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Intra-fraction prostate displacement in radiotherapy estimated from pre- and post-treatment imaging of patients with implanted fiducial markers
Radiotherapy and Oncology 95 (2010) 191–197
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Intra-fraction prostate displacement in radiotherapy estimated from pre- and post-treatment imaging of patients with implanted fiducial markers Tomas Kron a,b,*, Jessica Thomas c, Chris Fox a, Ann Thompson d, Rebecca Owen d, Alan Herschtal e, Annette Haworth a,b, Keen-Hun Tai c,f, Farshad Foroudi c,f a e
Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Australia; b Applied Physics, RMIT University, Melbourne, Australia; c Radiation Oncology; d Radiation Therapy; and Biostatisitics and Clinical Trials, Peter MacCallum Cancer Centre, Melbourne, Australia; f Department of Pathology, University of Melbourne, Parkville, Australia
a r t i c l e
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Article history: Received 1 June 2009 Received in revised form 21 January 2010 Accepted 23 January 2010 Available online 26 February 2010 Keywords: Fiducial markers Image-guided radiation therapy Intra-fraction displacement Prostate cancer
a b s t r a c t Purpose: To determine intra-fraction displacement of the prostate gland from imaging pre- and postradiotherapy delivery of prostate cancer patients with three implanted fiducial markers. Methods and materials: Data were collected from 184 patients who had two orthogonal X-rays pre- and post-delivery on at least 20 occasions using a Varian On Board kV Imaging system. A total of 5778 image pairs covering time intervals between 3 and 30 min between pre- and post-imaging were evaluated for intra-fraction prostate displacement. Results: The mean three dimensional vector shift between images was 1.7 mm ranging from 0 to 25 mm. No preferential direction of displacement was found; however, there was an increase of prostate displacement with time between images. There was a large variation in typical shifts between patients (range 1 ± 1 to 6 ± 2 mm) with no apparent trends throughout the treatment course. Images acquired in the first five fractions of treatment could be used to predict displacement patterns for individual patients. Conclusion: Intra-fraction motion of the prostate gland appears to be a limiting factor when considering margins for radiotherapy. Given the variation between patients, a uniform set of margins for all patients may not be satisfactory when high target doses are to be delivered. Ó 2010 Elsevier Ireland Ltd. All rights reserved. Radiotherapy and Oncology 95 (2010) 191–197
Radiotherapy is an important treatment modality for prostate cancer. There appears to be a dose response relationship with higher doses resulting in better local control [1] and biochemical failure-free survival [2]. As the prostate is located between critical structures such as bladder and rectum, there is also an increased risk of normal tissue toxicity [3] and optimised treatment delivery with minimal margins appears to be essential for maximising complication free tumour control. Unfortunately, the prostate is a relatively mobile organ that can move substantially against the external contour of the patient and even internal bony anatomy. Both day-to-day variations in prostate location due to bladder and rectal filling have been reported as well as movement on a short-term basis over the time period of the radiation delivery itself [4]. Daily imaging of the target volume, a process usually referred to as image-guided radiation therapy (IGRT) [5,6] allows localisation of the target prior to every treatment fraction. This should facilitate a reduction in margins required to account for uncertainty in prostate position before treatment [7]. * Corresponding author. Address: Department of Physical Sciences, Peter MacCallum Cancer, St Andrews Place, Melbourne Victoria 3002, Australia. E-mail address: [email protected] (T. Kron). 0167-8140/$ - see front matter Ó 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.radonc.2010.01.010
The International Commission on Radiation Units and Measurements (ICRU) identifies in their report 62 [8] two major contributions to margins: 1. Internal margins take into account any variations in size, shape or location of an organ in relation to an internal reference point. Movement of a lung tumour or filling of the bladder are examples for this. 2. The set-up margin accounts then for any uncertainty in positioning this internal reference point at the correct position for treatment. Image guidance is mostly associated with reduction of the setup margin. However, by acquiring an image prior and post-radiotherapy, one can obtain an estimate of the minimum movement of the target organ during the delivery of radiation. Clearly, continuous three dimensional localisation of the target during treatment would be preferable. This can be achieved using electronic portalimaging movies (Nederveen et al.) [9], multiple fluoroscopy systems such as real time tumour tracking [10,11] or the Calypso system [12–14]. While less information can be gained by preand post-treatment localisation of the prostate, it is easy to do and interpret, allows verification of any pre-treatment patient
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repositioning and provides at least an estimate of displacement of the gland during treatment. The aim of the present study was to determine the difference in prostate location from pre- and post-treatment kV imaging of patients with implanted fiducial markers. Intra- and inter-patient variation in movement patterns was evaluated to predict the displacement pattern of a patient from the first five images. Methods Patient population and imaging sequence A total of 184 patients treated with radical external beam radiotherapy at Peter MacCallum Cancer Centre between March 2007 and November 2008 were included in the study. All patients were treated to 74 or 78 Gy using 3D conformal or intensity-modulated radiation therapy (approximately 20% of patients). The typical margin used in our centre is 10 mm with exception for the posterior direction where a margin of 7 mm is used. All patients had three fiducial gold markers (diameter 1 mm, length 5 mm) implanted in the prostate under transrectal ultrasound guidance a minimum of 1 week prior to simulation [15]. Prior to each treatment delivery, the patient was imaged using two orthogonal kV X-ray images (On board imaging, OBI, Varian Medical Systems, Palo Alto). The images were matched with reference to digitally reconstructed radiographs from a radiotherapy treatment planning system XiO (CMS Inc, St Louis, MI) or Eclipse (Varian Medical Systems, Palo Alto, CA) using the fiducial markers manual match. The Varian software displays reference and verification imaging for both exposures on the same screen and allows the user to move the images until the best match is achieved. The high effective atomic number of the gold seeds ensures that the fiducials are easily identifiable. The software and automatic couch movements are tested every morning using a test object. The residual uncertainty of position in the test object is less than 1 mm independent of the operator. The system provides the user with translational mismatches in three dimensions. Rotations of the patient were not checked. Any translational mismatch was corrected by moving the treatment couch with the patient to the desired location. As this can be performed from outside the treatment room, the additional time required is very small and after extensive testing of the system no verification of the correctness of the move is performed. A daily quality assurance programme verifies the correctness of the couch motion. A second set of two kV images was acquired for each treatment directly after completion of the radiation delivery. As any displacement of the patient had been corrected after the first imaging, any mismatch in the post-treatment image identifies a combination of the residual error after correcting the patient position and any displacement that occurred during the delivery. The process provides a value for the minimum displacement of the prostate throughout the treatment delivery as temporary excursions of the prostate throughout the fraction would not be identified. Data collection and evaluation All shifts and measured differences between image sets were recorded in a record and verify system (Impac MultiAccess, Elekta Stockholm). The system also records the times when the images were acquired. The time between the second kV images in each set was taken as time between images. Reports were created of the Impac database using Crystal Reports (Crystal Reports 11, Business Objects Software, San Jose) software. The reports were processed using in-house written software to combine all relevant information for all patients in a Microsoft
Access Database (Microsoft, Redmond, Washington) that allows easy access to the data. More information on the database is provided by Fox et al. [16]. On occasions, images were not recorded or additional images were taken. Only patients with at least 20 image pairs were included in the study. Image pairs that were less than 3 min or more than 30 min apart were also excluded as they were deemed to reflect other issues than motion of the prostate during treatment (e.g. patient off couch to void). In total 5778 image pairs or 97% of all images were included in the evaluation. The data were evaluated using the statistical software R version 2.7.2 (http://www.r-project.org/). The analysis included the three orthogonal distances, anterior/posterior (AP), superior/inferior (SI) and left/right (LR) recorded in millimetre increments. The total displacement, D, was determined as the vector of the three distances:
D¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi AP2 þ LR2 þ SI2
This can be used for the evaluation of the adequacy of margins. Without actually performing a dose calculation taking beam directions and properties into account, it is impossible to determine the dosimetric impact of the prostate moving into a particular direction. As such we scored if the clinical target volume (the prostate) would move out of the planning target volume (PTV) created using a given set of CTV to PTV margins. The resulting geographic miss [17] does not necessarily result in a significant underdose as the beam directions and penumbra are not taken into account.
