Y Lei

Automatic planning on hippocampal avoidance whole-brain radiotherapy

Mounting evidence suggests that radiation-induced damage to the hippocampus plays a role in neurocognitive decline for patients receiving whole-brain radiotherapy (WBRT). Hippocampal avoidance whole-brain radiotherapy (HA-WBRT) has been proposed to reduce the putative neurocognitive deficits by limiting the dose to the hippocampus. However, urgency of palliation for patients as well as the complexities of the treatment planning may be barriers to protocol enrollment to accumulate further clinical evidence. This warrants expedited quality planning of HA-WBRT. Pinnacle3 Automatic treatment planning was designed to increase planning efficiency while maintaining or improving plan quality and consistency. The aim of the present study is to evaluate the performance of the Pinnacle3 Auto-Planning on HA-WBRT treatment planning. Ten patients previously treated for brain metastases were selected. Hippocampal volumes were contoured on T1 magnetic resonance (MR) images, and planning target volumes (PTVs) were generated based on RTOG0933. The following 2 types of plans were generated by Pinnacle3 Auto-Planning: the one with 2 coplanar volumetric modulated arc therapy (VMAT) arcs and the other with 9-field noncoplanar intensity-modulated radiation therapy (IMRT). D2% and D98% of PTV were used to calculate homogeneity index (HI). HI and Paddick Conformity index (CI) of PTV as well as D100% and Dmax of the hippocampus were used to evaluate the plan quality. All the auto-plans met the dose coverage and constraint objectives based on RTOG0933. The auto-plans eliminated the necessity of generating pseudostructures by the planners, and it required little manual intervention which expedited the planning process. IMRT quality assurance (QA) results also suggest that all the auto-plans are practically acceptable on delivery. Pinnacle3 Auto-Planning generates acceptable plans by RTOG0933 criteria without time-consuming planning process. The expedited quality planning achieved by Auto-Planning (AP) may facilitate protocol enrollment of patients to further investigate the hippocampal-sparing effect and be used to ensure timely start of palliative treatment in future clinical practice.

Investigations of a GPU-based levy-firefly algorithm for constrained optimization of radiation therapy treatment planning

Abstract Intensity modulated radiation therapy (IMRT) affords the potential to decrease radiation therapy associated toxicity by creating highly conformal dose distribution to tumor. Inverse optimization of IMRT treatment plans is often a time intensive task due to the large scale solution space, and the indubitably complexity of the task. Furthermore, the incorporation of conflicting dose constraints in the treatment plan, usually introduces an additional degree of intricacy. Metaheuristic algorithms have been proposed in the past for global optimization in IMRT treatment planning. However one disadvantage of the aforementioned methods is their extensive computational cost. One way to ameliorate their performance deficiency is to parallelize the application. In the current study we propose a GPU-based levy-firefly algorithm (LFA) for constrained optimization of IMRT treatment planning. The evaluation of our method was realized for two treatment cases: a prostate and a head and neck (H&N) cancer IMRT plans. The studies indicated an ascendable increase of the speedup factor as a function of the number of pencil beams with a maximum of ~11, whereas the performance of the algorithm was decreasing as a function of the population of the swarm particles. In addition, from our simulation results we concluded that 200 fireflies were sufficient for the algorithm to converge in less than 80 iterations. Finally, we demonstrated the effect of penalizing factors on constraining the maximum dose at the organs at risk (OAR) by impeding the dose coverage of the tumor target. The impetus behind our study was to elucidate the performance and generic attributes of the proposed algorithm, as well as the potential of its applicability for IMRT optimization problems.

