Modelling the dosimetric consequences of organ motion at CT imaging on radiotherapy treatment planning

Assessment of intrafractional prostate motion and its dosimetric impact in MRI-guided online adaptive radiotherapy with gating

PURPOSE

This study aimed to evaluate the intrafractional prostate motion captured during gated magnetic resonance imaging (MRI)-guided online adaptive radiotherapy for prostate cancer and analyze its impact on the delivered dose as well as the effect of gating.

METHODS

Sagittal 2D cine-MRI scans were acquired at 4 Hz during treatment at a ViewRay MRIdian (ViewRay Inc., Oakwood Village, OH, USA) MR linac. Prostate shifts in anterior-posterior (AP) and superior-inferior (SI) directions were extracted separately. Using the static dose cloud approximation, the planned fractional dose was shifted according to the 2D gated motion (residual motion in gating window) to estimate the delivered dose by superimposing and averaging the shifted dose volumes. The dose of a hypothetical non-gated delivery was reconstructed similarly using the non-gated motion. For the clinical target volume (CTV), rectum, and bladder, dose-volume histogram parameters of the planned and reconstructed doses were compared.

RESULTS

In total, 174 fractions (15.7 h of cine-MRI) from 10 patients were evaluated. The average (±1 σ) non-gated prostate motion was 0.6 ± 1.0 mm in the AP and 0.0 ± 0.6 mm in the SI direction with respect to the centroid position of the gating boundary. 95% of the shifts were within [-3.5, 2.7] mm in the AP and [-2.9, 3.2] mm in the SI direction. For the gated treatment and averaged over all fractions, CTV D_98% decreased by less than 2% for all patients. The rectum and the bladder D_2% increased by less than 3% and 0.5%, respectively. Doses reconstructed for gated and non-gated delivery were similar for most fractions.

CONCLUSION

A pipeline for extraction of prostate motion during gated MRI-guided radiotherapy based on 2D cine-MRI was implemented. The 2D motion data enabled an approximate estimation of the delivered dose. For the majority of fractions, the benefit of gating was negligible, and clinical dosimetric constraints were met, indicating safety of the currently adopted gated MRI-guided treatment workflow.

Current state and future applications of radiological image guidance for particle therapy

In this review paper, we first give a short overview of radiological image guidance in photon radiotherapy, placing emphasis on the fact that linac based radiotherapy has outpaced particle therapy in the adoption of volumetric image guidance. While cone beam computed tomography (CBCT) has been an established technique in linac treatment rooms for almost two decades, the widespread adoption of volumetric image guidance in particle therapy, whether by means of CBCT or in-room CT imaging, is recent. This lag may be attributable to the bespoke nature and lower number of particle therapy installations, as well as the differences in geometry between those installations and linac treatment rooms. In addition, for particle therapy the so called shift invariance of the dose distribution rarely applies. An overview of the different volumetric image guidance solutions found at modern particle therapy facilities is provided, covering gantry, nozzle, C-arm, and couch-mounted CBCT as well different in-room CT configurations. A summary of the use of in-room volumetric imaging data beyond anatomy-based positioning is also presented as well as the necessary corrections to CBCT images for accurate water equivalent thickness calculation. Finally, the use of non-ionizing imaging modalities is discussed.

Tumor delineation: The weakest link in the search for accuracy in radiotherapy

Radiotherapy is one of the most effective modalities for the treatment of cancer. However, there is a high degree of uncertainty associated with the target volume of most cancer sites. The sources of these uncertainties include, but are not limited to, the motion of the target, patient setup errors, patient movements, and the delineation of the target volume. Recently, many imaging techniques have been introduced to track the motion of tumors. The treatment delivery using these techniques is collectively called image-guided radiation therapy (IGRT). Ultimately, IGRT is only as good as the accuracy with which the target is known. There are reports of interobserver variability in tumor delineation across anatomical sites, but the widest ranges of variations have been reported for the delineation of head and neck tumors as well as esophageal and lung carcinomas. Significant interobserver variability in target delineation can be attributed to many factors including the impact of imaging and the influence of the observer (specialty, training, and personal bias). The visibility of the target can be greatly improved with the use of multimodality imaging by co-registration of CT with a second modality such as magnetic resonance imaging (MRI) and/or positron emission tomography. Also, continuous education, training, and cross-collaboration of the radiation oncologist with other specialties can reduce the degree of variability in tumor delineation.

