Calculating geometrical margins for hypofractionated radiotherapy

Population-based asymmetric margins for moving targets in real-time tumor tracking

BACKGROUND

Both geometric and dosimetric components are commonly considered when determining the margin for planning target volume (PTV). As dose distribution is shaped by controlling beam aperture in peripheral dose prescription and dose-escalated simultaneously integrated boost techniques, adjusting the margin by incorporating the variable dosimetric component into the PTV margin is inappropriate; therefore, geometric components should be accurately estimated for margin calculations.

PURPOSE

We introduced an asymmetric margin-calculation theory using the guide to the expression of uncertainty in measurement (GUM) and intra-fractional motion. The margins in fiducial marker-based real-time tumor tracking (RTTT) for lung, liver, and pancreatic cancers were calculated and were then evaluated using Monte Carlo (MC) simulations.

METHODS

A total of 74 705, 73 235, and 164 968 sets of intra- and inter-fractional positional data were analyzed for 48 lung, 48 liver, and 25 pancreatic cancer patients, respectively, in RTTT clinical trials. The 2.5th and 97.5th percentiles of the positional error were considered representative values of each fraction of the disease site. The population-based statistics of the probability distributions of these representative positional errors (PD-RPEs) were calculated in six directions. A margin covering 95% of the population was calculated using the proposed formula. The content rate in which the clinical target volume (CTV) was included in the PTV was calculated through MC simulations using the PD-RPEs.

RESULTS

The margins required for RTTT were at most 6.2, 4.6, and 3.9 mm for lung, liver, and pancreatic cancer, respectively. MC simulations revealed that the median content rates using the proposed margins satisfied 95% for lung and liver cancers and 93% for pancreatic cancer, closer to the expected rates than the margins according to van Herk's formula.

CONCLUSIONS

Our proposed formula based on the GUM and motion probability distributions (MPD) accurately calculated the practical margin size for fiducial marker-based RTTT. This was verified through MC simulations.

SGRT-based stereotactic body radiotherapy for lung cancer setup accuracy and margin of the PTV

OBJECTIVE

Surface-guided radiation therapy (SGRT, AlignRT) was used to analyze motion during stereotactic body radiotherapy (SBRT) in lung cancer patients and to explore the margin of the planning target volume (PTV).

METHODS

The residual errors of the AlignRT were evaluated based on grayscale cone-beam computed tomography registration results before each treatment. AlignRT log file was used to analyze the correlation between the frequency and longest duration of errors larger than 2 mm and lasting longer than 2 s and maximum error with age and treatment duration. The displacement value at the end of treatment, the average displacement value, and the 95% probability density displacement interval were defined as intrafraction errors, and PTV1, PTV2, PTV3 were calculated by Van Herk formula or Z score analysis. Organ dosimetric differences were compared after the experience-based margin was replaced with PTV3.

RESULTS

The interfraction residual errors were Vrt0 , 0.06 ± 0.18 cm; Lng0 , -0.03 ± 0.19 cm; Lat0 , 0.02 ± 0.15 cm; Pitch0 , 0.23 ± 0.7°; Roll0 , 0.1 ± 0.69°; Rtn0 , -0.02 ± 0.79°. The frequency, longest duration and maximum error in vertical direction were correlated with treatment duration (r = 0.404, 0.353, 0.283, p < 0.05, respectively). In the longitudinal direction, the frequency was correlated with age and treatment duration (r = 0.376, 0.283, p < 0.05, respectively), maximum error was correlated with age (r = 0.4, P < 0.05). Vertical, longitudinal, lateral margins of PTV1, PTV2, PTV3 were 2 mm, 4 mm, 2 mm; 2 mm, 2 mm, 2 mm, 3 mm, 5 mm, 3 mm, respectively. After replacing the original PTV, mean lung dose (MLD), 2-cm3 chest wall dose (CD), lung V20 decreased by 0.2 Gy, 2.1 Gy, 0.5%, respectively (p < 0.05).

CONCLUSION

AlignRT can be used for interfraction setup and monitoring intrafraction motion. It is more reasonable to use upper and lower limits of the 95% probability density interval as an intrafraction error.

