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Robustness of 4D-optimized scanned carbon ion beam therapy against interfractional changes in lung cancer
Radiotherapy and Oncology 122 (2017) 387–392
Contents lists available at ScienceDirect
Radiotherapy and Oncology journal homepage: www.thegreenjournal.com
Particle therapy in lung cancer
Robustness of 4D-optimized scanned carbon ion beam therapy against interfractional changes in lung cancer Christian Graeff ⇑ GSI Helmholzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany
a r t i c l e
i n f o
Article history: Received 6 September 2016 Received in revised form 16 November 2016 Accepted 2 December 2016 Available online 7 January 2017 Keywords: Ion beam therapy Charged particle therapy Moving targets 4D-optimization Interfractional changes Lung cancer
a b s t r a c t Background and purpose: Moving targets could be conformally treated with actively scanned carbon ion beams using 4D-optimization. As this heavily exploits 4D-CTs, an important question is whether the conformity also upholds in the context of interfractional changes, i.e. variable positioning, anatomy and breathing patterns. Materials and methods: In 4 lung cancer patients, 6 weekly 4D-CTs were available. 4D-CTs and their phases were non-rigidly registered to propagate contours and 4D-doses. On the first 4D-CT, a 4Doptimized plan delivering a uniform dose to each motion phase (total dose 9.4 Gy(RBE)) was simulated, as well as an ITV plan for comparison. On the five following 4D-CTs, 4D-dose was forward calculated and evaluated for target coverage and conformity. Variable uniform (3–7 mm) and range margins (2 mm/%) were investigated. Results: For all patients, target coverage (V95 > 95% accumulated over 5 fractions) could be achieved, but with variable margin size weakly depending on motion amplitude and range changes. The same margins were also necessary for ITV plans, which lead to lower conformity and higher integral doses. Conclusion: 4D-optimization appears feasible also under interfractional changes and maintains a dosimetric advantage over less conformal ITV irradiations. Further studies are needed to identify patients benefiting most from the technically more complex 4D-optimization. Ó 2016 Elsevier Ireland Ltd. All rights reserved. Radiotherapy and Oncology 122 (2017) 387–392
The treatment of moving targets with scanned ion beams is challenging, both due to interplay effects and changes in the water-equivalent thickness (WET) to the target [1]. This latter effect is especially severe in lung cancer due to the large density differences present. Motion compensation through 4Doptimization, i.e. on the entire 4DCT, can incorporate both target motion and WET changes in the treatment plan [2]. By calculating a plan for each motion phase, the delivered dose is highly conformal to the target even in the face of complex tumor geometries and large motions. Such a 4D-treatment plan requires a delivery synchronized to the patient motion, though [3]. A promising strategy of 4D-optimization is to optimize a uniform dose to each motion phase [4], though this eliminates the possibility to exploit target motion for organ at risk (OAR) sparing [5]. The homogeneous doses delivered to each of typically 10 motion phases induce a rescanning effect. This helps to mitigate random errors such as variations in the breathing cycle; hence the method will be called 4D-Rescanning for the remainder of this ⇑ Address: Planckstrasse 1, D-64291 Darmstadt, Germany. E-mail address: [email protected] http://dx.doi.org/10.1016/j.radonc.2016.12.017 0167-8140/Ó 2016 Elsevier Ireland Ltd. All rights reserved.
paper. Still, a major issue of 4D-optimization in general is the fact that the 4DCT available for planning is not necessarily representative for the later treatment situation. An overfitting of the treatment plan on the planning 4DCT might thus even be harmful if the real patient motion deviates strongly. The aim of this paper is to investigate in a treatment planning study (a) whether 4D-Rescanning is capable of delivering dose over a treatment course with variable breathing and patient positions. (b) the necessary margins for this purpose and if there is a relation of margin size to motion amplitude in the initial planning 4DCT. (c) if margins sufficient to ensure target dose still give an advantage in terms of conformity over an ITV strategy [6]. To address these questions, 4D-optimized treatment plans were computed on the first and forward-calculated on the following 4DCTs of a sequential dataset of lung cancer patients.
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Robustness of 4D-optimization in ion beam therapy
All optimizations and dose calculations were carried out with TRiP4D, which uses a pencil beam algorithm with multiple Coulomb scattering [14].
Material and methods Patient data A set of 4 NSCLC patients with weekly sequential 4DCTs was available from MD Anderson Cancer Center (MDACC, Houston, Tx). The 4DCTs (120 kV, 500 mm FOV, 2.5 mm slice thickness, 10 motion phases) were taken over the course of treatment planning and radiotherapy. Target and OAR contours were available from MDACC. A total body contour as depicted in the CT and both lungs were segmented automatically, in both cases the CTV was excluded for evaluation. Contours were propagated from the reference phase (end-exhale) of the first 4DCT to all following 4DCTs by deformable image registration (DIR) using the software Plastimatch [7]. Quantitative and qualitative controls of the DIR were carried out [8]. In a multicentric study, the inaccuracy of Plastimatch in the thorax was 2.0 mm [9]. Subsequently, contours were also propagated to all other phases of the respective CTs [10]. Details of the patients can be found in Table 1.