Influence of increased target dose inhomogeneity on margins for breathing motion compensation in conformal stereotactic body radiotherapy

Background

Breathing motion should be considered for stereotactic body radiotherapy (SBRT) of lung tumors. Four-dimensional computer tomography (4D-CT) offers detailed information of tumor motion. The aim of this work is to evaluate the influence of inhomogeneous dose distributions in the presence of breathing induced target motion and to calculate margins for motion compensation.

Methods

Based on 4D-CT examinations, the probability density function of pulmonary tumors was generated for ten patients. The time-accumulated dose to the tumor was calculated using one-dimensional (1D) convolution simulations of a 'static' dose distribution and target probability density function (PDF). In analogy to stereotactic body radiotherapy (SBRT), different degrees of dose inhomogeneity were allowed in the target volume: minimum doses of 100% were prescribed to the edge of the target and maximum doses varied between 102% (P102) and 150% (P150). The dose loss due to breathing motion was quantified and margins were added until this loss was completely compensated.

Results

With the time-weighted mean tumor position as the isocentre, a close correlation with a quadratic relationship between the standard deviation of the PDF and the margin size was observed. Increased dose inhomogeneity in the target volume required smaller margins for motion compensation: margins of 2.5 mm, 2.4 mm and 1.3 mm were sufficient for compensation of 11.5 mm motion range and standard deviation of 3.9 mm in P105, P125 and P150, respectively. This effect of smaller margins for increased dose inhomogeneity was observed for all patients. Optimal sparing of the organ-at-risk surrounding the target was achieved for dose prescriptions P105 to P118. The internal target volume concept over-compensated breathing motion with higher than planned doses to the target and increased doses to the surrounding normal tissue.

Conclusion

Treatment planning with inhomogeneous dose distributions in the target volume required smaller margins for compensation of breathing induced target motion with the consequence of lower doses to the surrounding organs-at-risk.

Target coverage in image-guided stereotactic body radiotherapy of liver tumors

PURPOSE

To determine the effect of image-guided procedures (with computed tomography [CT] and electronic portal images before each treatment fraction) on target coverage in stereotactic body radiotherapy for liver patients using a stereotactic body frame (SBF) and abdominal compression. CT guidance was used to correct for day-to-day variations in the tumor's mean position in the SBF.

METHODS AND MATERIALS

By retrospectively evaluating 57 treatment sessions, tumor coverage, as obtained with the clinically applied CT-guided protocol, was compared with that of alternative procedures. The internal target volume-plus (ITV(+)) was introduced to explicitly include uncertainties in tumor delineations resulting from CT-imaging artifacts caused by residual respiratory motion. Tumor coverage was defined as the volume overlap of the ITV(+), derived from a tumor delineated in a treatment CT scan, and the planning target volume. Patient stability in the SBF, after acquisition of the treatment CT scan, was evaluated by measuring the displacement of the bony anatomy in the electronic portal images relative to CT.

RESULTS

Application of our clinical protocol (with setup corrections following from manual measurements of the distances between the contours of the planning target volume and the daily clinical target volume in three orthogonal planes, multiple two-dimensional) increased the frequency of nearly full (> or = 99%) ITV(+) coverage to 77% compared with 63% without setup correction. An automated three-dimensional method further improved the frequency to 96%. Patient displacements in the SBF were generally small (< or = 2 mm, 1 standard deviation), but large craniocaudal displacements (maximal 7.2 mm) were occasionally observed.

CONCLUSION

Daily, CT-assisted patient setup may substantially improve tumor coverage, especially with the automated three-dimensional procedure. In the present treatment design, patient stability in the SBF should be verified with portal imaging.

