Optimization of intensity-modulated radiotherapy plans based on the equivalent uniform dose

Development and validation of an automated Tomotherapy planning method for cervical cancer

PURPOSE

This study aimed to develop an automated Tomotherapy (TOMO) planning method for cervical cancer treatment, and to validate its feasibility and effectiveness.

MATERIALS AND METHODS

The study enrolled 30 cervical cancer patients treated with TOMO at our center. Utilizing scripting and Python environment within the RayStation (RaySearch Labs, Sweden) treatment planning system (TPS), we developed automated planning methods for TOMO and volumetric modulated arc therapy (VMAT) techniques. The clinical manual TOMO (M-TOMO) plans for the 30 patients were re-optimized using automated planning scripts for both TOMO and VMAT, creating automated TOMO (A-TOMO) and automated VMAT (A-VMAT) plans. We compared A-TOMO with M-TOMO and A-VMAT plans. The primary evaluated relevant dosimetric parameters and treatment plan efficiency were assessed using the two-sided Wilcoxon signed-rank test for statistical analysis, with a P-value < 0.05 indicating statistical significance.

RESULTS

A-TOMO plans maintained similar target dose uniformity compared to M-TOMO plans, with improvements in target conformity and faster dose drop-off outside the target, and demonstrated significant statistical differences (P+ < 0.01). A-TOMO plans also significantly outperformed M-TOMO plans in reducing V50Gy, V40Gy and Dmean for the bladder and rectum, as well as Dmean for the bowel bag, femoral heads, and kidneys (all P+ < 0.05). Additionally, A-TOMO plans demonstrated better consistency in plan quality. Furthermore, the quality of A-TOMO plans was comparable to or superior than A-VMAT plans. In terms of efficiency, A-TOMO significantly reduced the time required for treatment planning to approximately 20 min.

CONCLUSION

We have successfully developed an A-TOMO planning method for cervical cancer. Compared to M-TOMO plans, A-TOMO plans improved target conformity and reduced radiation dose to OARs. Additionally, the quality of A-TOMO plans was on par with or surpasses that of A-VMAT plans. The A-TOMO planning method significantly improved the efficiency of treatment planning.

Overview and Recommendations for Prospective Multi-institutional Spatially Fractionated Radiation Therapy Clinical Trials

PURPOSE

The highly heterogeneous dose delivery of spatially fractionated radiation therapy (SFRT) is a profound departure from standard radiation planning and reporting approaches. Early SFRT studies have shown excellent clinical outcomes. However, prospective multi-institutional clinical trials of SFRT are still lacking. This NRG Oncology/American Association of Physicists in Medicine working group consensus aimed to develop recommendations on dosimetric planning, delivery, and SFRT dose reporting to address this current obstacle toward the design of SFRT clinical trials.

METHODS AND MATERIALS

Working groups consisting of radiation oncologists, radiobiologists, and medical physicists with expertise in SFRT were formed in NRG Oncology and the American Association of Physicists in Medicine to investigate the needs and barriers in SFRT clinical trials.

RESULTS

Upon reviewing the SFRT technologies and methods, this group identified challenges in several areas, including the availability of SFRT, the lack of treatment planning system support for SFRT, the lack of guidance in the physics and dosimetry of SFRT, the approximated radiobiological modeling of SFRT, and the prescription and combination of SFRT with conventional radiation therapy.

CONCLUSIONS

Recognizing these challenges, the group further recommended several areas of improvement for the application of SFRT in cancer treatment, including the creation of clinical practice guidance documents, the improvement of treatment planning system support, the generation of treatment planning and dosimetric index reporting templates, and the development of better radiobiological models through preclinical studies and through conducting multi-institution clinical trials.

Risk adaptive planning with biology-based constraints may lead to higher tumor control probability in tumors of the canine brain: A planning study

BACKGROUND

Classical radiation protocols are guided by physical dose delivered homogeneously over the target. Protocols are chosen to keep normal tissue complication probability (NTCP) at an acceptable level. Organs at risk (OAR) adjacent to the target volume could lead to underdosage of the tumor and a decrease of tumor control probability (TCP). The intent of our study was to explore a biology-based dose escalation: by keeping NTCP for OAR constant, radiation dose was to be maximized, allowing to result in heterogeneous dose distributions.

METHODS

We used computed tomography datasets of 25 dogs with brain tumors, previously treated with 10x4 Gy (40 Gy to PTV D50). We generated 3 plans for each patient: A) original treatment plan with homogeneous dose distribution, B) heterogeneous dose distribution with strict adherence to the same NTCPs as in A), and C) heterogeneous dose distribution with adherence to NTCP <5%. For plan comparison, TCPs and TCP equivalent doses (homogenous target dose which results in the same TCP) were calculated. To enable the use of the generalized equivalent uniform dose (gEUD) metric of the tumor target in plan optimization, the calculated TCP values were used to obtain the volume effect parameter a.

RESULTS

As intended, NTCPs for all OARs did not differ from plan A) to B). In plan C), however, NTCPs were significantly higher for brain (mean 2.5% (SD±1.9, 95%CI: 1.7,3.3), p<0.001), optic chiasm (mean 2.0% (SD±2.2, 95%CI: 1.0,2.8), p=0.010) compared to plan A), but no significant increase was found for the brainstem. For 24 of 25 of the evaluated patients, the heterogenous plans B) and C) led to an increase in target dose and projected increase in TCP compared to the homogenous plan A). Furthermore, the distribution of the projected individual TCP values as a function of the dose was found to be in good agreement with the population TCP model.

CONCLUSION

Our study is a first step towards risk-adaptive radiation dose optimization. This strategy utilizes a biologic objective function based on TCP and NTCP instead of an objective function based on physical dose constraints.

Accounting for fractionation and heterogeneous dose distributions in the modelling of osteoradionecrosis in oropharyngeal carcinoma treatment

BACKGROUND AND PURPOSE

Osteoradionecrosis (ORN) of the mandible is a severe complication following radiotherapy (RT). With a renewed interest in hypofractionation for head and neck radiotherapy, more information concerning ORN development after high fraction doses is important. The aim of this explorative study was to develop a model for ORN risk prediction applicable across different fractionation schemes using Equivalent Uniform Doses (EUD).

MATERIAL AND METHODS

We performed a retrospective cohort study in 334 oropharyngeal squamous cell carcinoma (OPSCC) patients treated with either a hypofractionated Stereotactic Body Radiation Therapy (HF-SBRT) boost or conventional Intensity Modulated Radiation Therapy (IMRT). ORN was scored with the CTCAE v5.0. HF-SBRT and IMRT dose distributions were converted into equivalent dose in 2 Gy fractions (α/β = 0.85 Gy) and analyzed using EUD. The parameter a that led to an EUD that best discriminated patients with and without grade ≥ 2 ORN was selected. Patient and treatment-related risk factors of ORN were analyzed with uni- and multivariable regression analysis.

RESULTS

A total of 32 patients (9.6%) developed ORN grade ≥ 2. An EUD(a = 8) best discriminated between ORN and non-ORN (AUC = 0.71). In multivariable regression, pre-RT extractions (SHR = 2.34; p = 0.012), mandibular volume (SHR = 1.04; p = 0.003), and the EUD(a = 8) (SHR = 1.14; p < 0.001) were significantly associated with ORN.

CONCLUSION

Risk models for ORN based on conventional DVH parameters cannot be directly applied to HF-SBRT fractionation schemes and dose distributions. However, after correcting for fractionation and non-uniform dose distributions using EUD, a single model can distinguish between ORN and non-ORN after conventionally fractionated radiotherapy and hypofractionated boost treatments.

Effects on the Hypothalamo-Pituitary Axis in Patients with CNS or Head and Neck Tumors following Radiotherapy

BACKGROUND

Knowledge about the precise effects of radiotherapy on hypothalamo-pituitary functions is limited. Reduction of side effects is a major goal of advanced radiotherapy modalities. We assessed strategies for monitoring and replacement of hormone deficiencies in irradiated patients.

METHODS

A search strategy was systematically conducted on PubMed®. Additional articles were retrieved to describe endocrine mechanisms.

RESULTS

45 studies were evaluated from 2000 to 2022. They were predominantly retrospective and highly heterogeneous concerning patient numbers, tumor types, radiotherapy technique and follow-up. Endocrine deficiencies occurred in about 40% of patients within a median follow-up of 5.6 years without a clear difference between radiotherapy modalities. Somatotropic and thyrotropic axes were, respectively, the most and least radiosensitive.