Treatment planning and simulation The treatment was based on the hypofractionated photon therapy scheme of Greco et al. [11] with a single fraction dose of 24 Gy, or a biologically effective dose (BED) of 120 Gy assuming an a/b of 6. The local effect model (LEM) version IV [12] was used to compute relative biological effective (RBE) doses. To exploit the available 5 follow-up CTs for each patient, a fractionated dose with an equal BED of 5 9.4 Gy(RBE) was simulated. For each patient, 2 or 3 carbon ion fields were selected and optimized as single field uniform dose (SFUD) on the first 4DCT, see Table 1. The methodology for creating and delivering a 4D-Rescanning plan was described elsewhere [3,4]. Briefly, on each CT phase one treatment plan was optimized using a common raster point grid, that is using identical energy slices and spot positions. Each plan is thus tailored to the moving target, including the correct ranges from the CT phase. For the scope of this paper, a perfectly synchronized delivery was assumed, i.e. each sub-plan was delivered to its associated phase. Plans were optimized on the CTV and using uniform margins of 3, 5 and 7 mm. In addition, range margins of 2 mmH2O and percent of range were added to each field and each motion phase individually, resulting in a total of 6 margin combinations. For comparison, field-specific range-considering ITVs were computed using the same margin sets [6,13]. Also here, isotropic margins were added to the CTV, and subsequently the ITV was computed, so that range changes within the margins were taken into account. For a fair comparison to the perfectly synchronized 4D-optimized plans, interplay was not considered by delivering a uniform 10% of the spot weight to each motion phase. For the simulation on the weekly 4DCTs, the target point was shifted to the center of mass of the respective CTV, mimicking a rigid translation for patient setup.
Data evaluation The tumor motion was evaluated on each 4DCT from the average DIR vector length between end-exhale and end-inhale (CTV amplitude), and between end-exhale and each motion phase to assess variability over the weekly CTs. The water-equivalent thickness (WET) of each CTV voxel was computed for each field in each motion phase of each 4D-CT. For statistical evaluation, absolute differences of the averages over the CTV of both motion amplitude and WET of each phase of each weekly 4DCT to the planning 4DCT were used. Target coverage was assessed by V95 and D95, with V95 > 95% judged as sufficient target dose. The dose homogeneity was expressed as D5-D95, and conformity with the conformity number CN [15]. Doses in both lung and total body were evaluated excluding the CTV. Differences were assessed with a paired t-test, with p < 0.05 considered as statistically significant. Exploratory regression analysis was used to assess correlations between target coverage and motion differences, range differences, tumor size and 4DCT phase. Results are reported as the Pearson correlation coefficient r or the explained variance r2. Results Motion and water-equivalent thickness variability The inhale to exhale amplitude varied considerably over the 6 4DCTs, see Table 1. For the two patients with larger motion (>10 mm at week 1) changes of more than 5 mm were observed. Changes in WET were largest for the patient with largest motion P4, but also exceeded 5 mm for P1, the patient with the initially smallest amplitude. Changes in WET were not correlated to changes in amplitude. For P4, WET was consistently smaller in all subsequent 4DCTs, while for the other patients, both positive and negative changes were observed. Margins and dose coverage Table 1 shows the margins necessary to achieve an adequate dose coverage (V95 > 95%) in the accumulated dose of weeks 2–6. The margin size varies considerably, with 3 mm isotropic margins sufficient for P3, but 7 mm plus additional range margins necessary for P2 and P4. The 4D-dose distribution for P4 is shown in Fig. 1, both for the planning CT as well as the accumulated dose of weeks 2–6 on the planning CT. As expected, the additional variability of the fractions leads to a blurring of the dose with a diminished volume of full target coverage (red), and slightly expanded region of lower doses outside the target.
Table 1 Characteristics of the 4 patients included in the study, as well as the margins necessary to achieve dose coverage in weeks 2–6. The absolute difference of range to the target (abs DRange) was calculated for each motion phase between each week and week 1. Planning 4DCT (week 1)
Fraction 4DCTs (weeks 2–6)
Patient
Tumor location
Fields
CTV amplitude [mm]
CTV size [cc]
CTV amplitude (min–max) [mm]
abs DRange: Week n week 1 (median, range) [mm H2O]
Necessary margins V95 > 95% [mm + mm, %]
P1 P2 P3 P4
Left upper lobe Right lower lobe Left upper lobe Left lower lobe
3 3 2 3
3.3 12.6 5.6 22.2
236.5 160.2 44.7 125.3
2.8–3.9 6.6–15.9 2.1–5.4 20.6–27.5
2.2 4.3 1.6 6.9
3+2 7+2 3 7+2
(1.3–5.9) (1.3–6.3) (0.8–3.0) (4.4–11.2)
C. Graeff / Radiotherapy and Oncology 122 (2017) 387–392
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Fig. 1. Comparison of 4D dose distribution resulting from 4D-optimization (panels A + C) and ITV-plans (B + D) for Patient 4, on the planning 4DCT (top row, A + B) and accumulated dose from all weekly 4DCTs (bottom row, C + D).
The impact of the different margin sizes and additional range margins is depicted in Supplementary Fig. 1 for P2 and P4, the patients with initial motion >10 mm. The range margins are of considerable importance, especially for P4, where 7 mm isotropic margins alone resulted in comparable dose coverage as 3 mm isotropic plus range margins. As the isotropic margins were not waterequivalent, their extent in beam’s eye view in the low density lung tissue is effectively rather small. Correlation of dose coverage to motion variability To study the effect of motion and WET variability, dose coverage for the 4D-Rescanning plans without margins was considered. Fig. 2 shows the strong correlation of dose coverage to changes in WET, explaining 63% of the variance as opposed to only 23% explained by changes in the motion amplitude. The average range change for each 4DCT shows an even higher r2 = 0.71, indicating interfractional effects such as patient setup or anatomy changes rather than intrafractional variation dominates. A multi-variate linear regression model of absolute motion and WET differences increases the r2 to 0.8. All regressions were highly significant (p < 0.0001).