The use of spatial dose gradients and probability density function to evaluate the effect of internal organ motion for prostate IMRT treatment planning

The aim of this study is to investigate the effects of internal organ motion on IMRT treatment planning of prostate patients using a spatial dose gradient and probability density function. Spatial dose distributions were generated from a Pinnacle3 planning system using a co-planar, five-field intensity modulated radiation therapy (IMRT) technique. Five plans were created for each patient using equally spaced beams but shifting the angular displacement of the beam by 15 degree increments. Dose profiles taken through the isocentre in anterior-posterior (A-P), right-left (R-L) and superior-inferior (S-I) directions for IMRT plans were analysed by exporting RTOG file data from Pinnacle. The convolution of the 'static' dose distribution D0(x, y, z) and probability density function (PDF), denoted as P(x, y, z), was used to analyse the combined effect of repositioning error and internal organ motion. Organ motion leads to an enlarged beam penumbra. The amount of percentage mean dose deviation (PMDD) depends on the dose gradient and organ motion probability density function. Organ motion dose sensitivity was defined by the rate of change in PMDD with standard deviation of motion PDF and was found to increase with the maximum dose gradient in anterior, posterior, left and right directions. Due to common inferior and superior field borders of the field segments, the sharpest dose gradient will occur in the inferior or both superior and inferior penumbrae. Thus, prostate motion in the S-I direction produces the highest dose difference. The PMDD is within 2.5% when standard deviation is less than 5 mm, but the PMDD is over 2.5% in the inferior direction when standard deviation is higher than 5 mm in the inferior direction. Verification of prostate organ motion in the inferior directions is essential. The margin of the planning target volume (PTV) significantly impacts on the confidence of tumour control probability (TCP) and level of normal tissue complication probability (NTCP). Smaller margins help to reduce the dose to normal tissues, but may compromise the dose coverage of the PTV. Lower rectal NTCP can be achieved by either a smaller margin or a steeper dose gradient between PTV and rectum. With the same DVH control points, the rectum has lower complication in the seven-beam technique used in this study because of the steeper dose gradient between the target volume and rectum. The relationship between dose gradient and rectal complication can be used to evaluate IMRT treatment planning. The dose gradient analysis is a powerful tool to improve IMRT treatment plans and can be used for QA checking of treatment plans for prostate patients.

Inverse plan optimization accounting for random geometric uncertainties with a multiple instance geometry approximation (MIGA)

Radiotherapy treatment plans that are optimized to be highly conformal based on a static patient geometry can be degraded by setup errors and/or intratreatment motion, particularly for IMRT plans. To achieve improved plans in the face of geometrical uncertainties, direct simulation of multiple instances of the patient anatomy (to account for setup and/or motion uncertainties) is used within the inverse planning process. This multiple instance geometry approximation (MIGA) method uses two or more instances of the patient anatomy and optimizes a single beam arrangement for all instances concurrently. Each anatomical instance can represent expected extremes or a weighted distribution of geometries. The current implementation supports mapping between instances that include distortions, but this report is limited to the use of rigid body translations/ rotations. For inverse planning, the method uses beamlet dose calculations for each instance, with the resulting doses combined using a weighted sum of the results for the multiple instances. Beamlet intensities are then optimized using the inverse planning system based on the cost for the composite dose distribution. MIGA can simulate various types of geometrical uncertainties, including random setup error and intratreatment motion. A limited number of instances are necessary to simulate Gaussian-distributed errors. IMRT plans optimized using MIGA show significantly less degradation in the face of geometrical errors, and are robust to the expected (simulated) motions. Results for a complex head/neck plan involving multiple target volumes and numerous normal structures are significantly improved when the MIGA method of inverse planning is used. Inverse planning using MIGA can lead to significant improvements over the use of simple PTV volume expansions for inclusion of geometrical uncertainties into inverse planning, since it can account for the correlated motions of the entire anatomical representation. The optimized plan results reflect the differing patient geometry situations which can be important near the surface or heterogeneities. For certain clinical situations, the MIGA optimization approach can correct for a significant part of the degradation of the plan caused by the setup uncertainties.

Dosimetrische Auswirkungen der Verwendung eines Rektumhüllen-Volumens für die Bestrahlungsplanung fluenzmodulierter Strahlentherapie von Prostatakrebs

The present study evaluated a hull-volume definition strategy for the planning organ at risk volume (PRV) for the rectum in the planning of radiotherapy of prostate cancer. The bounding volumes of rectum contours of 1 to 5 CT scans were compared on the basis of the rectum coverage probabilities for 5 patients. In addition, IMRT treatment plans were optimized using the rectum hull PRV5 of 5 CTs and each of the conventional rectum contours PRV1. The plans were compared on the basis of the organ doses caused by the individual organ motion. PRV5 allowed to cover the rectum with a probability of nearly 90% (PRV1 67%). Rectal wall dose showed a great variability for PRV1, while planned and treatment dose agreed well for PRV5 due to the improved geometric information which resulted in a better rectal sparing. In conclusion, the rectum hull-volume PRV5 is a well suited PRV for planning of IMRT dose distributions allowing dose escalation as well as rectal sparing.

