International Journal of

Radiation Oncology

biology physics

www.redjournal.org

Physics Contribution

Quantifying Rigid and Nonrigid Motionof Liver Tumors During Stereotactic BodyRadiation TherapyQianyi Xu, PhD,* George Hanna, MS,* Jimm Grimm, PhD,y

Gregory Kubicek, MD,* Niraj Pahlajani, MD,z Sucha Asbell, MD,*Jiajin Fan, PhD,x Yan Chen, PhD,* and Tamara LaCouture, MD*

*Department of Radiation Oncology, MD Anderson Cancer Center at Cooper, Camden, New Jersey;yDepartment of Radiation Oncology, Holy Redeemer Hospital, Bott Cancer Center, Meadowbrook,Pennsylvania; zDepartment of Radiation Oncology, First Radiation and Oncology Group,Jacksonville, Florida; and xDepartment of Radiation Oncology, Fox Chase Cancer Center,Philadelphia, Pennsylvania

Received Jan 9, 2014, and in revised form May 1, 2014. Accepted for publication May 5, 2014.

Summary

This is the first report of rigidand nonrigid motion of livertumors based on precise3-dimensional fiducialreconstructions using theCyberKnife stereo imagingsystem. The fiducials from4824 pairs of x-ray images for23 patients were recon-structed. The rotational andtranslational motions of thefiducials, as well as nonrigidfiducial displacements, arereported. These data could befurther used for tumor margindefinition and tumor motionmanagement in conventionallinear acceleratorebasedtreatments.

Reprint requests to: Qianyi Xu, PhD, D

Oncology, MD Anderson Cancer Center at

Int J Radiation Oncol Biol Phys, Vol. 90, No. 1

0360-3016/$ - see front matter � 2014 Elsevie

http://dx.doi.org/10.1016/j.ijrobp.2014.05.007

Purpose: To quantify rigid and nonrigid motion of liver tumors using reconstructed3-dimensional (3D) fiducials from stereo imaging during CyberKnife-based stereotac-tic body radiation therapy (SBRT).Methods and Materials: Twenty-three liver patients treated with 3 fractions of SBRTwere used in this study. After 2 orthogonal kilovoltage images were taken during treat-ment, the 3D locations of the fiducials were generated by the CyberKnife system andvalidated using geometric derivations. A total of 4824 pairs of kilovoltage images fromstart to end of treatment were analyzed. For rigid motion, the rotational angles andtranslational shifts were reported by aligning 3D fiducial groups from different imagepairs, using least-squares fitting. For nonrigid motion, we quantified interfractional tu-mor volume variations by using the proportional volume derived from the fiducials,which correlates to the sum of interfiducial distances. The individual fiducial displace-ments were also reported (1) after rigid corrections and (2) without angle corrections.Results: The proportional volume derived by the fiducials demonstrated a volume-increasing trend in the second (101.9% � 3.6%) and third (101.0 � 5.9%) fractionsamong most patients, possibly due to radiation-induced edema. For all patients, thetranslational shifts in left-right, anteroposterior, and superoinferior directions were2.1 � 2.3 mm, 2.9 � 2.8 mm, and 6.4 � 5.5 mm, respectively. The greatest transla-tional shifts occurred in the superoinferior direction, likely due to respiratory motionfrom the diaphragm. The rotational angles in roll, pitch, and yaw were 1.2� � 1.8�,1.8� � 2.4�, and 1.7� � 2.1�, respectively. The 3D individual fiducial displacements

epartment of Radiation

Cooper, Suite C, 715

Fellowship Rd, Mt. Laurel, NJ 08054. Tel: (856) 380-6756; E-mail:

xuqianyi@gmail.com

Conflict of interest: none.

, pp. 94e101, 2014r Inc. All rights reserved.

Volume 90 � Number 1 � 2014 Rigid and nonrigid liver tumor motion 95

with rigid corrections were 0.2 � 0.2 mm and increased to 0.5 � 0.4 mm without rota-tional corrections.Conclusions: Accurate 3D locations of internal fiducials can be reconstructed from ste-reo imaging during treatment. As an effective surrogate to tumor motion, fiducials pro-vide a close estimation of both rigid and nonrigid motion of liver tumors. The reporteddisplacements could be further utilized for tumor margin definition and motion manage-ment in conventional linear acceleratorebased liver SBRT. � 2014 Elsevier Inc.

