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Optimization of a newly defined target volume in fiducial marker-based dynamic tumor-tracking radiotherapy
Physics and Imaging in Radiation Oncology 4 (2017) 1–5
Contents lists available at ScienceDirect
Physics and Imaging in Radiation Oncology journal homepage: www.elsevier.com/locate/phro
Original Research Article
Optimization of a newly defined target volume in fiducial marker-based dynamic tumor-tracking radiotherapy
T
⁎
Yusuke Iizukaa, Yukinori Matsuoa, , Mitsuhiro Nakamuraa, Satoshi Kozawab, Nami Uekic, Takamasa Mitsuyoshia, Takashi Mizowakia, Masahiro Hiraokaa a b c
Department of Radiation Oncology and Image-applied Therapy, Kyoto University Graduate School of Medicine, Kyoto, Japan Division of Clinical Radiology Service, Kyoto University Hospital, Kyoto, Japan Department of Radiation Oncology, Hyogo Prefectural Amagasaki General Medical Center, Amagasaki, Japan
A B S T R A C T Background and purpose: To optimize the selection of fiducial markers used to determine the “internal target volume for tracking” (ITVtracking) for fiducial marker-based dynamic tumor-tracking (DTT) radiotherapy for lung tumors, with four-dimensional 320-row area-detector computed tomography (320-ADCT). Materials and methods: Ten patients with early-stage non-small cell lung carcinomas or metastatic lung tumors were enrolled. After implanting 4 or 5 fiducial markers around the lung tumor, all patients underwent 320-ADCT to determine the coordinates of the tumors and markers. The coordinate origin of each phase CT dataset was translated so that the marker-derived coordinate centers coincided. The ITVtracking was then defined by compositing the gross tumor volumes from all four-dimensional CT phases. We compared the ITVtracking with the typical ITV used in motion-encompassing method. We also compared the following 5 scenarios in selection of fiducial markers to define the coordinate center: a) the closest marker to the tumor, b) the closest two makers, c) the centroid of the all markers, d) the farthest two markers, and e) the farthest marker. Results: The scenario b was the best in 5 patients. The difference of the ITVtracking between the best scenario and b was less than 20% in the other 5 patients. The scenario c was the best in 4 patients. The ITVtracking was smaller than the typical ITV. Conclusion: ITVtracking was reasonable target in DTT radiotherapy. Proper ITVtracking might be created with choosing those midway between the two markers closest to the tumor or in the centroid of the markers.
1. Introduction Stereotactic body radiation therapy (SBRT) is a technique that delivers high-dose radiation to limited areas with high accuracy. It has an excellent local control rate and is an effective alternative treatment for early-stage [1–3] and small metastatic [4,5] lung tumors. As respiratory motion affects the amount of radiation delivered to the target in lung SBRT, appropriate respiratory motion management is recommended. The American Association of Physicists in Medicine task group 76 proposed five methods to control motion: motion-encompassing, respiratory-gating, breath-holding, forced shallow breathing with abdominal compression, and dynamic tumor-tracking (DTT). Of these, DTT is considered the best method for managing respiratory motion with respect to normal tissue irradiation, treatment duration, and patient compliance [6]. Fiducial markers implanted in or near the tumor are often used as internal surrogates for estimating tumor position via respiratory⁎
synchronized irradiation procedures such as respiratory-gating and DTT [7–9]. In general, the markers in these procedures compose a static vector that indicates the target from a representative position; however, the relative positions of the tumor and markers constantly vary during respiration, especially when the markers are distal to the tumor or respiratory motion is large [10–12]. We previously reported DTT-SBRT for lung tumor cases using multiple fiducial markers and with gimbal mounted linac [8]. Unlike the conventional motion-encompassing method, we assumed that DTT is somewhat hampered by geometric uncertainty owing to relative positional variations and tumor deformation during respiration. Numerous reports assessed the clinical outcome of DTT with robotic arm linac using a 5-mm gross tumor volume (GTV)-to-planning target volume (PTV) margin [13–15]. Another study used a 5-mm clinical target volume-to-PTV margin to safely account for geometric uncertainties; this margin size was based on knowledge of the mechanical performance of the gimbal mounted linac [16]. However, despite
Corresponding author at: 54, Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan. E-mail address: [email protected] (Y. Matsuo).
http://dx.doi.org/10.1016/j.phro.2017.10.001 Received 15 June 2017; Received in revised form 4 October 2017; Accepted 11 October 2017 2405-6316/ © 2017 The Authors. Published by Elsevier Ireland Ltd on behalf of European Society of Radiotherapy & Oncology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
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Y. Iizuka et al.
general usage of a 5-mm margin, no theoretical or quantitative method for determining target position via DTT with multiple fiducial markers has been established. Various imaging techniques used for motion-managed target determination in radiation therapy planning include four-dimensional computed tomography (4DCT). This technique accounts for respiratory motion by adding a time axis to conventional three-dimensional (3D) CT and has been widely applied. Drawbacks of 4DCT include frequent misalignments and the presence of motion-created artifacts at the interface between adjacent couch positions [17–19]; consequently, precise determination of target position is often difficult. In addition, it is impossible to determine 3D tumor position using single-source fluoroscopy. Another technique is wide detector CT (e.g., 320-row area-detector CT [320-ADCT]), which has been extensively used in diagnostic cardiology. The greatest advantage of 320-ADCT is that the entire respiratory trajectory of the tumor and markers can be imaged without couch movement. There was no previous study which had evaluated optimal combination of fiducial markers to minimize the target volume in DTT for lung tumor via 320-ADCT. The purpose of this study was two-fold: 1) to discuss the advantage of the internal target volume for tracking (ITVtracking) compared to the internal target volume (ITV) based on motion-encompassing method and 2) to determine the optimal combination of fiducial marker positions for generating ITVtracking, via 320-ADCT.
Fig. 1. The fluoroscopic images of patient 10 show that the relative positions between the tumor (orange circle) and fiducial markers (colored squares) are not static during the respiratory cycle.
when this study was performed. We used as many as markers to create ITVtracking in the clinical case regardless of the tumor size, but we excepted markers which moved in intra- or inter-fraction because they were not fixed in bronchiole. 320-ADCT images were acquired an average of 14 days after implantation of the fiducial markers. This study was approved by our institutional review board, and informed consent was obtained from all participants.