A patient-specific deep learning framework for 3D motion estimation and volumetric imaging during lung cancer radiotherapy

Objective. Respiration introduces a constant source of irregular motion that poses a significant challenge for the precise irradiation of thoracic and abdominal cancers. Current real-time motion management strategies require dedicated systems that are not available in most radiotherapy centers. We sought to develop a system that estimates and visualises the impact of respiratory motion in 3D given the 2D images acquired on a standard linear accelerator.Approach. In this paper we introduceVoxelmap, a patient-specific deep learning framework that achieves 3D motion estimation and volumetric imaging using the data and resources available in standard clinical settings. Here we perform a simulation study of this framework using imaging data from two lung cancer patients.Main results. Using 2D images as input and 3D-3DElastixregistrations as ground-truth,Voxelmapwas able to continuously predict 3D tumor motion with mean errors of 0.1 ± 0.5, -0.6 ± 0.8, and 0.0 ± 0.2 mm along the left-right, superior-inferior, and anterior-posterior axes respectively.Voxelmapalso predicted 3D thoracoabdominal motion with mean errors of -0.1 ± 0.3, -0.1 ± 0.6, and -0.2 ± 0.2 mm respectively. Moreover, volumetric imaging was achieved with mean average error 0.0003, root-mean-squared error 0.0007, structural similarity 1.0 and peak-signal-to-noise ratio 65.8.Significance. The results of this study demonstrate the possibility of achieving 3D motion estimation and volumetric imaging during lung cancer treatments on a standard linear accelerator.

Assessing the impact of intrafraction motion correction on PTV margins and target and OAR dosimetry for single-fraction free-breathing lung stereotactic body radiation therapy

The objective of this research is to investigate intrafraction motion correction on planning target volume (PTV) margin requirements and target and organ-at-risk (OAR) dosimetry in single-fraction lung stereotactic body radiation therapy (SBRT). Sixteen patients (15 with upper lobe lesions, 1 with a middle lobe lesion) were treated with single-fraction lung SBRT. Cone-beam computed tomography (CBCT) images were acquired before the treatment, between the arcs, and after the delivery of the treatment fraction. Shifts from the reference images were recorded in anterior-posterior (AP), superior-inferior (SI), and lateral (LAT) dimensions. The deviations from the reference image were calculated for 3 clinical scenarios: not applying intratreatment couch shifts and not correcting for pretreatment deviations < 3 mm ( scenario 1), not applying intratreatment couch shifts and correcting for pretreatment deviations < 3 mm ( scenario 2), and applying all pre- and intratreatment couch shifts (scenario 3). PTV margins were determined using the van Herk formalism for each scenario and maximum and average deviations were assessed. The clinical scenarios were modelled in the treatment planning system based on each patient dataset to assess target and OAR dosimetry. Calculated lower-bound PTV margins in the AP, SI, and LAT dimensions were [4.6, 3.5, 2.3] mm in scenario 1, [4.6, 2.4, 2.2] mm in scenario 2, and [1.7, 1.2, 1.0] mm in scenario 3. The margins are lower bounds because they do not include contributions from nonmotion related errors. Average and maximum intrafraction deviations were larger in the AP dimension compared to the SI and LAT dimensions for all scenarios. A unidimensional movement (several mm) in the negative AP dimension was observed in clinical scenarios 1 and 2 but not scenario 3. Average intrafraction deviation vectors were 1.2, 1.1, and 0.3 mm for scenarios 1, 2, and 3, respectively. Modelled clinical scenarios revealed that using scenario 3 yields significantly fewer treatment plan objective failures compared to scenarios 1 and 2 using a Wilcoxon signed-rank test. Intratreatment motion correction between each arc may enable reductions PTV margin requirements. It may also compensate for unidimensional negative AP movement, and improve target and OAR dosimetry.

Empirical planning target volume modeling for high precision MRI guided intracranial radiotherapy

Purpose

Magnetic resonance image-guided radiotherapy for intracranial indications is a promising advance; however, uncertainties remain for both target localization after translation-only MR setup and intrafraction motion. This investigation quantified these uncertainties and developed a population-based planning target volume (PTV) model to explore target and organ-at-risk (OAR) volumetric coverage tradeoffs.