CONCLUSIONS

Current pituitary gland dose constraints may underestimate radiation-induced endocrine deficiencies, thus impairing quality of life. Little difference might be expected between radiation techniques for PG tumors. For non-PG tumors, dose constraints should be applied more systematically.

Effective optimization strategy for large optimization volume object, remaining volume at risk (RVR):α-value selection and usage from generalized equivalent uniform dose (gEUD) curve deviation perspective

Objective.A large optimization volume for intensity-modulated radiation therapy (IMRT), such as the remaining volume at risk (RVR), is traditionally unsuitable for dose-volume constraint control and requires planner-specific empirical considerations owing to the patient-specific shape. To enable less empirical optimization, the generalized equivalent uniform dose (gEUD) optimization is effective; however, the utilization of parametera-values remains elusive. Our study clarifies thea-value characteristics for optimization and to enable effectivea-value use.Approach.The gEUD can be obtained as a function of itsa-value, which is the weighted generalized mean; its curve has a continuous, differentiable, and sigmoid shape, deforming in its optimization state with retained curve characteristics. Using differential geometry, the gEUD curve changes in optimization is considered a geodesic deviation intervened by the forces between deforming and retaining the curve. The curvature and gradient of the curve are radically related to optimization. The vertex point (a=a_k) was set and thea-value roles were classified into the following three parts of the curve with respect to thea-value: (i) high gradient and middle curvature, (ii) middle gradient and high curvature, and (iii) low gradient and low curvature. Then, a strategy for multiplea-values was then identified using RVR optimization.Main results.Eleven head and neck patients who underwent static seven-field IMRT were used to verify thea-value characteristics and curvature effect for optimization. The lowera-value (i) (a= 1-3) optimization was effective for the whole dose-volume range; in contrast, the effect of highera-value (iii) (a= 12-20) optimization addressed strongly the high-dose range of the dose volume. The middlea-value (ii) (arounda=a_k) showed intermediate but effective high-to-low dose reduction. Thesea-value characteristics were observed as superimpositions in the optimization. Thus, multiple gEUD-based optimization was significantly superior to the exponential constraints normally applied to the RVR that surrounds the PTV, normal tissue objective (NTO), resulting in up to 25.9% and 8.1% improvement in dose-volume indices D2% and V10Gy, respectively.Significance.This study revealed an appropriatea-value for gEUD optimization, leading to favorable dose-volume optimization for the RVR region using fixed multiplea-value conditions, despite the very large and patient-specific shape of the region.

Automated Contouring and Planning in Radiation Therapy: What Is 'Clinically Acceptable'?

Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is 'clinical acceptability'? Quantitative and qualitative approaches have been used to assess this ill-defined concept, all of which have advantages and disadvantages or limitations. The approach chosen may depend on the goal of the study as well as on available resources. In this paper, we discuss various aspects of 'clinical acceptability' and how they can move us toward a standard for defining clinical acceptability of new autocontouring and planning tools.

An integrated solution of deep reinforcement learning for automatic IMRT treatment planning in non-small-cell lung cancer

Purpose

To develop and evaluate an integrated solution for automatic intensity-modulated radiation therapy (IMRT) planning in non-small-cell lung cancer (NSCLC) cases.

Methods

A novel algorithm named as multi-objectives adjustment policy network (MOAPN) was proposed and trained to learn how to adjust multiple optimization objectives in commercial Eclipse treatment planning system (TPS), based on the multi-agent deep reinforcement learning (DRL) scheme. Furthermore, a three-dimensional (3D) dose prediction module was developed to generate the patient-specific initial optimization objectives to reduce the overall exploration space during MOAPN training. 114 previously treated NSCLC cases suitable for stereotactic body radiotherapy (SBRT) were selected from the clinical database. 87 cases were used for the model training, and the remaining 27 cases for evaluating the feasibility and effectiveness of MOAPN in automatic treatment planning.

Results

For all tested cases, the average number of adjustment steps was 21 ± 5.9 (mean ± 1 standard deviation). Compared with the MOAPN initial plans, the actual dose of chest wall, spinal cord, heart, lung (affected side), esophagus and bronchus in the MOAPN final plans reduced by 14.5%, 11.6%, 4.7%, 16.7%, 1.6% and 7.7%, respectively. The dose result of OARs in the MOAPN final plans was similar to those in the clinical plans. The complete automatic treatment plan for a new case was generated based on the integrated solution, with about 5-6 min.

Conclusion

We successfully developed an integrated solution for automatic treatment planning. Using the 3D dose prediction module to obtain the patient-specific optimization objectives, MOAPN formed action-value policy can simultaneously adjust multiple objectives to obtain a high-quality plan in a shorter time. This integrated solution contributes to improving the efficiency of the overall planning workflow and reducing the variation of plan quality in different regions and treatment centers. Although improvement is warranted, this proof-of-concept study has demonstrated the feasibility of this integrated solution in automatic treatment planning based on the Eclipse TPS.

Comparison of dosimetric effects of MLC positional errors on VMAT and IMRT plans for SBRT radiotherapy in non-small cell lung cancer

The positional accuracy of multi-leaf collimators (MLC) is important in stereotactic body radiotherapy (SBRT). The aim of this study was to investigate the impact between MLC positional error and dosimetry of volume intensity modulated (VMAT) and general intensity modulated (IMRT) plans for non-small cell lung cancer (NSCLC). Fifteen patients with NSCLC were selected to design the 360 SBRT-VMAT plans and the 360 SBRT-IMRT error plans. The DICOM files for these treatment plans were imported into a proprietary computer program that introduced delivery errors. Random and systematic MLC position (0.1, 0.2, 0.5, 1.0, 1.5, and 2.0 mm) errors were introduced. The systematic errors were shift errors (caused by gravity), opening errors, and closing errors. The CI, GI, d2cm and generalized equivalent uniform dose (gEUD) were calculated for the original plan and all treatment plans, accounting for the errors. Dose sensitivity was calculated using linear regression for MLC position errors. The random MLC errors were relatively insignificant. MLC shift, opening, and closing errors had a significant effect on the dose distribution of the SBRT plan. VMAT was more significant than IMRT. To ensure that the gEUD variation of PTV is controlled within 2%, the shift error, opening error, and closing error of IMRT should be less than 2.4 mm, 1.15 mm, and 0.97 mm, respectively. For VMAT, the shift error, opening error, and closing error should be less than 0.95 mm, 0.32 mm, and 0.38 mm, respectively. The dose sensitivity results obtained in this study can be used as a guide for patient-based quality assurance efforts. The position error of the MLC system had a significant impact on the gEUD of the SBRT technology. The MLC systematic error has a greater dosimetric impact on the VMAT plan than on the IMRT plan for SBRT, which should be carefully monitored.

A novel knowledge-based prediction model for estimating an initial equivalent uniform dose in semi-auto-planning for cervical cancer

Background

We developed a novel concept, equivalent uniform length (EUL), to describe the relationship between the generalized equivalent uniform dose (EUD) and the geometric anatomy around a tumor target. By correlating EUL with EUD, we established two EUD–EUL knowledge-based (EEKB) prediction models for the bladder and rectum that predict initial EUD values for generating quality treatment plans.

Methods

EUL metrics for the rectum and bladder were extracted and collected from the intensity-modulated radiotherapy therapy (IMRT) plans of 60 patients with cervical cancer. The two EEKB prediction models were built using linear regression to establish the relationships between EUL_r and EUD_r (EUL and EUD of rectum) and EUL_b, and EUD_b (EUL and EUD of bladder), respectively. The EE plans were optimized by incorporating the predicted initial EUD parameters for the rectum and bladder with the conventional pinnacle auto-planning (PAP) initial dose parameters for other organs. The efficiency of the predicted initial EUD values were then evaluated by comparing the consistency and quality of the EE plans, PAP plans (based on default PAP initial parameters), and manual plans (designed manually by different dosimetrists) for a sample of 20 patients.

Results

Linear regression analyses showed a significant correlation between EUL and EUD (R² = 0.79 and 0.69 for EUD_b and EUD_r, respectively). In a sample of 20 patients, the average bladder V40 and V50 derived from the EE plans were significantly lower (V40: 30.00 ± 5.76, V50: 14.36 ± 4.00) than the V40 and V50 values derived from manual plans (V40: 36.03 ± 8.02, V50: 19.02 ± 5.42). Compared with the PAP plans, the EE plans produced significantly lower average V30 and Dmean values for the bladder (V30: 50.55 ± 6.33, Dmean: 31.48 ± 1.97 Gy).