2. Materials and methods 2.1. Concept of ITVtracking
2.3. 320-ADCT acquisition and segmentation This study used a novel target volume definition based on a special coordinate system which was defined by the position of the markers, termed the “marker-derived coordinate” to account for geometric uncertainty in DTT with multiple fiducial markers. Assuming n implanted fiducial markers, the three-dimensional marker-derived coordinate center (P) position was defined as follows:
A 320-slice volumetric CT scanner (320-slice Aquilion ONE; Toshiba Medical Systems, Otawara, Tokyo) was used to scan the tumor and markers for one respiratory cycle. The patients were placed in a supine position with both arms raised and asked to breathe freely during the scanning and we waited for several minutes until their respiratory cycle became stable. Images were acquired in the continuous volume mode (16-cm craniocaudal [CC] coverage per rotation). The scan slice thickness (CC detector row interval) and image slice thickness were 0.5 mm and 1.0 mm, respectively. The CT system has 512 × 512 transverse × 320 CC elements, each approximately 0.5 mm × 0.5 mm, at the center of the rotation. The time for a single rotation was 0.275 s. The cine duration of the scan exceeded the maximum observed respiratory period. The scan settings were 120 kVp and 50 mAs, the voxel size was 512 × 512 (field of view, 400 mm), and a reconstruction filter was used. The respiratory signals were obtained by using a respiratory gating system (AZ-733V; Anzai Medical Co., LTD, Tokyo, Japan). The CT rotation time was the same as that of a respiratory cycle, and the acquired volume was sorted into 10 respiratory phase bins. All images were transferred to the MIM maestro 6.6 software (MIM Software Inc., Cleveland, OH). The GTVs and markers were delineated semi-automatically by using the Hounsfield unit threshold, and their coordinates were then calculated. Maximum intensity projection (MIP) images from ten phases of images without CT center translation were also created, and MIP-based ITVs were created with the composition of GTVs as a target based on the motion-encompassing method.
P= a1p1 + a2p2 + ···+anpn, where ak (1 ≤ k ≤ n) was a weighting coefficient for the kth fiducial marker, and pk was the kth three-dimensional position of the fiducial marker. The order of the markers reflected their distance from the tumor: the marker closest to the tumor was “1,” and the marker farthest from the tumor was “n”. In our previous reported study, P was set as a centroid of the markers and an was 1/n [8]. After determining the marker-derived coordinate center on each phase CT dataset, all phase CT datasets were transported into a reference CT dataset so that the coordinate centers in each phase CT dataset coincided. The ITVtracking was then defined by compositing the GTVs from all of the phase images. We assumed that this target included the positional variation between the coordinate center and the tumor (Fig. 1 and Supplementary Fig. 1). 2.2. Patients Between January 2013 and February 2014, this study enrolled 10 patients with early-stage non-small cell lung carcinomas or metastatic lung tumors who received DTT-SBRT via gimbal mounted linac (Vero4DRT system; formerly MHI-TM2000; Mitsubishi Heavy Industries Ltd., Tokyo, Japan and BrainLab AG, Feldkirchen, Germany) as we previously reported [8]. Two patients who did not receive DTTSBRT because some of their markers had substantially migrated were not included. Four or five fiducial markers (Disposable Gold Marker [FMR-201CR]; Olympus Medical Systems, Tokyo, Japan), each with a diameter of 1.5 mm, were inserted around the tumor 1 week before treatment planning under bronchoscopy guidance. These markers were only wedged in bronchiole and not inserted into the tumor. Our treatment system required at least three markers for DTT-based irradiation
2.4. Determination of the ITVtracking and assessment We evaluated the following five scenarios in selection of fiducial markers used to determine each ITVtracking: a. The point corresponding to the marker closest to the tumor (p1) (a1 = 1) b. The central point between the closest marker (p1) and the second closest marker (p2) to the tumor (a1 = a2 = 1/2) 2
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Y. Iizuka et al.
tracking of lung tumors, and concluded that beacon placement and surrogacy error should be considered during planning and beacon insertion [20]. In DTT with multiple fiducial markers, the geometrical uncertainties due to tumor deformation, rotation of the tumor and markers, and positional variations during the respiratory cycle should be compensated. Isotropic margins cannot fully do so, and therefore, determination of the ITVtracking is clinically important when performing DTT. There are few reports about the target volumes for DTT. Li et al. used a tumor-tracking beam’s eye view for 4D radiotherapy planning, which was highly accurate with a low clinical workload [21]. However, their method for defining the target volume for DTT differed from the method described herein. To our knowledge, no previous studies proposed tumor-tracking strategies that included the positions of fiducial markers. We reported the proper ITVtracking created with scenario a to c was smaller than the general MIP-based ITV. This result indicates the ITVtracking was superior to the general MIP-based ITV in the DTT radiotherapy. To date, no reports have evaluated the relationship between target size and the marker-based location used to determine target size. Since the difference in the ITVtracking values for the scenario a, b, d, and e versus c (the clinical situation) was as high as 94.8%, optimization of the marker position effectively reduces the ITVtracking. Although c is used to determine the ITVtracking in our clinic, it is not always the best choice (Table 2). In all patients, except patient 6, the marker locations producing the smallest ITVtracking were those midway between the two markers closest to the tumor and in the centroid of the markers. In patient 6, the markers were placed far from the tumor, and moved in different directions with affection of a heartbeat, most notably anteriorly and posteriorly. The difference of the volume was less than 10% compared to the two markers closest to the tumor. The centroid of the markers gave the smallest ITVtracking in patient 2, 3, 5 and 9. But the difference of the volume was less than 20% compared to the two markers closest to the tumor. We found that we might create appropriate ITVtracking with selecting those midway between the two markers closest to the tumor or in the centroid of the markers without calculation of coordinates of the markers. The marker closest to the tumor did not give the smallest ITVtracking. Two patients did not receive DTT-SBRT because some of their markers had substantially migrated. The fixation rate of spherical gold markers was reported to be 75–78% in two studies [11,22]. At least two markers are required for DTT-SBRT using the current the Vero4DRT system. There are several approaches to insert the fiducial markers to the lung. Among them, transcutaneous and transbronchial approaches are common. The transcutaneous methods have higher risk of pneumothorax which can cause a delay of the radiotherapy than the transbronchial method, while it allows us to insert the markers very close or inside the tumor [23]. Two limitations of this study warrant discussion. First, the 320ADCT images were acquired in only one respiratory cycle. The duration of the human respiratory cycle is not fixed; the time between and amplitude of each cycle varies [24–26], although the patients were asked to breathe regularly and quietly by the radiological technicians during 320-ADCT acquisition. Second, the end-exhalation phase served as the reference phase in this study. However, Nakamura et al. found that marker-related target localization error was not appreciably higher in the end-exhalation phase than in the mid-ventilation phase [12]. Therefore, variations in the ITVtracking would be small even when the mid-ventilation phase is used. Moreover, severe motion artifacts are commonly observed when 4DCT is performed in the mid-ventilation phase of 4DCT [19]; because fewer motion artifacts occur in the endexhalation phase, it was used in this study. In conclusion, we found that we can create proper ITVtracking with choosing the midway between the two markers closest to the tumor or the centroid of the markers as the coordinate center in DTT
Table 1 Characteristics of the patients and tumors (n = 10). Patient no.