Methods

Sixty-six patients, 49 with a primary brain tumor and 17 with a post-surgical resection cavity, treated on a 1.5T-based MR-linac across 1329 fractions were included. At each fraction, patients were setup by translation-only fusion of the online T1 MRI to the planning image. Each fusion was independently repeated offline accounting for rotations. The six degree-of-freedom difference between fusions was applied to transform the planning CTV at each fraction (CTV_fx). A PTV model parameterized by volumetric CTV_fx coverage, proportion of fractions, and proportion of patients was developed. Intrafraction motion was quantified in a 412 fraction subset as the fusion difference between post- and pre-irradiation T1 MRIs.

Results

For the left-right/anterior-posterior/superior-inferior axes, mean ± SD of the rotational fusion differences were 0.1 ± 0.8/0.1 ± 0.8/-0.2 ± 0.9°. Covering 98 % of the CTV_fx in 95 % of fractions in 95 % of patients required a 3 mm PTV margin. Margin reduction decreased PTV-OAR overlap; for example, the proportion of optic chiasm overlapped by the PTV was reduced up to 23.5 % by margin reduction from 4 mm to 3 mm.

Conclusions

An evidence-based PTV model was developed for brain cancer patients treated on the MR-linac. Informed by this model, we have clinically adopted a 3 mm PTV margin for conventionally fractionated intracranial patients.

Intra-fraction motion of pelvic oligometastases and feasibility of PTV margin reduction using MRI guided adaptive radiotherapy

Purpose

This study assesses the impact of intra-fraction motion and PTV margin size on target coverage for patients undergoing radiation treatment of pelvic oligometastases. Dosimetric sparing of the bowel as a function of the PTV margin is also evaluated.

Materials and methods

Seven patients with pelvic oligometastases previously treated on our MR-linac (35 Gy in 5 fractions) were included in this study. Retrospective adaptive plans were created for each fraction on the daily MRI datasets using PTV margins of 5 mm, 3 mm, and 2 mm. Dosimetric constraint violations and GTV coverage were measured as a function of PTV margin size. The impact of intra-fraction motion on GTV coverage was assessed by tracking the GTV position on the cine MR images acquired during treatment delivery and creating an intra-fraction dose distribution for each IMRT beam. The intra-fraction dose was accumulated for each fraction to determine the total dose delivered to the target for each PTV size.

Results

All OAR constraints were achieved in 85.7%, 94.3%, and 100.0% of fractions when using 5 mm, 3 mm, and 2 mm PTV margins while scaling to 95% PTV coverage. Compared to plans with a 5 mm PTV margin, there was a 27.4 ± 12.3% (4.0 ± 2.2 Gy) and an 18.5 ± 7.3% (2.7 ± 1.4 Gy) reduction in the bowel D_0.5cc dose for 2 mm and 3 mm PTV margins, respectively. The target dose (GTV V_{35 Gy}) was on average 100.0 ± 0.1% (99.6 - 100%), 99.6 ± 1.0% (97.2 - 100%), and 99.0 ± 1.4% (95.0 - 100%), among all fractions for the 5 mm, 3 mm, and 2 mm PTV margins on the adaptive plans when accounting for intra-fraction motion, respectively.

Conclusion

A 2 mm PTV margin achieved a minimum of 95% GTV coverage while reducing the dose to the bowel for all patients.

Adaptive margins for online adaptive radiotherapy

Objective. In online adaptive radiotherapy a new plan is generated every fraction based on the organ and clinical target volume (CTV) delineations of that fraction. This allows for a planning target volume margin that does not need to be constant over the whole course of treatment, as is the case in conventional radiotherapy. This work aims to introduce an approach to update the margins each fraction based on the per-patient treatment history and explore the potential benefits of such adaptive margins. Approach. We introduce a novel methodology to implement adaptive margins, isotropic and anisotropic, during a treatment course based on the accumulated dose to the CTV. We then simulate treatment histories for treatments delivered in up to 20 fractions using various choices for the standard deviations of the systematic and random errors and homogeneous and inhomogeneous dose distributions. The treatment-averaged adaptive margin was compared to standard constant margins. The change in the minimum dose delivered to the CTV was compared on a patient and a population level. All simulations were performed within the van Herk approach and its known limitations. Main results. The population mean treatment-averaged margins are down to 70% and 55% of the corresponding necessary constant margins for the isotropic and anisotropic approach. The reduction increases with longer fractionation schemes and an inhomogeneous target dose distribution. Most of the benefit can be attributed to the elimination of the effective systematic error over the course of treatment. Interpatient differences in treatment-averaged margins were largest for the isotropic margins. For the 10% of patients that would receive a lower than prescribed dose to the CTV this minimum dose to the CTV is increased using the adaptive margin approaches. Significance. Adaptive margins can allow to reduce margins in most patients without compromising patients with greater than average target motion.

