. It can be realized with fast GPU-based Monte-Carlo dose calculation. The project was in part supported by NIH grants U19 CA 021239-36 and C06 CA 059267.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-EF-304-08: LET-Based Inverse Planning for IMPT

Purpose: Cell survival experiments suggest that the relative biological effectiveness (RBE) of proton beams depends on linear energy transfer (LET), leading to higher RBE near the end of range. With intensity-modulated proton therapy (IMPT), multiple treatment plans that differ in the dose contribution per field may yield a similar physical dose distribution, but the RBE-weighted dose distribution may be disparate. RBE models currently do not have the required predictive power to be included in an optimization model due to the variations in experimental data. We propose an LET-based planning method that guides IMPT optimization models towards plans with reduced RBE-weighted dose in surrounding organs at risk (OARs) compared to inverse planning based on physical dose alone. Methods: Optimization models for physical dose are extended with a term for dose times LET (doseLET). Monte Carlo code is used to generate the physical dose and doseLET distribution of each individual pencil beam. The method is demonstrated for an atypical meningioma patient where the target volume abuts the brainstem and partially overlaps with the optic nerve. Results: A reference plan optimized based on physical dose alone yields high doseLET values in parts of the brainstem and optic nerve. Minimizing doseLET in these critical structures as an additional planning goal reduces the risk of high RBE-weighted dose. The resulting treatment plan avoids the distal fall-off of the Bragg peaks for shaping the dose distribution in front of critical stuctures. The maximum dose in the OARs evaluated with RBE models from literature is reduced by 8–14\% with our method compared to conventional planning. Conclusion: LET-based inverse planning for IMPT offers the ability to reduce the RBE-weighted dose in OARs without sacrificing target dose. This project was in part supported by NCI - U19 CA 21239.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

TH-A-BRE-01: The Status of Intensity Modulated Proton and Ion Therapy

IMRT with photons has become a radiation therapy standard of care for many cancer treatment sites. The situation is quite different with intensity modulated particle (protons and ion) radiation therapy (IMPT). With the rapid development of beam scanning techniques and many of the newer proton facilities exclusively offering active beam scanning as their radiation delivery technique, it is timely to give an update on the status and challenges of IMPT. The leading principle in IMPT is to aim at the target from several, not necessarily coplanar, directions with multiple pencil beams that are modulated in their intensity and adjusted in their energy such that a desired dose distribution or, more generally, a desired bio-effective dose distribution is achieved. Different from low-LET photons, the varying relative biological effectiveness (RBE) along the beam path adds an additional dimension to the treatment planning process and will require biophysical modeling at least for carbon ion therapy. IMPT involves computationally challenging tasks, yet it needs to be very fast in order to be clinically relevant. To make IMPT computationally tractable, robust and efficient optimization methods are required. Lastly, IMPT planning is very sensitive to accurate knowledge of relative stopping and scattering powers of the intervening tissues as well as intra- and inter-fraction motion. Robust planning methods are being developed in order to obtain IMPT plans that are less sensitive against such uncertainties. This therapy symposium will present an update on the current status and emerging developments of IMPT from the medical physics perspective. Learning Objectives: Become familiar with current delivery techniques for IMPT and their limitations. Understand the basics of dose calculational algorithms and commissioning of IMPT. Learn how to assess the accuracy of planning and delivery of IMPT treatments. Get an overview of currently used and emerging optimization techniques. Learn about the pro or contra arguments for using IMPT for moving targets.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2014