Introduction

Stereotactic body radiation therapy (SBRT) has beendemonstrated to be an effective treatment modality forunresectable primary and metastatic liver cancers, witha high rate of local control (1-5). During SBRT, a very highand conformal dose is delivered in a short period of time toensure cancer cell death. Studies have shown that doseescalation may be beneficial to liver cancer patients and thatlower tumor control rates for liver cancer were correlatedwith lower doses (6, 7). However, administration of highdose requires more accurate dose delivery to the tumor sothat nearby critical structures and healthy liver can be spared.

Motion management is critical to ensure successfulSBRT treatment of liver cancer. Liver motion up to 40 mmin shallow breathing mode and 80 mm in deep breathingmode have been observed in the superior-inferior (SI) di-rection (8). With the reduced margins used during SBRT,special attention to liver tumor motion is needed to accountfor liver tumor deformation, translational shifts, and largeangles of rotation. Such techniques include active breathcontrol (9, 10), abdominal compression (AC) (11), respi-ratory gating (12), and real-time tumor tracking (13).Multiple groups have reported liver and/or liver tumor rigidand nonrigid motions mostly under AC and their impact ontreatment margins, patient setup, and dose escalation, using4-dimensional cone beam computed tomography (4DCBCT) (14), 4D magnetic resonance imaging (4DMRI)(15), and combinations of 4DCT and 4D CBCT (16-18).Cao et al (19) reported rotational motion of liver tumors inpitch, roll, and yaw after registration of the CBCT andplanning CT. In these studies, uncertainties were inevitablyinduced due to imaging, 4D reconstruction, contour delin-eation, and deformable and/or rigid image registration.Recently, fiducials have been shown to be effective surro-gates for liver tumor positioning during SBRT, with thehypothesis that the relative location between the fiducialsand tumors are unchanging throughout treatment (seeDiscussion below regarding fiducial migration throughouttreatment). Proposed methods for estimating 3D fiducialpositions have been studied to evaluate liver motion. Parket al (20) developed a method to reconstruct 3D fiducialtrajectories using 2D projections from CBCT scans. Wun-derink et al (21) proposed estimating 3D fiducial positionsfrom 2 fluoroscopic videos acquired separately. In bothstudies, the 3D locations of the fiducials were approximatedwithin a reasonable estimation. Worm et al (22) were the

first to report precise 3D fiducial locations in a landmarkstudy after reconstruction from simultaneous kilovoltage(kV) and megavoltage (MV) image pairs using a conven-tional linear accelerator (LINAC) (22). The intrafractionaland intrafield liver tumor motions were reported based onapproximately 50,000 images from 10 patients.

In this study, we aimed to characterize intrafractionalliver motion, along with interfractional relative liver shapevariations throughout liver SBRT by using kV x-ray imagesacquired during treatment. We report 3D fiducial positionsreconstructed from 4824 pairs of orthogonal kV x-ray im-ages acquired simultaneously during SBRT of 23 liver pa-tients. For nonrigid motion, we quantified 3D liver tumorshape by using the proportional volume derived by the fi-ducials. The individual fiducial displacements relative tothe centroid of mass of the fiducial group are also reported.For rigid motion, we aligned fiducial groups from x-rayimage pairs after finding best matches, and we report cor-responding translational and rotational motions.

Methods and Materials

Patients and SBRT treatment technique

Twenty-three patients previously treated for liver cancer atthe Department of Radiation Oncology of MD AndersonCancer Center at Cooper from 2008 to 2011 as part ofinstitutional review boardeapproved studies of retrospec-tive analyses of SBRT with CyberKnife (Accuray, Inc,Sunnyvale, CA) were enrolled in this study. For each pa-tient, 3 to 7 gold fiducials were implanted in or near thetumor depending on the number and size of the tumors. Thefiducial had a cylindrical shape with 0.75- � 1.2-mmdiameter and were 3 to 5 mm in length. The procedureswere completed at least 1 to 2 weeks prior to the planningscan so that the fiducial positions could be stabilized fortreatment. Within 1 to 2 weeks after planning CT scanswere obtained, all patients were treated with 3 fractions oftotal doses ranging from 30 to 48 Gy (median, 36 Gy). Themean � standard deviations of the maximum dose, pre-scription isodose lines, and planning target volume (PTV)and gross target volume (GTV) coverage were52.8 � 19.5 Gy, 69.5% � 8.6%, 94.9% � 3.2%, and99.1% � 1.3%, respectively. Patients were allowed tobreath freely during treatment, and Synchrony fiducialtracking (CyberKnife) was used for all treatments.