Evaluation of internal margins for prostate for step and shoot intensity-modulated radiation therapy and volumetric modulated arc therapy using different margin formulas

PURPOSE

This feasibility study evaluated the intra-fractional prostate motion using an ultrasound image-guided system during step and shoot intensity-modulated radiation therapy (SS-IMRT) and volumetric modulated arc therapy (VMAT). Moreover, the internal margins (IMs) using different margin formulas were calculated.

METHODS

Fourteen consecutive patients with prostate cancer who underwent SS-IMRT (n = 5) or VMAT (n = 9) between March 2019 and April 2020 were considered. The intra-fractional prostate motion was observed in the superior-inferior (SI), anterior-posterior (AP), and left-right (LR) directions. The displacement of the prostate was defined as the displacement from the initial position at the scanning start time, which was evaluated using the mean ± standard deviation (SD). IMs were calculated using the van Herk and restricted maximum likelihood (REML) formulas for SS-IMRT and VMAT.

RESULTS

For SS-IMRT, the maximum displacements of the prostate motion were 0.17 ± 0.18, 0.56 ± 0.86, and 0.18 ± 0.59 mm in the SI, AP, and LR directions, respectively. For VMAT, the maximum displacements of the prostate motion were 0.19 ± 0.64, 0.22 ± 0.35, and 0.14 ± 0.37 mm in the SI, AP, and LR directions, respectively. The IMs obtained for SS-IMRT and VMAT were within 2.3 mm and 1.2 mm using the van Herk formula and within 1.2 mm and 0.8 mm using the REML formula.

CONCLUSIONS

This feasibility study confirmed that intra-fractional prostate motion was observed with SS-IMRT and VMAT using different margin formulas. The IMs should be determined according to each irradiation technique using the REML margin.

Minimum non-isotropic and asymmetric margins for taking into account intrafraction prostate motion during moderately hypofractionated radiotherapy

PURPOSE

To investigate the impact on dose distribution of intrafraction motion during moderate hypofractionated prostate cancer treatments and to estimate minimum non-isotropic and asymmetric (NI-AS) treatment margins taking motion into account.

METHODS

Prostate intrafraction 3D displacements were recorded with a transperineal ultrasound probe and were evaluated in 46 prostate cancer patients (876 fractions) treated by moderate hypofractionated radiation therapy (60 Gy in 20 fractions). For 18 patients (346 fractions), treatment plans were recomputed increasing CTV-to-PTV margins from 0 to 6 mm with an auto-planning optimization algorithm. Dose distribution was estimated using the voxel shifting method by displacing CTV structure according to the retrieved movements. Time-dependent margins were finally calculated using both van Herk's formula and the voxel shifting method.

RESULTS

Mean intrafraction prostate displacements observed were -0.02 ± 0.52 mm, 0.27 ± 0.78 mm and -0.43 ± 1.06 mm in left-right, supero-inferior and antero-posterior directions, respectively. The CTV dosimetric coverage increased with increased CTV-to-PTV margins but it decreased with time. Hence using van Herk's formula, after 7 min of treatment, a margin of 0.4 and 0.5 mm was needed in left and right, 1.5 and 0.7 mm in inferior and superior and 1.1 and 3.2 mm in anterior and posterior directions, respectively. Conversely, using the voxel shifting method, a margin of 0 mm was needed in left-right, 2 mm in superior, 3 mm in inferior and anterior and 5 mm in posterior directions, respectively. With this latter NI-AS margin strategy, the dosimetric target coverage was equivalent to the one obtained with a 5 mm homogeneous margin.