A new variable for SRS plan quality evaluation based on normal tissue sparing: the effect of prescription isodose levels

OBJECTIVE A new dosimetric variable, dose-dropping speed (DDS), was proposed and used to evaluate normal tissue sparing among stereotactic radiosurgery (SRS) plans with different prescription isodose lines. METHODS 40 plans were generated for 8 intracranial SRS cases, prescribing to isodose levels (IDLs) ranging from 50% to 90% in 10% increments. Whilst maintaining similar coverage and conformity, plans at different IDLs were evaluated in terms of normal tissue sparing using the proposed DDS. The DDS was defined as the greater decay coefficient in a double exponential decay fit of the dose drop-off outside the planning target volume (PTV), which models the steep portion of the drop-off. Provided that the prescription dose covers the whole PTV, a greater DDS indicates better normal tissue sparing. RESULTS Among all plans, the DDS was found to be the lowest for the prescription at 90% IDL and the highest for the prescription at 60% or 70%. The beam profile slope change in the penumbra and its field size dependence were explored and given as the physical basis of the findings. CONCLUSION A variable was proposed for SRS plan quality evaluation. Using this measure, prescriptions at 60% and 70% IDLs were found to provide best normal tissue sparing. ADVANCES IN KNOWLEDGE A new variable was proposed based on which normal tissue sparing was quantitatively evaluated, comparing different prescription IDLs in SRS.

A self-tuned bat algorithm for optimization in radiation therapy treatment planning

The performance of any optimization algorithm largely depends on the setting of its algorithm-dependent parameters. Swarm intelligence algorithms are popular methods in optimization since they have been proved very efficient. One drawback of those methods though, is that the appropriate setting of the algorithm-dependent parameters has a significant impact on the algorithms performance. The “parameter tuning” of an algorithm in such a way to be able to find the optimal solution by using the minimum number of iterations, quite often is a difficult and time consuming task depending on the optimization problem. Essentially this is a hyper-optimization problem, that is, the optimization of the optimization algorithm. In this paper, a novel self-tuned metaheuristic algorithm is presented for optimization in radiation therapy treatment planning. The proposed Self-Tuned Bat Algorithm (STBA) finds itself the optimal set of algorithm-dependent parameters and therefore minimizes the number of iterations required for the optimization to reach sub-optimal solution. The applicability of the proposed algorithm is demonstrated in the optimization of a prostate case using intensity modulation radiation therapy (IMRT).

Estimation of internal organ motion-induced variance in radiation dose in non-gated radiotherapy

In the delivery of non-gated radiotherapy (RT), owing to intra-fraction organ motion, a certain degree of RT dose uncertainty is present. Herein, we propose a novel mathematical algorithm to estimate the mean and variance of RT dose that is delivered without gating. These parameters are specific to individual internal organ motion, dependent on individual treatment plans, and relevant to the RT delivery process. This algorithm uses images from a patients 4D simulation study to model the actual patient internal organ motion during RT delivery. All necessary dose rate calculations are performed in fixed patient internal organ motion states. The analytical and deterministic formulae of mean and variance in dose from non-gated RT were derived directly via statistical averaging of the calculated dose rate over possible random internal organ motion initial phases, and did not require constructing relevant histograms. All results are expressed in dose rate Fourier transform coefficients for computational efficiency. Exact solutions are provided to simplified, yet still clinically relevant, cases. Results from a volumetric-modulated arc therapy (VMAT) patient case are also presented. The results obtained from our mathematical algorithm can aid clinical decisions by providing information regarding both mean and variance of radiation dose to non-gated patients prior to RT delivery.

Technical Note: Fabricating Cerrobend grids with 3D printing for spatially modulated radiation therapy: A feasibility study.