superior-inferior motion amplitude of the tumor that was included in the ITV, see also the stomach DVH in Fig. 3D. In general, the ITV plans resulted in minor overdose but otherwise comparable target coverage. As depicted in the DVHs for the entire 4DCT (Fig. 3B) and the ipsilateral lung (Fig. 3C), 4DRescanning resulted in an amplitude-dependent lower dose outside the target. Patients 2 and 4 with the larger amplitudes showed a larger difference. For P4, this effect is less visible for the lung, as the excessive dose mostly extends into the stomach, i.e. inferior of the target situated close to the diaphragm, see Fig. 3D. It should be noted that the dose to the contralateral lung was minimal for all cases (V20 = 0 for P2–4, and 7.0%/8.4% for P1 using 4Doptimization/ITV, respectively). The mean total body dose excluding the CTV was reduced for all patients when using 4D-optimization, the ratio 4D to ITV being 95.5%, 85.2%, 83.9%, and 78.3%, for patients P1-P4, respectively. Comparable findings to the accumulated dose were observed for the dose in each weekly 4DCT. Target coverage was comparable for ITV and 4D-Rescanning (difference n.s.), but conformity (p < 0.001) and dose homogeneity (D5-D95, p < 0.001) were significantly better, see Fig. 4. The better homogeneity can be explained by the 10 independently optimized plans used for 4D-Rescanning which resulted in a smoothed dose distribution.
Comparison of 4D-Rescanning and ITV plans Values for dose coverage, homogeneity, conformity and the dose outside the target are given in Table 2, both for the planning 4DCT and the accumulated dose of all CTs on the planning CT. An example for the difference of 4D-Rescanning and ITV is given in Fig. 1. Especially the dose gradient surrounding the high dose area was considerably larger both on the planning CT as well as for the accumulated dose in case of the ITV plans. In patient P4, the 4D-Rescanning plans essentially spared the stomach completely, while it received considerable dose due to the large
Discussion This study is the first to investigate 4D-optimization in the context of interfractional changes using sequential 4DCTs. For all patients adequate target coverage could be achieved, also in the presence of large changes both in range to the target and motion amplitude. The strategy of 4D-Rescanning uses independent optimizations for each motion phase, so that internal gradients between motion
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Robustness of 4D-optimization in ion beam therapy
Fig. 2. Correlation of the absolute differences between the phases of the planning CT and of each weekly CT for both range (panel A) and motion (C) to target coverage V95. V95 is slightly better predicted by the weekly average of range differences (B). A multivariate linear regression model of absolute motion difference and weekly average range differences gives an excellent prediction of V95 (D). Dashed regression lines are shown (except panel D: y = x).
Table 2 Dose characteristics on the planning 4DCT and of the accumulated dose of weeks 2–6 on the planning 4DCT. All values are percent of the planned dose (9.4 Gy(RBE), week 1) or the total dose (47 Gy(RBE), week 2–6), or percent of the respective volume. Patient
Mode
Planning 4DCT (week 1)
Accumulated dose (weeks 2–6)
V95
D95
D5-D95
CN
Body V20
Lung V20
V95
D95
D5-D95
CN
Body V20
Lung V20
P1
4D ITV
100.0 100.0
98.9 98.7
2.6 5.4
49.3 47.3
8.6 9.2
22.0 23.5
99.9 99.9
99.0 99.0
1.9 4.3
53.4 49.6
9.5 9.8
22.9 24.1
P2
4D ITV
100.0 99.1
99.0 97.3
2.3 8.4
41.0 38.7
5.4 6.4
13.4 14.9
98.1 98.0
97.2 96.7
3.7 8.8
47.5 41.6
6.1 7.0
15.3 16.7
P3
4D ITV
100.0 100.0
99.0 99.1
1.9 1.9
39.9 30.6
1.9 2.2
5.6 6.1
99.5 100.0
97.4 99.0
3.4 1.9
50.3 34.9
2.0 2.3
5.6 6.1
P4
4D ITV
100.0 100.0
99.0 99.3
1.9 3.3
46.7 44.8
6.7 9.1
8.6 11.0
96.2 96.5
96.4 96.4
4.6 6.6
58.7 57.4
8.0 9.7
9.2 10.2
phases are avoided. This helps to make the delivery robust against variations, and simple margins sufficient for motion mitigation. It could also be combined with robust optimization techniques as done by Liu et al. [2], but it is essentially a conformal technique, while the strategy of Liu et al. in essence resembles an ITV treatment. The necessary margin size varied considerably, with larger margins necessary for patients with larger initial target motion. For patient P3, who showed very little variability over the weekly 4DCTs, 3 mm isotropic margins were sufficient to achieve target coverage. On the other hand, for patients P2 and P4, with initial motion amplitude >10 mm, and considerable interfraction variation, isotropic margins of 7 mm and additional range margins were necessary. The reduction in target coverage was mostly determined by changes in WET over the course of treatment, which is not available at the planning stage. Multiple imaging or other anal-
yses such as motion traces might be helpful to estimate potentially necessary margins. Due to the low number of patients, no general conclusions should be drawn at this time. Studies including interfractional changes are rare for moving targets, as the required 4D image sequences are rare, also due to the high imaging dose exposure of up to 30 mSv [16]. Most planning studies focus on single 4DCTs, which severely limits the clinical applicability. Especially for particle therapy, the importance of WET changes has to be considered [17,18]. For thoracic or abdominal targets with a moving and deformable anatomy, using a single 4DCT both for planning and simulation eliminates interfractional effects. This kind of variability is also difficult to study using even sophisticated thorax phantoms [19], which still lack the mobility of the human torso and abdomen. Indeed in this study, interfractional WET changes caused a larger degradation in dose coverage as compared to changes in motion amplitude. This underlines the
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Fig. 3. DVHs from the dose in weeks 2–6 accumulated to the planning 4DCT of the 4 patients for the CTV (panel A), total body volume depicted on the 4DCTs (B), and the ipsilateral lung (C). Panel (D) shows the DVH of the stomach for patient 4 only. Solid lines show the 4D-optimized plans, dashed lines the ITV plans.