CONCLUSIONS

NI-AS margins would be required to optimally take into account intrafraction motion.

Analytical setup margin for spinal stereotactic body radiotherapy based on measured errors

Background

No consensus currently exists about the correct margin size to use for spinal SBRT. Margins have been proposed to account for various errors individually, but not with all errors combined to result in a single margin value. The purpose of this work was to determine a setup margin for five-fraction spinal SBRT based on known errors during radiotherapy to achieve at least 90% coverage of the clinical target volume with the prescription dose for at least 90% of patients and not exceed a 30 Gy point dose or 23 Gy to 10% of the spinal cord subvolume.

Methods

The random and systematic error components of intrafraction motion, residual setup error, and end-to-end system accuracy were measured. The patient’s surface displacement was measured to quantify intrafraction motion, the residual setup error was quantified by re-registering accepted daily cone beam computed tomography setup images, and the displacement between measured and planned dose profiles in a phantom quantified the end-to-end system accuracy. These errors and parameters were used to identify the minimum acceptable margin size. The margin recommendation was validated by assessing dose delivery across 140 simulated patient plans suffering from various random shifts representative of the measured errors.

Results

The errors were quantified in three dimensions and the analytical margin generated was 2.4 mm. With this margin applied in the superior/inferior direction only, at least 90% of the CTV was covered with the prescription dose for 96% of the 140 patients simulated with minimal negative effect on the spinal cord dose levels.

Conclusions

The findings of this work support that a 2.4 mm margin applied in the superior/inferior direction can achieve at least 90% coverage of the CTV for at least 90% of dual-arc volumetric modulated arc therapy spinal SBRT patients in the presence of errors when immobilized with vacuum bags.

Intrafractional motion models based on principal components in Magnetic Resonance guided prostate radiotherapy

Background and purpose

Devices that combine an MR-scanner with a Linac for radiotherapy, referred to as MR-Linac systems, introduce the possibility to acquire high resolution images prior and during treatment. Hence, there is a possibility to acquire individualised learning sets for motion models for each fraction and the construction of intrafractional motion models. We investigated the feasibility for a principal component analysis (PCA) based, intrafractional motion model of the male pelvic region.

Materials and methods

4D-scans of nine healthy male volunteers were utilized, FOV covering the entire pelvic region including prostate, bladder and rectum with manual segmentation of each organ at each time frame. Deformable image registration with an optical flow algorithm was performed for each subject with the first time frame as reference. PCA was performed on a subset of the resulting displacement vector fields to construct individualised motion models evaluated on the remaining fields.

Results

The registration algorithm produced accurate registration result, in general DICE overlap >0.95 across all time frames. Cumulative variance of the eigen values from the PCA showed that 50% or more of the motion is explained in the first component for all subjects. However, the size and direction for the components differed between subjects. Adding more than two components did not improve the accuracy significantly and the model was able to explain motion down to about 1 mm.

Conclusions

An individualised intrafractional male pelvic motion model is feasible. Geometric accuracy was about 1 mm based on 1–2 principal components.

Image-guided Radiotherapy to Manage Respiratory Motion: Lung and Liver

Organ motion as a result of respiratory and cardiac motion poses significant challenges for the accurate delivery of radiotherapy to both the thorax and the upper abdomen. Modern imaging techniques during radiotherapy simulation and delivery now permit better quantification of organ motion, which in turn reduces tumour and organ at risk position uncertainty. These imaging advances, coupled with respiratory correlated radiotherapy delivery techniques, have led to the development of a range of approaches to manage respiratory motion. This review summarises the key strategies of image-guided respiratory motion management with a focus on lung and liver radiotherapy.