Age (years)
Sex
PS
GTV(cm3)*
Tumor motion (mm)**
Tumor location
No. of markers
1 2 3 4 5 6 7 8 9 10
85 74 85 80 88 84 74 78 77 64
M M F F M M M M M M
0 2 0 1 1 1 1 1 1 0
1.2 20.0 2.0 4.6 2.2 6.4 8.5 3.2 6.6 0.5
31.5 4.2 33.1 37.9 9.1 4.8 5.2 25.3 11.1 7.8
Rt S6 Rt S6 Rt S9 Rt S10 Lt S10 Lt S5 Lt S6 Rt S10 Rt S6 Rt S6
4 5 4 3 5 3 5 5 3 5
Abbreviations: M = male; F = female; PS = Eastern Cooperative Oncology Group performance status; GTV = gross tumor volume; Rt = right lung; Lt = left lung; S = segment. * GTV was measured in the reference CT. ** Tumor motion was calculated with the coordinates of tumor center in the end of inhale and exhale phase in 320-ADCT.
c. The currently clinically applied configuration: the centroid of the markers with ak = 1/k, with 3 ≤ k ≤ 5 d. The central point between the second farthest marker (pn−1) and the farthest marker (pn) from the tumor (an−1 = an = 1/2) e. the point corresponding to the marker farthest from the tumor (pn) (an = 1) Based on the coordinate centers associated with each marker-based location (five scenarios) on each CT dataset (10 CT datasets), each CT center was translated. Thereafter, the translated CT datasets was transposed into the reference CT (end-exhale phase) on the iPlan image 4.1.1 treatment planning system (BrainLAB AG). The iPlan system was used to determine the ITVtracking based on each marker-based location as a composite of the GTV. The differences between the ITVtracking and MIP-based ITV were compared and statistically evaluated with t-test. 3. Results Forty-three markers in 10 patients were evaluated. Table 1 summarizes the characteristics of the patients and tumors and the number of markers per patient. The median GTV size was 3.9 cm3 (range 0.5–8.5 cm3) and median tumor motion was 10.1 mm (range, 4.2–37.9 mm). Table 2 shows the values for MIP-based ITV and five ITVtrackings in each scenario. The median difference in the ITVtracking values in a, b, c, d, and MIP-based ITV was -27.8 to -10% (a positive number indicates the value in ITVtracking was larger). The scenario producing the smallest ITVtracking varied among the patients, and a, b, c, d, and e produced the smallest ITVtracking in 0, 5, 4, 0, and 1 patients respectively. The smallest ITVtracking in these five scenarios was significantly smaller than MIPbased ITV (p value = 0.04). In five patients, the ITVtracking was smaller in any scenario than the MIP-based ITV. 4. Discussion We discussed the concept of ITVtracking and showed that we can create proper ITVtracking with choosing the midway between the two markers closest to the tumor or the centroid of the markers as the coordinate center with 320-ADCT. This appropriate marker selection can make a smaller ITVtracking than a MIP-based ITV. These results are able to be applied to 4DCT using CT with less detectors, because the positional relationship between the tumor and the markers are the same regardless of the number of CT detectors in theory. Hardcastle et al. quantified the geometric accuracy of beacons as surrogates for tumor motion in real-time dynamic multileaf collimator 3
Physics and Imaging in Radiation Oncology 4 (2017) 1–5
Y. Iizuka et al.
Table 2 The volume of the MIP-based ITV and ITVtracking in each scenario. Patient number
1
ITV
a
Vol (cm3)
Vol (cm3) rate (%)
Dis (mm)
Vol (cm3) rate (%)
Dis (mm)
3.5
2.7 −22.9 32.0 −27.1 5.4 −12.9 7.5 −16.7 5.2 −1.9 11.3 −8.9 10.5 −9.4 5.2 −3.7 9.4 −12.1 0.7 −30
11
* 2.6 −25.7 31.1 −29.2 5.0 −19.4 * 7.1 −21.1 5.3 0 10.9 −12.1 * 10.4 −10.3 * 4.2 −22.2 10.6 −1.0 * 0.7 −30
16.3
2
43.9
3
6.2
4
9.0
5
5.3
6
12.4
7
11.6
8
5.4
9
10.7
10
1.0
b
18.6 26.2 19.5 31.3 54.7 14.8 26.3 34.9 25.8
c
24.2 12.3 36.4 61.6 8.0 18.3 27.1 26.8
e
Vol (cm3) rate (%)
Dis (mm)
Vol (cm3) rate (%)
Dis (mm)
Vol (cm3) rate (%)
Dis (mm)
2.9 −17.1 30.1 −31.4 * 4.9 −21.0 8.1 −10 * 4.5 −15.1 10.5 −15.3 11.1 −4.3 4.3 −20.4 * 9.3 −13.1 0.8 −20
15.0
3.0 −14.3 31.7 −27.8 5.3 −14.5 15.6 73.3 5.4 1.9 10.3 −16.9 12.4 6.9 6.2 −14.8 9.3 −13.1 0.9 −10
31.1
3.3 −5.7 34.0 −22.6 5.7 −8.1 15.8 75.6 6.7 26.4 * 10.2 −17.7 14.1 21.6 7.1 −31.5 11.4 6.5 1.0 0
36.2
*
12.1
d
15.7 27.3 32.3 25.0 64.3 23.0 18.4 29.8 32.2
37.8 43.8 56.6 42.5 70.6 61.7 41.5 39.1 53.7
78.1 49.4 70.8 69.0 70.7 64.0 63.1 57.2 57.0
The scenarios to create the ITVtracking in selection of fiducial markers are as follows: a, closest to the tumor (p1); b, the central point between p1 and p2; c, the centroid of the markers used in clinical cases; d, the central point between pn−1 and pn; and e, farthest from the tumor (pn). The percentages in the Vol column indicate the difference in the volume compared to the conventional internal target volume (ITV) based on maximum intensity projection. A positive number indicates the value in ITVtracking was larger. Abbreviations: MIP = maximum intensity projection, ITV = internal target volume, Vol = volume (cm3); Dis = distance between the coordinate center and the tumor (mm). * The smallest tumor volume. [8] Matsuo Y, Ueki N, Takayama K, Nakamura M, Miyabe Y, Ishihara Y, et al. Evaluation of dynamic tumour tracking radiotherapy with real-time monitoring for lung tumours using a gimbal mounted linac. Radiother Oncol 2014;112:360–4. [9] van der Voort van Zyp NC, Hoogeman MS, van de Water S, Levendag PC PC, van der Holt B, Heijimen BJ. Stability of markers used for real-time tumor tracking after percutaneous intrapulmonary placement. Int J Radiat Oncol Biol Phys 2011;81:e75–81. [10] Seppenwoolde Y, Shirato H, Kitamura K, Shimizu S, van Herk M, Lebesque JV, et al. Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. Int J Radiat Oncol Biol Phys 2002;53:822–34. [11] Ueki N, Matsuo Y, Nakamura M, Mukumoto N, Iizuka Y, Miyabe Y, et al. Intra- and interfractional variations in geometric arrangement between lung tumours and implanted markers. Radiother Oncol 2014;110:523–8. [12] Nakamura M, Takamiya M, Akimoto M, Ueki N, Tanabe H, Mukumoto N, et al. Target localization errors from fiducial markers implanted around a lung tumor for dynamic tumor tracking. Physica Med 2015;31:934–41. [13] Collins BT, Erickson K, Reichner CA, Collins SP, Gagnon GJ, Dieterich S, et al. Radical stereotactic radiosurgery with real-time tumor motion tracking in the treatment of small peripheral lung tumors. Radiat Oncol 2007;2:39. [14] Nuyttens JJ, van der Voort van Zyp NC, Praag J J, Aluwini S, van Klaveren RJ, Verhoef C, et al. Outcome of four-dimensional stereotactic radiotherapy for centrally located lung tumors. Radiother Oncol 2012;102:383–7. [15] van der Voort van Zyp NC, Prevost JB, Hoogeman MS, Praag J, Van der Holt B, Levendag PC. Stereotactic radiotherapy with real-time tumor tracking for non-small cell lung cancer: clinical outcome. Radiother Oncol 2009;91:296–300. [16] Depuydt T, Poels K, Verellen D, Engels B, Collen C, Buleteanu M, et al. Treating patients with real-time tumor tracking using the Vero gimbaled linac system: implementation and first review. Radiother Oncol 2014;112:343–51. [17] Fitzpatrick MJ, Starkschall G, Antolak JA, Fu J, Shukla H, Keall PJ, et al. Displacement-based binning of time-dependent computed tomography image data sets. Med Phys 2006;33:235–46. [18] Persson GF, Nygaard DE, Brink C, Jahn JW, Munck af Rosenschold P, Specht L. Deviations in delineated GTV caused by artefacts in 4DCT. Radiother Oncol 2010;96:61–6. [19] Yamamoto T, Langner U, Loo Jr. BW, Shen J, Keall PJ. Retrospective analysis of artifacts in four-dimensional CT images of 50 abdominal and thoracic radiotherapy patients. Int J Radiat Oncol Biol Phys 2008;72:1250–8. [20] Hardcastle N, Booth J, Caillet V, O’Brien R, Haddad C, Crasta C, et al. MO-FG-BA06: electromagnetic beacon insertion in lung cancer patients and resultant surrogacy errors for dynamic MLC tumour tracking. Med Phys 2016;43:3710–1. [21] Li G, Cohen P, Xie H, Low D, Li D, Rimner A. A novel four-dimensional radiotherapy planning strategy from a tumor-tracking beam's eye view. Phys Med Biol 2012;57:7579–98. [22] Imura M, Yamazaki K, Shirato H, Onimaru R, Fujino M, Harada T, et al. Insertion and fixation of fiducial markers for setup and tracking of lung tumors in radiotherapy. Int J Radiat Oncol Biol Phys 2005;63:1442–7. [23] Kupelian PA, Forbes A, Willoughby TR, Wallace K, Manon RR, Meeks SL, et al.
radiotherapy. However, we should be careful about patients with their fiducial markers locating far from the tumor. Conflict of interest Authors and authors’ institutions have no conflict of interest. Acknowledgement This study was partially funded by a Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research (A) 25253078. The funding program had no effect on the study design or data assessment. 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.phro.2017.10.001. References [1] Hiraoka M, Nagata Y. Stereotactic body radiation therapy for early-stage non-smallcell lung cancer: the Japanese experience. Int J Clin Oncol 2004;9:352–5. [2] Nagata Y, Hiraoka M, Shibata T, Onishi T, Kokubo M, Karasawa K, et al. A phase II trial of stereotactic body radiation therapy for operable T1N0M0 non-small cell lung cancer: Japan Clinical Oncology Group (JCOG0403). Int J Radiat Oncol Biol Phys 2010;78:S27–8. [3] Timmerman R, Paulus R, Galvin J, Michalski J, Straube W, Bradley J, et al. Stereotactic body radiation therapy for inoperable early stage lung cancer. JAMA 2010;303:1070–6. [4] Okunieff P, Petersen AL, Philip A, Milano MT, Katz AW, Boros L, et al. Stereotactic Body Radiation Therapy (SBRT) for lung metastases. Acta Oncol 2006;45:808–17. [5] Rusthoven KE, Kavanagh BD, Burri SH, Chen C, Cardenes H, Chidel MA, et al. Multiinstitutional phase I/II trial of stereotactic body radiation therapy for lung metastases. J Clin Oncol 2009;27:1579–84. [6] Keall PJ, Mageras GS, Balter JM, Emery RS, Forster KM, Jiang SB, et al. The management of respiratory motion in radiation oncology report of AAPM Task Group 76. Med Phys 2006;33:3874–900. [7] Iizuka Y, Matsuo Y, Ishihara Y, Akimoto M, Tanabe H, Takayama K, et al. Dynamic tumor-tracking radiotherapy with real-time monitoring for liver tumors using a gimbal mounted linac. Radiother Oncol 2015;117:496–500.
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Y. Iizuka et al. Implantation and stability of metallic fiducials within pulmonary lesions. Int J Radiat Oncol Biol Phys 2007;69:777–85. [24] Benchetrit G. Breathing pattern in humans: diversity and individuality. Respir Physiol 2000;122:123–9. [25] Mageras GS, Yorke E, Rosenzweig K, Braban L, Keatley E, Ford E, et al. Fluoroscopic
evaluation of diaphragmatic motion reduction with a respiratory gated radiotherapy system. J Appl Clin Med Phys 2001;2:191–200. [26] Murphy MJ. Tracking moving organs in real time. Semin Radiat Oncol 2004;14:91–100.