Fig. 4. Target coverage (V95, D95), dose conformity (CN) and homogeneity (D5–D95) for 4D-optimized and ITV irradiations in each fraction (week 2–6) for the margins stated in Table 1. Target coverage shows no significant differences, but conformity and homogeneity are significantly better in 4D-optimization (*: p < 0.001).
importance of careful patient setup, and also especially for 3D imaging at the treatment site, which facilitates identifying changes in the beam entry path due to deformed anatomy. Even more interesting are methods directly imaging WET such as particle radiography or computed tomography [20,21], or methods to detect particle range in the patient, such as prompt gamma [22] and particle emission [23] or in-beam PET [24]. In the comparison between 4D-optimized and ITV plans, 4Doptimization consistently resulted in lower normal tissue exposure. This benefit was small especially for P1, with a comparably large tumor but little motion, but more significant for patient P2 and P4. For larger motions, OARs situated in the main motion direction of the target (i.e. usually inferior-superior) can be spared most effectively due to the missing ITV margins, as illustrated for the stomach for P4. Patients suitable for the more complex
4D-optimization strategy should thus be carefully selected. Possible candidates could include patients with a large motion and associated range change, patients with critical OAR otherwise situated in an ITV, and patients who are either not able to cooperate in simpler clinical motion compensation strategies such as deep-inspiration breath-hold [25] or where a gating strategy would lead to prohibitively long irradiation times. This study has limitations. For each time point, only a single 4DCT was available, so that a repeating breathing cycle had to be used for 4D dose calculation. Irregular breathing would require longer image sequences as potentially available from 4D-MRI [26]. Also, the 4DCTs were taken weekly over the course of radiotherapy, so that interfractional changes are probably overstated as compared to a day-to-day fractionation scheme as simulated here. Finally, an ideal delivery was assumed with each treatment plan being delivered to its associated phase. In practice, the accuracy of the motion detection as well as physical properties of the beam delivery system would have to be considered. Motion detection is still a major research field, but promising approaches were realized, showing sufficient accuracy to support 4D-optimization [27–29]. Realistic modeling of measurement delays and errors is complex though and will be subject of a later study. For a fair comparison to the ITV plan, interplay was neglected. In practice, both strategies will thus lead to slightly worse results. In conclusion, 4D-optimization for scanned carbon ions seems feasible also for variable breathing conditions and including interfractional variations. The margins required were quite large, but also a more conservative ITV strategy required similar margins, indicating that more careful patient positioning for treatment than for the available imaging data sets is necessary. More studies with a larger patient population will be needed to verify these results and to see if patient-specific margins can be used. Given the large difference between patient’s margins, this appears to be a sensible option. In addition, future studies need to identify patient cohorts showing a sufficient clinical benefit from employing the technically demanding 4D-optimization strategy.
Conflicts of interest Dr. Graeff has no conflicts of interest to report.
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Robustness of 4D-optimization in ion beam therapy
Acknowledgements Dr. Romain Brevet and Dr. Kristjan Anderle were extremely helpful in providing the non-rigid registration maps. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.radonc.2016.12. 017. References [1] Bert C, Durante M. Motion in radiotherapy: particle therapy. Phys Med Biol 2011;56. R113-R44. [2] Liu W, Schild SE, Chang JY, Liao Z, Chang YH, Wen Z, et al. Exploratory study of 4D versus 3D robust optimization in intensity modulated proton therapy for lung cancer. Int J Radiat Oncol Biol Phys 2015. [3] Graeff C, Luchtenborg R, Eley JG, Durante M, Bert C. A 4D-optimization concept for scanned ion beam therapy. Radiother Oncol 2013;109:419–24. [4] Graeff C. Motion mitigation in scanned ion beam therapy through 4Doptimization. Phys Med 2014;30:570–7. [5] Eley JG, Newhauser WD, Luchtenborg R, Graeff C, Bert C. 4D optimization of scanned ion beam tracking therapy for moving tumors. Phys Med Biol 2014;59:3431–52. [6] Rietzel E, Bert C. Respiratory motion management in particle therapy. Med Phys 2010;37:449–60. [7] Shackleford JA, Kandasamy N, Sharp GC. On developing B-spline registration algorithms for multi-core processors. Phys Med Biol 2010;55:6329–51. [8] Anderle K. In silico comparison of photons versus carbon ions in single fraction therapy of lung cancer [Dissertation]. Darmstadt: Technical University Darmstadt; 2016. [9] Brock KK. Results of a multi-institution deformable registration accuracy study (MIDRAS). Int J Radiat Oncol Biol Phys 2010;76:583–96. [10] Brevet R, Richter D, Graeff C, Durante M, Bert C. Treatment parameters optimization to compensate for interfractional anatomy variability and intrafractional tumor motion. Front Oncol 2015;5:291. [11] Greco C, Zelefsky MJ, Lovelock M, Fuks Z, Hunt M, Rosenzweig K, et al. Predictors of local control after single-dose stereotactic image-guided intensity-modulated radiotherapy for extracranial metastases. Int J Radiat Oncol Biol Phys 2011;79:1151–7. [12] Elsässer T, Weyrather WK, Friedrich T, Durante M, Iancu G, Kramer M, et al. Quantification of the relative biological effectiveness for ion beam radiotherapy: direct experimental comparison of proton and carbon ion beams and a novel approach for treatment planning. Int J Radiat Oncol Biol Phys 2010;78:1177–83. [13] Graeff C, Durante M, Bert C. Motion mitigation in intensity modulated particle therapy by internal target volumes covering range changes. Med Phys 2012;39:6004–13.