Improvement of kilovoltage intrafraction monitoring accuracy through gantry angles selection

Kilovoltage intrafraction monitoring (KIM) is a method allowing to precisely infer the tumour trajectory based on cone beam computed tomography (CBCT) 2D-projections. However, its accuracy is deteriorated in the case of highly mobile tumours involving hysteresis. A first adaptation of KIM consisting of a prior amplitude based binning step has been developed in order to minimize the errors of the original model (phase-KIM). In this work, we propose enhanced methods (KIM_{sub-arc optim}and phase-KIM_{sub-arc optim}) to improve the accuracy of KIM and phase-KIM which relies on the selection of the optimal starting CBCT gantry angle. Aiming at demonstrating the interest of our approach, we carried out a simulation study and an experimental study: we compared the accuracy of the conventional versus sub-arc optim methods on simulated realistic tumour motions with amplitudes ranging from 5 to 30 mm in 1 mm increments. The same approach was performed using a lung dynamic phantom generating a 30 mm amplitude sinusoidal motion. The results show that for in-silico simulated motions of 10, 20 and 30 mm amplitude, the three-dimensional root mean square error (3D-RMSE) can be reduced by 0.67 mm, 0.91 mm, 0.94 mm and 0.18 mm, 0.25 mm, 0.28 mm using KIM_{sub-arc optim}and phase-KIM_{sub-arc optim}respectively. Considering all in-silico simulated trajectories, the percentage of errors larger than 1 mm decreases from 21.9% down to 1.6% for KIM (p < 0.001) and from 6.6% down to 1.2% for phase-KIM (p < 0.001). Experimentally, the 3D-RMSE is lowered by 0.5732 mm for KIM and by 0.1 mm for phase-KIM. The percentage of errors larger than 1 mm falls from 39.7% down to 18.5% for KIM and from 23.2% down to 11.1% for phase-KIM. In conclusion, our method efficiently anticipates CBCT gantry angles associated with a significantly better accuracy by using KIM and phase-KIM.

Impact of a vacuum cushion on intrafraction motion during online adaptive MR-guided SBRT for pelvic and para-aortic lymph node oligometastases

BACKGROUND AND PURPOSE

Vacuum cushion immobilization is commonly used during stereotactic body radiotherapy (SBRT) to reduce intrafraction motion. We investigated target and bony anatomy intrafraction motion (translations and rotations) during online adaptive SBRT on an MR-linac for pelvic/para-aortic lymph node metastases with and without vacuum cushion.

MATERIALS AND METHODS

Thirty-nine patients underwent 5x7 Gy SBRT on a 1.5T MR-linac, 19 patients were treated with vacuum cushion, 19 without and 1 patient sequentially with and without. Intrafraction motion was calculated for target lymph nodes (GTVs) and nearby bony anatomy, for three time intervals (pre-position verification (PV), pre-post, PV-post, relating to the online MRI scans) per treatment fraction.

RESULTS

Vacuum cushion immobilization significantly reduced anterior-posterior translations for the pre-PV and pre-post intervals, for bony anatomy and pre-post interval for GTV (p < 0.05). Mean GTV intrafraction motion reduction in posterior direction was 0.7 mm (95% confidence interval 0.3-1.1 mm) for pre-post interval (mean time = 32 min). Shifts in other directions were not significantly reduced. More motion occurred in pre-PV interval than in PV-post interval (mean time = 16 min for both); vacuum cushion immobilization did not reduce intrafraction motion during the beam-on period.

CONCLUSION

A vacuum cushion reduces GTV and bony anatomy intrafraction motion in posterior direction during pelvic/para-aortic lymph node SBRT. This motion reduction was found for the first 16 min per session. For single targets this motion can be corrected for directly with an MR-linac. Intrafraction motion was not reduced during the second half of the session, the period of radiotherapy delivery on an MR-linac. Vacuum cushion immobilization may not be necessary for patients with single lymph node oligometastases undergoing SBRT on an MR-linac.

Estimating PTV Margins in Head and Neck Stereotactic Ablative Radiation Therapy (SABR) Through Target Site Analysis of Positioning and Intrafractional Accuracy

PURPOSE

Recurrent or previously irradiated head and neck cancers (HNC) are therapeutically challenging and may benefit from high-dose, highly accurate radiation techniques, such as stereotactic ablative radiation therapy (SABR). Here, we compare set-up and positioning accuracy across HNC subsites to further optimize the treatment process and planning target volume (PTV) margin recommendations for head and neck SABR.