Statistical methods The relationship between time between images and 3D displacement was assessed using linear-mixed effects models (random intercepts) that take into account the fact that the observations are grouped by patient. In the model time was considered as a continuous variable. Two models were considered: a straight line relationship and a quadratic relationship that includes a squared term for time between images. To assess the probability of the prostate having moved more than a specified amount (referred to hereafter as a displacement value) during a single fraction as a function of time between images, logistic regressions were used. Four displacement values were chosen: 3, 5, 7 and 10 mm. For each displacement value the data were dichotomised according to whether an observation was below or above the displacement value. A logistic regression was preformed on this binary data with time between images as the explanatory variable. The fitted probabilities from the four models were plotted.
Estimation of a margin component for intra-fraction prostate displacement The displacement of the prostate during treatment can be divided in random and systematic components. This allows the application of a formalism to determine margins based on the observed data following the work of van Herk and Remeijer [18,19]. The required margin to achieve 95% of dose coverage for 90% of patients given the measured intra-fraction displacement (MIFD) was determined as:
MIFD ¼ 2:5R þ 0:7r with R as the systematic component of the displacement and r the random one. This was performed for the three groups of image pairs defined for different times between the images.
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Prediction of displacement patterns in individual patients from the first five fractions Of particular interest is whether displacement patterns can be predicted for individual patients from images acquired in the first part of the treatment. As such we evaluated if the first five treatment fractions are representatives for the rest of the treatment. In the evaluation, the displacement patterns were divided into three groups: Small: AP standard deviation of displacement, LR standard deviation of displacement and SI standard deviation of displacement all less than 0.1 cm. Large: at least of one of the AP, LR and SI standard deviations greater than or equal to 0.2 cm. Medium: those not classified as either small or large.
Fig. 1. Displacement of the prostate as a function of time between pre- and posttreatment imaging. Shown are the means with upper and lower quartiles for the given time intervals with the straight line showing a linear regression (solid line) and the curve a quadratic fit to the data (dash/dot line).
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Results Evaluation of all images A total of 5778 image pairs were evaluated of 184 patients (median 33 image pairs per patient). Times <3 min and >30 min were excluded from the evaluation and are not shown. The most likely time between pre- and post-treatment image acquisition was 6 min which reflects the fact that most patients were treated with a five-field conformal treatment. Only 2.9% of patients experienced a time on the treatment couch between pre- and postimaging of 15 min or longer. The intra-fraction displacements were found to be generally small and only 4.7% and 0.4% are above 5 and 10 mm respectively. The mean displacement in AP, LR and SI directions was 0.04 ± 0.16 cm (1SD), 0.02 ± 0.11 cm, and 0.01 ± 0.15 cm, respectively. Only the dislocations in AP and SI direction were associated with each other (p < 0.0001). No association between any of the other directional movements was found. The 3D difference in the location of the prostate between preand post-treatment image is shown in Fig. 1 as a function of time between the images. The means for the given time intervals with upper and lower quartiles are shown. While there is a relatively large displacement after 3 min, there is an increase of the distance with time. The solid line in Fig. 1 represents a linear fit to all the data with time between images considered as a continuous variable. Based on the linear model the average displacement increased by 0.2 mm every 5 min with a 95% confidence interval of (0.16, 0.33). A quadratic function, which is also shown in Fig. 1, provides a better fit of the data with no indication that a maximum average displacement is reached after 30 min. No particular direction was found to dominate this change. The increase of displacement with time can also be seen in Fig. 2, which shows the three dimensional vector displacement for three different treatment duration groups. The characteristics for the three groups are given in Table 1. The number of large displacements is greater in the group of treatment times exceeding 9 min (statistically different to both other groups with p-values from non-parametric tests of a difference in distributions: 0.0131 vs. 6–9 min group, <0.0001 vs. <6 min group).
Fig. 2. Frequency of a displacement for three different time intervals between pre- and post-treatment imaging.
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Table 1 Characteristics of three groups of patients/images reflecting different times between pre- and post-treatment imaging. Group time interval (min)
Number of images (% total images)
Number of patients that contribute at least one image (% of patients)
<6 6–9 >9
2950 (51) 2089 (36) 739 (13)
180 (98) 184 (100) 184 (100)
Fig. 3 illustrates the effect of the increasing displacement on the probability of the CTV not being covered by the PTV resulting in a potential partial miss. Different margins are used to create different PTV sizes as shown in the figure. One can see that after 18 min there is a 10% probability that the prostate has moved by more than 5 mm. In total, 11% of patients have more than one fraction with a displacement greater than 7 mm while 1% of patients have more than one fraction with a displacement greater than 10 mm. Table 2 shows the component of a margin for the planning target volume to account for intra-fraction displacement. The data are given for the three groups with different times between the preand post-imaging as defined in Table 1. Evaluation of individual patients Different patients showed different patterns of displacement. This can be seen in Fig. 4 which shows the mean and standard
Fig. 4. Distribution of mean displacement and standard deviation of the prostate between pre- and post-treatment image for the 184 patients in the study. Shown is the displacement in the three cardinal directions.
deviation of the displacement for all patients in the three cardinal directions. In the AP and LR directions systematic differences between the medians and 0 were observed with an average of 0.3 mm posterior median displacement and 0.2 mm left median displacement for all patients. However, the majority of patients were found to have a mean within 2 mm of the target value indicating a small systematic error. As can be expected, the displacement in the lateral direction is the smallest. This is also true for the standard deviations from the mean for all patients. Fig. 3. Probability of prostate displacement larger than a given distance as a function of time.
Table 2 Margins calculated using the van Herk formalism based on the intra-fraction displacements identified for the three groups of patients identified in Table 1 with different times between the image pairs. Group time interval (min)
Dimension
Systematic error (cm)
Random uncertainty (cm)
van Herk margin (cm)
<6
AP LR SI AP LR SI AP LR SI
0.079 0.054 0.071 0.085 0.056 0.081 0.125 0.105 0.128
0.124 0.084 0.118 0.119 0.078 0.113 0.126 0.067 0.118
0.284 0.194 0.259 0.297 0.194 0.281 0.401 0.309 0.402
6–9
>9
Prediction of motion patterns from the first five fractions The displacement patterns of the prostate in the first five fractions were analysed and compared to the displacement observed in the remaining fractions. As not all patients had images for all fractions in the data base, there may have been circumstances where the first five image pairs do not reflect the first five fractions. However, in all patients, at least an additional 15 fractions were available for analysis of the remainder of the treatment course (typically more than 25 images were available as the median number of images per patient was 33). Fig. 5 shows how the first five fractions are associated with the remainder of the treatment for the three cardinal directions of displacement. The association was found to be moderate (Pearson’s correlation of 0.58, 0.73 and 0.60 for AP, LR and SI means respectively). We also saw a degree of bias when using the mean of the first five fractions to predict the mean of the remaining fractions, with the mean from the first five fractions tending to be more
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Table 3 Cross-classification between the displacement groups of fiducial markers as determined from the first five fractions and those seen in the whole treatment. Classification from entire treatment
Total
Small
Medium
Large
Classification from first five fractions Small Medium Large
27 (47%) 10 (11%) 0 (0%)
29 (50%) 70 (76%) 17 (50%)
2 (3%) 12 (13%) 17 (50%)
58 92 34
Total
37 (20%)
116 (63%)
31 (17%)
184
In order to test if patients could be classified into groups of small, normal and large displacements we grouped patients into three groups as outlined in the methods section. The group sizes and predictions are summarised in Table 3. The classification from the first five fractions was found to be not very sensitive. The probability of being correctly classified as small is 0.47. The probability of being correctly classified as large is 0.5. However, for practical considerations it may be sufficient to ensure that patients do not display large displacements. As can be seen in Table 3, of those patients classified as small from the first five fractions, only 3% were found to be in the large group when their remaining data were examined. Conversely, of those patients initially classified as large, none were found to be classified as small for their remaining fractions. It is not surprising that based on a Chi-square analysis there are more patients in the small–small cell and the large-large cell than we would expect if the classification after the first five fractions had no association with the classification for the entire treatment. Discussion
Fig. 5. Displacement patterns of the prostate between pre- and post-treatment imaging for the remaining treatment course as a function of the displacement pattern determined in the first five image pairs. The figure shows data for the mean displacement in the three cardinal directions (a: anterior/posterior; b: left/right; c: superior/inferior).
extreme than the mean for the remaining fractions (observed slopes from the best fitting straight line were 0.46, 0.64 and 0.54 for AP, LR and SI respectively; the ideal/non-biased slope is 1).
