Interactive dose shaping part 2: proof of concept study for six prostate patients

Per-voxel constraints to minimize hot spots in linear energy transfer-guided robust optimization for base of skull head and neck cancer patients in IMPT

PURPOSE

Due to the employment of quadratic programming using soft constraints to implement dose volume constraints and the "trial-and-error" procedure needed to achieve a clinically acceptable plan, conventional dose volume constraints (upper limit) are not adequately effective in controlling small and isolated hot spots in the dose/linear energy transfer (LET) distribution. Such hot spots can lead to adverse events. In order to mitigate the risk of brain necrosis, one of the most clinically significant adverse events in patients receiving intensity-modulated proton therapy (IMPT) for base of skull (BOS) cancer, we propose per-voxel constraints to minimize hot spots in LET-guided robust optimization.

METHODS AND MATERIALS

Ten BOS cancer patients treated with IMPT were carefully selected by meeting one of the following conditions: (1) diagnosis of brain necrosis during follow-up; and (2) considered high risk for brain necrosis by not meeting dose constraints to the brain. An optimizing structure (BrainOPT) and an evaluating structure (BrainROI) that both contained the aforementioned hot dose regions in the brain were generated for optimization and evaluation, respectively. Two plans were generated for every patient: one using conventional dose-only robust optimization, the other using LET-guided robust optimization. The impact of LET was integrated into the optimization via a term of extra biological dose (xBD). A novel optimization tool of per-voxel constraints to control small and isolated hot spots in either the dose, LET, or combined (dose/LET) distribution was developed and used to minimize dose/LET hot spots of the selected structures. Indices from dose-volume histogram (DVH) and xBD dose-volume histogram (xBDVH) were used in the plan evaluation. A newly developed tool of the dose-LET-volume histogram (DLVH) was also adopted to illustrate the underlying mechanism. Wilcoxon signed-rank test was used for statistical comparison of the DVH and xBDVH indices between the conventional dose-only and the LET-guided robustly optimized plans.

RESULTS

Per-voxel constraints effectively and efficiently minimized dose hot spots in both dose-only and LET-guided robust optimization and LET hot spots in LET-guided robust optimization. Compared to the conventional dose-only robust optimization, the LET-guided robust optimization could generate plans with statistically lower xBD hot spots in BrainROI (VxBD,50 Gy[RBE], p = 0.009; VxBD,60 Gy[RBE], p = 0.025; xBD1cc, p = 0.017; xBD2cc, p = 0.022) with comparable dose coverage, dose hot spots in the target, and dose hot spots in BrainROI. DLVH analysis indicated that LET-guided robust optimization could either reduce LET at the same dose level or redistribute high LET from high dose regions to low dose regions.

CONCLUSION

Per-voxel constraint is a powerful tool to minimize dose/LET hot spots in IMPT. The LET-guided robustly optimized plans outperformed the conventional dose-only robustly optimized plans in terms of xBD hot spots control.

Real-time interactive planning for radiotherapy of head and neck cancer with volumetric modulated arc therapy

Background and purpose

Planning complex radiotherapy treatments can be inefficient, with large variation in plan quality. In this study we evaluated plan quality and planning efficiency using real-time interactive planning (RTIP) for head and neck (HN) volumetric modulated arc therapy (VMAT).

Materials and methods

RTIP allows manipulation of dose volume histograms (DVHs) in real-time to assess achievable planning target volume (PTV) coverage and organ at risk (OAR) sparing. For 20 HN patients previously treated with VMAT, RTIP was used to minimize OAR dose while maintaining PTV coverage. RTIP DVHs were used to guide VMAT optimization. Dosimetric differences between RTIP-assisted plans and original clinical plans were assessed. Five blinded radiation oncologists indicated their preference for each PTV, OAR and overall plan. To assess efficiency, ten patients were planned de novo by experienced and novice planners and a RTIP user.

Results

The average planning time with RTIP was <20 min, and most plans required only one optimization. All 20 RTIP plans were preferred by a majority of oncologists due to improvements in OAR sparing. The average maximum dose to the spinal cord was reduced by 10.5 Gy (from 49.5 to 39.0 Gy), and the average mean doses for the oral cavity, laryngopharynx, contralateral parotid and submandibular glands were reduced by 3.5 Gy (39.1-35.7 Gy), 6.8 Gy (42.5-35.7 Gy), 1.7 Gy (17.0-15.3 Gy) and 3.3 Gy (22.9-19.5 Gy), respectively.

Conclusions

Incorporating RTIP into clinical workflows may increase both planning efficiency and OAR sparing.