Xu et al. International Journal of Radiation Oncology � Biology � Physics96

3D fiducial reconstruction and validation

The CyberKnife system is capable of detecting and trackinga moving tumor based on fiducials during beam delivery.Image guidance is provided from 2 orthogonal x-ray cam-eras mounted on the ceiling and a pair of detector panelsunderneath the floor (Fig. 1a). Pairs of x-ray images aretaken simultaneously for 3D tumor localization duringtreatment. The diagram of the imaging system for cameraA is shown in Figure 1b. The imaging system of cameraB is orthogonal to camera A, with the same geometry. Forboth the camera A and B systems, multiple equations canbe created using similar triangles. The trajectory ya inFigure 1b will be listed as the trajectory shared by bothsystems in the equations. Thus, the 3D coordinates of thefiducial can be derived as shown in Equations 1-3, aftercombining shared geometry information,

xZð1� tan a �Oxb=taÞ=ð1=Oxaþ tan a

� tan b �Oxb=ðta � tbÞÞ ð1Þ

yZ�Oxb � ð1þ tan b � xa=tbÞ ð2ÞzZOza � xa=Oxa ð3Þ

where x is left-right (LR), y is anterior-posterior (AP) and zis SI; subscripts a and b refer to cameras a and b, and a andb refer to the camera view angles.

During treatment, the 3D locations of the fiducials arereconstructed by the CyberKnife system and stored in logfiles after each pair of x-ray images is acquired.We validatedthe reconstruction algorithm using the stereotactic doseverification phantom (SDVP; Standard Imaging, Inc, Mid-dleton, WI). The mean difference between the 3D locationsof the fiducials reported by the CyberKnife system and thosederived from Equations 1-3 was 0.45 mm. Because the logfile contains ample clinical information, we decided to reportthe 3D fiducial locations from the log files for all of the pa-tients. For each patient, 3 to 4 fiducialswere selected based onmultiple criteria: fiducials had to be used for treatment; thedetection confidence level for the selected fiducials had to behigher than a threshold value to ensure manufacture-specified extraction accuracy (the mean threshold value for

Fig. 1. CyberKnife fiducial localization system using 2 orthogoand its detector (b). Xa and Za are the trajectories of the fiducial ithe projected trajectories of the fiducial in the patient plane (pajectories where the imaging ray intersects with the patient plane

all patients was approximately 60%); the space between any2 fiducials had to be greater than 1 cm; and the angle formedby any 3 fiducials had to be greater than 15� (to avoidcollinear effects). The confidence level was a parameterdefined by the system to evaluate fiducial matching betweenthe live x-ray images and digitally reconstructed radiographs(DRRs), as well as the correctness of the fiducial extraction.

Proportional volume derived by fiducials

We adopted a similar idea proposed by King et al (23) toevaluate the proportional volume derived by the fiducials. InKing et al (23), 3 transponderswere implanted in the prostate,and the perimeter of the trianglewas calculated. Based on thescaling laws, the volume of the prostate was proportional tothe cubic of this perimeter. Here, we calculated the sum ofinterfiducial distances for each patient. This parameter maynot be suitable for absolute volume verification but should besufficient for evaluating interfractional relative volume var-iations. To account for possible intrafractional nonrigid mo-tion, we calculated the mean of Vf (Vf ) for all pairs of x-rayimages taken within each fraction, where Vf is the calculatedvolume from each image pair. On average, 210 pairs ofintrafractional images were analyzed for each patient.

Rotational and translational motions

Before evaluating rigid motion, a reference pair of x-rayimages near the start of each treatment fraction was selectedwith a relatively high detection confidence level for fiducialdelineation. The group of 3D fiducials (Xfloat) in the otherpairs of images were then translated and rotated to maprelative to the reference 3D fiducials (Yref) (24). Because the2 groups of the fiducials might not have perfect mapping, thefollowing least-squares problem needed to be solved,

minXn

iZ1

kRXi þ d� Yik2; ð4Þ

where Xfloat Z {X1,., Xn}, Yref Z {Y1,., Yn}, n is thenumber of fiducials, R is the rotational matrix, and d is the

nal cameras and detectors (a) and the diagram of camera An the detector plane following the imaging ray, xa and za arerallel to the detector plane), and Oza and Oxa are the tra-.