The distribution of times between pre- and post-treatment imaging and the typical prostate movements during that period are consistent with the literature and expectations. The times do not include patient set-up and as such a treatment time slot for prostate cancer patients with daily image guidance in our institution is 15–25 min depending on complexity of the treatment (e.g. IMRT). It is interesting to note that the increase of displacement with time is small. However, after a relatively short interval of 3 min, the vector displacement is likely to exceed 1.5 mm (compare Fig. 1). There is also an underlying uncertainty in interpreting the images. The process of marker matching in two orthogonal kV images is tested daily with a simple QA phantom. Over a period of 6 months the residual displacement of the phantom after applying the couch shift as identified by the kV/kV match was 0.18 ± 0.55 mm (mean of all axes ±1SD). This indicates that any displacements above 1 mm are likely to be associated with the movement of the prostate. Therefore, the relatively large initial displacement could be a reflection of patient movement due to the couch shift to reposition the patient after the first imaging. It could also imply that patients have a relatively large prostate displacement in a short period of time. Finally, it could be an indication that the rate of prostate excursions is rather fast and our measure of difference between prostate location at commencement and end of treatment delivery does not reflect the true extent of prostate mobility. A system like Calypso™ would be required to follow these individual excursions [12,13]. However, given the relatively large displacement found in our study even after short treatment times, one needs to be cautious to argue that a significant reduction of overall delivery time, such as possible with intensity modulated arc radiotherapy [20,21] can justify a substantial
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reduction in margin for internal motion. The risk of doing this, has recently been demonstrated by Engels et al. who reported on increased biochemical failure rate for patients who were treated with substantially reduced margins after the introduction of image guidance [22]. It is important to appreciate that the present data only shows the displacement of the prostate between correction of patient position after pre-treatment imaging and the post-treatment image acquisition. It is acknowledged that the data have three major limitations: 1. It does not show any movement of the prostate during the time of delivery. For example, in a recent study with the Calypso™ real time monitoring system Noel et al. concluded in a study of 35 patients that their ‘‘results suggest that pre- and post-treatment imaging is not a sensitive method of assessing intra-fraction prostate motion, and that intermittent imaging is sufficiently sensitive only at a high sampling rate” [23]. This could explain the slow increase of displacement with time between images as intermediate movements would not add to the observed displacement in the present study.Kupelian and Langen showed in their studies of patients with implanted markers for the Calypso™ real time tracking system that several types of prostate motion could be observed [12,13]. The same was illustrated earlier by Nederveen et al. using movie EPI and automatic marker detection on 10 patients [9,24]. A slow continuous drift would be detected using our method while short excursions may be missed. 2. The data are limited to translational movements. Our data confirm that anterior/posterior and craniocaudal motion is correlated indicating rotation of the prostate around a left/ right axis [25,26]. Rotation of the prostate is well documented in the literature [25,27,28] and the intra-fraction component for rotation was reported to be relatively small by Aubry et al. [27]. It is also generally assumed that in the case of a round object rotation can be compensated for by translations [29]; however, this may not be the case if seminal vesicles are to be included in the treatment field [30]. 3. The information gathered pertains only to the fiducial markers. As such, deformation of the prostate is not recorded and no information on seminal vesicle or critical structures is available. This would require daily volumetric imaging which only recently has become available. It is also doubtful that meaningful decisions about target deformation can be made on-line under time pressure at the treatment unit. However, the assessment of displacement from pre- and posttreatment imaging is fast and can be performed for large numbers of patients such as in the present study without prolonging treatment. We are currently working on an assessment of the utility of additional imaging during treatment to increase our ability to obtain an accurate assessment of individual patients’ prostate motion patterns. It is important to note that Fig. 3 only shows the probability of geographic miss. Depending on the actual dose distribution, beam penumbra and beam directions, the geographic miss may or may not result in a significant reduction of dose to the target. The analysis also pertains to a partial miss only where each event is scored equally even if the miss may affect different portions of the clinical target volume. This would overestimate the impact in conventional radiotherapy where only a systematic miss is likely to affect tumour control probability. However, in the context of hypofractionation [31,32] even a single miss could reduce the dose by more than the 5% deemed to be acceptable in many treatment scenarios [33].
A different approach to estimate the impact of intra-fraction displacement is to calculate the margin which would be required to account for the displacement patterns observed. This is done in Table 2 and it can be seen that the margin has to be increased if the treatment delivery takes longer. The advantage of the use of a margin recipe such as the one by van Herk used here is that the beam penumbra is taken into account [18,19]. While it is necessary to allow for other uncertainties when deriving actual margins [34] the table provides some guidance as to the magnitude of margin for intra-fraction displacement alone. Fig. 4 shows mean and standard deviation of the prostate displacement in the three cardinal directions. The means can be interpreted as a systematic uncertainty while the standard deviations would reflect a random uncertainty [19]. Aubry et al. reported similar data for 18 patients where intra-fraction displacement (termed ‘translation’ in their paper) was determined from two consecutive images without any correction performed in between [27]. Compared to their data our systematic displacement is larger while the random component is similar. This highlights the fact that motion patterns can be significantly different for different institutions and must be determined locally to derive meaningful margins. The data shown in Fig. 4 also only reflect intra-fraction displacement as the initial set-up uncertainty has been corrected in the first step in the image guidance protocol. As shown on the left side of Fig. 4, the residual systematic uncertainty is typically very small, both for individual patients and the cohort of patients. In this case it is likely that other uncertainties dominate the problem of determining appropriate margins for the intra-fraction displacement [34]. In particular the delineation uncertainty of the prostate in relation to the fiducial markers that are used for daily image guidance would be significant. [34] Also the field arrangement chosen will determine the required margin – therefore needs to be cautious to use the present data to explicitly calculate a margin using a recipe [18,35,36]. However, as shown in Fig. 5 there is potential scope for individualisation of margins. For the development of these it would be helpful if one could identify the motion patterns of individual patients early in the treatment course. Based on a simple categorisation of patients into three groups, it was possible to predict the displacement pattern using the displacement of the prostate between pre- and post-treatment imaging as determined in the first five fractions. For 95% of patients a classification into small or large average displacements has been successful. While the displacement is not necessarily providing complete information on motion patterns, it can be assumed that large displacements are associated with large motion of the prostate also during treatment. The consistency of displacement patterns in individual patients also indicates that the present classification may be adequate to consider individualised margins. There are clear limitations in using only pre- and post-treatment images. However, the assessment is simple and can be performed using many commercially available solutions without adding considerable time to the treatment. The displacement provides at least a lower estimate for the overall prostate motion between the images. In addition to this, pre- and post-delivery imaging may be used to categorise patients. This could result in a simple method to individualise margins and therefore reduce toxicity. Conclusion Intra-fraction motion of the prostate gland varies from patient to patient and appears to be a limiting factor when considering margins for radiotherapy. Even in relatively short times there is a significant probability that the prostate has moved more than