[14] Richter D, Schwarzkopf A, Trautmann J, Kramer M, Durante M, Jakel O, et al. Upgrade and benchmarking of a 4D treatment planning system for scanned ion beam therapy. Med Phys 2013;40:051722. [15] van’t Riet A, Mak AC, Moerland MA, Elders LH, van der Zee W. A conformation number to quantify the degree of conformality in brachytherapy and external beam irradiation: application to the prostate. Int J Radiat Oncol Biol Phys 1997;37:731–6. [16] Matsuzaki Y, Fujii K, Kumagai M, Tsuruoka I, Mori S. Effective and organ doses using helical 4DCT for thoracic and abdominal therapies. J Radiat Res 2013;54:962–70. [17] Mori S, Dong L, Starkschall G, Mohan R, Chen GT. A serial 4DCT study to quantify range variations in charged particle radiotherapy of thoracic cancers. J Radiat Res 2014;55:309–19. [18] Mori S, Lu HM, Wolfgang JA, Choi NC, Chen GT. Effects of interfractional anatomical changes on water-equivalent pathlength in charged-particle radiotherapy of lung cancer. J Radiat Res 2009;50:513–9. [19] Steidl P, Richter D, Schuy C, Schubert E, Haberer T, Durante M, et al. A breathing thorax phantom with independently programmable 6D tumour motion for dosimetric measurements in radiation therapy. Phys Med Biol 2012;57:2235–50. [20] Arbor N, Dauvergne D, Dedes G, Letang JM, Parodi K, Quinones CT, et al. Monte Carlo comparison of x-ray and proton CT for range calculations of proton therapy beams. Phys Med Biol 2015;60:7585–99. [21] Poludniowski G, Allinson NM, Evans PM. Proton radiography and tomography with application to proton therapy. Br J Radiol 2015;88:20150134. [22] Richter C, Pausch G, Barczyk S, Priegnitz M, Keitz I, Thiele J, et al. First clinical application of a prompt gamma based in vivo proton range verification system. Radiother Oncol 2016. [23] Piersanti L, Bellini F, Bini F, Collamati F, De Lucia E, Durante M, et al. Measurement of charged particle yields from PMMA irradiated by a 220 MeV/ u (12)C beam. Phys Med Biol 2014;59:1857–72. [24] Tian Y, Stutzer K, Enghardt W, Priegnitz M, Helmbrecht S, Bert C, et al. Experimental investigation of irregular motion impact on 4D PET-based particle therapy monitoring. Phys Med Biol 2016;61. N20-34. [25] Josipovic M, Persson GF, Dueck J, Bangsgaard JP, Westman G, Specht L, et al. Geometric uncertainties in voluntary deep inspiration breath hold radiotherapy for locally advanced lung cancer. Radiother Oncol 2016;118:510–4. [26] Boye D, Lomax T, Knopf A. Mapping motion from 4D-MRI to 3D-CT for use in 4D dose calculations: a technical feasibility study. Med Phys 2013;40:061702. [27] Poulsen PR, Worm ES, Petersen JB, Grau C, Fledelius W, Hoyer M. Kilovoltage intrafraction motion monitoring and target dose reconstruction for stereotactic volumetric modulated arc therapy of tumors in the liver. Radiother Oncol 2014;111:424–30. [28] Fassi A, Seregni M, Riboldi M, Cerveri P, Sarrut D, Ivaldi GB, et al. Surrogatedriven deformable motion model for organ motion tracking in particle radiation therapy. Phys Med Biol 2015;60:1565–82. [29] Rydhog JS, Mortensen SR, Larsen KR, Clementsen P, Jolck RI, Josipovic M, et al. Liquid fiducial marker performance during radiotherapy of locally advanced non small cell lung cancer. Radiother Oncol 2016.
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Radiotherapy and Oncology journal homepage: www.thegreenjournal.com
Particle therapy in lung cancer
Robustness of 4D-optimized scanned carbon ion beam therapy against interfractional changes in lung cancer Christian Graeff ⇑ GSI Helmholzzentrum für Schwerionenforschung GmbH, Darmstadt, Germany
a r t i c l e
i n f o
Article history: Received 6 September 2016 Received in revised form 16 November 2016 Accepted 2 December 2016 Available online 7 January 2017 Keywords: Ion beam therapy Charged particle therapy Moving targets 4D-optimization Interfractional changes Lung cancer
a b s t r a c t Background and purpose: Moving targets could be conformally treated with actively scanned carbon ion beams using 4D-optimization. As this heavily exploits 4D-CTs, an important question is whether the conformity also upholds in the context of interfractional changes, i.e. variable positioning, anatomy and breathing patterns. Materials and methods: In 4 lung cancer patients, 6 weekly 4D-CTs were available. 4D-CTs and their phases were non-rigidly registered to propagate contours and 4D-doses. On the first 4D-CT, a 4Doptimized plan delivering a uniform dose to each motion phase (total dose 9.4 Gy(RBE)) was simulated, as well as an ITV plan for comparison. On the five following 4D-CTs, 4D-dose was forward calculated and evaluated for target coverage and conformity. Variable uniform (3–7 mm) and range margins (2 mm/%) were investigated. Results: For all patients, target coverage (V95 > 95% accumulated over 5 fractions) could be achieved, but with variable margin size weakly depending on motion amplitude and range changes. The same margins were also necessary for ITV plans, which lead to lower conformity and higher integral doses. Conclusion: 4D-optimization appears feasible also under interfractional changes and maintains a dosimetric advantage over less conformal ITV irradiations. Further studies are needed to identify patients benefiting most from the technically more complex 4D-optimization. Ó 2016 Elsevier Ireland Ltd. All rights reserved. Radiotherapy and Oncology 122 (2017) 387–392
The treatment of moving targets with scanned ion beams is challenging, both due to interplay effects and changes in the water-equivalent thickness (WET) to the target [1]. This latter effect is especially severe in lung cancer due to the large density differences present. Motion compensation through 4Doptimization, i.e. on the entire 4DCT, can incorporate both target motion and WET changes in the treatment plan [2]. By calculating a plan for each motion phase, the delivered dose is highly conformal to the target even in the face of complex tumor geometries and large motions. Such a 4D-treatment plan requires a delivery synchronized to the patient motion, though [3]. A promising strategy of 4D-optimization is to optimize a uniform dose to each motion phase [4], though this eliminates the possibility to exploit target motion for organ at risk (OAR) sparing [5]. The homogeneous doses delivered to each of typically 10 motion phases induce a rescanning effect. This helps to mitigate random errors such as variations in the breathing cycle; hence the method will be called 4D-Rescanning for the remainder of this ⇑ Address: Planckstrasse 1, D-64291 Darmstadt, Germany. E-mail address: [email protected] http://dx.doi.org/10.1016/j.radonc.2016.12.017 0167-8140/Ó 2016 Elsevier Ireland Ltd. All rights reserved.