METHODS AND MATERIALS

We prospectively collected data on 405 treatment fractions across 79 patients treated with SABR for recurrent/previously irradiated HNC. First, interfractional error was determined by comparing ExacTrac x-ray to the treatment plan. Patients were then shifted and residual error was measured with repeat x-ray. Next, cone beam computed tomography (CBCT) was compared with ExacTrac for positioning agreement, and final shifts were applied. Lastly, intrafractional error was measured with x-ray before each arc. Results were stratified by treatment site into skull base, neck/parotid, and mucosal.

RESULTS

Most patients (66.7%) were treated to 45 Gy in 5 fractions (range, 21-47.5 Gy in 3-5 fractions). The initial mean ± standard deviation interfractional errors were -0.2 ± 1.4 mm (anteroposterior), 0.2 ± 1.8 mm (craniocaudal), and -0.1 ± 1.7 mm (left-right). Interfractional 3-dimensional vector error was 2.48 ± 1.44, with skull base significantly lower than other sites (2.22 vs 2.77; P = .0016). All interfractional errors were corrected to within 1.3 mm and 1.8°. CBCT agreed with ExacTrac to within 3.6 mm and 3.4°. CBCT disagreements and intrafractional errors of >1 mm or >1° occurred at significantly lower rates in skull base sites (CBCT: 16.4% vs 50.0% neck, 52.0% mucosal, P < .0001; intrafractional: 22.0% vs 48.7% all others, P < .0001). Final PTVs were 1.5 mm (skull base), 2.0 mm (neck/parotid), and 1.8 mm (mucosal).

CONCLUSIONS

Head and neck SABR PTV margins should be optimized by target site. PTV margins of 1.5 to 2 mm may be sufficient in the skull base, whereas 2 to 2.5 mm may be necessary for neck and mucosal targets. When using ExacTrac, skull base sites show significantly fewer uncertainties throughout the treatment process, but neck/mucosal targets may require the addition of CBCT to account for positioning errors and internal organ motion.

A study of nonuniform CTV to PTV margin expansion incorporating both rotational and translational uncertainties

PURPOSE

In this work, we implemented a method to obtain a nonuniform clinical target volume (CTV) to planning target volume (PTV) margin caused by both rotational and translational uncertainties and evaluated it in the treatment planning system (TPS).

MATERIALS AND METHOD

Based on a previously published statistical model, the relationship between a target margin and the distance d (from isocenter to target point), setup uncertainties, and significance level was established. For a single CTV, it can be thought as a combination of many small volume elements or target points. The margin of each point could be obtained using the suggested statistical model. The whole nonuniform CTV-PTV margin was determined by the union of all possible margins of the CTV boundary points. This method was implemented in the Pinnacle³ treatment planning system and compared with uniform margin algorithm. Ten vertebral metastases targets and multiple brain metastases targets were chosen for evaluation.

RESULTS

The combined CTV-PTV margin as a function of d for various initial translational margin and rotational uncertainties was calculated. The combined margin increases as d, rotational uncertainties and translational margin increase. For the same rotational uncertainty, a smaller initial translational margin requires a larger rotational margin to compensate for the rotational error. Compared with the uniform margin algorithm, the advantage of this method is that it could minimize the PTVs volume for given CTVs to obtain same significance level. Using vertebral metastases targets and multiple brain metastases targets, a series of volume difference was obtained for various translational margins and rotational uncertainties. The volume difference of PTV could be more than 17% when translational margin is 2 mm and rotational uncertainty is 1.4°.

CONCLUSION

Nonuniform margin algorithm could avoid excessive compensation for the CTV boundary points near isocenter. This method could be used for clinical margin determination and might be useful for the protection of risk organs.