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3 mm. Given the variation between patients, using the same set of margins for all patients may not be satisfactory when high doses are to be delivered. In this case, images acquired over the first five fractions of a patient’s course of radiotherapy may predict displacement patterns and could be used to identify patients in whom daily image guidance is essential. Conflict of interest notification None. Acknowledgement We would like to acknowledge the financial support of the Peter MacCallum Cancer Centre Foundation for this project. References [1] Zelefsky MJ, Yamada Y, Fuks Z, et al. Long-term results of conformal radiotherapy for prostate cancer: impact of dose escalation on biochemical tumor control and distant metastases-free survival outcomes. Int J Radiat Oncol Biol Phys 2008;71:1028–33. [2] Hanks GE, Hanlon AL, Epstein B, Horwitz EM. Dose response in prostate cancer with 8–12 years’ follow-up. Int J Radiat Oncol Biol Phys 2002;54:427–35. [3] Al-Mamgani A, van Putten WL, Heemsbergen WD, et al. Update of Dutch multicenter dose-escalation trial of radiotherapy for localized prostate cancer. Int J Radiat Oncol Biol Phys 2008;72:980–8. [4] Ghilezan MJ, Jaffray DA, Siewerdsen JH, et al. Prostate gland motion assessed with cine-magnetic resonance imaging (cine-MRI). Int J Radiat Oncol Biol Phys 2005;62:406–17. [5] Mackie TR, Kapatoes J, Ruchala K, et al. Image guidance for precise conformal radiotherapy. Int J Radiat Oncol Biol Phys 2003;56:89–105. [6] van Herk M. Different styles of image-guided radiotherapy. Semin Radiat Oncol 2007;17:258–67. [7] Gauthier I, Carrier JF, Beliveau-Nadeau D, Fortin B, Taussky D. Dosimetric impact and theoretical clinical benefits of fiducial markers for dose escalated prostate cancer radiation treatment. Int J Radiat Oncol Biol Phys 2009;74:1128–33. [8] ICRU. ICRU report 62: Prescribing, recording, and reporting photon beam therapy (Supplement to ICRU report 50). ICRU reports, Bethesda: International Commission on Radiological Units and Measurements. 2000. [9] Nederveen AJ, Van der Heide UA, Dehnad H, van Moorselaar RJ, Hofman P, Lagendijk JJ. Measurements and clinical consequences of prostate motion during a radiotherapy fraction. Int J Radiat Oncol Biol Phys 2002;53:206–14. [10] Kitamura K, Shirato H, Seppenwoolde Y, et al. Three-dimensional intrafractional movement of prostate measured during real-time tumortracking radiotherapy in supine and prone treatment positions. Int J Radiat Oncol Biol Phys 2002;53:1117–23. [11] Shimizu S, Shirato H, Kitamura K, et al. Use of an implanted marker and realtime tracking of the marker for the positioning of prostate and bladder cancers. Int J Radiat Oncol Biol Phys 2000;48:1591–7. [12] Langen KM, Willoughby TR, Meeks SL, et al. Observations on real-time prostate gland motion using electromagnetic tracking. Int J Radiat Oncol Biol Phys 2008;71:1084–90. [13] Kupelian P, Willoughby T, Mahadevan A, et al. Multi-institutional clinical experience with the Calypso System in localization and continuous, real-time monitoring of the prostate gland during external radiotherapy. Int J Radiat Oncol Biol Phys 2007;67:1088–98. [14] Noel. Prediction of intrafraction prostate motion. 2009.
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[15] Thompson A, Fox C, Foroudi F, et al. Planning and implementing an implanted fiducial programme for prostate cancer radiation therapy. J Med Imaging Radiat Oncol 2008;52:419–24. [16] Fox C, Fisher R, Kron T, Foroudi F. Extraction of data for margin calculations in prostate radiotherapy from a commercial record and verify system. J Med Imag Radiat Oncol 2009. [17] Everitt S, MacManus M, Kron T, Leong T. Geographic miss in radiation oncology: have we missed the boat? Opinion piece. J Med Imaging Radiat Oncol 2009. [18] van Herk M, Remeijer P, Lebesque JV. Inclusion of geometric uncertainties in treatment plan evaluation. Int J Radiat Oncol Biol Phys 2002;52: 1407–22. [19] van Herk M, Remeijer P, Rasch C, Lebesque JV. The probability of correct target dosage: dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys 2000;47:1121–35. [20] Otto K. Volumetric modulated arc therapy: IMRT in a single gantry arc. Med Phys 2008;35:310–7. [21] Palma D, Vollans E, James K, et al. Volumetric modulated arc therapy for delivery of prostate radiotherapy: comparison with intensity-modulated radiotherapy and three-dimensional conformal radiotherapy. Int J Radiat Oncol Biol Phys 2008;72:996–1001. [22] Engels B, Soete G, Verellen D, Storme G. Conformal arc radiotherapy for prostate cancer: increased biochemical failure in patients with distended rectum on the planning computed tomogram despite image guidance by implanted markers. Int J Radiat Oncol Biol Phys 2009;74: 388–91. [23] Noel C, Parikh PJ, Roy M, et al. Prediction of intrafraction prostate motion: accuracy of pre- and post-treatment imaging and intermittent imaging. Int J Radiat Oncol Biol Phys 2009;73:692–8. [24] Nederveen A, Lagendijk J, Hofman P. Detection of fiducial gold markers for automatic on-line megavoltage position verification using a marker extraction kernel (MEK). Int J Radiat Oncol Biol Phys 2000;47: 1435–42. [25] Hoogeman MS, van Herk M, de Bois J, Lebesque JV. Strategies to reduce the systematic error due to tumor and rectum motion in radiotherapy of prostate cancer. Radiother Oncol 2005;74:177–85. [26] van Herten YR, Van de Kamer JB, van Wieringen N, Pieters BR, Bel A. Dosimetric evaluation of prostate rotations and their correction by couch rotations. Radiother Oncol 2008;88:156–62. [27] Aubry JF, Beaulieu L, Girouard LM, et al. Measurements of intrafraction motion and interfraction and intrafraction rotation of prostate by three-dimensional analysis of daily portal imaging with radiopaque markers. Int J Radiat Oncol Biol Phys 2004;60:30–9. [28] Owen, R, Foroudi, F, Cox, J, Kron, T, Duchesne, G. Inter-fraction prostate rotation determined from in-room computerised tomography (CT) images taken during radiotherapy verification. Med Dosim; submitted. [29] Redpath AT, Wright P, Muren LP. The contribution of on-line correction for rotational organ motion in image-guided radiotherapy of the bladder and prostate. Acta Oncol 2008;47:1367–72. [30] Liang J, Wu Q, Yan D. The role of seminal vesicle motion in target margin assessment for online image-guided radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys 2008. [31] Miles EF, Lee WR. Hypofractionation for prostate cancer: a critical review. Semin Radiat Oncol 2008;18:41–7. [32] Ritter M, Forman J, Kupelian P, Lawton C, Petereit D. Hypofractionation for prostate cancer. Cancer J 2009;15:1–6. [33] ICRU. ICRU report 50: Prescribing, recording, and reporting photon beam therapy. ICRU reports, Bethesda: International Commission on Radiological Units and Measurements. 1993. [34] van Herk M. Errors and margins in radiotherapy. Semin Radiat Oncol 2004;14:52–64. [35] McKenzie AL, van Herk M, Mijnheer B. The width of margins in radiotherapy treatment plans. Phys Med Biol 2000;45:3331–42. [36] Herschtal A, Kron T, Fox C. Radiotherapy margin design with particular consideration of high curvature CTVs. Med Phys 2009;36:684–97.