Conclusions

Our EEKB prediction models predicted reasonable initial EUD values for the rectum and bladder based on patient-specific geometric EUL values, thereby improving optimization and planning efficiency.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-022-02120-4.

Applying pytorch toolkit to plan optimization for circular cone based robotic radiotherapy

Background

Robotic linac is ideally suited to deliver hypo-fractionated radiotherapy due to its compact head and flexible positioning. The non-coplanar treatment space improves the delivery versatility but the complexity also leads to prolonged optimization and treatment time.

Methods

In this study, we attempted to use the deep learning (pytorch) framework for the plan optimization of circular cone based robotic radiotherapy. The optimization problem was topologized into a simple feedforward neural network, thus the treatment plan optimization was transformed into network training. With this transformation, the pytorch toolkit with high-efficiency automatic differentiation (AD) for gradient calculation was used as the optimization solver. To improve the treatment efficiency, plans with fewer nodes and beams were sought. The least absolute shrinkage and selection operator (lasso) and the group lasso were employed to address the “sparsity” issue.

Results

The AD-S (AD sparse) approach was validated on 6 brain and 6 liver cancer cases and the results were compared with the commercial MultiPlan (MLP) system. It was found that the AD-S plans achieved rapid dose fall-off and satisfactory sparing of organs at risk (OARs). Treatment efficiency was improved by the reduction in the number of nodes (28%) and beams (18%), and monitor unit (MU, 24%), respectively. The computational time was shortened to 47.3 s on average.

Conclusions

In summary, this first attempt of applying deep learning framework to the robotic radiotherapy plan optimization is promising and has the potential to be used clinically.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-022-02045-y.

Including Volume Effects in Biological Treatment Plan Optimization for Carbon Ion Therapy: Generalized Equivalent Uniform Dose-Based Objective in TRiP98

We describe a way to include biologically based objectives in plan optimization specific for carbon ion therapy, beyond the standard voxel-dose-based criteria already implemented in TRiP98, research planning software for ion beams. The aim is to account for volume effects—tissue architecture-dependent response to damage—in the optimization procedure, using the concept of generalized equivalent uniform dose (gEUD), which is an expression to convert a heterogeneous dose distribution (e.g., in an organ at risk (OAR)) into a uniform dose associated with the same biological effect. Moreover, gEUD is closely related to normal tissue complication probability (NTCP). The multi-field optimization problem here takes also into account the relative biological effectiveness (RBE), which in the case of ion beams is not factorizable and introduces strong non-linearity. We implemented the gEUD-based optimization in TRiP98, allowing us to control the whole dose–volume histogram (DVH) shape of OAR with a single objective by adjusting the prescribed gEUD₀ and the volume effect parameter a, reducing the volume receiving dose levels close to mean dose when a = 1 (large volume effect) while close to maximum dose for a >> 1 (small volume effect), depending on the organ type considered. We studied the role of gEUD₀ and a in the optimization, and we compared voxel-dose-based and gEUD-based optimization in chordoma cases with different anatomies. In particular, for a plan containing multiple OARs, we obtained the same target coverage and similar DVHs for OARs with a small volume effect while decreasing the mean dose received by the proximal parotid, thus reducing its NTCP by a factor of 2.5. Further investigations are done for this plan, considering also the distal parotid gland, obtaining a NTCP reduction by a factor of 1.9 for the proximal and 2.9 for the distal one. In conclusion, this novel optimization method can be applied to different OARs, but it achieves the largest improvement for organs whose volume effect is larger. This allows TRiP98 to perform a double level of biologically driven optimization for ion beams, including at the same time RBE-weighted dose and volume effects in inverse planning. An outlook is presented on the possible extension of this method to the target.

Treatment Planning Study for Microbeam Radiotherapy Using Clinical Patient Data

Microbeam radiotherapy (MRT) is a novel, still preclinical dose delivery technique. MRT has shown reduced normal tissue effects at equal tumor control rates compared to conventional radiotherapy. Treatment planning studies are required to permit clinical application. The aim of this study was to establish a dose comparison between MRT and conventional radiotherapy and to identify suitable clinical scenarios for future applications of MRT. We simulated MRT treatment scenarios for clinical patient data using an inhouse developed planning algorithm based on a hybrid Monte Carlo dose calculation and implemented the concept of equivalent uniform dose (EUD) for MRT dose evaluation. The investigated clinical scenarios comprised fractionated radiotherapy of a glioblastoma resection cavity, a lung stereotactic body radiotherapy (SBRT), palliative bone metastasis irradiation, brain metastasis radiosurgery and hypofractionated breast cancer radiotherapy. Clinically acceptable treatment plans were achieved for most analyzed parameters. Lung SBRT seemed the most challenging treatment scenario. Major limitations comprised treatment plan optimization and dose calculation considering the tissue microstructure. This study presents an important step of the development towards clinical MRT. For clinical treatment scenarios using a sophisticated dose comparison concept based on EUD and EQD2, we demonstrated the capability of MRT to achieve clinically acceptable dose distributions.

Conic formulation of fluence map optimization problems

The convexity of objectives and constraints in fluence map optimization (FMO) for radiation therapy has been extensively studied. Next to convexity, there is another important characteristic of optimization functions and problems, which has thus far not been considered in FMO literature: conic representation. Optimization problems that are conically representable using quadratic, exponential and power cones are solvable with advanced primal-dual interior-point algorithms. These algorithms guarantee an optimal solution in polynomial time and have good performance in practice. In this paper, we construct conic representations for most FMO objectives and constraints. This paper is the first that shows that FMO problems containing multiple biological evaluation criteria can be solved in polynomial time. For fractionation-corrected functions for which no exact conic reformulation is found, we provide an accurate approximation that is conically representable. We present numerical results on the TROTS data set, which demonstrate very stable numerical performance for solving FMO problems in conic form. With ongoing research in the optimization community, improvements in speed can be expected, which makes conic optimization a promising alternative for solving FMO problems.

Influence of Using a Contrast-Enhanced CT Image as the Primary Image on CyberKnife Brain Radiosurgery Treatment Plans

Background and Purpose

This study aimed to quantify the differences between pre- and post-contrast agent (CA) CT for CyberKnife brain SRS plans.

Materials and Methods

Twenty-five patients were retrospectively analyzed. They were divided into two categories, inhomogeneous cases (13 patients) and homogeneous cases (12 patients), according to whether the tumor was close to the cavity and inhomogeneous tissues or not. The pre-CA and post-CA plans were designed and calculated using the same monitor unit and paths as those in the ray-tracing algorithm, respectively.

Results

The CT number difference of tumor between pre- and post-CA was significant (on average, 24.78 ± 18.56 HU, P-value < 0.01). The deviation value of the target was the largest at approximately 37 HU (inhomo-) and 13 HU (homo-) (P < 0.01), and the values of the organs at risk (OARs) were not statistically significant (P-value > 0.05). However, it was not statistically significant for the dose difference between the two groups with the injection of CA (P-value > 0.05). The absolute effective depth difference generally remained at a level of 1 mm, but the dose difference was quitely fluctuated sometimes more than 20%. The absolute effective depth difference of the inhomo-case (0.62 mm) was larger than that of the homo-case (0.37 mm) on median, as well as the variation amplitude (P-value < 0.05). Moreover, the relative dose differences between the two cases were 0.38% (inhomo-) and 0.2% (homo-), respectively (P-value < 0.05). At the criterion of 1 mm/1%, the gamma pass rate of the homo-case (95.89%) was larger than that of the inhomo-case (93.79%). For the OARs, except for the cochlea, the two cases were almost the same (>98.85%). The tumor control probability of the target was over 99.99% before and after injection of a CA, as well as the results for the homo-case and inhomo-case.

Conclusions

Considering the difference of evaluation indexes between pre- and post-CA images, we recommended plain CT to be employed as the primary image for improving the CK treatment accuracy of brain SRS, especially when the target was close to CA-sensitive OARs and cavity.

Automated robust SBPT planning using EUD-based prediction of SBRT plan for patients with lung cancer

PURPOSE

To evaluate the quality of robust stereotactic body proton therapy (RSBPT) plans generated by one-clicking scripting method for patients with lung cancer.

MATERIALS AND METHODS

Retrospective analysis was performed on fifty lung cancer patients whose plan with robustly stereotactic body radiation therapy (SBRT). Thirty out of fifty patients were used for training to build a regression model, based on robust SBRT reference doses, to predict EUD values of ROIs for robust SBPT planning. Thereafter, robust SBPT plans with both automated EUD-Based mimicking (Automated Robust Proton ARP) and manual (Manual Robust Proton MRP) methods were evaluated in the remaining 20 patients. Plans were compared in terms of dosimetric parameters and planning time.