Novel adaptive beam-dependent margins for additional OAR sparing

Margins are employed in radiotherapy treatment planning to mitigate the dosimetric effects of geometric uncertainties for the clinical target volume (CTV). Unfortunately, whilst the use of margins can increase the probability that sufficient dose is delivered to the CTV, it can also result in delivering high dose of radiation to surrounding organs at risk (OARs). We expand on our previous work on beam-dependent margins and propose a novel adaptive margin concept, where margins are moulded away from selected OARs for better OAR-high-dose sparing, whilst maintaining similar dose coverage probability to the CTV. This, however, comes at a cost of a larger irradiation volume, and thus can negatively impact other structures. We investigate the impact of the adaptive margin concept when applied to prostate radiotherapy treatments, and compare treatment plans generated using our beam-dependent margins without adaptation, with adaption from the rectum and with adaptation from both the rectum and bladder. Five prostate patients were used in this planning study. All plans achieved similar dose coverage probability, and were able to ensure at least 90% population coverage with the target receiving at least 95% of the prescribed dose to [Formula: see text]. We observed overall better high-dose sparing to OARs that were considered when using the adapted beam-dependent PTVs, with the degree of sparing dependent on both the number of OARs under consideration as well as the relative position between the CTV and the OARs.

Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations

Radiotherapy treatment planning of complex radiotherapy techniques, such as intensity modulated radiotherapy and volumetric modulated arc therapy, is a resource-intensive process requiring a high level of treatment planner intervention to ensure high plan quality. This can lead to variability in the quality of treatment plans and the efficiency in which plans are produced, depending on the skills and experience of the operator and available planning time. Within the last few years, there has been significant progress in the research and development of intensity modulated radiotherapy treatment planning approaches with automation support, with most commercial manufacturers now offering some form of solution. There is a rapidly growing number of research articles published in the scientific literature on the topic. This paper critically reviews the body of publications up to April 2018. The review describes the different types of automation algorithms, including the advantages and current limitations. Also included is a discussion on the potential issues with routine clinical implementation of such software, and highlights areas for future research.

Magnetic Resonance Imaging-Guided Adaptive Radiation Therapy: A "Game Changer" for Prostate Treatment?

Radiation therapy to the prostate involves increasingly sophisticated delivery techniques and changing fractionation schedules. With a low estimated α/β ratio, a larger dose per fraction would be beneficial, with moderate fractionation schedules rapidly becoming a standard of care. The integration of a magnetic resonance imaging (MRI) scanner and linear accelerator allows for accurate soft tissue tracking with the capacity to replan for the anatomy of the day. Extreme hypofractionation schedules become a possibility using the potentially automated steps of autosegmentation, MRI-only workflow, and real-time adaptive planning. The present report reviews the steps involved in hypofractionated adaptive MRI-guided prostate radiation therapy and addresses the challenges for implementation.

Online dose reconstruction for tracked volumetric arc therapy: Real-time implementation and offline quality assurance for prostate SBRT

PURPOSE

Firstly, this study provides a real-time implementation of online dose reconstruction for tracked volumetric arc therapy (VMAT). Secondly, this study describes a novel offline quality assurance tool, based on commercial dose calculation algorithms.

METHODS

Online dose reconstruction for VMAT is a computationally challenging task in terms of computer memory usage and calculation speed. To potentially reduce the amount of memory used, we analyzed the impact of beam angle sampling for dose calculation on the accuracy of the dose distribution. To establish the performance of the method, we planned two single-arc VMAT prostate stereotactic body radiation therapy cases for delivery with dynamic MLC tracking. For quality assurance of our online dose reconstruction method we have also developed a stand-alone offline dose reconstruction tool, which utilizes the RayStation treatment planning system to calculate dose.

RESULTS

For the online reconstructed dose distributions of the tracked deliveries, we could establish strong resemblance for 72 and 36 beam co-planar equidistant beam samples with less than 1.2% deviation for the assessed dose-volume indicators (clinical target volume D98 and D2, and rectum D2). We could achieve average runtimes of 28-31 ms per reported MLC aperture for both dose computation and accumulation, meeting our real-time requirement. To cross-validate the offline tool, we have compared the planned dose to the offline reconstructed dose for static deliveries and found excellent agreement (3%/3 mm global gamma passing rates of 99.8%-100%).

CONCLUSION

Being able to reconstruct dose during delivery enables online quality assurance and online replanning strategies for VMAT. The offline quality assurance tool provides the means to validate novel online dose reconstruction applications using a commercial dose calculation engine.

A novel probabilistic approach to generating PTV with partial voxel contributions

Radiotherapy treatment planning for use with high-energy photon beams currently employs a binary approach in defining the planning target volume (PTV). We propose a margin concept that takes the beam directions into account, generating beam-dependent PTVs (bdPTVs) on a beam-by-beam basis. The resulting degree of overlaps between the bdPTVs are used within the optimisation process; the optimiser effectively considers the same voxel to be both target and organ at risk (OAR) with fractional contributions. We investigate the impact of this novel approach when applied to prostate radiotherapy treatments, and compare treatment plans generated using beam dependent margins to conventional margins. Five prostate patients were used in this planning study, and plans using beam dependent margins improved the sparing of high doses to target-surrounding OARs, though a trade-off in delivering additional low dose to the OARs can be observed. Plans using beam dependent margins are observed to have a slightly reduced target coverage. Nevertheless, all plans are able to satisfy 90% population coverage with the target receiving at least 95% of the prescribed dose to [Formula: see text].

