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S Gaede H Fakir (2012)
Development of a novel ArcCheck insert for routine quality assurance of VMAT delivery including dose calculation with inhomogeneitiesMed Phys, 39
(BoggulaRLorenzFMüllerLBirknerMWertzHStielerFSteilVLohrFWenzFExperimental validation of a commercial 3D dose verification system for intensity-modulated arc therapiesPhys Med Biol2010555619563310.1088/0031-9155/55/19/00120826904)
BoggulaRLorenzFMüllerLBirknerMWertzHStielerFSteilVLohrFWenzFExperimental validation of a commercial 3D dose verification system for intensity-modulated arc therapiesPhys Med Biol2010555619563310.1088/0031-9155/55/19/00120826904BoggulaRLorenzFMüllerLBirknerMWertzHStielerFSteilVLohrFWenzFExperimental validation of a commercial 3D dose verification system for intensity-modulated arc therapiesPhys Med Biol2010555619563310.1088/0031-9155/55/19/00120826904, BoggulaRLorenzFMüllerLBirknerMWertzHStielerFSteilVLohrFWenzFExperimental validation of a commercial 3D dose verification system for intensity-modulated arc therapiesPhys Med Biol2010555619563310.1088/0031-9155/55/19/00120826904
(FogliataANicoliniGVanettiEClivioAWinklerPCozziLThe impact of photon dose calculation algorithms on expected dose distributions in lungs under different respiratory phasesPhys Med Biol2008532375239010.1088/0031-9155/53/9/01118421117)
FogliataANicoliniGVanettiEClivioAWinklerPCozziLThe impact of photon dose calculation algorithms on expected dose distributions in lungs under different respiratory phasesPhys Med Biol2008532375239010.1088/0031-9155/53/9/01118421117FogliataANicoliniGVanettiEClivioAWinklerPCozziLThe impact of photon dose calculation algorithms on expected dose distributions in lungs under different respiratory phasesPhys Med Biol2008532375239010.1088/0031-9155/53/9/01118421117, FogliataANicoliniGVanettiEClivioAWinklerPCozziLThe impact of photon dose calculation algorithms on expected dose distributions in lungs under different respiratory phasesPhys Med Biol2008532375239010.1088/0031-9155/53/9/01118421117
(ChandrarajVStathakisSManickamREsquivelCSupeSPapanikolauNConsistency and reproducibility of the VMAT plan delivery using three independent validation methodsJ Appl Clin Med Phys201012337321330988)
ChandrarajVStathakisSManickamREsquivelCSupeSPapanikolauNConsistency and reproducibility of the VMAT plan delivery using three independent validation methodsJ Appl Clin Med Phys201012337321330988ChandrarajVStathakisSManickamREsquivelCSupeSPapanikolauNConsistency and reproducibility of the VMAT plan delivery using three independent validation methodsJ Appl Clin Med Phys201012337321330988, ChandrarajVStathakisSManickamREsquivelCSupeSPapanikolauNConsistency and reproducibility of the VMAT plan delivery using three independent validation methodsJ Appl Clin Med Phys201012337321330988
(NicoliniGVanettiEClivioAFogliataAKorremanSBocanekJCozziLThe GLAaS algorithm for portal dosimetry and quality assurance of RapidArc, an intensity modulated rotational therapyRadiat Oncol200832410.1186/1748-717X-3-2418782447)
NicoliniGVanettiEClivioAFogliataAKorremanSBocanekJCozziLThe GLAaS algorithm for portal dosimetry and quality assurance of RapidArc, an intensity modulated rotational therapyRadiat Oncol200832410.1186/1748-717X-3-2418782447NicoliniGVanettiEClivioAFogliataAKorremanSBocanekJCozziLThe GLAaS algorithm for portal dosimetry and quality assurance of RapidArc, an intensity modulated rotational therapyRadiat Oncol200832410.1186/1748-717X-3-2418782447, NicoliniGVanettiEClivioAFogliataAKorremanSBocanekJCozziLThe GLAaS algorithm for portal dosimetry and quality assurance of RapidArc, an intensity modulated rotational therapyRadiat Oncol200832410.1186/1748-717X-3-2418782447
WB Harms DA Low (2008)
A technique for quantitative evaluation of dose distributionsMed Phys, 25
G Nicolini A Fogliata (2012)