RESULTS

A statistically significantly improvement in target dose fall off was observed for ARP plans compare to MRP plans (Dose fall off: 135 for MRP and 88 for ARP, p < 0.01), while no differences in target coverage and conformity. A statistically significantly reduce in normal lung tissue were observed for ARP plans compare to MRP plans (Lung [D_mean cGy (RBE)]: MRP: 478 vs. ARP: 351, p < 0.01; Lung [V_{5Gy (RBE)} (%)]: MRP: 16.1 vs. ARP: 12.1, p < 0.01; Lung [V_{20Gy (RBE)} (%)]: MRP: 8.5 vs. ARP: 6.8, p < 0.01). Planning time was reduced for ARP plans compare to MRP plans (optimization time: 12 min for MRP vs. 8 min for ARP; total plan time: 23 min for MRP vs. 18 min for ARP).

CONCLUSION

The automated robust SBPT plans using EUD-Based mimicking of SBRT reference dose improve target dose fall off, reduced the radiation doses to the lungs, reduce planning time, which might be beneficial for patient with lung cancer in clinical.

Radiobiological evaluation considering setup error on single-isocenter irradiation in stereotactic radiosurgery

Purpose

We calculated the dosimetric indices and estimated the tumor control probability (TCP) considering six degree‐of‐freedom (6DoF) patient setup errors in stereotactic radiosurgery (SRS) using a single‐isocenter technique.

Methods

We used simulated spherical gross tumor volumes (GTVs) with diameters of 1.0 cm (GTV 1), 2.0 cm (GTV 2), and 3.0 cm (GTV 3), and the distance (d) between the target center and isocenter was set to 0, 5, and 10 cm. We created the dose distribution by convolving the blur component to uniform dose distribution. The prescription dose was 20 Gy and the dose distribution was adjusted so that D95 (%) of each GTV was covered by 100% of the prescribed dose. The GTV was simultaneously rotated within 0°–1.0° (δR) around the x‐, y‐, and z‐axes and then translated within 0–1.0 mm (δT) in the x‐, y‐, and z‐axis directions. D95, conformity index (CI), and conformation number (CN) were evaluated by varying the distance from the isocenter. The TCP was estimated by translating the calculated dose distribution into a biological response. In addition, we derived the x‐y‐z coordinates with the smallest TCP reduction rate that minimize the sum of squares of the residuals as the optimal isocenter coordinates using the relationship between 6DoF setup error, distance from isocenter, and GTV size.

Results

D95, CI, and CN were decreased with increasing isocenter distance, decreasing GTV size, and increasing setup error. TCP of GTVs without 6DoF setup error was estimated to be 77.0%. TCP were 25.8% (GTV 1), 35.0% (GTV 2), and 53.0% (GTV 3) with (d, δT_,δR) = (10 cm, 1.0 mm, 1.0°). The TCP was 52.3% (GTV 1), 54.9% (GTV 2), and 66.1% (GTV 3) with (d, δT_,δR) = (10 cm, 1.0 mm, 1.0°) at the optimal isocenter position.

Conclusion

The TCP in SRS for multiple brain metastases with a single‐isocenter technique may decrease with increasing isocenter distance and decreasing GTV size when the 6DoF setup errors are exceeded (1.0 mm, 1.0°). Additionally, it might be possible to better maintain TCP for GTVs with 6DoF setup errors by using the optimal isocenter position.

Automated Non-Coplanar VMAT for Dose Escalation in Recurrent Head and Neck Cancer Patients

Simple Summary

The ability to escalate the radiation dose to head and neck tumors has been shown to offer improved local control, and consequently, survival for recurrent head and neck cancer (rHNC) patients. This study evaluates the HyperArc automated non-coplanar planning technique (originally developed for intracranial treatment) for 20 rHNC patients, and compares this technique to conventional planning methods. HyperArc enables significant tumor dose escalation, with average increases in mean target dose of over 11.5 Gy (26%), while maintaining clinically-equivalent doses to nearby organs. Our results show that the average probability of tumor control is 23% higher for HyperArc than conventional techniques.

Abstract

This study evaluates the potential for tumor dose escalation in recurrent head and neck cancer (rHNC) patients with automated non-coplanar volumetric modulated arc therapy (VMAT) stereotactic body radiation therapy (SBRT) planning (HyperArc). Twenty rHNC patients are planned with conventional VMAT SBRT to 40 Gy while minimizing organ-at-risk (OAR) doses. They are then re-planned with the HyperArc technique to match these minimal OAR doses while escalating the target dose as high as possible. Then, we compare the dosimetry, tumor control probability (TCP), and normal tissue complication probability (NTCP) for the two plan types. Our results show that the HyperArc technique significantly increases the mean planning target volume (PTV) and gross tumor volume (GTV) doses by 10.8 ± 4.4 Gy (25%) and 11.5 ± 5.1 Gy (26%) on average, respectively. There are no clinically significant differences in OAR doses, with maximum dose differences of <2 Gy on average. The average TCP is 23% (± 21%) higher for HyperArc than conventional plans, with no significant differences in NTCP for the brainstem, cord, mandible, or larynx. HyperArc can achieve significant tumor dose escalation while maintaining minimal OAR doses in the head and neck—potentially enabling improved local control for rHNC SBRT patients without increased risk of treatment-related toxicities.

Radiobiological Comparison of Teardrop Technique for Breast Cancer Radiotherapy Treatment Planning on a Tomotherapy System

Breast cancer is one of the most common cancer worldwide with large morbidity. In Mexico, it is the first cause of death by cancer in women. Radiotherapy has proven to be a great tool to control such ailments and TomoTherapy is a relatively new technology to accomplish it. To obtain good clinical outcomes, tight dosimetric constraints are placed on organs at risk (OARs) to maximize tumor control and minimize normal tissue complication probabilities. The teardrop technique helps meeting these constraints by placing a virtual block over parts of the ipsilateral lung and the heart but it contributes to lengthen the treatment time. In this work, we present our experience in using this technique and compare its radiobiological estimations with similar plans without it. Ten patients diagnosed with breast cancer were planned twice, with and without the teardrop technique. Dose-volume histograms were obtained and analyzed to get uncomplicated tumor control probability (UTCP) and optimization estimator (fEUD) parameters. Classical dosimetrical parameters for planning target volumes (PTVs): conformity index, homogeneity index, and coverage were also recorded and statistically described. Several dosimetrical parameters for OARs were recorded and analyzed. The UTCP parameter had a mean value of 0.968 ± 0.023 when no block was used and 0.966 ± 0.022 with the teardrop. The fEUD parameter values were: 0.515 ± 0.049 without blocks and 0.541 ± 0.057 with the teardrop. Optimization of every plan was stopped only after all constraints were met, and it was easier to accomplish this goal with the teardrop technique. The teardrop technique permitted a 5% gain in fEUD. The teardrop technique was observed to have a net radiobiological benefit with little impact on patient scheduling.

Optimization in treatment planning of high dose-rate brachytherapy - Review and analysis of mathematical models

Treatment planning in high dose-rate brachytherapy has traditionally been conducted with manual forward planning, but inverse planning is today increasingly used in clinical practice. There is a large variety of proposed optimization models and algorithms to model and solve the treatment planning problem. Two major parts of inverse treatment planning for which mathematical optimization can be used are the decisions about catheter placement and dwell time distributions. Both these problems as well as integrated approaches are included in this review. The proposed models include linear penalty models, dose-volume models, mean-tail dose models, quadratic penalty models, radiobiological models, and multiobjective models. The aim of this survey is twofold: (i) to give a broad overview over mathematical optimization models used for treatment planning of brachytherapy and (ii) to provide mathematical analyses and comparisons between models. New technologies for brachytherapy treatments and methods for treatment planning are also discussed. Of particular interest for future research is a thorough comparison between optimization models and algorithms on the same dataset, and clinical validation of proposed optimization approaches with respect to patient outcome.