Robust treatment planning for intensity modulated radiotherapy of prostate cancer based on coverage probabilities

BACKGROUND AND PURPOSE

To evaluate an optimization approach where coverage probabilities are incorporated into the optimization of intensity modulated radiotherapy (IMRT) to overcome the problem of margin definition in the case of overlapping planning target volume and organs at risk.

PATIENTS AND METHODS

IMRT plans were generated for three optimization approaches: based on a planning CT plus margin (A), on prostate and rectum contours from five pre-treatment CT plus margin (B), and on coverage probabilities (C). For approach (C), the probability of organ occupation was computed for each voxel from five pre-treatment CTs and the population distribution of systematic setup error and it was used as local weight in the costfunctions. Monte Carlo simulations of treatment courses were used to compute the probability distribution of prostate and rectal wall equivalent uniform dose (EUD).

RESULTS

Treatment simulations showed best and most robust results for prostate and rectal wall EUD within the population for (C). For (A) the rectal wall EUD was on average about 1.5 Gy greater than in (C), while the prostate EUD was lower than those from (C) for most of the patients for (B) (especially for those with great organ motion).

CONCLUSIONS

The incorporation of coverage probabilities as local weights allows for dose escalation as well as improved rectal sparing and results in a safer and more robust IMRT treatment.

Modelling the variation in rectal dose due to inter-fraction rectal wall deformation in external beam prostate treatments

Prostate radiotherapy inevitably deposits radiation dose in the rectal wall, and the dose delivered to prostate is limited by the expected rectal complications. Accurate evaluation of the rectal dose is non-trivial due to a number of factors. One of these is variation of the shape and position of the rectal wall (with respect to the clinical target volume (CTV)), which may differ daily from that taken during planning CT acquisition. This study uses data currently available in the literature on rectal wall motion to provide estimates of mean population rectal wall dose. The rectal wall geometry is characterized by a population mean radius of the rectum as well as inter-patient and inter-fraction standard deviations in rectum radius. The model is used to evaluate the range of inter-fraction and inter-patient rectal dose variations. The simulation of individual patients with full and empty rectum in the planning CT scan showed that large variations in rectal dose (>15 Gy) are possible. Mean calculated dose accounting for treatment and planning uncertainties in the rectal wall surface was calculated as well as the map of planning dose over/underpredictions. It was found that accuracy of planning dose is dependent on the CTV-PTV margin size with larger margins producing more accurate estimates. Over a patient population, the variation in rectal dose is reduced by increasing the number of pre-treatment CT scans.

EUD-based radiotherapy treatment plan evaluation: incorporating physical and Monte Carlo statistical dose uncertainties

The purpose of this work is to quantify the impact of dose uncertainty on radiobiologically based treatment plan evaluation. Dose uncertainties are divided into two categories: physical and statistical. Physical dose uncertainty is associated with the systematic and/or random errors incurred during treatment planning and/or delivery. The dose uncertainty associated with Monte Carlo calculated dose distributions is deemed statistical and noted as artificial with respect to the actual delivered dose. We will refer to all dose uncertainties that arise from either calculation or delivery as stochastic. Both physical and statistical dose uncertainties are considered at the intra- and inter-voxel levels. To account for voxel dose uncertainty, we calculate the mean survival fraction (SF) for the random dose deposition. Mathematically, the expression for the mean survival fraction is identical to that used by Niemierko (1997 Med. Phys. 24 103-10) in defining equivalent uniform dose (EUD). To distinguish between spatial and probabilistic dose variations, we define equivalent stochastic dose (ESD) as a voxel dose that gives the mean expected survival fraction for the randomly deposited dose. For a probability density function f(D), that represents the probabilistic voxel dose, SF(ESD) can be calculated by convolving SF(D) with f(D). In the case where the probability density function follows a Gaussian distribution, an analytic expression is derived for SF(ESD). The derived expression is verified using the Monte Carlo method and ESD values calculated with varied radiosensitivities for cases of 60 and 70 Gy at 2 Gy per fraction. The analytic expression is also extended to account for a multi-voxel dose distribution that incorporates a spatial dose heterogeneity. The results show that survival fraction increases with an increased dose uncertainty. This reduction depends on radiobiological parameters attributed to tissue and tumour. For tissue, ESD drops to 55% of the mean physical dose when the dose has a 10% intra- and inter-voxel dose uncertainty and inhomogeneity.