Critical appraisal of Acuros XB and Anisotropic Analytical Algorithm dose calculation in advanced non-small cell lung cancer treatmentsInt J Radiat Oncol Biol Phys, 83
K Otto (2008)
Volumetric modulated arc therapy: IMRT in a single gantry arcMed Phys, 35
(GodartJKorevaarEVisserRWaubenDvan’t VeldAReconstruction of high resolution 3D dose from matrix measurements: error detection capability of the COMPASS correction kernel methodPhys Med Biol2011565029504310.1088/0031-9155/56/15/02321772084)
GodartJKorevaarEVisserRWaubenDvan’t VeldAReconstruction of high resolution 3D dose from matrix measurements: error detection capability of the COMPASS correction kernel methodPhys Med Biol2011565029504310.1088/0031-9155/56/15/02321772084GodartJKorevaarEVisserRWaubenDvan’t VeldAReconstruction of high resolution 3D dose from matrix measurements: error detection capability of the COMPASS correction kernel methodPhys Med Biol2011565029504310.1088/0031-9155/56/15/02321772084, GodartJKorevaarEVisserRWaubenDvan’t VeldAReconstruction of high resolution 3D dose from matrix measurements: error detection capability of the COMPASS correction kernel methodPhys Med Biol2011565029504310.1088/0031-9155/56/15/02321772084
G Nicolini A Fogliata (2011)
On the dosimetric impact of inhomogeneity management in the Acuros XB algorithm for breast treatmentRadiat Oncol, 6
(FakirHGaedeSMulliganMChenJDevelopment of a novel ArcCheck insert for routine quality assurance of VMAT delivery including dose calculation with inhomogeneitiesMed Phys2012394203420810.1118/1.472822222830753)
FakirHGaedeSMulliganMChenJDevelopment of a novel ArcCheck insert for routine quality assurance of VMAT delivery including dose calculation with inhomogeneitiesMed Phys2012394203420810.1118/1.472822222830753FakirHGaedeSMulliganMChenJDevelopment of a novel ArcCheck insert for routine quality assurance of VMAT delivery including dose calculation with inhomogeneitiesMed Phys2012394203420810.1118/1.472822222830753, FakirHGaedeSMulliganMChenJDevelopment of a novel ArcCheck insert for routine quality assurance of VMAT delivery including dose calculation with inhomogeneitiesMed Phys2012394203420810.1118/1.472822222830753
(BoggulaRJahnkeLWertzHLohrFWenzFPatient-specific 3D pretreatment and potential 3D online dose verification of Monte Carlo-calculated IMRT prostate treatment plansInt J Radiat Oncol Biol Phys2011811168117510.1016/j.ijrobp.2010.09.01021093168)
BoggulaRJahnkeLWertzHLohrFWenzFPatient-specific 3D pretreatment and potential 3D online dose verification of Monte Carlo-calculated IMRT prostate treatment plansInt J Radiat Oncol Biol Phys2011811168117510.1016/j.ijrobp.2010.09.01021093168BoggulaRJahnkeLWertzHLohrFWenzFPatient-specific 3D pretreatment and potential 3D online dose verification of Monte Carlo-calculated IMRT prostate treatment plansInt J Radiat Oncol Biol Phys2011811168117510.1016/j.ijrobp.2010.09.01021093168, BoggulaRJahnkeLWertzHLohrFWenzFPatient-specific 3D pretreatment and potential 3D online dose verification of Monte Carlo-calculated IMRT prostate treatment plansInt J Radiat Oncol Biol Phys2011811168117510.1016/j.ijrobp.2010.09.01021093168
A Bergman T Teke (2010)
Monte Carlo based patient specific RapidArc QA using Linac log filesMed Phys, 37
L Jahnke R Boggula (2011)
Patient-specific 3D pretreatment and potential 3D online dose verification of Monte Carlo-calculated IMRT prostate treatment plansInt J Radiat Oncol Biol Phys, 81
(FogliataANicoliniGClivioAVanettiECozziLCritical appraisal of Acuros XB and Anisotropic Analytical Algorithm dose calculation in advanced non-small cell lung cancer treatmentsInt J Radiat Oncol Biol Phys2012831587159510.1016/j.ijrobp.2011.10.07822300575)