Real-time 4D dose reconstruction for tracked dynamic MLC deliveries for lung SBRT

PURPOSE

This study provides a proof of concept for real-time 4D dose reconstruction for lung stereotactic body radiation therapy (SBRT) with multileaf collimator (MLC) tracking and assesses the impact of tumor tracking on the size of target margins.

METHODS

The authors have implemented real-time 4D dose reconstruction by connecting their tracking and delivery software to an Agility MLC at an Elekta Synergy linac and to their in-house treatment planning software (TPS). Actual MLC apertures and (simulated) target positions are reported to the TPS every 40 ms. The dose is calculated in real-time from 4DCT data directly after each reported aperture by utilization of precalculated dose-influence data based on a Monte Carlo algorithm. The dose is accumulated onto the peak-exhale (reference) phase using energy-mass transfer mapping. To investigate the impact of a potentially reducible safety margin, the authors have created and delivered treatment plans designed for a conventional internal target volume (ITV) + 5 mm, a midventilation approach, and three tracking scenarios for four lung SBRT patients. For the tracking plans, a moving target volume (MTV) was established by delineating the gross target volume (GTV) on every 4DCT phase. These were rigidly aligned to the reference phase, resulting in a unified maximum GTV to which a 1, 3, or 5 mm isotropic margin was added. All scenarios were planned for 9-beam step-and-shoot IMRT to meet the criteria of RTOG 1021 (3 × 18 Gy). The GTV 3D center-of-volume shift varied from 6 to 14 mm.

RESULTS

Real-time dose reconstruction at 25 Hz could be realized on a single workstation due to the highly efficient implementation of dose calculation and dose accumulation. Decreased PTV margins resulted in inadequate target coverage during untracked deliveries for patients with substantial tumor motion. MLC tracking could ensure the GTV target dose for these patients. Organ-at-risk (OAR) doses were consistently reduced by decreased PTV margins. The tracked MTV + 1 mm deliveries resulted in the following OAR dose reductions: lung V20 up to 3.5%, spinal cord D2 up to 0.9 Gy/Fx, and proximal airways D2 up to 1.4 Gy/Fx.

CONCLUSIONS

The authors could show that for patient data at clinical resolution and realistic motion conditions, the delivered dose could be reconstructed in 4D for the whole lung volume in real-time. The dose distributions show that reduced margins yield lower doses to healthy tissue, whilst target dose can be maintained using dynamic MLC tracking.

Physically constrained voxel-based penalty adaptation for ultra-fast IMRT planning

Conventional treatment planning in intensity-modulated radiation therapy (IMRT) is a trial-and-error process that usually involves tedious tweaking of optimization parameters. Here, we present an algorithm that automates part of this process, in particular the adaptation of voxel-based penalties within normal tissue. Thereby, the proposed algorithm explicitly considers a priori known physical limitations of photon irradiation. The efficacy of the developed algorithm is assessed during treatment planning studies comprising 16 prostate and 5 head and neck cases. We study the eradication of hot spots in the normal tissue, effects on target coverage and target conformity, as well as selected dose volume points for organs at risk. The potential of the proposed method to generate class solutions for the two indications is investigated. Run-times of the algorithms are reported. Physically constrained voxel-based penalty adaptation is an adequate means to automatically detect and eradicate hot-spots during IMRT planning while maintaining target coverage and conformity. Negative effects on organs at risk are comparably small and restricted to lower doses. Using physically constrained voxel-based penalty adaptation, it was possible to improve the generation of class solutions for both indications. Considering the reported run-times of less than 20 s, physically constrained voxel-based penalty adaptation has the potential to reduce the clinical workload during planning and automated treatment plan generation in the long run, facilitating adaptive radiation treatments.

Interactive dose shaping part 1: a new paradigm for IMRT treatment planning

In this work we present a novel treatment planning technique called interactive dose shaping (IDS) to be employed for the optimization of intensity modulated radiation therapy (IMRT). IDS does not rely on a Newton-based optimization algorithm which is driven by an objective function formed of dose volume constraints on pre-segmented volumes of interest (VOIs). Our new planning technique allows for direct, interactive adaptation of localized planning features. This is realized by a dose modification and recovery (DMR) planning engine which implements a two-step approach: firstly, the desired localized plan adaptation is imposed on the current plan (modification) while secondly inevitable, undesired disturbances of the dose pattern elsewhere are compensated for automatically by the recovery module. Together with an ultra-fast dose update calculation method the DMR engine has been implemented in a newly designed 3D therapy planning system Dynaplan enabling true real-time interactive therapy planning. Here we present the underlying strategy and algorithms of the DMR based planning concept. The functionality of the IDS planning approach is demonstrated for a phantom geometry of clinical resolution and size.