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Physics and Imaging in Radiation Oncology journal homepage: www.elsevier.com/locate/phro
Original Research Article
Optimization of a newly defined target volume in fiducial marker-based dynamic tumor-tracking radiotherapy
T
⁎
Yusuke Iizukaa, Yukinori Matsuoa, , Mitsuhiro Nakamuraa, Satoshi Kozawab, Nami Uekic, Takamasa Mitsuyoshia, Takashi Mizowakia, Masahiro Hiraokaa a b c
Department of Radiation Oncology and Image-applied Therapy, Kyoto University Graduate School of Medicine, Kyoto, Japan Division of Clinical Radiology Service, Kyoto University Hospital, Kyoto, Japan Department of Radiation Oncology, Hyogo Prefectural Amagasaki General Medical Center, Amagasaki, Japan
A B S T R A C T Background and purpose: To optimize the selection of fiducial markers used to determine the “internal target volume for tracking” (ITVtracking) for fiducial marker-based dynamic tumor-tracking (DTT) radiotherapy for lung tumors, with four-dimensional 320-row area-detector computed tomography (320-ADCT). Materials and methods: Ten patients with early-stage non-small cell lung carcinomas or metastatic lung tumors were enrolled. After implanting 4 or 5 fiducial markers around the lung tumor, all patients underwent 320-ADCT to determine the coordinates of the tumors and markers. The coordinate origin of each phase CT dataset was translated so that the marker-derived coordinate centers coincided. The ITVtracking was then defined by compositing the gross tumor volumes from all four-dimensional CT phases. We compared the ITVtracking with the typical ITV used in motion-encompassing method. We also compared the following 5 scenarios in selection of fiducial markers to define the coordinate center: a) the closest marker to the tumor, b) the closest two makers, c) the centroid of the all markers, d) the farthest two markers, and e) the farthest marker. Results: The scenario b was the best in 5 patients. The difference of the ITVtracking between the best scenario and b was less than 20% in the other 5 patients. The scenario c was the best in 4 patients. The ITVtracking was smaller than the typical ITV. Conclusion: ITVtracking was reasonable target in DTT radiotherapy. Proper ITVtracking might be created with choosing those midway between the two markers closest to the tumor or in the centroid of the markers.
1. Introduction Stereotactic body radiation therapy (SBRT) is a technique that delivers high-dose radiation to limited areas with high accuracy. It has an excellent local control rate and is an effective alternative treatment for early-stage [1–3] and small metastatic [4,5] lung tumors. As respiratory motion affects the amount of radiation delivered to the target in lung SBRT, appropriate respiratory motion management is recommended. The American Association of Physicists in Medicine task group 76 proposed five methods to control motion: motion-encompassing, respiratory-gating, breath-holding, forced shallow breathing with abdominal compression, and dynamic tumor-tracking (DTT). Of these, DTT is considered the best method for managing respiratory motion with respect to normal tissue irradiation, treatment duration, and patient compliance [6]. Fiducial markers implanted in or near the tumor are often used as internal surrogates for estimating tumor position via respiratory⁎
synchronized irradiation procedures such as respiratory-gating and DTT [7–9]. In general, the markers in these procedures compose a static vector that indicates the target from a representative position; however, the relative positions of the tumor and markers constantly vary during respiration, especially when the markers are distal to the tumor or respiratory motion is large [10–12]. We previously reported DTT-SBRT for lung tumor cases using multiple fiducial markers and with gimbal mounted linac [8]. Unlike the conventional motion-encompassing method, we assumed that DTT is somewhat hampered by geometric uncertainty owing to relative positional variations and tumor deformation during respiration. Numerous reports assessed the clinical outcome of DTT with robotic arm linac using a 5-mm gross tumor volume (GTV)-to-planning target volume (PTV) margin [13–15]. Another study used a 5-mm clinical target volume-to-PTV margin to safely account for geometric uncertainties; this margin size was based on knowledge of the mechanical performance of the gimbal mounted linac [16]. However, despite
Corresponding author at: 54, Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan. E-mail address: [email protected] (Y. Matsuo).
http://dx.doi.org/10.1016/j.phro.2017.10.001 Received 15 June 2017; Received in revised form 4 October 2017; Accepted 11 October 2017 2405-6316/ © 2017 The Authors. Published by Elsevier Ireland Ltd on behalf of European Society of Radiotherapy & Oncology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
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general usage of a 5-mm margin, no theoretical or quantitative method for determining target position via DTT with multiple fiducial markers has been established. Various imaging techniques used for motion-managed target determination in radiation therapy planning include four-dimensional computed tomography (4DCT). This technique accounts for respiratory motion by adding a time axis to conventional three-dimensional (3D) CT and has been widely applied. Drawbacks of 4DCT include frequent misalignments and the presence of motion-created artifacts at the interface between adjacent couch positions [17–19]; consequently, precise determination of target position is often difficult. In addition, it is impossible to determine 3D tumor position using single-source fluoroscopy. Another technique is wide detector CT (e.g., 320-row area-detector CT [320-ADCT]), which has been extensively used in diagnostic cardiology. The greatest advantage of 320-ADCT is that the entire respiratory trajectory of the tumor and markers can be imaged without couch movement. There was no previous study which had evaluated optimal combination of fiducial markers to minimize the target volume in DTT for lung tumor via 320-ADCT. The purpose of this study was two-fold: 1) to discuss the advantage of the internal target volume for tracking (ITVtracking) compared to the internal target volume (ITV) based on motion-encompassing method and 2) to determine the optimal combination of fiducial marker positions for generating ITVtracking, via 320-ADCT.
Fig. 1. The fluoroscopic images of patient 10 show that the relative positions between the tumor (orange circle) and fiducial markers (colored squares) are not static during the respiratory cycle.
when this study was performed. We used as many as markers to create ITVtracking in the clinical case regardless of the tumor size, but we excepted markers which moved in intra- or inter-fraction because they were not fixed in bronchiole. 320-ADCT images were acquired an average of 14 days after implantation of the fiducial markers. This study was approved by our institutional review board, and informed consent was obtained from all participants.