TH-E-BRF-01: Exploiting Tumor Shrinkage in Split-Course Radiotherapy

Purpose: In split-course radiotherapy, a patient is treated in several stages separated by weeks or months. This regimen has been motivated by radiobiological considerations. However, using modern image-guidance, it also provides an approach to reduce normal tissue dose by exploiting tumor shrinkage. In this work, we consider the optimal design of split-course treatments, motivated by the clinical management of large liver tumors for which normal liver dose constraints prohibit the administration of an ablative radiation dose in a single treatment. Methods: We introduce a dynamic tumor model that incorporates three factors: radiation induced cell kill, tumor shrinkage, and tumor cell repopulation. The design of splitcourse radiotherapy is formulated as a mathematical optimization problem in which the total dose to the liver is minimized, subject to delivering the prescribed dose to the tumor. Based on the model, we gain insight into the optimal administration of radiation over time, i.e. the optimal treatment gaps and dose levels. Results: We analyze treatments consisting of two stages in detail. The analysis confirms the intuition that the second stage should be delivered just before the tumor size reaches a minimum and repopulation overcompensates shrinking. Furthermore, it was found that, for a large range of model parameters, approximately one third of the dose should be delivered in the first stage. The projected benefit of split-course treatments in terms of liver sparing depends on model assumptions. However, the model predicts large liver dose reductions by more than a factor of two for plausible model parameters. Conclusion: The analysis of the tumor model suggests that substantial reduction in normal tissue dose can be achieved by exploiting tumor shrinkage via an optimal design of multi-stage treatments. This suggests taking a fresh look at split-course radiotherapy for selected disease sites where substantial tumor regression translates into reduced target volumes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-E-T-478: Sliding Window Multi-Criteria IMRT Optimization

Purpose: To demonstrate a method for what-you-see-is-what-you-get multi-criteria Pareto surface navigation for step and shoot IMRT treatment planning. Methods: We show mathematically how multiple sliding window treatment plans can be averaged to yield a single plan whose dose distribution is the dosimetric average of the averaged plans. This is incorporated into the Pareto surface navigation based approach to treatment planning in such a way that as the user navigates the surface, the plans he/she is viewing are ready to be delivered (i.e. there is no extra ‘segment the plans’ step that often leads to unacceptable plan degradation in step and shoot Pareto surface navigation). We also describe how the technique can be applied to VMAT. Briefly, sliding window VMAT plans are created such that MLC leaves paint out fluence maps every 15 degrees or so. These fluence map leaf trajectories are averaged in the same way the static beam IMRT ones are. Results: We show mathematically that fluence maps are exactly averaged using our leaf sweep averaging algorithm. Leaf transmission and output factor corrections effects, which are ignored in this work, can lead to small errors in terms of the dose distributions not being exactly averaged even though the fluence maps are. However, our demonstrations show that the dose distributions are almost exactly averaged as well. We demonstrate the technique both for IMRT and VMAT. Conclusions: By turning to sliding window delivery, we show that the problem of losing plan fidelity during the conversion of an idealized fluence map plan into a deliverable plan is remedied. This will allow for multicriteria optimization that avoids the pitfall that the planning has to be redone after the conversion into MLC segments due to plan quality decline. David Craft partially funded by RaySearch Laboratories.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

SU-E-T-549: A Combinatorial Optimization Approach to Treatment Planning with Non-Uniform Fractions in Intensity Modulated Proton Therapy

Purpose: Non-uniform fractionation, i.e. delivering distinct dose distributions in two subsequent fractions, can potentially improve outcomes by increasing biological dose to the target without increasing dose to healthy tissues. This is possible if both fractions deliver a similar dose to normal tissues (exploit the fractionation effect) but high single fraction doses to subvolumes of the target (hypofractionation). Optimization of such treatment plans can be formulated using biological equivalent dose (BED), but leads to intractable nonconvex optimization problems. We introduce a novel optimization approach to address this challenge. Methods: We first optimize a reference IMPT plan using standard techniques that delivers a homogeneous target dose in both fractions. The method then divides the pencil beams into two sets, which are assigned to either fraction one or fraction two. The total intensity of each pencil beam, and therefore the physical dose, remains unchanged compared to the reference plan. The objectives are to maximize the mean BED in the target and to minimize the mean BED in normal tissues, which is a quadratic function of the pencil beam weights. The optimal reassignment of pencil beams to one of the two fractions is formulated as a binary quadratic optimization problem. A near-optimal solution to this problem can be obtained by convex relaxation and randomized rounding. Results: The method is demonstrated for a large arteriovenous malformation (AVM) case treated in two fractions. The algorithm yields a treatment plan, which delivers a high dose to parts of the AVM in one of the fractions, but similar doses in both fractions to the normal brain tissue adjacent to the AVM. Using the approach, the mean BED in the target was increased by approximately 10% compared to what would have been possible with a uniform reference plan for the same normal tissue mean BED.

61 RADIATION PROTECTION AND DOSIMETRY↗