Real-time intrafraction motion monitoring in external beam radiotherapy

Radiotherapy (RT) aims to deliver a spatially conformal dose of radiation to tumours while maximizing the dose sparing to healthy tissues. However, the internal patient anatomy is constantly moving due to respiratory, cardiac, gastrointestinal and urinary activity. The long term goal of the RT community to 'see what we treat, as we treat' and to act on this information instantaneously has resulted in rapid technological innovation. Specialized treatment machines, such as robotic or gimbal-steered linear accelerators (linac) with in-room imaging suites, have been developed specifically for real-time treatment adaptation. Additional equipment, such as stereoscopic kilovoltage (kV) imaging, ultrasound transducers and electromagnetic transponders, has been developed for intrafraction motion monitoring on conventional linacs. Magnetic resonance imaging (MRI) has been integrated with cobalt treatment units and more recently with linacs. In addition to hardware innovation, software development has played a substantial role in the development of motion monitoring methods based on respiratory motion surrogates and planar kV or Megavoltage (MV) imaging that is available on standard equipped linacs. In this paper, we review and compare the different intrafraction motion monitoring methods proposed in the literature and demonstrated in real-time on clinical data as well as their possible future developments. We then discuss general considerations on validation and quality assurance for clinical implementation. Besides photon RT, particle therapy is increasingly used to treat moving targets. However, transferring motion monitoring technologies from linacs to particle beam lines presents substantial challenges. Lessons learned from the implementation of real-time intrafraction monitoring for photon RT will be used as a basis to discuss the implementation of these methods for particle RT.

A novel CBCT-based method for derivation of CTV-PTV margins for prostate and pelvic lymph nodes treated with stereotactic ablative radiotherapy

BACKGROUND

Traditional CTV-PTV margin recipes are not generally applicable in the situation of stereotactic ablative radiotherapy (SABR) treatments of multiple target volumes with a single isocentre. In this work, we present a novel geometric method of margin derivation based on CBCT-derived anatomical data.

METHODS

Twenty patients with high-risk localized prostate cancer were selected for retrospective review. Individual volumes of interest (prostate, prostate and seminal vesicles and pelvic lymph nodes) were delineated on five representative CBCTs and registered to the planning CT using two registration protocols: bone match or prostate-based soft tissue match. Margins were incrementally expanded around composite CTV structures until 95% overlap was achieved.

RESULTS

CTV-PTV margins of 5.2, 6.5 and 7.6 mm were required for prostate, prostate and seminal vesicles and pelvic lymph nodes respectively using a prostate matching protocol. For the prostate and seminal vesicle structures, margins calculated using our method displayed good agreement with a conventional margin recipe (within ±1.0 mm).

CONCLUSIONS

We have presented an alternative method of CTV-PTV margin derivation that is applicable to SABR treatments with more than one isocentric target. These results have informed an institutional trial of prostate and pelvic nodal SABR in men with high-risk localized prostate cancer.

Positional Accuracy of Treating Multiple Versus Single Vertebral Metastases With Stereotactic Body Radiotherapy

The aim of this study is to determine whether stereotactic body radiotherapy for multiple vertebral metastases treated with a single isocenter results in greater intrafraction errors than stereotactic body radiotherapy for single vertebral metastases and to determine whether the currently used spinal cord planning organ at risk volume and planning target volume margins are appropriate. Intrafraction errors were assessed for 65 stereotactic body radiotherapy treatments for vertebral metastases. Cone beam computed tomography images were acquired before, during, and after treatment for each fraction. Residual translational and rotational errors in patient positioning were recorded and planning organ at risk volume and planning target volume margins were calculated in each direction using this information. The mean translational residual errors were smaller for single (0.4 (0.4) mm) than for multiple vertebral metastases (0.5 (0.7) mm; P = .0019). The mean rotational residual errors were similar for single (0.3° (0.3°) and multiple vertebral metastases (0.3° (0.3°); P = .862). The maximum calculated planning organ at risk volume margin in any direction was 0.83 mm for single and 1.22 for multiple vertebral metastases. The maximum calculated planning target volume margin in any direction was 1.4 mm for single and 1.9 mm for multiple vertebral metastases. Intrafraction errors were small for both single and multiple vertebral metastases, indicating that our strategy for patient immobilization and repositioning is robust. Calculated planning organ at risk volume and planning target volume margins were smaller than our clinically employed margins, indicating that our clinical margins are appropriate.

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

PURPOSE

The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy.

METHODS

Balanced data according to the one-factor random effect model were assumed.

RESULTS

Analysis-of-variance (anova)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The anova-based estimation can be extended to a multifactor model considering multiple causes of setup errors (e.g., interpatient, interfraction, and intrafraction).

CONCLUSIONS

Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.