paper. Still, a major issue of 4D-optimization in general is the fact that the 4DCT available for planning is not necessarily representative for the later treatment situation. An overfitting of the treatment plan on the planning 4DCT might thus even be harmful if the real patient motion deviates strongly. The aim of this paper is to investigate in a treatment planning study (a) whether 4D-Rescanning is capable of delivering dose over a treatment course with variable breathing and patient positions. (b) the necessary margins for this purpose and if there is a relation of margin size to motion amplitude in the initial planning 4DCT. (c) if margins sufficient to ensure target dose still give an advantage in terms of conformity over an ITV strategy [6]. To address these questions, 4D-optimized treatment plans were computed on the first and forward-calculated on the following 4DCTs of a sequential dataset of lung cancer patients.
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Robustness of 4D-optimization in ion beam therapy
All optimizations and dose calculations were carried out with TRiP4D, which uses a pencil beam algorithm with multiple Coulomb scattering [14].
Material and methods Patient data A set of 4 NSCLC patients with weekly sequential 4DCTs was available from MD Anderson Cancer Center (MDACC, Houston, Tx). The 4DCTs (120 kV, 500 mm FOV, 2.5 mm slice thickness, 10 motion phases) were taken over the course of treatment planning and radiotherapy. Target and OAR contours were available from MDACC. A total body contour as depicted in the CT and both lungs were segmented automatically, in both cases the CTV was excluded for evaluation. Contours were propagated from the reference phase (end-exhale) of the first 4DCT to all following 4DCTs by deformable image registration (DIR) using the software Plastimatch [7]. Quantitative and qualitative controls of the DIR were carried out [8]. In a multicentric study, the inaccuracy of Plastimatch in the thorax was 2.0 mm [9]. Subsequently, contours were also propagated to all other phases of the respective CTs [10]. Details of the patients can be found in Table 1.
Treatment planning and simulation The treatment was based on the hypofractionated photon therapy scheme of Greco et al. [11] with a single fraction dose of 24 Gy, or a biologically effective dose (BED) of 120 Gy assuming an a/b of 6. The local effect model (LEM) version IV [12] was used to compute relative biological effective (RBE) doses. To exploit the available 5 follow-up CTs for each patient, a fractionated dose with an equal BED of 5 9.4 Gy(RBE) was simulated. For each patient, 2 or 3 carbon ion fields were selected and optimized as single field uniform dose (SFUD) on the first 4DCT, see Table 1. The methodology for creating and delivering a 4D-Rescanning plan was described elsewhere [3,4]. Briefly, on each CT phase one treatment plan was optimized using a common raster point grid, that is using identical energy slices and spot positions. Each plan is thus tailored to the moving target, including the correct ranges from the CT phase. For the scope of this paper, a perfectly synchronized delivery was assumed, i.e. each sub-plan was delivered to its associated phase. Plans were optimized on the CTV and using uniform margins of 3, 5 and 7 mm. In addition, range margins of 2 mmH2O and percent of range were added to each field and each motion phase individually, resulting in a total of 6 margin combinations. For comparison, field-specific range-considering ITVs were computed using the same margin sets [6,13]. Also here, isotropic margins were added to the CTV, and subsequently the ITV was computed, so that range changes within the margins were taken into account. For a fair comparison to the perfectly synchronized 4D-optimized plans, interplay was not considered by delivering a uniform 10% of the spot weight to each motion phase. For the simulation on the weekly 4DCTs, the target point was shifted to the center of mass of the respective CTV, mimicking a rigid translation for patient setup.
Data evaluation The tumor motion was evaluated on each 4DCT from the average DIR vector length between end-exhale and end-inhale (CTV amplitude), and between end-exhale and each motion phase to assess variability over the weekly CTs. The water-equivalent thickness (WET) of each CTV voxel was computed for each field in each motion phase of each 4D-CT. For statistical evaluation, absolute differences of the averages over the CTV of both motion amplitude and WET of each phase of each weekly 4DCT to the planning 4DCT were used. Target coverage was assessed by V95 and D95, with V95 > 95% judged as sufficient target dose. The dose homogeneity was expressed as D5-D95, and conformity with the conformity number CN [15]. Doses in both lung and total body were evaluated excluding the CTV. Differences were assessed with a paired t-test, with p < 0.05 considered as statistically significant. Exploratory regression analysis was used to assess correlations between target coverage and motion differences, range differences, tumor size and 4DCT phase. Results are reported as the Pearson correlation coefficient r or the explained variance r2. Results Motion and water-equivalent thickness variability The inhale to exhale amplitude varied considerably over the 6 4DCTs, see Table 1. For the two patients with larger motion (>10 mm at week 1) changes of more than 5 mm were observed. Changes in WET were largest for the patient with largest motion P4, but also exceeded 5 mm for P1, the patient with the initially smallest amplitude. Changes in WET were not correlated to changes in amplitude. For P4, WET was consistently smaller in all subsequent 4DCTs, while for the other patients, both positive and negative changes were observed. Margins and dose coverage Table 1 shows the margins necessary to achieve an adequate dose coverage (V95 > 95%) in the accumulated dose of weeks 2–6. The margin size varies considerably, with 3 mm isotropic margins sufficient for P3, but 7 mm plus additional range margins necessary for P2 and P4. The 4D-dose distribution for P4 is shown in Fig. 1, both for the planning CT as well as the accumulated dose of weeks 2–6 on the planning CT. As expected, the additional variability of the fractions leads to a blurring of the dose with a diminished volume of full target coverage (red), and slightly expanded region of lower doses outside the target.