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Quality assurance
Intra-fraction prostate displacement in radiotherapy estimated from pre- and post-treatment imaging of patients with implanted fiducial markers Tomas Kron a,b,*, Jessica Thomas c, Chris Fox a, Ann Thompson d, Rebecca Owen d, Alan Herschtal e, Annette Haworth a,b, Keen-Hun Tai c,f, Farshad Foroudi c,f a e
Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Australia; b Applied Physics, RMIT University, Melbourne, Australia; c Radiation Oncology; d Radiation Therapy; and Biostatisitics and Clinical Trials, Peter MacCallum Cancer Centre, Melbourne, Australia; f Department of Pathology, University of Melbourne, Parkville, Australia
a r t i c l e
i n f o
Article history: Received 1 June 2009 Received in revised form 21 January 2010 Accepted 23 January 2010 Available online 26 February 2010 Keywords: Fiducial markers Image-guided radiation therapy Intra-fraction displacement Prostate cancer
a b s t r a c t Purpose: To determine intra-fraction displacement of the prostate gland from imaging pre- and postradiotherapy delivery of prostate cancer patients with three implanted fiducial markers. Methods and materials: Data were collected from 184 patients who had two orthogonal X-rays pre- and post-delivery on at least 20 occasions using a Varian On Board kV Imaging system. A total of 5778 image pairs covering time intervals between 3 and 30 min between pre- and post-imaging were evaluated for intra-fraction prostate displacement. Results: The mean three dimensional vector shift between images was 1.7 mm ranging from 0 to 25 mm. No preferential direction of displacement was found; however, there was an increase of prostate displacement with time between images. There was a large variation in typical shifts between patients (range 1 ± 1 to 6 ± 2 mm) with no apparent trends throughout the treatment course. Images acquired in the first five fractions of treatment could be used to predict displacement patterns for individual patients. Conclusion: Intra-fraction motion of the prostate gland appears to be a limiting factor when considering margins for radiotherapy. Given the variation between patients, a uniform set of margins for all patients may not be satisfactory when high target doses are to be delivered. Ó 2010 Elsevier Ireland Ltd. All rights reserved. Radiotherapy and Oncology 95 (2010) 191–197
Radiotherapy is an important treatment modality for prostate cancer. There appears to be a dose response relationship with higher doses resulting in better local control [1] and biochemical failure-free survival [2]. As the prostate is located between critical structures such as bladder and rectum, there is also an increased risk of normal tissue toxicity [3] and optimised treatment delivery with minimal margins appears to be essential for maximising complication free tumour control. Unfortunately, the prostate is a relatively mobile organ that can move substantially against the external contour of the patient and even internal bony anatomy. Both day-to-day variations in prostate location due to bladder and rectal filling have been reported as well as movement on a short-term basis over the time period of the radiation delivery itself [4]. Daily imaging of the target volume, a process usually referred to as image-guided radiation therapy (IGRT) [5,6] allows localisation of the target prior to every treatment fraction. This should facilitate a reduction in margins required to account for uncertainty in prostate position before treatment [7]. * Corresponding author. Address: Department of Physical Sciences, Peter MacCallum Cancer, St Andrews Place, Melbourne Victoria 3002, Australia. E-mail address: [email protected] (T. Kron). 0167-8140/$ - see front matter Ó 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.radonc.2010.01.010
The International Commission on Radiation Units and Measurements (ICRU) identifies in their report 62 [8] two major contributions to margins: 1. Internal margins take into account any variations in size, shape or location of an organ in relation to an internal reference point. Movement of a lung tumour or filling of the bladder are examples for this. 2. The set-up margin accounts then for any uncertainty in positioning this internal reference point at the correct position for treatment. Image guidance is mostly associated with reduction of the setup margin. However, by acquiring an image prior and post-radiotherapy, one can obtain an estimate of the minimum movement of the target organ during the delivery of radiation. Clearly, continuous three dimensional localisation of the target during treatment would be preferable. This can be achieved using electronic portalimaging movies (Nederveen et al.) [9], multiple fluoroscopy systems such as real time tumour tracking [10,11] or the Calypso system [12–14]. While less information can be gained by preand post-treatment localisation of the prostate, it is easy to do and interpret, allows verification of any pre-treatment patient
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repositioning and provides at least an estimate of displacement of the gland during treatment. The aim of the present study was to determine the difference in prostate location from pre- and post-treatment kV imaging of patients with implanted fiducial markers. Intra- and inter-patient variation in movement patterns was evaluated to predict the displacement pattern of a patient from the first five images. Methods Patient population and imaging sequence A total of 184 patients treated with radical external beam radiotherapy at Peter MacCallum Cancer Centre between March 2007 and November 2008 were included in the study. All patients were treated to 74 or 78 Gy using 3D conformal or intensity-modulated radiation therapy (approximately 20% of patients). The typical margin used in our centre is 10 mm with exception for the posterior direction where a margin of 7 mm is used. All patients had three fiducial gold markers (diameter 1 mm, length 5 mm) implanted in the prostate under transrectal ultrasound guidance a minimum of 1 week prior to simulation [15]. Prior to each treatment delivery, the patient was imaged using two orthogonal kV X-ray images (On board imaging, OBI, Varian Medical Systems, Palo Alto). The images were matched with reference to digitally reconstructed radiographs from a radiotherapy treatment planning system XiO (CMS Inc, St Louis, MI) or Eclipse (Varian Medical Systems, Palo Alto, CA) using the fiducial markers manual match. The Varian software displays reference and verification imaging for both exposures on the same screen and allows the user to move the images until the best match is achieved. The high effective atomic number of the gold seeds ensures that the fiducials are easily identifiable. The software and automatic couch movements are tested every morning using a test object. The residual uncertainty of position in the test object is less than 1 mm independent of the operator. The system provides the user with translational mismatches in three dimensions. Rotations of the patient were not checked. Any translational mismatch was corrected by moving the treatment couch with the patient to the desired location. As this can be performed from outside the treatment room, the additional time required is very small and after extensive testing of the system no verification of the correctness of the move is performed. A daily quality assurance programme verifies the correctness of the couch motion. A second set of two kV images was acquired for each treatment directly after completion of the radiation delivery. As any displacement of the patient had been corrected after the first imaging, any mismatch in the post-treatment image identifies a combination of the residual error after correcting the patient position and any displacement that occurred during the delivery. The process provides a value for the minimum displacement of the prostate throughout the treatment delivery as temporary excursions of the prostate throughout the fraction would not be identified. Data collection and evaluation All shifts and measured differences between image sets were recorded in a record and verify system (Impac MultiAccess, Elekta Stockholm). The system also records the times when the images were acquired. The time between the second kV images in each set was taken as time between images. Reports were created of the Impac database using Crystal Reports (Crystal Reports 11, Business Objects Software, San Jose) software. The reports were processed using in-house written software to combine all relevant information for all patients in a Microsoft
Access Database (Microsoft, Redmond, Washington) that allows easy access to the data. More information on the database is provided by Fox et al. [16]. On occasions, images were not recorded or additional images were taken. Only patients with at least 20 image pairs were included in the study. Image pairs that were less than 3 min or more than 30 min apart were also excluded as they were deemed to reflect other issues than motion of the prostate during treatment (e.g. patient off couch to void). In total 5778 image pairs or 97% of all images were included in the evaluation. The data were evaluated using the statistical software R version 2.7.2 (http://www.r-project.org/). The analysis included the three orthogonal distances, anterior/posterior (AP), superior/inferior (SI) and left/right (LR) recorded in millimetre increments. The total displacement, D, was determined as the vector of the three distances:
D¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi AP2 þ LR2 þ SI2
This can be used for the evaluation of the adequacy of margins. Without actually performing a dose calculation taking beam directions and properties into account, it is impossible to determine the dosimetric impact of the prostate moving into a particular direction. As such we scored if the clinical target volume (the prostate) would move out of the planning target volume (PTV) created using a given set of CTV to PTV margins. The resulting geographic miss [17] does not necessarily result in a significant underdose as the beam directions and penumbra are not taken into account.