Dosimetric consequences of the application of off-line setup error correction protocols and a hull-volume definition strategy for intensity modulated radiotherapy of prostate cancer

PURPOSE

To evaluate the consequences of a planning volume definition based on multiple CTs and the application of off-line setup error correction for the treatment of prostate cancer with intensity-modulated radiotherapy (IMRT). Further, to compare various setup correction protocols (SCP) by their influence on the average dose distributions.

MATERIALS AND METHODS

A planning target volume (PTV) consisting of the bounding volume of prostate contours of five CTs (CTV_hull) plus an additional margin of 5mm and a virtual Rectum_hull volume (the solid bounding volume of the five corresponding rectum contours) are used for treatment planning. Simulations of treatment courses with the non-parametric bootstrap method allow to estimate the distribution of the expected equivalent uniform dose (EUD). The impact of off-line setup error correction protocols is evaluated based on estimated EUD distributions.

RESULTS

Off-line SCP allow to achieve the intended prostate and rectum EUD and a reliable coverage of the CTV despite the reduced margins. The EUD of the virtual hull volumes is a good estimate for the EUD of prostate and rectal wall.

CONCLUSION

Treatment planning based on Rectum_hull and CTV_hull plus setup margin as PTV in combination with SCP results in a robust and safe IMRT planning concept.

Limitations of a convolution method for modeling geometric uncertainties in radiation therapy. I. The effect of shift invariance

Convolution methods have been used to model the effect of geometric uncertainties on dose delivery in radiation therapy. Convolution assumes shift invariance of the dose distribution. Internal inhomogeneities and surface curvature lead to violations of this assumption. The magnitude of the error resulting from violation of shift invariance is not well documented. This issue is addressed by comparing dose distributions calculated using the Convolution method with dose distributions obtained by Direct Simulation. A comparison of conventional Static dose distributions was also made with Direct Simulation. This analysis was performed for phantom geometries and several clinical tumor sites. A modification to the Convolution method to correct for some of the inherent errors is proposed and tested using example phantoms and patients. We refer to this modified method as the Corrected Convolution. The average maximum dose error in the calculated volume (averaged over different beam arrangements in the various phantom examples) was 21% with the Static dose calculation, 9% with Convolution, and reduced to 5% with the Corrected Convolution. The average maximum dose error in the calculated volume (averaged over four clinical examples) was 9% for the Static method, 13% for Convolution, and 3% for Corrected Convolution. While Convolution can provide a superior estimate of the dose delivered when geometric uncertainties are present, the violation of shift invariance can result in substantial errors near the surface of the patient. The proposed Corrected Convolution modification reduces errors near the surface to 3% or less.

Limitations of a convolution method for modeling geometric uncertainties in radiation therapy. II. The effect of a finite number of fractions

Convolution methods can be used to model the effect of geometric uncertainties on the planned dose distribution in radiation therapy. This requires several assumptions, including that the patient is treated with an infinite number of fractions, each delivering an infinitesimally small dose. The error resulting from this assumption has not been thoroughly quantified. This is investigated by comparing dose distributions calculated using the Convolution method with the result of Stochastic simulations of the treatment. Additionally, the dose calculated using the conventional Static method, a Corrected Convolution method, and a Direct Simulation are compared to the Stochastic result. This analysis is performed for single beam, parallel opposed pair, and four-field box techniques in a cubic water phantom. Treatment plans for a simple and a complex idealized anatomy were similarly analyzed. The average maximum error using the Static method for a 30 fraction simulation for the three techniques in phantoms was 23%, 11% for Convolution, 10% for Corrected Convolution, and 10% for Direct Simulation. In the two anatomical examples, the mean error in tumor control probability for Static and Convolution methods was 7% and 2%, respectively, of the result with no uncertainty, and 35% and 9%, respectively, for normal tissue complication probabilities. Convolution provides superior estimates of the delivered dose when compared to the Static method. In the range of fractions used clinically, considerable dosimetric variations will exist solely because of the random nature of the geometric uncertainties. However, the effect of finite fractionation appears to have a greater impact on the dose distribution than plan evaluation parameters.