PURPOSE Grid therapy has promising applications in the radiation treatment of large tumors. However, research and applications of grid therapy are limited by the accessibility of the specialized blocks that produce the grid of pencil-like radiation beams. In this study, a Cerrobend grid block was fabricated using the 3D printing technique. METHODS A grid block mold was designed with flared tubes which follow the divergence of the beam. The mold was 3D printed using a resin with the working temperature below 230 °C. The melted Cerrobend liquid at 120 °C was cast into the resin mold to yield a block with a thickness of 7.4 cm. At the isocenter plane, the grid had a hexagonal pattern, with each pencil beam diameter of 1.4 cm; the distance between the beam centers was 2.1 cm. RESULTS The dosimetric properties of the grid block were studied using small field dosimeters: a pinpoint ionization chamber and a stereotactic diode. For a 6 MV photon beam, its valley-to-peak ratio was 20% at dmax and 30% at 10 cm depth; the output factor was 84.9% at dmax and 65.1% at 10 cm depth. CONCLUSIONS This study demonstrates that it is feasible to implement 3D printing technique in applying grid therapy in clinic.

Using weighted power mean for equivalent square estimation

Abstract Purpose Equivalent Square (ES) enables the calculation of many radiation quantities for rectangular treatment fields, based only on measurements from square fields. While it is widely applied in radiotherapy, its accuracy, especially for extremely elongated fields, still leaves room for improvement. In this study, we introduce a novel explicit ES formula based on Weighted Power Mean (WPM) function and compare its performance with the Sterling formula and Vadash/Bjärngards formula. Methods The proposed WPM formula is ESWPMa,b=waα+1−wbα1/α for a rectangular photon field with sides a and b. The formula performance was evaluated by three methods: standard deviation of model fitting residual error, maximum relative model prediction error, and models Akaike Information Criterion (AIC). Testing datasets included the ES table from British Journal of Radiology (BJR), photon output factors (S cp) from the Varian TrueBeam Representative Beam Data (Med Phys. 2012;39:6981–7018), and published S cp data for Varian TrueBeam Edge (J Appl Clin Med Phys. 2015;16:125‐148). Results For the BJR dataset, the best‐fit parameter value α = −1.25 achieved a 20% reduction in standard deviation in ES estimation residual error compared with the two established formulae. For the two Varian datasets, employing WPM reduced the maximum relative error from 3.5% (Sterling) or 2% (Vadash/Bjärngard) to 0.7% for open field sizes ranging from 3 cm to 40 cm, and the reduction was even more prominent for 1 cm field sizes on Edge (J Appl Clin Med Phys. 2015;16:125–148). The AIC value of the WPM formula was consistently lower than its counterparts from the traditional formulae on photon output factors, most prominent on very elongated small fields. Conclusion The WPM formula outperformed the traditional formulae on three testing datasets. With increasing utilization of very elongated, small rectangular fields in modern radiotherapy, improved photon output factor estimation is expected by adopting the WPM formula in treatment planning and secondary MU check.

A feasibility study of applying thermal imaging to assist quality assurance of high-dose rate brachytherapy

Aim: High-dose rate (HDR) brachytherapy poses a special challenge to radiation safety and quality assurance (QA) due to its high radioactivity, and it is thus critical to verify the HDR source location and its radioactive strength. This study explores a new application for thermal imaging, to visualize/locate the HDR source and measure radioactivity using temperature information. A potential application would relate to HDR QA and safety improvement. Methods: Heating effects by an HDR source were studied using finite element analysis (FEA). Thermal cameras were used to visualize an HDR source inside a plastic catheter made of polyvinylidene difluoride (PVDF). Using different source dwell times, relationships between the HDR source strength and heating effects were studied, thus establishing potential daily QA criteria using thermal imaging. Results: For an Ir-192 source with a source radioactivity of 10 Ci, the decay-induced heating power inside the source was about 13.3 mW. After the HDR source was extended into the PVDF applicator and reached thermal equilibrium, thermal imaging visualized the temperature gradient of 10 K/cm along the PVDF catheter surface, which agreed with FEA modeling. For the Ir-192 source strengths ranging from 16.9 to 41.1 kU, thermal imaging could verify source activity with a relative error of 6.3% with a dwell time of 10 s, and a relative error of 2.5% with 100 s. Conclusion: Thermal imaging could be a feasible tool to visualize HDR source dwell positions and verify source integrity. Potentially, patient safety and treatment quality may be improved by integrating thermal measurements into HDR QA procedures.