Volume 90 � Number 1 � 2014 Rigid and nonrigid liver tumor motion 97

translational shift. Because d is linear and R is nonlinear,d and R needed to be solved separately. Therefore, another4 matrices were introduced,

XfloatZ1

n

Xn

iZ1

Xfloat;

YrefZ1

n

Xn

iZ1

Yref ;

AZ�X1 �Xfloat; :::;Xn �Xfloat

�; and

BZ�Y1 � Yref ; :::;Yn � Yref

�

Now the rotational matrix could be solved as

minXn

iZ1

kRA�BkF2; ð5Þ

where F stands for the Frobenius norm of a matrix. This iswell known as the Orthogonal Procrustes problem, whichcan be solved using. More technical details regarding thesingular value decomposition method can be found in thestudy by Arun et al (24). After R was solved, the trans-lational shift was found by

dZYref �RXfloat

Fiducial displacement

Fiducial displacement is the residual error after rigidmapping. For each patient, the mean location of each in-dividual fiducial was calculated after 3D fiducials from all

Fig. 2. Histogram of intrafractional volume (Vf) v

image pairs were mapped to the reference fiducials. Thedisplacement of each fiducial relative to its own meanlocation was calculated after the alignment. We alsonoticed that in practice it would be difficult to adjust thebeam to correct for rotational tumor motion. The fiducialdisplacement without rotational corrections would be veryuseful information for treatment margin design. For eachpatient, we aligned the 3D fiducials from all the x-rayimage pairs based on their centroids without rotationalcorrections. The mean location of each individual fiducialwas then calculated again, and the displacement of the eachfiducial relative to its own mean location was reported.

Results

A total of 4824 pairs of x-ray images evenly distributedfrom the start to finish of treatment were analyzed for 23patients. For 6 patients, 3 fiducials were selected, and forthe remaining patients, 4 fiducials were selected. For eachpatient, the individual Vf value from each pair of x-rayimages was normalized by Vf for that fraction. Thenormalized Vf values from all patients were grouped intothe 3 individual fractions. A histogram of normalizedintrafractional variations in Vf is shown in Figure 2. InFigure 2, the variations of the normalized Vf followed asimilar Gaussian distribution across all fractions, and theranges of variations were similar within each fraction.

To evaluate interfractional volume variations, weselected the Vf value of the first fraction as the baseline, and

ariations from fractions 1 to 3 for all patients.

Xu et al. International Journal of Radiation Oncology � Biology � Physics98

the Vf in the remaining fractions were normalized to thatbaseline for each patient. The mean � SD of the normal-ized Vf of the second and third fractions were101.9% � 3.6% and 101.0% � 5.9%, respectively.Comparing the Vf of the first fraction, the Vf of both thesecond and third fractions exhibited increases in volume. Areview of individual patient data showed that Vf increasedfor 18 of the 23 patients in the second fraction and for 16 ofthe 23 patients in the third fraction. The main cause of thevolume increase could be radiation-induced edema, whichis the body’s natural response to cell death after 12 to 17 Gyof dose delivered in a single fraction (25).

A plot of the intrafractional translational shifts relativeto each reference pair is displayed in Figure 3, and a his-togram of intrafractional rotational angle variations is dis-played in Figure 4, with the 3D intrafractional translationalshifts presented in absolute values. The absolute valuemeans � SD of shifts in x, y, and z were 2.1 � 2.3 mm,2.9 � 2.8 mm, and 6.4 � 5.5 mm, respectively. The greatestshift occurred in SI direction, probably due to the breathingmotion from the diaphragm, and the smallest shift was inLR direction. The mean � SD of the 3D shifts relative toeach reference pair was 8.0 � 5.9 mm. The rotational an-gles in roll, pitch, and yaw, with corresponding rotationalaxes in SI, LR, and AP directions, are shown in Figure 4.The absolute value means � SD of the roll, pitch, and yawangles were 1.2� � 1.8�, 1.8� � 2.4�, and 1.7� � 2.1�,respectively.