Dosimetric comparison between volumetric modulated arc therapy planning techniques for prostate cancer in the presence of intrafractional organ deformation

The purpose of this study was to compare single-arc (SA) and double-arc (DA) treatment plans, which are planning techniques often used in prostate cancer volumetric modulated arc therapy (VMAT), in the presence of intrafractional deformation (ID) to determine which technique is superior in terms of target dose coverage and sparing of the organs at risk (OARs). SA and DA plans were created for 27 patients with localized prostate cancer. ID was introduced to the clinical target volume (CTV), rectum and bladder to obtain blurred dose distributions using an in-house software. ID was based on the motion probability function of each structure voxel and the intrafractional motion of the respective organs. From the resultant blurred dose distributions of SA and DA plans, various parameters, including the tumor control probability, normal tissue complication probability, homogeneity index, conformity index, modulation complexity score for VMAT, dose-volume indices and monitor units (MUs), were evaluated to compare the two techniques. Statistical analysis showed that most CTV and rectum parameters were significantly larger for SA plans than for DA plans (P < 0.05). Furthermore, SA plans had fewer MUs and were less complex (P < 0.05). The significant differences observed had no clinical significance, indicating that both plans are comparable in terms of target and OAR dosimetry when ID is considered. The use of SA plans is recommended for prostate cancer VMAT because they can be delivered in shorter treatment times than DA plans, and therefore benefit the patients.

The Technical and Clinical Implementation of LATTICE Radiation Therapy (LRT)

The concept of spatially fractionated radiation therapy (SFRT) was conceived over 100 years ago, first in the form of GRID, which has been applied to clinical practice since its early inception and continued to the present even with markedly improved instrumentation in radiation therapy. LATTICE radiation therapy (LRT) was introduced in 2010 as a conceptual 3D extension of GRID therapy with several uniquely different features. Since 2014, when the first patient was treated, over 150 patients with bulky tumors worldwide have received LRT. Through a brief review of the basic principles and the analysis of the collective clinical experience, a set of technical recommendations and guidelines are proposed for the clinical implementation of LRT. It is to be recognized that the current clinical practice of SFRT (GRID or LRT) is still largely based on the heuristic principles. With advancements in basic biological research and the anticipated clinical trials to systemically assess the efficacy and risk, progressively robust optimizations of the technical parameters are essential for the broader application of SFRT in clinical practice.

Standard versus hypofractionated intensity-modulated radiotherapy for prostate cancer: assessing the impact on dose modulation and normal tissue effects when using patient-specific cancer biology

Hypofractionation of prostate cancer radiotherapy achieves tumour control at lower total radiation doses, however, increased rectal and bladder toxicities have been observed. To realise the radiobiological advantage of hypofractionation whilst minimising harm, the potential reduction in dose to organs at risk was investigated for biofocused radiotherapy. Patient-specific tumour location and cell density information were derived from multiparametric imaging. Uniform-dose plans and biologically-optimised plans were generated for a standard schedule (78 Gy/39 fractions) and hypofractionated schedules (60 Gy/20 fractions and 36.25 Gy/5 fractions). Results showed that biologically-optimised plans yielded statistically lower doses to the rectum and bladder compared to isoeffective uniform-dose plans for all fractionation schedules. A reduction in the number of fractions increased the target dose modulation required to achieve equal tumour control. On average, biologically-optimised, moderately-hypofractionated plans demonstrated 15.3% (p-value: <0.01) and 23.8% (p-value: 0.02) reduction in rectal and bladder dose compared with standard fractionation. The tissue-sparing effect was more pronounced in extreme hypofractionation with mean reduction in rectal and bladder dose of 43.3% (p-value: < 0.01) and 41.8% (p-value: 0.02), respectively. This study suggests that the ability to utilise patient-specific tumour biology information will provide greater incentive to employ hypofractionation in the treatment of localised prostate cancer with radiotherapy. However, to exploit the radiobiological advantages given by hypofractionation, greater attention to geometric accuracy is required due to increased sensitivity to treatment uncertainties.

Predicting Radiotherapy Impact on Late Bladder Toxicity in Prostate Cancer Patients: An Observational Study

BACKGROUND AND PURPOSE

The aim of our study was to elaborate a suitable model on bladder late toxicity in prostate cancer (PC) patients treated by radiotherapy with volumetric technique.

MATERIALS AND METHODS

PC patients treated between September 2010 and April 2017 were included in the analysis. An observational study was performed collecting late toxicity data of any grade, according to RTOG and CTCAE 4.03 scales, cumulative dose volumes histograms were exported for each patient. Vdose, the value of dose to a specific volume of organ at risk (OAR), impact was analyzed through the Mann-Whitney rank-sum test. Logistic regression was used as the final model. The model performance was estimated by taking 1000 samples with replacement from the original dataset and calculating the AUC average. In addition, the calibration plot (Hosmer-Lemeshow goodness-of-fit test) was used to evaluate the performance of internal validation. RStudio Software version 3.3.1 and an in house developed software package "Moddicom" were used.

RESULTS

Data from 175 patients were collected. The median follow-up was 39 months (min-max 3.00-113.00). We performed Mann-Whitney rank-sum test with continuity correction in the subset of patients with late bladder toxicity grade ≥ 2: a statistically significant p-value with a Vdose of 51.43 Gy by applying a logistic regression model (coefficient 4.3, p value 0.025) for the prediction of the development of late G ≥ 2 GU toxicity was observed. The performance for the model's internal validation was evaluated, with an AUC equal to 0.626. Accuracy was estimated through the elaboration of a calibration plot.

CONCLUSIONS

Our preliminary results could help to optimize treatment planning procedures and customize treatments.

Split Common Coincidence Point Problem: A Formulation Applicable to (Bio)Physically-Based Inverse Planning Optimization

Inverse planning is a method of radiotherapy treatment planning where the care team begins with the desired dose distribution satisfying prescribed clinical objectives, and then determines the treatment parameters that will achieve it. The variety in symmetry, form, and characteristics of the objective functions describing clinical criteria requires a flexible optimization approach in order to obtain optimized treatment plans. Therefore, we introduce and discuss a nonlinear optimization formulation called the split common coincidence point problem (SCCPP). We show that the SCCPP is a suitable formulation for the inverse planning optimization problem with the flexibility of accommodating several biological and/or physical clinical objectives. Also, we propose an iterative algorithm for approximating the solution of the SCCPP, and using Bregman techniques, we establish that the proposed algorithm converges to a solution of the SCCPP and to an extremum of the inverse planning optimization problem. We end with a note on useful insights on implementing the algorithm in a clinical setting.

Application of dose-volume histogram prediction in biologically related models for nasopharyngeal carcinomas treatment planning

PURPOSE

In this study, we employed a gated recurrent unit (GRU)-based recurrent neural network (RNN) using dosimetric information induced by individual beam to predict the dose-volume histogram (DVH) and investigated the feasibility and usefulness of this method in biologically related models for nasopharyngeal carcinomas (NPC) treatment planning.

METHODS AND MATERIALS

One hundred patients with NPC undergoing volumetric modulated arc therapy (VMAT) between 2018 and 2019 were randomly selected for this study. All the VMAT plans were created using the Monaco treatment planning system (Elekta, Sweden) and clinically approved: > 98% of PGTVnx received the prescribed doses of 70 Gy, > 98% of PGTVnd received the prescribed doses of 66 Gy and > 98% of PCTV received 60 Gy. Of these, the data from 80 patients were used to train the GRU-RNN, and the data from the other 20 patients were used for testing. For each NPC patient, the DVHs of different organs at risk were predicted by a trained GRU-based RNN using the information given by individual conformal beams. Based on the predicted DVHs, the equivalent uniform doses (EUD) were calculated and applied as dose constraints during treatment planning optimization. The regenerated VMAT experimental plans (EPs) were evaluated by comparing them with the clinical plans (CPs).

RESULTS

For the 20 test patients, the regenerated EPs guided by the GRU-RNN predictive model achieved good consistency relative to the CPs. The EPs showed better consistency in PTV dose distribution and better dose sparing for many organs at risk, and significant differences were found in the maximum/mean doses to the brainstem, brainstem PRV, spinal cord, lenses, temporal lobes, parotid glands and larynx with P-values < 0.05. On average, compared with the CPs, the maximum/mean doses to these OARs were altered by - 3.44 Gy, - 1.94 Gy, - 1.88 Gy, 0.44 Gy, 1.98 Gy, - 1.82 Gy and 2.27 Gy, respectively. In addition, significant differences were also found in brainstem and spinal cord for the dose received by 1 cc volume with 4.11 and 1.67 Gy dose reduction in EPs on average.

CONCLUSION

The GRU-RNN-based DVH prediction method was capable of accurate DVH prediction. The regenerated plans guided by the predicted EUDs were not inferior to the manual plans, had better consistency in PTVs and better dose sparing in critical OARs, indicating the usefulness and effectiveness of biologically related model in knowledge-based planning.