Statistical methods The relationship between time between images and 3D displacement was assessed using linear-mixed effects models (random intercepts) that take into account the fact that the observations are grouped by patient. In the model time was considered as a continuous variable. Two models were considered: a straight line relationship and a quadratic relationship that includes a squared term for time between images. To assess the probability of the prostate having moved more than a specified amount (referred to hereafter as a displacement value) during a single fraction as a function of time between images, logistic regressions were used. Four displacement values were chosen: 3, 5, 7 and 10 mm. For each displacement value the data were dichotomised according to whether an observation was below or above the displacement value. A logistic regression was preformed on this binary data with time between images as the explanatory variable. The fitted probabilities from the four models were plotted.
Estimation of a margin component for intra-fraction prostate displacement The displacement of the prostate during treatment can be divided in random and systematic components. This allows the application of a formalism to determine margins based on the observed data following the work of van Herk and Remeijer [18,19]. The required margin to achieve 95% of dose coverage for 90% of patients given the measured intra-fraction displacement (MIFD) was determined as:
MIFD ¼ 2:5R þ 0:7r with R as the systematic component of the displacement and r the random one. This was performed for the three groups of image pairs defined for different times between the images.
T. Kron et al. / Radiotherapy and Oncology 95 (2010) 191–197
Prediction of displacement patterns in individual patients from the first five fractions Of particular interest is whether displacement patterns can be predicted for individual patients from images acquired in the first part of the treatment. As such we evaluated if the first five treatment fractions are representatives for the rest of the treatment. In the evaluation, the displacement patterns were divided into three groups: Small: AP standard deviation of displacement, LR standard deviation of displacement and SI standard deviation of displacement all less than 0.1 cm. Large: at least of one of the AP, LR and SI standard deviations greater than or equal to 0.2 cm. Medium: those not classified as either small or large.
Fig. 1. Displacement of the prostate as a function of time between pre- and posttreatment imaging. Shown are the means with upper and lower quartiles for the given time intervals with the straight line showing a linear regression (solid line) and the curve a quadratic fit to the data (dash/dot line).
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Results Evaluation of all images A total of 5778 image pairs were evaluated of 184 patients (median 33 image pairs per patient). Times <3 min and >30 min were excluded from the evaluation and are not shown. The most likely time between pre- and post-treatment image acquisition was 6 min which reflects the fact that most patients were treated with a five-field conformal treatment. Only 2.9% of patients experienced a time on the treatment couch between pre- and postimaging of 15 min or longer. The intra-fraction displacements were found to be generally small and only 4.7% and 0.4% are above 5 and 10 mm respectively. The mean displacement in AP, LR and SI directions was 0.04 ± 0.16 cm (1SD), 0.02 ± 0.11 cm, and 0.01 ± 0.15 cm, respectively. Only the dislocations in AP and SI direction were associated with each other (p < 0.0001). No association between any of the other directional movements was found. The 3D difference in the location of the prostate between preand post-treatment image is shown in Fig. 1 as a function of time between the images. The means for the given time intervals with upper and lower quartiles are shown. While there is a relatively large displacement after 3 min, there is an increase of the distance with time. The solid line in Fig. 1 represents a linear fit to all the data with time between images considered as a continuous variable. Based on the linear model the average displacement increased by 0.2 mm every 5 min with a 95% confidence interval of (0.16, 0.33). A quadratic function, which is also shown in Fig. 1, provides a better fit of the data with no indication that a maximum average displacement is reached after 30 min. No particular direction was found to dominate this change. The increase of displacement with time can also be seen in Fig. 2, which shows the three dimensional vector displacement for three different treatment duration groups. The characteristics for the three groups are given in Table 1. The number of large displacements is greater in the group of treatment times exceeding 9 min (statistically different to both other groups with p-values from non-parametric tests of a difference in distributions: 0.0131 vs. 6–9 min group, <0.0001 vs. <6 min group).
Fig. 2. Frequency of a displacement for three different time intervals between pre- and post-treatment imaging.
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Table 1 Characteristics of three groups of patients/images reflecting different times between pre- and post-treatment imaging. Group time interval (min)
Number of images (% total images)
Number of patients that contribute at least one image (% of patients)
<6 6–9 >9
2950 (51) 2089 (36) 739 (13)
180 (98) 184 (100) 184 (100)
Fig. 3 illustrates the effect of the increasing displacement on the probability of the CTV not being covered by the PTV resulting in a potential partial miss. Different margins are used to create different PTV sizes as shown in the figure. One can see that after 18 min there is a 10% probability that the prostate has moved by more than 5 mm. In total, 11% of patients have more than one fraction with a displacement greater than 7 mm while 1% of patients have more than one fraction with a displacement greater than 10 mm. Table 2 shows the component of a margin for the planning target volume to account for intra-fraction displacement. The data are given for the three groups with different times between the preand post-imaging as defined in Table 1. Evaluation of individual patients Different patients showed different patterns of displacement. This can be seen in Fig. 4 which shows the mean and standard
Fig. 4. Distribution of mean displacement and standard deviation of the prostate between pre- and post-treatment image for the 184 patients in the study. Shown is the displacement in the three cardinal directions.
deviation of the displacement for all patients in the three cardinal directions. In the AP and LR directions systematic differences between the medians and 0 were observed with an average of 0.3 mm posterior median displacement and 0.2 mm left median displacement for all patients. However, the majority of patients were found to have a mean within 2 mm of the target value indicating a small systematic error. As can be expected, the displacement in the lateral direction is the smallest. This is also true for the standard deviations from the mean for all patients. Fig. 3. Probability of prostate displacement larger than a given distance as a function of time.
Table 2 Margins calculated using the van Herk formalism based on the intra-fraction displacements identified for the three groups of patients identified in Table 1 with different times between the image pairs. Group time interval (min)
Dimension
Systematic error (cm)
Random uncertainty (cm)
van Herk margin (cm)
<6
AP LR SI AP LR SI AP LR SI
0.079 0.054 0.071 0.085 0.056 0.081 0.125 0.105 0.128
0.124 0.084 0.118 0.119 0.078 0.113 0.126 0.067 0.118
0.284 0.194 0.259 0.297 0.194 0.281 0.401 0.309 0.402
6–9
>9
Prediction of motion patterns from the first five fractions The displacement patterns of the prostate in the first five fractions were analysed and compared to the displacement observed in the remaining fractions. As not all patients had images for all fractions in the data base, there may have been circumstances where the first five image pairs do not reflect the first five fractions. However, in all patients, at least an additional 15 fractions were available for analysis of the remainder of the treatment course (typically more than 25 images were available as the median number of images per patient was 33). Fig. 5 shows how the first five fractions are associated with the remainder of the treatment for the three cardinal directions of displacement. The association was found to be moderate (Pearson’s correlation of 0.58, 0.73 and 0.60 for AP, LR and SI means respectively). We also saw a degree of bias when using the mean of the first five fractions to predict the mean of the remaining fractions, with the mean from the first five fractions tending to be more
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Table 3 Cross-classification between the displacement groups of fiducial markers as determined from the first five fractions and those seen in the whole treatment. Classification from entire treatment
Total
Small
Medium
Large
Classification from first five fractions Small Medium Large
27 (47%) 10 (11%) 0 (0%)
29 (50%) 70 (76%) 17 (50%)
2 (3%) 12 (13%) 17 (50%)
58 92 34
Total
37 (20%)
116 (63%)
31 (17%)
184
In order to test if patients could be classified into groups of small, normal and large displacements we grouped patients into three groups as outlined in the methods section. The group sizes and predictions are summarised in Table 3. The classification from the first five fractions was found to be not very sensitive. The probability of being correctly classified as small is 0.47. The probability of being correctly classified as large is 0.5. However, for practical considerations it may be sufficient to ensure that patients do not display large displacements. As can be seen in Table 3, of those patients classified as small from the first five fractions, only 3% were found to be in the large group when their remaining data were examined. Conversely, of those patients initially classified as large, none were found to be classified as small for their remaining fractions. It is not surprising that based on a Chi-square analysis there are more patients in the small–small cell and the large-large cell than we would expect if the classification after the first five fractions had no association with the classification for the entire treatment. Discussion
Fig. 5. Displacement patterns of the prostate between pre- and post-treatment imaging for the remaining treatment course as a function of the displacement pattern determined in the first five image pairs. The figure shows data for the mean displacement in the three cardinal directions (a: anterior/posterior; b: left/right; c: superior/inferior).
extreme than the mean for the remaining fractions (observed slopes from the best fitting straight line were 0.46, 0.64 and 0.54 for AP, LR and SI respectively; the ideal/non-biased slope is 1).