As shown in histograms in Figure 5, we also evaluatedindividual fiducial displacements with rigid corrections(Fig. 5, black) and without rotational corrections (Fig. 5,red). Displacements in x (Fig. 5, top left), y (Fig. 5, topright), and z (Fig. 5, bottom left) from all the fiducials are

Fig. 3. Shifts in LR, AP, and SI directions for all patients, wroposterior; LR Z left-right; SI Z superoinferior.

displayed. The means � SD of the displacements in x, y,and z were 0.1 � 0.1 mm, 0.1 � 0.1 mm, and0.1 � 0.1 mm, respectively, with rigid corrections and0.2 � 0.3 mm, 0.2 � 0.3 mm, and 0.2 � 0.3 mm,respectively, without rotational corrections. The 3Ddisplacement of each fiducial was calculated from its owndisplacement in x, y, and z (Fig. 5, bottom right). Themeans � SD of the 3D displacement with corrections were0.2 � 0.2 mm and increased to 0.5 � 0.4 mm withoutrotational corrections.

Discussion

Quantification of intra- and interfractional liver tumormotion is challenging due to difficulties in free-breathingtumor imaging, tumor delineation, and the complex natureof tumor motion: rigid (translational and rotational),nonrigid deformation, and the combination of both types ofmotion. Eccles et al (14) registered CBCT images at theend of exhalation to planning CT images in the same phaseby using the finite element model. Due to the difficulties ofdelineation of the GTV in CBCT, they predicted the shiftsin the GTV centroid of mass using deformable registration.Their study showed a mean deformation of 2.8 mm (LR),3.7 mm (AP), and 2.7 mm (SI) and fairly small GTV dis-placements for patients under AC. The same group alsoreported liver motion after rigid registration between 4DCTimages and 4D CBCT images (16). For 14 patients with ACand 15 patients with free breathing, the mean liver motionwas 1.8 mm (LR), 4.3 mm (AP), and 8 mm (SI). Romeroet al (26) found that MRI might provide better delineationbetween the liver tumor and normal tissues. von Siebenthal

ith the patient number labeled along the axis. AP Z ante-

Fig. 4. Rotational angles in roll, pitch, and yaw for all patients.

Volume 90 � Number 1 � 2014 Rigid and nonrigid liver tumor motion 99

et al (15) reconstructed 4DMR images by retrospectivelysorting 2D images using internal image information.Twelve healthy volunteers were recruited, and the motionof the whole liver was analyzed. After nonrigid registrationof MR images from different phases, they showed themotion of voxels in the liver varied significantly amongpatients and at different locations even in the same patient.

Fig. 5. Individual fiducial displacements in x, y, and z and 3Darea Z without rotational corrections. A color version of thie fi

The averaged magnitude of the motion ranged from 6.5 mmto 20.1 mm among patients. They also reported the averagerange of deformation, or drift, mainly in the AP part of theliver was 2.4 mm to 7.1 mm.

Recently, fiducials have been used more frequently astumor surrogates for patient setup, treatment, and livermotion evaluation because they can be delineated more

displacements. Black area Z with rigid corrections; redgure is available at www.redjournal.org.

Xu et al. International Journal of Radiation Oncology � Biology � Physics100

easily by different imaging modalities. A successfulfiducial-based SBRT of liver tumors relies on the hypoth-esis that the fiducials do not migrate in the liver. In ourinstitution, the planning CT is scanned 1 to 2 weeks afterthe fiducials are implanted so they can settle in a stableposition. Studies show that gross fiducial migration is lesslikely to happen in the liver. Kothary et al (27) reported nogross fiducial migration in 34 patients with fiducialsimplanted in the liver under CT guidance. Another similarreport can be found in the study by Shirato et al (28). Forour patients, gross fiducial migration was observed only in1 patient. The patient had 6 fiducials implanted, but only 4of them were observed and used for treatment. Reports ofmigration of fiducials within the liver are very limited dueto the complex nature of the motion. Kitamura et al (29)estimated the maximum standard deviation of migrationerrors to be less than 2.5 mm in each direction for liverpatients, but tumor rotation and deformation were notconsidered in that study. In our study, the fiducials werealigned rigidly, and the mean � SD of 3D fiducial dis-placements was 0.2 � 0.2 mm. This indicates that thechance for intrafractional fiducial migration is small. Theimpact of interfractional fiducial migration should beminimal as well because no large variations in the Vfvaluewere observed between fractions. Meanwhile, most patientsfinished treatment in 3 consecutive days to minimize po-tential interfractional fiducial migration.