Table 1 Characteristics of the 4 patients included in the study, as well as the margins necessary to achieve dose coverage in weeks 2–6. The absolute difference of range to the target (abs DRange) was calculated for each motion phase between each week and week 1. Planning 4DCT (week 1)
Fraction 4DCTs (weeks 2–6)
Patient
Tumor location
Fields
CTV amplitude [mm]
CTV size [cc]
CTV amplitude (min–max) [mm]
abs DRange: Week n week 1 (median, range) [mm H2O]
Necessary margins V95 > 95% [mm + mm, %]
P1 P2 P3 P4
Left upper lobe Right lower lobe Left upper lobe Left lower lobe
3 3 2 3
3.3 12.6 5.6 22.2
236.5 160.2 44.7 125.3
2.8–3.9 6.6–15.9 2.1–5.4 20.6–27.5
2.2 4.3 1.6 6.9
3+2 7+2 3 7+2
(1.3–5.9) (1.3–6.3) (0.8–3.0) (4.4–11.2)
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Fig. 1. Comparison of 4D dose distribution resulting from 4D-optimization (panels A + C) and ITV-plans (B + D) for Patient 4, on the planning 4DCT (top row, A + B) and accumulated dose from all weekly 4DCTs (bottom row, C + D).
The impact of the different margin sizes and additional range margins is depicted in Supplementary Fig. 1 for P2 and P4, the patients with initial motion >10 mm. The range margins are of considerable importance, especially for P4, where 7 mm isotropic margins alone resulted in comparable dose coverage as 3 mm isotropic plus range margins. As the isotropic margins were not waterequivalent, their extent in beam’s eye view in the low density lung tissue is effectively rather small. Correlation of dose coverage to motion variability To study the effect of motion and WET variability, dose coverage for the 4D-Rescanning plans without margins was considered. Fig. 2 shows the strong correlation of dose coverage to changes in WET, explaining 63% of the variance as opposed to only 23% explained by changes in the motion amplitude. The average range change for each 4DCT shows an even higher r2 = 0.71, indicating interfractional effects such as patient setup or anatomy changes rather than intrafractional variation dominates. A multi-variate linear regression model of absolute motion and WET differences increases the r2 to 0.8. All regressions were highly significant (p < 0.0001).
superior-inferior motion amplitude of the tumor that was included in the ITV, see also the stomach DVH in Fig. 3D. In general, the ITV plans resulted in minor overdose but otherwise comparable target coverage. As depicted in the DVHs for the entire 4DCT (Fig. 3B) and the ipsilateral lung (Fig. 3C), 4DRescanning resulted in an amplitude-dependent lower dose outside the target. Patients 2 and 4 with the larger amplitudes showed a larger difference. For P4, this effect is less visible for the lung, as the excessive dose mostly extends into the stomach, i.e. inferior of the target situated close to the diaphragm, see Fig. 3D. It should be noted that the dose to the contralateral lung was minimal for all cases (V20 = 0 for P2–4, and 7.0%/8.4% for P1 using 4Doptimization/ITV, respectively). The mean total body dose excluding the CTV was reduced for all patients when using 4D-optimization, the ratio 4D to ITV being 95.5%, 85.2%, 83.9%, and 78.3%, for patients P1-P4, respectively. Comparable findings to the accumulated dose were observed for the dose in each weekly 4DCT. Target coverage was comparable for ITV and 4D-Rescanning (difference n.s.), but conformity (p < 0.001) and dose homogeneity (D5-D95, p < 0.001) were significantly better, see Fig. 4. The better homogeneity can be explained by the 10 independently optimized plans used for 4D-Rescanning which resulted in a smoothed dose distribution.
Comparison of 4D-Rescanning and ITV plans Values for dose coverage, homogeneity, conformity and the dose outside the target are given in Table 2, both for the planning 4DCT and the accumulated dose of all CTs on the planning CT. An example for the difference of 4D-Rescanning and ITV is given in Fig. 1. Especially the dose gradient surrounding the high dose area was considerably larger both on the planning CT as well as for the accumulated dose in case of the ITV plans. In patient P4, the 4D-Rescanning plans essentially spared the stomach completely, while it received considerable dose due to the large
Discussion This study is the first to investigate 4D-optimization in the context of interfractional changes using sequential 4DCTs. For all patients adequate target coverage could be achieved, also in the presence of large changes both in range to the target and motion amplitude. The strategy of 4D-Rescanning uses independent optimizations for each motion phase, so that internal gradients between motion
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Robustness of 4D-optimization in ion beam therapy
Fig. 2. Correlation of the absolute differences between the phases of the planning CT and of each weekly CT for both range (panel A) and motion (C) to target coverage V95. V95 is slightly better predicted by the weekly average of range differences (B). A multivariate linear regression model of absolute motion difference and weekly average range differences gives an excellent prediction of V95 (D). Dashed regression lines are shown (except panel D: y = x).