The distribution of times between pre- and post-treatment imaging and the typical prostate movements during that period are consistent with the literature and expectations. The times do not include patient set-up and as such a treatment time slot for prostate cancer patients with daily image guidance in our institution is 15–25 min depending on complexity of the treatment (e.g. IMRT). It is interesting to note that the increase of displacement with time is small. However, after a relatively short interval of 3 min, the vector displacement is likely to exceed 1.5 mm (compare Fig. 1). There is also an underlying uncertainty in interpreting the images. The process of marker matching in two orthogonal kV images is tested daily with a simple QA phantom. Over a period of 6 months the residual displacement of the phantom after applying the couch shift as identified by the kV/kV match was 0.18 ± 0.55 mm (mean of all axes ±1SD). This indicates that any displacements above 1 mm are likely to be associated with the movement of the prostate. Therefore, the relatively large initial displacement could be a reflection of patient movement due to the couch shift to reposition the patient after the first imaging. It could also imply that patients have a relatively large prostate displacement in a short period of time. Finally, it could be an indication that the rate of prostate excursions is rather fast and our measure of difference between prostate location at commencement and end of treatment delivery does not reflect the true extent of prostate mobility. A system like Calypso™ would be required to follow these individual excursions [12,13]. However, given the relatively large displacement found in our study even after short treatment times, one needs to be cautious to argue that a significant reduction of overall delivery time, such as possible with intensity modulated arc radiotherapy [20,21] can justify a substantial
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reduction in margin for internal motion. The risk of doing this, has recently been demonstrated by Engels et al. who reported on increased biochemical failure rate for patients who were treated with substantially reduced margins after the introduction of image guidance [22]. It is important to appreciate that the present data only shows the displacement of the prostate between correction of patient position after pre-treatment imaging and the post-treatment image acquisition. It is acknowledged that the data have three major limitations: 1. It does not show any movement of the prostate during the time of delivery. For example, in a recent study with the Calypso™ real time monitoring system Noel et al. concluded in a study of 35 patients that their ‘‘results suggest that pre- and post-treatment imaging is not a sensitive method of assessing intra-fraction prostate motion, and that intermittent imaging is sufficiently sensitive only at a high sampling rate” [23]. This could explain the slow increase of displacement with time between images as intermediate movements would not add to the observed displacement in the present study.Kupelian and Langen showed in their studies of patients with implanted markers for the Calypso™ real time tracking system that several types of prostate motion could be observed [12,13]. The same was illustrated earlier by Nederveen et al. using movie EPI and automatic marker detection on 10 patients [9,24]. A slow continuous drift would be detected using our method while short excursions may be missed. 2. The data are limited to translational movements. Our data confirm that anterior/posterior and craniocaudal motion is correlated indicating rotation of the prostate around a left/ right axis [25,26]. Rotation of the prostate is well documented in the literature [25,27,28] and the intra-fraction component for rotation was reported to be relatively small by Aubry et al. [27]. It is also generally assumed that in the case of a round object rotation can be compensated for by translations [29]; however, this may not be the case if seminal vesicles are to be included in the treatment field [30]. 3. The information gathered pertains only to the fiducial markers. As such, deformation of the prostate is not recorded and no information on seminal vesicle or critical structures is available. This would require daily volumetric imaging which only recently has become available. It is also doubtful that meaningful decisions about target deformation can be made on-line under time pressure at the treatment unit. However, the assessment of displacement from pre- and posttreatment imaging is fast and can be performed for large numbers of patients such as in the present study without prolonging treatment. We are currently working on an assessment of the utility of additional imaging during treatment to increase our ability to obtain an accurate assessment of individual patients’ prostate motion patterns. It is important to note that Fig. 3 only shows the probability of geographic miss. Depending on the actual dose distribution, beam penumbra and beam directions, the geographic miss may or may not result in a significant reduction of dose to the target. The analysis also pertains to a partial miss only where each event is scored equally even if the miss may affect different portions of the clinical target volume. This would overestimate the impact in conventional radiotherapy where only a systematic miss is likely to affect tumour control probability. However, in the context of hypofractionation [31,32] even a single miss could reduce the dose by more than the 5% deemed to be acceptable in many treatment scenarios [33].
A different approach to estimate the impact of intra-fraction displacement is to calculate the margin which would be required to account for the displacement patterns observed. This is done in Table 2 and it can be seen that the margin has to be increased if the treatment delivery takes longer. The advantage of the use of a margin recipe such as the one by van Herk used here is that the beam penumbra is taken into account [18,19]. While it is necessary to allow for other uncertainties when deriving actual margins [34] the table provides some guidance as to the magnitude of margin for intra-fraction displacement alone. Fig. 4 shows mean and standard deviation of the prostate displacement in the three cardinal directions. The means can be interpreted as a systematic uncertainty while the standard deviations would reflect a random uncertainty [19]. Aubry et al. reported similar data for 18 patients where intra-fraction displacement (termed ‘translation’ in their paper) was determined from two consecutive images without any correction performed in between [27]. Compared to their data our systematic displacement is larger while the random component is similar. This highlights the fact that motion patterns can be significantly different for different institutions and must be determined locally to derive meaningful margins. The data shown in Fig. 4 also only reflect intra-fraction displacement as the initial set-up uncertainty has been corrected in the first step in the image guidance protocol. As shown on the left side of Fig. 4, the residual systematic uncertainty is typically very small, both for individual patients and the cohort of patients. In this case it is likely that other uncertainties dominate the problem of determining appropriate margins for the intra-fraction displacement [34]. In particular the delineation uncertainty of the prostate in relation to the fiducial markers that are used for daily image guidance would be significant. [34] Also the field arrangement chosen will determine the required margin – therefore needs to be cautious to use the present data to explicitly calculate a margin using a recipe [18,35,36]. However, as shown in Fig. 5 there is potential scope for individualisation of margins. For the development of these it would be helpful if one could identify the motion patterns of individual patients early in the treatment course. Based on a simple categorisation of patients into three groups, it was possible to predict the displacement pattern using the displacement of the prostate between pre- and post-treatment imaging as determined in the first five fractions. For 95% of patients a classification into small or large average displacements has been successful. While the displacement is not necessarily providing complete information on motion patterns, it can be assumed that large displacements are associated with large motion of the prostate also during treatment. The consistency of displacement patterns in individual patients also indicates that the present classification may be adequate to consider individualised margins. There are clear limitations in using only pre- and post-treatment images. However, the assessment is simple and can be performed using many commercially available solutions without adding considerable time to the treatment. The displacement provides at least a lower estimate for the overall prostate motion between the images. In addition to this, pre- and post-delivery imaging may be used to categorise patients. This could result in a simple method to individualise margins and therefore reduce toxicity. Conclusion Intra-fraction motion of the prostate gland varies from patient to patient and appears to be a limiting factor when considering margins for radiotherapy. Even in relatively short times there is a significant probability that the prostate has moved more than