Multiple groups have reported rigid and nonrigid motionof liver tumors based on the reconstructed 3D fiducial lo-cations. Wunderink et al (21) obtained 2D coordinates ofthe fiducials in an AP fluoroscopic video taken beforetreatment. The coordinates of the fiducials in the thirddimension were estimated from an average motion of thefiducials in the video subsequently taken laterally. Thederivation of 3D coordinates in this study was approximate.If drift occurred (28), it would be difficult to reflect this inthe fiducial coordinates. Park et al (20) proposed estimatingthe trajectories of the fiducials from the projections in aCBCT scan. A few assumptions had to be made in thestudy, for example, the patients had to be stationary on thecouch and the movement of the fiducials had to be oscil-latory and confined to a certain range. The issues with bothmethods were lacking sufficient information for precise 3Dfiducial reconstructions. Worm et al (22) was the first groupto acquire kV/MV images simultaneously during treatmentusing a conventional LINAC (22). The precise 3D fiduciallocations were derived in that study. In this recent study, theauthors reported both intrafractional and intrafield livertumor motion based on the fiducial positions duringLINAC-based SBRT. During CyberKnife-based SBRT, thedeterminant solution of 3D fiducial reconstruction wasderived from Equations 1-3. Constant updates of recon-structed fiducials could very well account for tumor driftduring treatment. The limitations of CyberKnife are similarto all other fiducial-based methods, that is, the procedure offiducial implantation is invasive. Also, depending on thesize of the patient and location of the tumor, the fiducial

might not be well differentiated in the kV x-ray images,especially when 2 fiducials are too close in the projectedview. In our study, we visually checked the geometry offiducials in the x-ray images to avoid occlusion. The al-gorithm used to detect the center of the fiducial in the x-rayimage might also introduce minor errors.

Conclusions

This is the first report of quantifying rigid and nonrigidmotions of liver tumors during CyberKnife-based SBRT.We observed that the proportional volumes derived by thefiducials increased in the second and third fractions amongmost patients. The intrafractional fiducial displacementsdue to deformation were small after rigid corrections. Thetranslational shifts were comparable to those reported byother groups. Although the report was based on CyberKnifetreatment, the results from this study could also be used fortumor margin design and motion management for conven-tional LINAC treatments.

References

1. Herfarth KK, Debus J, Lohr F, et al. Stereotactic single-dose radiation

therapy of liver tumors: Results of a phase I/II trial. J Clin Oncol 2001;

19:164-170.

2. Schefter TE, Kavanagh BD, Timmerman RD, et al. A phase I trial of

stereotactic body radiation therapy (SBRT) for liver metastases. Int J

Radiat Oncol Biol Phys 2005;62:1371-1378.

3. Wulf J, Guckenberger M, Haedinger U, et al. Stereotactic radiotherapy

of primary liver cancer and hepatic metastases. Acta Oncol 2006;45:

838-847.

4. Regina VT, Hawkins M, Lockwood G, et al. Phase I study of indi-

vidualized stereotactic body radiotherapy for hepatocellular carcinoma

and intrahepatic cholangiocarcinoma. J Clin Oncol 2008;26:657-664.

5. Hyer M, Swaminath A, Bydder S, et al. Radiotherapy for liver me-

tastases: A review of evidence. Int J Radiat Oncol Biol Phys 2012;82:

1047-1057.

6. Ben-Josef E, Normolle D, Ensminger WD, et al. Phase II trial of high-

dose conformal radiation therapy with concurrent hepatic artery

floxuridine for unresectable intrahepatic malignancies. J Clin Oncol

2005;23:8739-8747.

7. Lee MT, Kim JJ, Dinniwell R, et al. Phase I study of individualized

stereotactic body radiotherapy of liver metastases. J Clin Oncol 2009;

27:1585-1591.

8. Suramo I, Paivansalo M, Myllyla V. Cranio-caudal movements of the

liver, pancreas and kidneys in respiration. Acta Radiol Diagn (Stockh)

1984;25:129-131.

9. Mageras GS, Yorke E. Deep inspiration breath hold and respiratory

gating strategies for reducing organ motion in radiation treatment.

Semin Radiat Oncol 2004;14:65.

10. Wong JW, Sharpe MB, Jaffray DA, et al. The use of active breathing

control (ABC) to reduce margin for breathing motion. Int J Radiat

Oncol Biol Phys 1999;44:911-919.

11. Wunderink W, Mendez Romero A, de Kruijf W, et al. Reduction of

respiratory liver tumor motion by abdominal compression in stereo-

tactic body frame, analyzed by tracking fiducial markers implanted in

liver. Int J Radiat Oncol Biol Phys 2008;71:907-915.