Conventional dose rate spatially-fractionated radiation therapy (SFRT) treatment response and its association with dosimetric parameters-A preclinical study in a Fischer 344 rat model

Purpose

To identify key dosimetric parameters that have close associations with tumor treatment response and body weight change in SFRT treatments with a large range of spatial-fractionation scale at dose rates of several Gy/min.

Methods

Six study arms using uniform tumor radiation, half-tumor radiation, 2mm beam array radiation, 0.3mm minibeam radiation, and an untreated arm were used. All treatments were delivered on a 320kV x-ray irradiator. Forty-two female Fischer 344 rats with fibrosarcoma tumor allografts were used. Dosimetric parameters studied are peak dose and width, valley dose and width, peak-to-valley-dose-ratio (PVDR), volumetric average dose, percentage volume directly irradiated, and tumor- and normal-tissue EUD. Animal survival, tumor volume change, and body weight change (indicative of treatment toxicity) are tested for association with the dosimetric parameters using linear regression and Cox Proportional Hazards models.

Results

The dosimetric parameters most closely associated with tumor response are tumor EUD (R² = 0.7923, F-stat = 15.26*; z-test = -4.07***), valley (minimum) dose (R² = 0.7636, F-stat = 12.92*; z-test = -4.338***), and percentage tumor directly irradiated (R² = 0.7153, F-stat = 10.05*; z-test = -3.837***) per the linear regression and Cox Proportional Hazards models, respectively. Tumor response is linearly proportional to valley (minimum) doses and tumor EUD. Average dose (R² = 0.2745, F-stat = 1.514 (no sig.); z-test = -2.811**) and peak dose (R² = 0.04472, F-stat = 0.6874 (not sig.); z-test = -0.786 (not sig.)) show the weakest associations to tumor response. Only the uniform radiation arm did not gain body weight post-radiation, indicative of treatment toxicity; however, body weight change in general shows weak association with all dosimetric parameters except for valley (minimum) dose (R² = 0.3814, F-stat = 13.56**), valley width (R² = 0.2853, F-stat = 8.783**), and peak width (R² = 0.2759, F-stat = 8.382**).

Conclusions

For a single-fraction SFRT at conventional dose rates, valley, not peak, dose is closely associated with tumor treatment response and thus should be used for treatment prescription. Tumor EUD, valley (minimum) dose, and percentage tumor directly irradiated are the top three dosimetric parameters that exhibited close associations with tumor response.

Study of Asymmetric Margins in Prostate Cancer Radiation Therapy Using Fuzzy Logic

PURPOSE

The purpose of present study is to estimate asymmetric margins of prostate target volume based on biological limitations with help of knowledge based fuzzy logic considering the effect of organ motion and setup errors.

MATERIALS AND METHODS

A novel application of fuzzy logic modelling technique considering radiotherapy uncertainties including setup, delineation and organ motion was used in this study to derive margins. The new margin was applied in prostate cancer treatment planning and the results compared very well to current techniques Here volumetric modulated arc therapy treatment plans using stepped increments of asymmetric margins of planning target volume (PTV) were performed to calculate the changes in prostate radiobiological indices and results were used to formulate the rule based and membership function for Mamdani-type fuzzy inference system. The optimum fuzzy rules derived from input data, the clinical goals and knowledge-based conditions imposed on the margin limits. The PTV margin obtained using the fuzzy model was compared to the commonly used margin recipe.

RESULTS

For total displacement standard errors ranging from 0 to 5 mm the fuzzy PTV margin was found to be up to 0.5 mm bigger than the vanHerk derived margin, however taking the modelling uncertainty into account results in a good match between the PTV margin calculated using our model and the one based on van Herk et al. formulation for equivalent errors of up to 5 mm standard deviation (s. d.) at this range. When the total displacement standard errors exceed 5 mm s. d., the fuzzy margin remained smaller than the van Herk margin.

CONCLUSION

The advantage of using knowledge based fuzzy logic is that a practical limitation on the margin size is included in the model for limiting the dose received by the critical organs. It uses both physical and radiobiological data to optimize the required margin as per clinical requirement in real time or adaptive planning, which is an improvement on most margin models which mainly rely on physical data only.

Prescription Value-Based Automatic Optimization of Importance Factors in Inverse Planning

Objective:

An automatic method for the optimization of importance factors was proposed to improve the efficiency of inverse planning.

Methods:

The automatic method consists of 3 steps: (1) First, the importance factors are automatically and iteratively adjusted based on our proposed penalty strategies. (2) Then, plan evaluation is performed to determine whether the obtained plan is acceptable. (3) If not, a higher penalty is assigned to the unsatisfied objective by multiplying it by a compensation coefficient. The optimization processes are performed alternately until an acceptable plan is obtained or the maximum iteration N_max of step (3) is reached.

Results:

Tested on 2 kinds of clinical cases and compared with manual method, the results showed that the quality of the proposed automatic plan was comparable to, or even better than, the manual plan in terms of the dose–volume histogram and dose distributions.

Conclusions:

The proposed algorithm has potential to significantly improve the efficiency of the existing manual adjustment methods for importance factors and contributes to the development of fully automated planning. Especially, the more the subobjective functions, the more obvious the advantage of our algorithm.

An extended dose-volume model in high dose-rate brachytherapy - Using mean-tail-dose to reduce tumor underdosage

Purpose

High dose–rate brachytherapy is a method of radiotherapy for cancer treatment in which the radiation source is placed within the body. In addition to give a high enough dose to a tumor, it is also important to spare nearby healthy organs [organs at risk (OAR)]. Dose plans are commonly evaluated using the so‐called dosimetric indices; for the tumor, the portion of the structure that receives a sufficiently high dose is calculated, while for OAR it is instead the portion of the structure that receives a sufficiently low dose that is of interest. Models that include dosimetric indices are referred to as dose–volume models (DVMs) and have received much interest recently. Such models do not take the dose to the coldest (least irradiated) volume of the tumor into account, which is a distinct weakness since research indicates that the treatment effect can be largely impaired by tumor underdosage even to small volumes. Therefore, our aim is to extend a DVM to also consider the dose to the coldest volume.

Methods

An improved DVM for dose planning is proposed. In addition to optimizing with respect to dosimetric indices, this model also takes mean dose to the coldest volume of the tumor into account.

Results

Our extended model has been evaluated against a standard DVM in ten prostate geometries. Our results show that the dose to the coldest volume could be increased, while also computing times for the dose planning were improved.

Conclusion

While the proposed model yields dose plans similar to other models in most aspects, it fulfils its purpose of increasing the dose to cold tumor volumes. An additional benefit is shorter solution times, and especially for clinically relevant times (of minutes) we show major improvements in tumour dosimetric indices.

A fast optimization approach for treatment planning of volumetric modulated arc therapy

Background

Volumetric modulated arc therapy (VMAT) is widely used in clinical practice. It not only significantly reduces treatment time, but also produces high-quality treatment plans. Current optimization approaches heavily rely on stochastic algorithms which are time-consuming and less repeatable. In this study, a novel approach is proposed to provide a high-efficient optimization algorithm for VMAT treatment planning.

Methods

A progressive sampling strategy is employed for beam arrangement of VMAT planning. The initial beams with equal-space are added to the plan in a coarse sampling resolution. Fluence-map optimization and leaf-sequencing are performed for these beams. Then, the coefficients of fluence-maps optimization algorithm are adjusted according to the known fluence maps of these beams. In the next round the sampling resolution is doubled and more beams are added. This process continues until the total number of beams arrived. The performance of VMAT optimization algorithm was evaluated using three clinical cases and compared to those of a commercial planning system.

Results

The dosimetric quality of VMAT plans is equal to or better than the corresponding IMRT plans for three clinical cases. The maximum dose to critical organs is reduced considerably for VMAT plans comparing to those of IMRT plans, especially in the head and neck case. The total number of segments and monitor units are reduced for VMAT plans. For three clinical cases, VMAT optimization takes < 5 min accomplished using proposed approach and is 3–4 times less than that of the commercial system.

Conclusions

The proposed VMAT optimization algorithm is able to produce high-quality VMAT plans efficiently and consistently. It presents a new way to accelerate current optimization process of VMAT planning.