FogliataANicoliniGClivioAVanettiECozziLCritical appraisal of Acuros XB and Anisotropic Analytical Algorithm dose calculation in advanced non-small cell lung cancer treatmentsInt J Radiat Oncol Biol Phys2012831587159510.1016/j.ijrobp.2011.10.07822300575FogliataANicoliniGClivioAVanettiECozziLCritical appraisal of Acuros XB and Anisotropic Analytical Algorithm dose calculation in advanced non-small cell lung cancer treatmentsInt J Radiat Oncol Biol Phys2012831587159510.1016/j.ijrobp.2011.10.07822300575, FogliataANicoliniGClivioAVanettiECozziLCritical appraisal of Acuros XB and Anisotropic Analytical Algorithm dose calculation in advanced non-small cell lung cancer treatmentsInt J Radiat Oncol Biol Phys2012831587159510.1016/j.ijrobp.2011.10.07822300575
G Nicolini A Fogliata (2008)
The impact of photon dose calculation algorithms on expected dose distributions in lungs under different respiratory phasesPhys Med Biol, 53
(ICRU report 83Prescribing, recording and reporting Intensity Modulated Photon Beam Therapy (IMRT) (ICRU report 83)2010Washington, DC: International Commission on Radiation Units and Measurements)
ICRU report 83Prescribing, recording and reporting Intensity Modulated Photon Beam Therapy (IMRT) (ICRU report 83)2010Washington, DC: International Commission on Radiation Units and MeasurementsICRU report 83Prescribing, recording and reporting Intensity Modulated Photon Beam Therapy (IMRT) (ICRU report 83)2010Washington, DC: International Commission on Radiation Units and Measurements, ICRU report 83Prescribing, recording and reporting Intensity Modulated Photon Beam Therapy (IMRT) (ICRU report 83)2010Washington, DC: International Commission on Radiation Units and Measurements
(VassilievOWareingTMcGheeJFaillaGSalehpourMMourtadaFValidation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beamsPhys Med Biol20105558159810.1088/0031-9155/55/3/00220057008)
VassilievOWareingTMcGheeJFaillaGSalehpourMMourtadaFValidation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beamsPhys Med Biol20105558159810.1088/0031-9155/55/3/00220057008VassilievOWareingTMcGheeJFaillaGSalehpourMMourtadaFValidation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beamsPhys Med Biol20105558159810.1088/0031-9155/55/3/00220057008, VassilievOWareingTMcGheeJFaillaGSalehpourMMourtadaFValidation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beamsPhys Med Biol20105558159810.1088/0031-9155/55/3/00220057008
(van ElmptWPetitSDe RuysscherDLambinPDekkerA3D dose delivery verification using repeated cone beam imaging and EPID dosimetry for stereotactic body radiotherapy of non small cell lung cancerRadiother Oncol20109418819410.1016/j.radonc.2009.12.02420083317)
van ElmptWPetitSDe RuysscherDLambinPDekkerA3D dose delivery verification using repeated cone beam imaging and EPID dosimetry for stereotactic body radiotherapy of non small cell lung cancerRadiother Oncol20109418819410.1016/j.radonc.2009.12.02420083317van ElmptWPetitSDe RuysscherDLambinPDekkerA3D dose delivery verification using repeated cone beam imaging and EPID dosimetry for stereotactic body radiotherapy of non small cell lung cancerRadiother Oncol20109418819410.1016/j.radonc.2009.12.02420083317, van ElmptWPetitSDe RuysscherDLambinPDekkerA3D dose delivery verification using repeated cone beam imaging and EPID dosimetry for stereotactic body radiotherapy of non small cell lung cancerRadiother Oncol20109418819410.1016/j.radonc.2009.12.02420083317
R Townson K Bush (2008)
Monte Carlo simulation of RapidArc radiotherapy deliveryPhys Med Biol, 53
S Petit W van Elmpt (2010)
3D dose delivery verification using repeated cone beam imaging and EPID dosimetry for stereotactic body radiotherapy of non small cell lung cancerRadiother Oncol, 94
L Leung M Kan (2012)
Dosimetric impact of using the Acuros XB algorithm for intensity modulated radiation therapy and RapidArc planning in nasopharyngeal carcinomasInt J Radiat Oncol Biol Phys, 85
(TekeTBergmanAKwaWGillBDuzenliCPopescuAMonte Carlo based patient specific RapidArc QA using Linac log filesMed Phys20103711612310.1118/1.326682120175472)