12. Wagman R, Yorke E, Ford E, et al. Respiratory gating for liver tu-

mors: Use in dose escalation. Int J Radiat Oncol Biol Phys 2003;55:

659-668.

Volume 90 � Number 1 � 2014 Rigid and nonrigid liver tumor motion 101

13. Goyal K, Einstein D, Yao M, et al. Cyberknife stereotactic body

radiation therapy for nonresectable tumors of the liver: Preliminary

results. HPB Surg 2010. Available at: www.hindawi.com/journals/hpb/

2010/309780/abs/. Accesssed July 8, 2014.

14. Eccles CL, Dawson LA, Moseley JL, et al. Interfraction liver shape

variability and impact on GTV position during liver stereotactic

radiotherapy using abdominal compression. Int J Radiat Oncol Biol

Phys 2011;80:938-946.

15. von Siebenthal M, Szekely G, Lomax A, et al. Systematic errors in

respiratory gating due to intrafraction deformations of the liver. Med

Phys 2007;34:3620.

16. Case RB, Sonke JJ, Moseley DJ, et al. Inter-and intrafraction vari-

ability in liver position in non-breath-hold stereotactic body radio-

therapy. Int J Radiat Oncol Biol Phys 2009;75:302.

17. Case RB, Moseley DJ, Sonke JJ, et al. Interfraction and intrafraction

changes in amplitude of breathing motion in stereotactic liver radio-

therapy. Int J Radiat Oncol Biol Phys 2010;77:918-925.

18. Velec M, Moseley JL, Craig T, et al. Accumulated dose in liver ste-

reotactic body radiotherapy: Positioning, breathing, and deformation

effects. Int J Radiat Oncol Biol Phys 2012;83:1132-1140.

19. Cao M, Lasley FD, Das IJ, et al. Evaluation of rotational errors in

treatment setup of stereotactic body radiation therapy of liver cancer.

Int J Radiat Oncol Biol Phys 2012;84:e435-e440.

20. Park JC, Park SH, Kim JH, et al. Four-dimensional cone-beam

computed tomography and digital tomosynthesis reconstructions

using respiratory signals extracted from transcutaneously inserted

metal markers for liver SBRT. Med Phys 2011;38:1028-1036.

21. Wunderink W, Mendez Romero A, Seppenwoolde Y, et al. Potentials

and limitations of guiding liver stereotactic body radiation therapy set-

up on liver-implanted fiducial markers. Int J Radiat Oncol Biol Phys

2010;77:1573-1583.

22. Worm ES, Høyer M, Fledelius W, et al. Three-dimensional, time-

resolved, intrafraction motion monitoring throughout stereotactic

liver radiation therapy on a conventional linear accelerator. Int J

Radiat Oncol Biol Phys 2013;86:190-197.

23. King BL, Butler WM, Merrick GS, et al. Electromagnetic transpon-

ders indicate prostate size increase followed by decrease during the

course of external beam radiation therapy. Int J Radiat Oncol Biol

Phys 2011;79:1350-1357.

24. Arun KS, Huang TS, Blostein SD. Least-squares fitting of two 3-D

point sets. IEEE Trans Pattern Anal Mach Intell 1987;6:698-700.

25. Kavanagh BD, Timmerman RD. Stereotactic body radiation therapy,

vol 29. Philadelphia: Lippincott Williams & Wilkins; 2005.

26. Mendez Romero A, Wunderink W, Hussain SM, et al. Stereo-

tactic body radiation therapy for primary and metastatic liver

tumors: A single institution phase I-II study. Acta Oncol 2006;45:

831-837.

27. Kothary N, Heit JJ, Louie JD, et al. Safety and efficacy of percuta-

neous fiducial marker implantation for image-guided radiation ther-

apy. J Vasc Interv Radiol 2009;20:235-239.

28. Shirato H, Harada T, Harabayashi T, et al. Feasibility of insertio-

n/implantation of 2.0-mm-diameter gold internal fiducial markers for

precise setup and real-time tumor tracking in radiotherapy. Int J

Radiat Oncol Biol Phys 2003;56:240-247.

29. Kitamura K, Shirato H, Shimizu S, et al. Registration accuracy and

possible migration of internal fiducial gold marker implanted in

prostate and liver treated with real-time tumor-tracking radiation

therapy (RTRT). Radiother Oncol 2002;62:275-281.