2. Materials and methods 2.1. Concept of ITVtracking
2.3. 320-ADCT acquisition and segmentation This study used a novel target volume definition based on a special coordinate system which was defined by the position of the markers, termed the “marker-derived coordinate” to account for geometric uncertainty in DTT with multiple fiducial markers. Assuming n implanted fiducial markers, the three-dimensional marker-derived coordinate center (P) position was defined as follows:
A 320-slice volumetric CT scanner (320-slice Aquilion ONE; Toshiba Medical Systems, Otawara, Tokyo) was used to scan the tumor and markers for one respiratory cycle. The patients were placed in a supine position with both arms raised and asked to breathe freely during the scanning and we waited for several minutes until their respiratory cycle became stable. Images were acquired in the continuous volume mode (16-cm craniocaudal [CC] coverage per rotation). The scan slice thickness (CC detector row interval) and image slice thickness were 0.5 mm and 1.0 mm, respectively. The CT system has 512 × 512 transverse × 320 CC elements, each approximately 0.5 mm × 0.5 mm, at the center of the rotation. The time for a single rotation was 0.275 s. The cine duration of the scan exceeded the maximum observed respiratory period. The scan settings were 120 kVp and 50 mAs, the voxel size was 512 × 512 (field of view, 400 mm), and a reconstruction filter was used. The respiratory signals were obtained by using a respiratory gating system (AZ-733V; Anzai Medical Co., LTD, Tokyo, Japan). The CT rotation time was the same as that of a respiratory cycle, and the acquired volume was sorted into 10 respiratory phase bins. All images were transferred to the MIM maestro 6.6 software (MIM Software Inc., Cleveland, OH). The GTVs and markers were delineated semi-automatically by using the Hounsfield unit threshold, and their coordinates were then calculated. Maximum intensity projection (MIP) images from ten phases of images without CT center translation were also created, and MIP-based ITVs were created with the composition of GTVs as a target based on the motion-encompassing method.
P= a1p1 + a2p2 + ···+anpn, where ak (1 ≤ k ≤ n) was a weighting coefficient for the kth fiducial marker, and pk was the kth three-dimensional position of the fiducial marker. The order of the markers reflected their distance from the tumor: the marker closest to the tumor was “1,” and the marker farthest from the tumor was “n”. In our previous reported study, P was set as a centroid of the markers and an was 1/n [8]. After determining the marker-derived coordinate center on each phase CT dataset, all phase CT datasets were transported into a reference CT dataset so that the coordinate centers in each phase CT dataset coincided. The ITVtracking was then defined by compositing the GTVs from all of the phase images. We assumed that this target included the positional variation between the coordinate center and the tumor (Fig. 1 and Supplementary Fig. 1). 2.2. Patients Between January 2013 and February 2014, this study enrolled 10 patients with early-stage non-small cell lung carcinomas or metastatic lung tumors who received DTT-SBRT via gimbal mounted linac (Vero4DRT system; formerly MHI-TM2000; Mitsubishi Heavy Industries Ltd., Tokyo, Japan and BrainLab AG, Feldkirchen, Germany) as we previously reported [8]. Two patients who did not receive DTTSBRT because some of their markers had substantially migrated were not included. Four or five fiducial markers (Disposable Gold Marker [FMR-201CR]; Olympus Medical Systems, Tokyo, Japan), each with a diameter of 1.5 mm, were inserted around the tumor 1 week before treatment planning under bronchoscopy guidance. These markers were only wedged in bronchiole and not inserted into the tumor. Our treatment system required at least three markers for DTT-based irradiation
2.4. Determination of the ITVtracking and assessment We evaluated the following five scenarios in selection of fiducial markers used to determine each ITVtracking: a. The point corresponding to the marker closest to the tumor (p1) (a1 = 1) b. The central point between the closest marker (p1) and the second closest marker (p2) to the tumor (a1 = a2 = 1/2) 2
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tracking of lung tumors, and concluded that beacon placement and surrogacy error should be considered during planning and beacon insertion [20]. In DTT with multiple fiducial markers, the geometrical uncertainties due to tumor deformation, rotation of the tumor and markers, and positional variations during the respiratory cycle should be compensated. Isotropic margins cannot fully do so, and therefore, determination of the ITVtracking is clinically important when performing DTT. There are few reports about the target volumes for DTT. Li et al. used a tumor-tracking beam’s eye view for 4D radiotherapy planning, which was highly accurate with a low clinical workload [21]. However, their method for defining the target volume for DTT differed from the method described herein. To our knowledge, no previous studies proposed tumor-tracking strategies that included the positions of fiducial markers. We reported the proper ITVtracking created with scenario a to c was smaller than the general MIP-based ITV. This result indicates the ITVtracking was superior to the general MIP-based ITV in the DTT radiotherapy. To date, no reports have evaluated the relationship between target size and the marker-based location used to determine target size. Since the difference in the ITVtracking values for the scenario a, b, d, and e versus c (the clinical situation) was as high as 94.8%, optimization of the marker position effectively reduces the ITVtracking. Although c is used to determine the ITVtracking in our clinic, it is not always the best choice (Table 2). In all patients, except patient 6, the marker locations producing the smallest ITVtracking were those midway between the two markers closest to the tumor and in the centroid of the markers. In patient 6, the markers were placed far from the tumor, and moved in different directions with affection of a heartbeat, most notably anteriorly and posteriorly. The difference of the volume was less than 10% compared to the two markers closest to the tumor. The centroid of the markers gave the smallest ITVtracking in patient 2, 3, 5 and 9. But the difference of the volume was less than 20% compared to the two markers closest to the tumor. We found that we might create appropriate ITVtracking with selecting those midway between the two markers closest to the tumor or in the centroid of the markers without calculation of coordinates of the markers. The marker closest to the tumor did not give the smallest ITVtracking. Two patients did not receive DTT-SBRT because some of their markers had substantially migrated. The fixation rate of spherical gold markers was reported to be 75–78% in two studies [11,22]. At least two markers are required for DTT-SBRT using the current the Vero4DRT system. There are several approaches to insert the fiducial markers to the lung. Among them, transcutaneous and transbronchial approaches are common. The transcutaneous methods have higher risk of pneumothorax which can cause a delay of the radiotherapy than the transbronchial method, while it allows us to insert the markers very close or inside the tumor [23]. Two limitations of this study warrant discussion. First, the 320ADCT images were acquired in only one respiratory cycle. The duration of the human respiratory cycle is not fixed; the time between and amplitude of each cycle varies [24–26], although the patients were asked to breathe regularly and quietly by the radiological technicians during 320-ADCT acquisition. Second, the end-exhalation phase served as the reference phase in this study. However, Nakamura et al. found that marker-related target localization error was not appreciably higher in the end-exhalation phase than in the mid-ventilation phase [12]. Therefore, variations in the ITVtracking would be small even when the mid-ventilation phase is used. Moreover, severe motion artifacts are commonly observed when 4DCT is performed in the mid-ventilation phase of 4DCT [19]; because fewer motion artifacts occur in the endexhalation phase, it was used in this study. In conclusion, we found that we can create proper ITVtracking with choosing the midway between the two markers closest to the tumor or the centroid of the markers as the coordinate center in DTT
Table 1 Characteristics of the patients and tumors (n = 10). Patient no.