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3 mm. Given the variation between patients, using the same set of margins for all patients may not be satisfactory when high doses are to be delivered. In this case, images acquired over the first five fractions of a patient’s course of radiotherapy may predict displacement patterns and could be used to identify patients in whom daily image guidance is essential. Conflict of interest notification None. Acknowledgement We would like to acknowledge the financial support of the Peter MacCallum Cancer Centre Foundation for this project. References [1] Zelefsky MJ, Yamada Y, Fuks Z, et al. Long-term results of conformal radiotherapy for prostate cancer: impact of dose escalation on biochemical tumor control and distant metastases-free survival outcomes. Int J Radiat Oncol Biol Phys 2008;71:1028–33. [2] Hanks GE, Hanlon AL, Epstein B, Horwitz EM. Dose response in prostate cancer with 8–12 years’ follow-up. Int J Radiat Oncol Biol Phys 2002;54:427–35. [3] Al-Mamgani A, van Putten WL, Heemsbergen WD, et al. Update of Dutch multicenter dose-escalation trial of radiotherapy for localized prostate cancer. Int J Radiat Oncol Biol Phys 2008;72:980–8. [4] Ghilezan MJ, Jaffray DA, Siewerdsen JH, et al. Prostate gland motion assessed with cine-magnetic resonance imaging (cine-MRI). Int J Radiat Oncol Biol Phys 2005;62:406–17. [5] Mackie TR, Kapatoes J, Ruchala K, et al. Image guidance for precise conformal radiotherapy. Int J Radiat Oncol Biol Phys 2003;56:89–105. [6] van Herk M. Different styles of image-guided radiotherapy. Semin Radiat Oncol 2007;17:258–67. [7] Gauthier I, Carrier JF, Beliveau-Nadeau D, Fortin B, Taussky D. Dosimetric impact and theoretical clinical benefits of fiducial markers for dose escalated prostate cancer radiation treatment. Int J Radiat Oncol Biol Phys 2009;74:1128–33. [8] ICRU. ICRU report 62: Prescribing, recording, and reporting photon beam therapy (Supplement to ICRU report 50). ICRU reports, Bethesda: International Commission on Radiological Units and Measurements. 2000. [9] Nederveen AJ, Van der Heide UA, Dehnad H, van Moorselaar RJ, Hofman P, Lagendijk JJ. Measurements and clinical consequences of prostate motion during a radiotherapy fraction. Int J Radiat Oncol Biol Phys 2002;53:206–14. [10] Kitamura K, Shirato H, Seppenwoolde Y, et al. Three-dimensional intrafractional movement of prostate measured during real-time tumortracking radiotherapy in supine and prone treatment positions. Int J Radiat Oncol Biol Phys 2002;53:1117–23. [11] Shimizu S, Shirato H, Kitamura K, et al. Use of an implanted marker and realtime tracking of the marker for the positioning of prostate and bladder cancers. Int J Radiat Oncol Biol Phys 2000;48:1591–7. [12] Langen KM, Willoughby TR, Meeks SL, et al. Observations on real-time prostate gland motion using electromagnetic tracking. Int J Radiat Oncol Biol Phys 2008;71:1084–90. [13] Kupelian P, Willoughby T, Mahadevan A, et al. Multi-institutional clinical experience with the Calypso System in localization and continuous, real-time monitoring of the prostate gland during external radiotherapy. Int J Radiat Oncol Biol Phys 2007;67:1088–98. [14] Noel. Prediction of intrafraction prostate motion. 2009.
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[15] Thompson A, Fox C, Foroudi F, et al. Planning and implementing an implanted fiducial programme for prostate cancer radiation therapy. J Med Imaging Radiat Oncol 2008;52:419–24. [16] Fox C, Fisher R, Kron T, Foroudi F. Extraction of data for margin calculations in prostate radiotherapy from a commercial record and verify system. J Med Imag Radiat Oncol 2009. [17] Everitt S, MacManus M, Kron T, Leong T. Geographic miss in radiation oncology: have we missed the boat? Opinion piece. J Med Imaging Radiat Oncol 2009. [18] van Herk M, Remeijer P, Lebesque JV. Inclusion of geometric uncertainties in treatment plan evaluation. Int J Radiat Oncol Biol Phys 2002;52: 1407–22. [19] van Herk M, Remeijer P, Rasch C, Lebesque JV. The probability of correct target dosage: dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys 2000;47:1121–35. [20] Otto K. Volumetric modulated arc therapy: IMRT in a single gantry arc. Med Phys 2008;35:310–7. [21] Palma D, Vollans E, James K, et al. Volumetric modulated arc therapy for delivery of prostate radiotherapy: comparison with intensity-modulated radiotherapy and three-dimensional conformal radiotherapy. Int J Radiat Oncol Biol Phys 2008;72:996–1001. [22] Engels B, Soete G, Verellen D, Storme G. Conformal arc radiotherapy for prostate cancer: increased biochemical failure in patients with distended rectum on the planning computed tomogram despite image guidance by implanted markers. Int J Radiat Oncol Biol Phys 2009;74: 388–91. [23] Noel C, Parikh PJ, Roy M, et al. Prediction of intrafraction prostate motion: accuracy of pre- and post-treatment imaging and intermittent imaging. Int J Radiat Oncol Biol Phys 2009;73:692–8. [24] Nederveen A, Lagendijk J, Hofman P. Detection of fiducial gold markers for automatic on-line megavoltage position verification using a marker extraction kernel (MEK). Int J Radiat Oncol Biol Phys 2000;47: 1435–42. [25] Hoogeman MS, van Herk M, de Bois J, Lebesque JV. Strategies to reduce the systematic error due to tumor and rectum motion in radiotherapy of prostate cancer. Radiother Oncol 2005;74:177–85. [26] van Herten YR, Van de Kamer JB, van Wieringen N, Pieters BR, Bel A. Dosimetric evaluation of prostate rotations and their correction by couch rotations. Radiother Oncol 2008;88:156–62. [27] Aubry JF, Beaulieu L, Girouard LM, et al. Measurements of intrafraction motion and interfraction and intrafraction rotation of prostate by three-dimensional analysis of daily portal imaging with radiopaque markers. Int J Radiat Oncol Biol Phys 2004;60:30–9. [28] Owen, R, Foroudi, F, Cox, J, Kron, T, Duchesne, G. Inter-fraction prostate rotation determined from in-room computerised tomography (CT) images taken during radiotherapy verification. Med Dosim; submitted. [29] Redpath AT, Wright P, Muren LP. The contribution of on-line correction for rotational organ motion in image-guided radiotherapy of the bladder and prostate. Acta Oncol 2008;47:1367–72. [30] Liang J, Wu Q, Yan D. The role of seminal vesicle motion in target margin assessment for online image-guided radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys 2008. [31] Miles EF, Lee WR. Hypofractionation for prostate cancer: a critical review. Semin Radiat Oncol 2008;18:41–7. [32] Ritter M, Forman J, Kupelian P, Lawton C, Petereit D. Hypofractionation for prostate cancer. Cancer J 2009;15:1–6. [33] ICRU. ICRU report 50: Prescribing, recording, and reporting photon beam therapy. ICRU reports, Bethesda: International Commission on Radiological Units and Measurements. 1993. [34] van Herk M. Errors and margins in radiotherapy. Semin Radiat Oncol 2004;14:52–64. [35] McKenzie AL, van Herk M, Mijnheer B. The width of margins in radiotherapy treatment plans. Phys Med Biol 2000;45:3331–42. [36] Herschtal A, Kron T, Fox C. Radiotherapy margin design with particular consideration of high curvature CTVs. Med Phys 2009;36:684–97.