Quantifying the effect of intrafraction motion during breast IMRT planning and dose delivery

Respiratory motion during intensity modulated radiation therapy (IMRT) causes two types of problems. First, the clinical target volume (CTV) to planning target volume (PTV) margin needed to account for respiratory motion means that the lung and heart dose is higher than would occur in the absence of such motion. Second, because respiratory motion is not synchronized with multileaf collimator (MLC) motion, the delivered dose is not the same as the planned dose. The aims of this work were to evaluate these problems to determine (a) the effects of respiratory motion and setup error during breast IMRT treatment planning, (b) the effects of the interplay between respiratory motion and multileaf collimator (MLC) motion during breast IMRT delivery, and (c) the potential benefits of breast IMRT using breath-hold, respiratory gated, and 4D techniques. Seven early stage breast cancer patient data sets were planned for IMRT delivered with a dynamic MLC (DMLC). For each patient case, eight IMRT plans with varying respiratory motion magnitudes and setup errors (and hence CTV to PTV margins) were created. The effects of respiratory motion and setup error on the treatment plan were determined by comparing the eight dose distributions. For each fraction of these plans, the effect of the interplay between respiratory motion and MLC motion during IMRT delivery was simulated by superimposing the respiratory trace on the planned DMLC leaf motion, facilitating comparisons between the planned and expected dose distributions. When considering respiratory motion in the CTV-PTV expansion during breast IMRT planning, our results show that PTV dose heterogeneity increases with respiratory motion. Lung and heart doses also increase with respiratory motion. Due to the interplay between respiratory motion and MLC motion during IMRT delivery, the planned and expected dose distributions differ. This difference increases with respiratory motion. The expected dose varies from fraction to fraction. However, for the seven patients studied and respiratory trace used, for no breathing, shallow breathing, and normal breathing, there were no statistically significant differences between the planned and expected dose distributions. Thus, for breast IMRT, intrafraction motion degrades treatment plans predominantly by the necessary addition of a larger CTV to PTV margin than would be required in the absence of such motion. This motion can be limited by breath-hold, respiratory gated, or 4D techniques.

The effects of radiotherapy treatment uncertainties on the delivered dose distribution and tumour control probability

Uncertainty in the precise quantity of radiation dose delivered to tumours in external beam radiotherapy is present due to many factors, and can result in either spatially uniform (Gaussian) or spatially non-uniform dose errors. These dose errors are incorporated into the calculation of tumour control probability (TCP) and produce a distribution of possible TCP values over a population. We also study the effect of inter-patient cell sensitivity heterogeneity on the population distribution of patient TCPs. This study aims to investigate the relative importance of these three uncertainties (spatially uniform dose uncertainty, spatially non-uniform dose uncertainty, and inter-patient cell sensitivity heterogeneity) on the delivered dose and TCP distribution following a typical course of fractionated external beam radiotherapy. The dose distributions used for patient treatments are modelled in one dimension. Geometric positioning uncertainties during and before treatment are considered as shifts of a pre-calculated dose distribution. Following the simulation of a population of patients, distributions of dose across the patient population are used to calculate mean treatment dose, standard deviation in mean treatment dose, mean TCP, standard deviation in TCP, and TCP mode. These parameters are calculated with each of the three uncertainties included separately. The calculations show that the dose errors in the tumour volume are dominated by the spatially uniform component of dose uncertainty. This could be related to machine specific parameters, such as linear accelerator calibration. TCP calculation is affected dramatically by inter-patient variation in the cell sensitivity and to a lesser extent by the spatially uniform dose errors. The positioning errors with the 1.5 cm margins used cause dose uncertainty outside the tumour volume and have a small effect on mean treatment dose (in the tumour volume) and tumour control.