Age (years)
Sex
PS
GTV(cm3)*
Tumor motion (mm)**
Tumor location
No. of markers
1 2 3 4 5 6 7 8 9 10
85 74 85 80 88 84 74 78 77 64
M M F F M M M M M M
0 2 0 1 1 1 1 1 1 0
1.2 20.0 2.0 4.6 2.2 6.4 8.5 3.2 6.6 0.5
31.5 4.2 33.1 37.9 9.1 4.8 5.2 25.3 11.1 7.8
Rt S6 Rt S6 Rt S9 Rt S10 Lt S10 Lt S5 Lt S6 Rt S10 Rt S6 Rt S6
4 5 4 3 5 3 5 5 3 5
Abbreviations: M = male; F = female; PS = Eastern Cooperative Oncology Group performance status; GTV = gross tumor volume; Rt = right lung; Lt = left lung; S = segment. * GTV was measured in the reference CT. ** Tumor motion was calculated with the coordinates of tumor center in the end of inhale and exhale phase in 320-ADCT.
c. The currently clinically applied configuration: the centroid of the markers with ak = 1/k, with 3 ≤ k ≤ 5 d. The central point between the second farthest marker (pn−1) and the farthest marker (pn) from the tumor (an−1 = an = 1/2) e. the point corresponding to the marker farthest from the tumor (pn) (an = 1) Based on the coordinate centers associated with each marker-based location (five scenarios) on each CT dataset (10 CT datasets), each CT center was translated. Thereafter, the translated CT datasets was transposed into the reference CT (end-exhale phase) on the iPlan image 4.1.1 treatment planning system (BrainLAB AG). The iPlan system was used to determine the ITVtracking based on each marker-based location as a composite of the GTV. The differences between the ITVtracking and MIP-based ITV were compared and statistically evaluated with t-test. 3. Results Forty-three markers in 10 patients were evaluated. Table 1 summarizes the characteristics of the patients and tumors and the number of markers per patient. The median GTV size was 3.9 cm3 (range 0.5–8.5 cm3) and median tumor motion was 10.1 mm (range, 4.2–37.9 mm). Table 2 shows the values for MIP-based ITV and five ITVtrackings in each scenario. The median difference in the ITVtracking values in a, b, c, d, and MIP-based ITV was -27.8 to -10% (a positive number indicates the value in ITVtracking was larger). The scenario producing the smallest ITVtracking varied among the patients, and a, b, c, d, and e produced the smallest ITVtracking in 0, 5, 4, 0, and 1 patients respectively. The smallest ITVtracking in these five scenarios was significantly smaller than MIPbased ITV (p value = 0.04). In five patients, the ITVtracking was smaller in any scenario than the MIP-based ITV. 4. Discussion We discussed the concept of ITVtracking and showed that we can create proper ITVtracking with choosing the midway between the two markers closest to the tumor or the centroid of the markers as the coordinate center with 320-ADCT. This appropriate marker selection can make a smaller ITVtracking than a MIP-based ITV. These results are able to be applied to 4DCT using CT with less detectors, because the positional relationship between the tumor and the markers are the same regardless of the number of CT detectors in theory. Hardcastle et al. quantified the geometric accuracy of beacons as surrogates for tumor motion in real-time dynamic multileaf collimator 3
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Table 2 The volume of the MIP-based ITV and ITVtracking in each scenario. Patient number
1
ITV
a
Vol (cm3)
Vol (cm3) rate (%)
Dis (mm)
Vol (cm3) rate (%)
Dis (mm)
3.5
2.7 −22.9 32.0 −27.1 5.4 −12.9 7.5 −16.7 5.2 −1.9 11.3 −8.9 10.5 −9.4 5.2 −3.7 9.4 −12.1 0.7 −30
11
* 2.6 −25.7 31.1 −29.2 5.0 −19.4 * 7.1 −21.1 5.3 0 10.9 −12.1 * 10.4 −10.3 * 4.2 −22.2 10.6 −1.0 * 0.7 −30
16.3
2
43.9
3
6.2
4
9.0
5
5.3
6
12.4
7
11.6
8
5.4
9
10.7
10
1.0
b
18.6 26.2 19.5 31.3 54.7 14.8 26.3 34.9 25.8
c
24.2 12.3 36.4 61.6 8.0 18.3 27.1 26.8
e
Vol (cm3) rate (%)
Dis (mm)
Vol (cm3) rate (%)
Dis (mm)
Vol (cm3) rate (%)
Dis (mm)
2.9 −17.1 30.1 −31.4 * 4.9 −21.0 8.1 −10 * 4.5 −15.1 10.5 −15.3 11.1 −4.3 4.3 −20.4 * 9.3 −13.1 0.8 −20
15.0
3.0 −14.3 31.7 −27.8 5.3 −14.5 15.6 73.3 5.4 1.9 10.3 −16.9 12.4 6.9 6.2 −14.8 9.3 −13.1 0.9 −10
31.1
3.3 −5.7 34.0 −22.6 5.7 −8.1 15.8 75.6 6.7 26.4 * 10.2 −17.7 14.1 21.6 7.1 −31.5 11.4 6.5 1.0 0
36.2
*
12.1
d
15.7 27.3 32.3 25.0 64.3 23.0 18.4 29.8 32.2
37.8 43.8 56.6 42.5 70.6 61.7 41.5 39.1 53.7
78.1 49.4 70.8 69.0 70.7 64.0 63.1 57.2 57.0
The scenarios to create the ITVtracking in selection of fiducial markers are as follows: a, closest to the tumor (p1); b, the central point between p1 and p2; c, the centroid of the markers used in clinical cases; d, the central point between pn−1 and pn; and e, farthest from the tumor (pn). The percentages in the Vol column indicate the difference in the volume compared to the conventional internal target volume (ITV) based on maximum intensity projection. A positive number indicates the value in ITVtracking was larger. Abbreviations: MIP = maximum intensity projection, ITV = internal target volume, Vol = volume (cm3); Dis = distance between the coordinate center and the tumor (mm). * The smallest tumor volume. [8] Matsuo Y, Ueki N, Takayama K, Nakamura M, Miyabe Y, Ishihara Y, et al. Evaluation of dynamic tumour tracking radiotherapy with real-time monitoring for lung tumours using a gimbal mounted linac. Radiother Oncol 2014;112:360–4. [9] van der Voort van Zyp NC, Hoogeman MS, van de Water S, Levendag PC PC, van der Holt B, Heijimen BJ. Stability of markers used for real-time tumor tracking after percutaneous intrapulmonary placement. Int J Radiat Oncol Biol Phys 2011;81:e75–81. [10] Seppenwoolde Y, Shirato H, Kitamura K, Shimizu S, van Herk M, Lebesque JV, et al. Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. Int J Radiat Oncol Biol Phys 2002;53:822–34. [11] Ueki N, Matsuo Y, Nakamura M, Mukumoto N, Iizuka Y, Miyabe Y, et al. Intra- and interfractional variations in geometric arrangement between lung tumours and implanted markers. Radiother Oncol 2014;110:523–8. [12] Nakamura M, Takamiya M, Akimoto M, Ueki N, Tanabe H, Mukumoto N, et al. Target localization errors from fiducial markers implanted around a lung tumor for dynamic tumor tracking. Physica Med 2015;31:934–41. [13] Collins BT, Erickson K, Reichner CA, Collins SP, Gagnon GJ, Dieterich S, et al. Radical stereotactic radiosurgery with real-time tumor motion tracking in the treatment of small peripheral lung tumors. Radiat Oncol 2007;2:39. [14] Nuyttens JJ, van der Voort van Zyp NC, Praag J J, Aluwini S, van Klaveren RJ, Verhoef C, et al. Outcome of four-dimensional stereotactic radiotherapy for centrally located lung tumors. Radiother Oncol 2012;102:383–7. [15] van der Voort van Zyp NC, Prevost JB, Hoogeman MS, Praag J, Van der Holt B, Levendag PC. Stereotactic radiotherapy with real-time tumor tracking for non-small cell lung cancer: clinical outcome. Radiother Oncol 2009;91:296–300. [16] Depuydt T, Poels K, Verellen D, Engels B, Collen C, Buleteanu M, et al. Treating patients with real-time tumor tracking using the Vero gimbaled linac system: implementation and first review. Radiother Oncol 2014;112:343–51. [17] Fitzpatrick MJ, Starkschall G, Antolak JA, Fu J, Shukla H, Keall PJ, et al. Displacement-based binning of time-dependent computed tomography image data sets. Med Phys 2006;33:235–46. [18] Persson GF, Nygaard DE, Brink C, Jahn JW, Munck af Rosenschold P, Specht L. Deviations in delineated GTV caused by artefacts in 4DCT. Radiother Oncol 2010;96:61–6. [19] Yamamoto T, Langner U, Loo Jr. BW, Shen J, Keall PJ. Retrospective analysis of artifacts in four-dimensional CT images of 50 abdominal and thoracic radiotherapy patients. Int J Radiat Oncol Biol Phys 2008;72:1250–8. [20] Hardcastle N, Booth J, Caillet V, O’Brien R, Haddad C, Crasta C, et al. MO-FG-BA06: electromagnetic beacon insertion in lung cancer patients and resultant surrogacy errors for dynamic MLC tumour tracking. Med Phys 2016;43:3710–1. [21] Li G, Cohen P, Xie H, Low D, Li D, Rimner A. A novel four-dimensional radiotherapy planning strategy from a tumor-tracking beam's eye view. Phys Med Biol 2012;57:7579–98. [22] Imura M, Yamazaki K, Shirato H, Onimaru R, Fujino M, Harada T, et al. Insertion and fixation of fiducial markers for setup and tracking of lung tumors in radiotherapy. Int J Radiat Oncol Biol Phys 2005;63:1442–7. [23] Kupelian PA, Forbes A, Willoughby TR, Wallace K, Manon RR, Meeks SL, et al.
radiotherapy. However, we should be careful about patients with their fiducial markers locating far from the tumor. Conflict of interest Authors and authors’ institutions have no conflict of interest. Acknowledgement This study was partially funded by a Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research (A) 25253078. The funding program had no effect on the study design or data assessment. 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.phro.2017.10.001. References [1] Hiraoka M, Nagata Y. Stereotactic body radiation therapy for early-stage non-smallcell lung cancer: the Japanese experience. Int J Clin Oncol 2004;9:352–5. [2] Nagata Y, Hiraoka M, Shibata T, Onishi T, Kokubo M, Karasawa K, et al. A phase II trial of stereotactic body radiation therapy for operable T1N0M0 non-small cell lung cancer: Japan Clinical Oncology Group (JCOG0403). Int J Radiat Oncol Biol Phys 2010;78:S27–8. [3] Timmerman R, Paulus R, Galvin J, Michalski J, Straube W, Bradley J, et al. Stereotactic body radiation therapy for inoperable early stage lung cancer. JAMA 2010;303:1070–6. [4] Okunieff P, Petersen AL, Philip A, Milano MT, Katz AW, Boros L, et al. Stereotactic Body Radiation Therapy (SBRT) for lung metastases. Acta Oncol 2006;45:808–17. [5] Rusthoven KE, Kavanagh BD, Burri SH, Chen C, Cardenes H, Chidel MA, et al. Multiinstitutional phase I/II trial of stereotactic body radiation therapy for lung metastases. J Clin Oncol 2009;27:1579–84. [6] Keall PJ, Mageras GS, Balter JM, Emery RS, Forster KM, Jiang SB, et al. The management of respiratory motion in radiation oncology report of AAPM Task Group 76. Med Phys 2006;33:3874–900. [7] Iizuka Y, Matsuo Y, Ishihara Y, Akimoto M, Tanabe H, Takayama K, et al. Dynamic tumor-tracking radiotherapy with real-time monitoring for liver tumors using a gimbal mounted linac. Radiother Oncol 2015;117:496–500.
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Physics and Imaging in Radiation Oncology 4 (2017) 1–5
Y. Iizuka et al. Implantation and stability of metallic fiducials within pulmonary lesions. Int J Radiat Oncol Biol Phys 2007;69:777–85. [24] Benchetrit G. Breathing pattern in humans: diversity and individuality. Respir Physiol 2000;122:123–9. [25] Mageras GS, Yorke E, Rosenzweig K, Braban L, Keatley E, Ford E, et al. Fluoroscopic
evaluation of diaphragmatic motion reduction with a respiratory gated radiotherapy system. J Appl Clin Med Phys 2001;2:191–200. [26] Murphy MJ. Tracking moving organs in real time. Semin Radiat Oncol 2004;14:91–100.
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