MO-FG-BRA-02: A Feasibility Study of Integrating Breathing Audio Signal with Surface Surrogates for Respiratory Motion Management

PURPOSE Tracking the surrogate placed on patient skin surface sometimes leads to problematic signals for certain patients, such as shallow breathers. This in turn impairs the 4D CT image quality and dosimetric accuracy. In this pilot study, we explored the feasibility of monitoring human breathing motion by integrating breathing sound signal with surface surrogates. METHODS The breathing sound signals were acquired though a microphone attached adjacently to volunteers nostrils, and breathing curve were analyzed using a low pass filter. Simultaneously, the Real-time Position Management™ (RPM) system from Varian were employed on a volunteer to monitor respiratory motion including both shallow and deep breath modes. The similar experiment was performed by using Calypso system, and three beacons taped on volunteer abdominal region to capture breath motion. The period of each breathing curves were calculated with autocorrelation functions. The coherence and consistency between breathing signals using different acquisition methods were examined. RESULTS Clear breathing patterns were revealed by the sound signal which was coherent with the signal obtained from both the RPM system and Calypso system. For shallow breathing, the periods of breathing cycle were 3.00±0.19 sec (sound) and 3.00±0.21 sec (RPM); For deep breathing, the periods were 3.49± 0.11 sec (sound) and 3.49±0.12 sec (RPM). Compared with 4.54±0.66 sec period recorded by the calypso system, the sound measured 4.64±0.54 sec. The additional signal from sound could be supplement to the surface monitoring, and provide new parameters to model the hysteresis lung motion. CONCLUSION Our preliminary study shows that the breathing sound signal can provide a comparable way as the RPM system to evaluate the respiratory motion. Its instantaneous and robust characteristics facilitate it possibly to be a either independently or as auxiliary methods to manage respiratory motion in radiotherapy.

SU-C-BRB-02: Automatic Planning as a Potential Strategy for Dose Escalation for Pancreas SBRT?

PURPOSE Stereotactic body radiation therapy (SBRT) has been suggested to provide high rates of local control for locally advanced pancreatic cancer. However, the close proximity of highly radiosensitive normal tissues usually causes the labor-intensive planning process, and may impede further escalation of the prescription dose. The present study evaluates the potential of an automatic planning system as a dose escalation strategy. METHODS Ten pancreatic cancer patients treated with SBRT were studied retrospectively. SBRT was delivered over 5 consecutive fractions with 6 ∼ 8Gy/fraction. Two plans were generated by Pinnacle Auto-Planning with the original prescription and escalated prescription, respectively. Escalated prescription adds 1 Gy/fraction to the original prescription. Manually-created planning volumes were excluded in the optimization goals in order to assess the planning efficiency and quality simultaneously. Critical organs with closest proximity were used to determine the plan normalization to ensure the OAR sparing. Dosimetric parameters including D100, and conformity index (CI) were assessed. RESULTS Auto-plans directly generate acceptable plans for 70% of the cases without necessity of further improvement, and two more iterations at most are necessary for the rest of the cases. For the pancreas SBRT plans with the original prescription, autoplans resulted in favorable target coverage and PTV conformity (D100 = 96.3% ± 1.48%; CI = 0.88 ± 0.06). For the plans with the escalated prescriptions, no significant target under-dosage was observed, and PTV conformity remains reasonable (D100 = 93.3% ± 3.8%, and CI = 0.84 ± 0.05). CONCLUSION Automatic planning, without substantial human-intervention process, results in reasonable PTV coverage and PTV conformity on the premise of adequate OAR sparing for the pancreas SBRT plans with escalated prescription. The results highlight the potential of autoplanning as a dose escalation strategy for pancreas SBRT treatment planning. Further investigations with a larger number of patients are necessary. The project is partially supported by Philips Medical Systems.