A quality control method for intensity-modulated radiation therapy planning based on generalized equivalent uniform dose

To ensure good quality intensity-modulated radiation therapy (IMRT) planning, we proposed the use of a quality control method based on generalized equivalent uniform dose (gEUD) that predicts absorbed radiation doses in organs at risk (OAR). We conducted a retrospective analysis of patients who underwent IMRT for the treatment of cervical carcinoma, nasopharyngeal carcinoma (NPC), or non-small cell lung cancer (NSCLC). IMRT plans were randomly divided into data acquisition and data verification groups. OAR in the data acquisition group for cervical carcinoma and NPC were further classified as sub-organs at risk (sOAR). The normalized volume of sOAR and normalized gEUD (a = 1) were analyzed using multiple linear regression to establish a fitting formula. For NSCLC, the normalized intersection volume of the planning target volume (PTV) and lung, the maximum diameter of the PTV (left-right, anterior-posterior, and superior-inferior), and the normalized gEUD (a = 1) were analyzed using multiple linear regression to establish a fitting formula for the lung gEUD (a = 1). The r-squared and P values indicated that the fitting formula was a good fit. In the data verification group, IMRT plans verified the accuracy of the fitting formula, and compared the gEUD (a = 1) for each OAR between the subjective method and the gEUD-based method. In conclusion, the gEUD-based method can be used effectively for quality control and can reduce the influence of subjective factors on IMRT planning optimization.

On the gEUD biological optimization objective for organs at risk in Photon Optimizer of Eclipse treatment planning system

Inverse planning optimization using biologically based objectives is becoming part of the intensity modulated optimization process. The performances and efficacy of the biologically based gEUD (generalized Equivalent Uniform Dose) objective implemented in the Photon Optimizer (PO) of Varian Eclipse treatment planning system have been here analyzed. gEUD is associated with the parameter a that accounts for the seriality of a structure, being higher for more serial organs. The PO was used to optimize volumetric modulated arc therapy (VMAT) plans on a virtual homogeneous cylindrical phantom presenting a target and an organ at risk (OAR). The OAR was placed at 4 mm, 1 and 2 cm distance, or cropped at 0, 2 and 4 mm from the target. Homogeneous target dose of 60 Gy in 20 fractions was requested with physical dose-volume objectives, while OAR dose was minimized with the upper gEUD objective. The gEUD specific a parameter was varied from 0.1 to 40 to assess its impact to OAR sparing and target coverage. Actual head and neck and prostate cases, with one parotid and the rectum as test OAR, were also analyzed to translate the results in the more complex clinical environment. Increasing the a parameter value in the gEUD objective, the optimization achieved lower volumes of the OAR which received the highest dose levels. The maximum dose in the OAR was minimized well with a values up to 20, while further increase of a to 40 did not further improve the result. The OAR mean dose was reduced for the OAR located at 1 and 2 cm distance from the target, enforced with increasing a. For cropped OARs, a mean dose reduction was achieved for a values up to 3-5, but mean dose increased for higher a values. The optimal choice of the parameter a depends on the mutual OAR and target position, and seriality of the organ. Today no significant compendium of clinical and biological specific a and gEUD values are available for a wide range of OARs.

Optimization of radiotherapy fractionation schedules based on radiobiological functions

OBJECTIVE

To present a method for optimizing radiotherapy fractionation schedules using radiobiological tools and taking into account the patient´s dose-volume histograms (DVH).

METHODS

This method uses a figure of merit based on the uncomplicated tumour control probability (P⁺) and the generalized equivalent uniform dose (gEUD). A set of doses per fraction is selected in order to find the dose per fraction and the total dose, thus maximizing the figure of merit and leading to a biologically effective dose that is similar to the prescribed schedule.

RESULTS

As a clinical example, a fractionation schedule for a prostate treatment plan is optimized and presented herein. From a prescription schedule of 70 Gy/35 × 2  Gy, the resulting optimal schema, using a figure of merit which only takes into account P⁺, is 54.4 Gy/16 × 3.4  Gy. If the gEUD is included in that figure of merit, the result is 65 Gy/26 × 2.5  Gy. Alternative schedules, which include tumour control probability (TCP) and the normal tissue complication probability (NTCP) values are likewise shown. This allows us to compare different schedules instead of solely finding the optimal value, as other possible clinical factors must be taken into account to make the best decision for treatment.

CONCLUSION

The treatment schedule can be optimized for each patient through radiobiological analysis. The optimization process shown below offers physicians alternative schedules that meet the objectives of the prescribed radiotherapy. Advances in knowledge: This article provides a simple, radiobiological-function-based method to take advantage of a patient's dose-volume histograms in order to better select the most suitable treatment schedule.

The use of TCP based EUD to rank and compare lung radiotherapy plans: in-silico study to evaluate the correlation between TCP with physical quality indices

BACKGROUND

To apply the equivalent uniform dose (EUD) radiobiological model to estimate the tumor control probability (TCP) scores for treatment plans using different radiobiological parameter settings, and to evaluate the correlation between TCP and physical quality indices of the treatment plans.

METHODS

Ten radiotherapy treatment plans for lung cancer were generated. The dose distributions were calculated using anisotropic analytical algorithm (AAA). Dose parameters and quality indices derived from dose volume histograms (DVH) for target volumes were evaluated. The predicted TCP was computed using EUD model with tissue-specific parameter (a=-10). The assumed radiobiological parameter setting for adjuvant therapy [tumor dose to control 50% of the tumor (TCD₅₀) =36.5 Gy and γ₅₀=0.72] and curative intent (TCD₅₀=51.24 Gy and γ₅₀=0.83) were used. The bootstrap method was used to estimate the 95% confidence interval (95% CI). The coefficients (ρ) from Spearman's rank test were calculated to assess the correlation between quality indices with TCP. Wilcoxon paired test was used to calculate P value.

RESULTS

The 95% CI of TCP were 70.6-81.5 and 46.6-64.7, respectively, for adjuvant radiotherapy and curative intent. The TCP outcome showed a positive and good correlation with calculated dose to 95% of the target volume (D95%) and minimum dose (Dmin). Consistently, TCP correlate negatively with heterogeneity indices.

CONCLUSIONS

This study confirms that more relevant and robust radiobiological parameters setting should be integrated according to cancer type. The positive correlation with quality indices gives chance to improve the clinical out-come by optimizing the treatment plans to maximize the Dmin and D95%. This attempt to increase the TCP should be carried out with the respect of dose constraints for organs at risks. However, the negative correlation with heterogeneity indices shows that the optimization of beam arrangements could be also useful. Attention should be paid to obtain an appropriate optimization of initial plans, when comparing and ranking radiotherapy plans using TCP models, to avoid over or underestimated for TCP outcome.

An integrated strategy of biological and physical constraints in biological optimization for cervical carcinoma

Background

For cervical carcinoma cases, this study aimed to evaluate the quality of intensity-modulated radiation therapy (IMRT) plans optimized by biological constraints. Furthermore, a new integrated strategy in biological planning module was proposed and verified.

Methods

Twenty patients of advanced stage cervical carcinoma were enrolled in this study. For each patient, dose volume optimization (DVO), biological model optimization (BMO) and integrated strategy optimization (ISO) plans were created using same treatment parameters. Different biological models were also used for organ at risk (OAR) in BMO plans, which include the LKB and Poisson models. Next, BMO plans were compared with their corresponding DVO plans, in order to evaluate BMO plan quality. ISO plans were also compared with DVO and BMO plans, in order to verify the performance of the integrated strategy.

Results

BMO plans produced slightly inhomogeneity and less coverage of planning target volume (PTV) (V95=96.79, HI = 0.10: p < 0.01). However, the tumor control probability (TCP) value, both from DVO and BMO plans, were comparable. For the OARs, BMO plans produced lower normal tissue complication probability (NTCP) of rectum (NTCP = 0.11) and bladder (NTCP = 0.14) than in the corresponding DVO plans (NTCP = 0.19 and 0.18 for rectum and bladder; p < 0.01 for rectum and p = 0.03 for bladder). V95, D98, CI and HI values that were produced by ISO plans (V95 = 98.31, D98 = 54.18Gy, CI = 0.76, HI = 0.09) were greatly better than BMO plans (V95 = 96.79, D98 = 53.42Gy, CI = 0.71, HI = 0.10) with significant differences. Furthermore, ISO plans produced lower NTCP values of rectum (NTCP = 0.14) and bladder (NTCP = 0.16) than DVO plans (NTCP = 0.19 and 0.18 for rectum and bladder, respectively) with significant differences.

Conclusions

BMO plans produced lower NTCP values of OARs compared to DVO plans for cervical carcinoma cases, and resulted in slightly less target coverage and homogeneity. The integrated strategy, proposed in this study, could improve the coverage, conformity and homogeneity of PTV greater than the BMO plans, as well as reduce the NTCP values of OARs greater than the DVO plans.