Table 2 Dose characteristics on the planning 4DCT and of the accumulated dose of weeks 2–6 on the planning 4DCT. All values are percent of the planned dose (9.4 Gy(RBE), week 1) or the total dose (47 Gy(RBE), week 2–6), or percent of the respective volume. Patient
Mode
Planning 4DCT (week 1)
Accumulated dose (weeks 2–6)
V95
D95
D5-D95
CN
Body V20
Lung V20
V95
D95
D5-D95
CN
Body V20
Lung V20
P1
4D ITV
100.0 100.0
98.9 98.7
2.6 5.4
49.3 47.3
8.6 9.2
22.0 23.5
99.9 99.9
99.0 99.0
1.9 4.3
53.4 49.6
9.5 9.8
22.9 24.1
P2
4D ITV
100.0 99.1
99.0 97.3
2.3 8.4
41.0 38.7
5.4 6.4
13.4 14.9
98.1 98.0
97.2 96.7
3.7 8.8
47.5 41.6
6.1 7.0
15.3 16.7
P3
4D ITV
100.0 100.0
99.0 99.1
1.9 1.9
39.9 30.6
1.9 2.2
5.6 6.1
99.5 100.0
97.4 99.0
3.4 1.9
50.3 34.9
2.0 2.3
5.6 6.1
P4
4D ITV
100.0 100.0
99.0 99.3
1.9 3.3
46.7 44.8
6.7 9.1
8.6 11.0
96.2 96.5
96.4 96.4
4.6 6.6
58.7 57.4
8.0 9.7
9.2 10.2
phases are avoided. This helps to make the delivery robust against variations, and simple margins sufficient for motion mitigation. It could also be combined with robust optimization techniques as done by Liu et al. [2], but it is essentially a conformal technique, while the strategy of Liu et al. in essence resembles an ITV treatment. The necessary margin size varied considerably, with larger margins necessary for patients with larger initial target motion. For patient P3, who showed very little variability over the weekly 4DCTs, 3 mm isotropic margins were sufficient to achieve target coverage. On the other hand, for patients P2 and P4, with initial motion amplitude >10 mm, and considerable interfraction variation, isotropic margins of 7 mm and additional range margins were necessary. The reduction in target coverage was mostly determined by changes in WET over the course of treatment, which is not available at the planning stage. Multiple imaging or other anal-
yses such as motion traces might be helpful to estimate potentially necessary margins. Due to the low number of patients, no general conclusions should be drawn at this time. Studies including interfractional changes are rare for moving targets, as the required 4D image sequences are rare, also due to the high imaging dose exposure of up to 30 mSv [16]. Most planning studies focus on single 4DCTs, which severely limits the clinical applicability. Especially for particle therapy, the importance of WET changes has to be considered [17,18]. For thoracic or abdominal targets with a moving and deformable anatomy, using a single 4DCT both for planning and simulation eliminates interfractional effects. This kind of variability is also difficult to study using even sophisticated thorax phantoms [19], which still lack the mobility of the human torso and abdomen. Indeed in this study, interfractional WET changes caused a larger degradation in dose coverage as compared to changes in motion amplitude. This underlines the
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Fig. 3. DVHs from the dose in weeks 2–6 accumulated to the planning 4DCT of the 4 patients for the CTV (panel A), total body volume depicted on the 4DCTs (B), and the ipsilateral lung (C). Panel (D) shows the DVH of the stomach for patient 4 only. Solid lines show the 4D-optimized plans, dashed lines the ITV plans.
Fig. 4. Target coverage (V95, D95), dose conformity (CN) and homogeneity (D5–D95) for 4D-optimized and ITV irradiations in each fraction (week 2–6) for the margins stated in Table 1. Target coverage shows no significant differences, but conformity and homogeneity are significantly better in 4D-optimization (*: p < 0.001).
importance of careful patient setup, and also especially for 3D imaging at the treatment site, which facilitates identifying changes in the beam entry path due to deformed anatomy. Even more interesting are methods directly imaging WET such as particle radiography or computed tomography [20,21], or methods to detect particle range in the patient, such as prompt gamma [22] and particle emission [23] or in-beam PET [24]. In the comparison between 4D-optimized and ITV plans, 4Doptimization consistently resulted in lower normal tissue exposure. This benefit was small especially for P1, with a comparably large tumor but little motion, but more significant for patient P2 and P4. For larger motions, OARs situated in the main motion direction of the target (i.e. usually inferior-superior) can be spared most effectively due to the missing ITV margins, as illustrated for the stomach for P4. Patients suitable for the more complex
4D-optimization strategy should thus be carefully selected. Possible candidates could include patients with a large motion and associated range change, patients with critical OAR otherwise situated in an ITV, and patients who are either not able to cooperate in simpler clinical motion compensation strategies such as deep-inspiration breath-hold [25] or where a gating strategy would lead to prohibitively long irradiation times. This study has limitations. For each time point, only a single 4DCT was available, so that a repeating breathing cycle had to be used for 4D dose calculation. Irregular breathing would require longer image sequences as potentially available from 4D-MRI [26]. Also, the 4DCTs were taken weekly over the course of radiotherapy, so that interfractional changes are probably overstated as compared to a day-to-day fractionation scheme as simulated here. Finally, an ideal delivery was assumed with each treatment plan being delivered to its associated phase. In practice, the accuracy of the motion detection as well as physical properties of the beam delivery system would have to be considered. Motion detection is still a major research field, but promising approaches were realized, showing sufficient accuracy to support 4D-optimization [27–29]. Realistic modeling of measurement delays and errors is complex though and will be subject of a later study. For a fair comparison to the ITV plan, interplay was neglected. In practice, both strategies will thus lead to slightly worse results. In conclusion, 4D-optimization for scanned carbon ions seems feasible also for variable breathing conditions and including interfractional variations. The margins required were quite large, but also a more conservative ITV strategy required similar margins, indicating that more careful patient positioning for treatment than for the available imaging data sets is necessary. More studies with a larger patient population will be needed to verify these results and to see if patient-specific margins can be used. Given the large difference between patient’s margins, this appears to be a sensible option. In addition, future studies need to identify patient cohorts showing a sufficient clinical benefit from employing the technically demanding 4D-optimization strategy.
Conflicts of interest Dr. Graeff has no conflicts of interest to report.
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