Robust plan optimization using edge-enhanced intensity for intrafraction organ deformation in prostate intensity-modulated radiation therapy

This study evaluated a method for prostate intensity-modulated radiation therapy (IMRT) based on edge-enhanced (EE) intensity in the presence of intrafraction organ deformation using the data of 37 patients treated with step-and-shoot IMRT. On the assumption that the patient setup error was already accounted for by image guidance, only organ deformation over the treatment course was considered. Once the clinical target volume (CTV), rectum, and bladder were delineated and assigned dose constraints for dose optimization, each voxel in the CTV derived from the DICOM RT-dose grid could have a stochastic dose from the different voxel location according to the probability density function as an organ deformation. The stochastic dose for the CTV was calculated as the mean dose at the location through changing the voxel location randomly 1000 times. In the EE approach, the underdose region in the CTV was delineated and optimized with higher dose constraints that resulted in an edge-enhanced intensity beam to the CTV. This was compared to a planning target volume (PTV) margin (PM) approach in which a CTV to PTV margin equivalent to the magnitude of organ deformation was added to obtain an optimized dose distribution. The total monitor units, number of segments, and conformity index were compared between the two approaches, and the dose based on the organ deformation of the CTV, rectum, and bladder was evaluated. The total monitor units, number of segments, and conformity index were significantly lower with the EE approach than with the PM approach, while maintaining the dose coverage to the CTV with organ deformation. The dose to the rectum and bladder were significantly reduced in the EE approach compared with the PM approach. We conclude that the EE approach is superior to the PM with regard to intrafraction organ deformation.

Toward a better prescription method for external radiotherapy

Aim: The aim of the study was to compare several methods of dose prescription, the mean dose, the median dose, the effective dose and the generalized Equivalent Uniform Dose (gEUD).

Background: The dose distribution in the planning target volume is never fully homogenous. Depending on the dose prescription method for the same prescribed dose different biologically equivalent doses are delivered. The latest ICRU Report 83 proposes to prescribe the dose to the median dose in the PTV. Several other methods are also in common use. It is important to know what are differences of doses actually delivered depending on the dose prescription method.

Materials and methods: The study was performed for three groups of patients treated radically with external beams in Brzozow, over the 2012-2013 period. The groups were of patients with breast, lung and prostate cancer. There were 10 patients in each group. For each patient all metrics, i.e. the mean dose, the median dose, the effective dose and the generalized Equivalent Uniform Dose, were calculated. The influence of the dose homogeneity in the PTV on the results is also evaluated. The gEUD was used as a reference dose prescription method.

Results: For all patients, an almost perfect correlation between the median dose and the gEUD was obtained. Worse correlation was obtained between other metrics and the gEUD. The median dose is almost always a little higher than the gEUD, but the ratio of these two values never exceeded 1.013.

Conclusion: The median dose seems to be a good and simple method of dose prescription.

Risks and benefits of reducing target volume margins in breast tangent radiotherapy

This study investigates the potential benefits of planning target volume (PTV) margin reduction for whole breast radiotherapy in relation to dose received by organs at risk (OARs), as well as reductions in radiation-induced secondary cancer risk. Such benefits were compared to the increased radiation-induced secondary cancer risk attributed from increased ionizing radiation imaging doses. Ten retrospective patients' computed tomography datasets were considered. Three computerized treatment plans with varied PTV margins (0, 5 and 10 mm) were created for each patient complying with the Radiation Therapy Oncology Group (RTOG) 1005 protocol requirements. The BEIR VII lifetime attributable risk (LAR) model was used to estimate secondary cancer risk to OARs. The LAR was assessed for all treatment plans considering (a) doses from PTV margin variation and (b) doses from two (daily and weekly) kilovoltage cone beam computed tomography (kV CBCT) imaging protocols during the course of treatment. We found PTV margins from largest to smallest resulted in a mean OAR relative dose reduction of 31% (heart), 28% (lung) and 23% (contralateral breast) and the risk of radiation-induced secondary cancer by a relative 23% (contralateral breast) and 22% (contralateral lung). Daily image-guidance using kV CBCT increased the risk of radiation induced secondary cancer to the contralateral breast and contralateral lung by a relative 1.6-1.9% and 1.9-2.5% respectively. Despite the additional dose from kV CBCT for the two considered imaging protocols, smaller PTV margins would still result in an overall reduction in secondary cancer risk.

Dosimetric effect of beam arrangement for intensity-modulated radiation therapy in the treatment of upper thoracic esophageal carcinoma

To evaluate the lung sparing in intensity-modulated radiation therapy (IMRT) for patients with upper thoracic esophageal tumors extending inferiorly to the thorax by different beam arrangement. Overall, 15 patient cases with cancer of upper thoracic esophagus were selected for a retrospective treatment-planning study. Intensity-modulated radiation therapy plans using 4, 5, and 7 beams (4B, 5B, and 7B) were developed for each patient by direct machine parameter optimization (DMPO). All plans were evaluated with respect to dose volumes to irradiated targets and normal structures, with statistical comparisons made between 4B with 5B and 7B intensity-modulated radiation therapy plans. Differences among plans were evaluated using a two-tailed Friedman test at a statistical significance of p < 0.05. The maximum dose, average dose, and the conformity index (CI) of planning target volume 1 (PTV1) were similar for 3 plans for each case. No significant difference of coverage for planning target volume 1 and maximum dose for spinal cords were observed among 3 plans in present study (p > 0.05). The average V₅, V₁₃, V₂₀, mean lung dose, and generalized equivalent uniform dose (gEUD) for the total lung were significantly lower in 4B-plans than those data in 5B-plans and 7B-plans (p < 0.01). Although the average V₃₀ for the total lung were significantly higher in 4B-plans than those in 5B-plans and 7B-plans (p < 0.05). In addition, when comparing with the 4B-plans, the conformity/heterogeneity index of the 5B- and 7B-plans were significantly superior (p < 0.05). The 4B-intensity-modulated radiation therapy plan has advantage to address the specialized problem of lung sparing to low- and intermediate-dose exposure in the thorax when dealing with relative long tumors extended inferiorly to the thoracic esophagus for upper esophageal carcinoma with the cost for less conformity. Studies are needed to compare the superiority of volumetric modulated arc therapy with intensity-modulated radiation therapy technique.

The benefit of using bladder sub-volume equivalent uniform dose constraints in prostate intensity-modulated radiotherapy planning

Background

To assess the benefits of bladder wall sub-volume equivalent uniform dose (EUD) constraints in prostate cancer intensity-modulated radiotherapy (IMRT) planning.

Methods

Two IMRT plans, with and without EUD constraints on the bladder wall, were generated using beams that deliver 80 Gy to the prostate and 46 Gy to the seminal vesicles and were compared in 53 prostate cancer patients. The bladder wall was defined as the volume between the external manually delineated wall and a contraction of 7 mm apart from it. The bladder wall was then separated into two parts: the internal-bladder wall (bla-in) represented by the portion of the bladder wall that intersected with the planning target volume (PTV) plus 5 mm extension; the external-bladder wall (bla-ex) represented by the remaining part of the bladder wall. In the IMRT plan with EUD constraints, the values of “a” parameter for the EUD models were 10.0 for bla-in and 2.3 for bla-ex. The plans with and without EUD constraints were compared in terms of dose–volume histograms, 5-year bladder and rectum normal tissue complication probability values, as well as tumor control probability (TCP) values.

Results

The use of bladder sub-volume EUD constraints decreased both the doses to the bladder wall (V₇₀: 22.76% vs 19.65%, D_mean: 39.82 Gy vs 35.45 Gy) and the 5-year bladder complication probabilities (≥LENT/SOMA Grade 2: 20.35% vs 17.96%; bladder bleeding: 10.63% vs 8.64%). The doses to the rectum wall and the rectum complication probabilities were also slightly decreased by the EUD constraints compared to physical constraints only. The minimal dose and the V_76Gy of PTV_prostate were, however, slightly decreased by EUD optimization, nevertheless without significant difference in TCP values between the two plans, and the PTV parameters finally respected the Groupe d’Etude des Tumeurs Uro-Génitales recommendations.

Conclusion

Separating the bladder wall into two parts with appropriate EUD optimization may reduce bladder toxicity in prostate IMRT. Combining biological constraints with physical constraints in the organs at risk at the inverse planning step of IMRT may improve the dose distribution.