TekeTBergmanAKwaWGillBDuzenliCPopescuAMonte Carlo based patient specific RapidArc QA using Linac log filesMed Phys20103711612310.1118/1.326682120175472TekeTBergmanAKwaWGillBDuzenliCPopescuAMonte Carlo based patient specific RapidArc QA using Linac log filesMed Phys20103711612310.1118/1.326682120175472, TekeTBergmanAKwaWGillBDuzenliCPopescuAMonte Carlo based patient specific RapidArc QA using Linac log filesMed Phys20103711612310.1118/1.326682120175472
(UlmerWPyyryJKaisslWA 3D photon superposition convolution algorithm and its foundation on results of Monte Carlo calculationsPhys Med Biol2005501767179010.1088/0031-9155/50/8/01015815095)
UlmerWPyyryJKaisslWA 3D photon superposition convolution algorithm and its foundation on results of Monte Carlo calculationsPhys Med Biol2005501767179010.1088/0031-9155/50/8/01015815095UlmerWPyyryJKaisslWA 3D photon superposition convolution algorithm and its foundation on results of Monte Carlo calculationsPhys Med Biol2005501767179010.1088/0031-9155/50/8/01015815095, UlmerWPyyryJKaisslWA 3D photon superposition convolution algorithm and its foundation on results of Monte Carlo calculationsPhys Med Biol2005501767179010.1088/0031-9155/50/8/01015815095
D Wauben E Korevaar (2011)
Clinical introduction of a linac head mounted 2D detector array based quality assurance system in head and neck IMRTRadiother Oncol, 100
(KorevaarEWaubenDvan der HulstPLagendijkJvan’t VeldAClinical introduction of a linac head mounted 2D detector array based quality assurance system in head and neck IMRTRadiother Oncol201110044645310.1016/j.radonc.2011.09.00721963288)
KorevaarEWaubenDvan der HulstPLagendijkJvan’t VeldAClinical introduction of a linac head mounted 2D detector array based quality assurance system in head and neck IMRTRadiother Oncol201110044645310.1016/j.radonc.2011.09.00721963288KorevaarEWaubenDvan der HulstPLagendijkJvan’t VeldAClinical introduction of a linac head mounted 2D detector array based quality assurance system in head and neck IMRTRadiother Oncol201110044645310.1016/j.radonc.2011.09.00721963288, KorevaarEWaubenDvan der HulstPLagendijkJvan’t VeldAClinical introduction of a linac head mounted 2D detector array based quality assurance system in head and neck IMRTRadiother Oncol201110044645310.1016/j.radonc.2011.09.00721963288
(LowDAHarmsWBMuticSPurdyJAA technique for quantitative evaluation of dose distributionsMed Phys2008256566619608475)
LowDAHarmsWBMuticSPurdyJAA technique for quantitative evaluation of dose distributionsMed Phys2008256566619608475LowDAHarmsWBMuticSPurdyJAA technique for quantitative evaluation of dose distributionsMed Phys2008256566619608475, LowDAHarmsWBMuticSPurdyJAA technique for quantitative evaluation of dose distributionsMed Phys2008256566619608475
A Dhabaan E Schreibmann (2009)
Patient specific quality assurance method for VMAT treatment deliveryMed Phys, 36
L Kumaraswamy M Bakhtiari (2011)
Using an EPID for patient specific VMAT quality assuranceMed Phys, 38
S Stathakis V Chandraraj (2011)
Comparison of four commercial devices for RapidArc and sliding window IMRT QAJ Appl Clin Med Phys, 12
(HanZNgSBhagwatMLyatskayaYZygmanskiPEvaluation of MatriXX for IMRT and VMAT dose verifications in peripheral dose regionsMed Phys2010373704371410.1118/1.345570720831078)
HanZNgSBhagwatMLyatskayaYZygmanskiPEvaluation of MatriXX for IMRT and VMAT dose verifications in peripheral dose regionsMed Phys2010373704371410.1118/1.345570720831078HanZNgSBhagwatMLyatskayaYZygmanskiPEvaluation of MatriXX for IMRT and VMAT dose verifications in peripheral dose regionsMed Phys2010373704371410.1118/1.345570720831078, HanZNgSBhagwatMLyatskayaYZygmanskiPEvaluation of MatriXX for IMRT and VMAT dose verifications in peripheral dose regionsMed Phys2010373704371410.1118/1.345570720831078
E Vanetti G Nicolini (2008)
The GLAaS algorithm for portal dosimetry and quality assurance of RapidArc, an intensity modulated rotational therapyRadiat Oncol, 3
W Ansbacher I Gagne (2008)
A Monte Carlo evaluation of RapidArc dose calculations for oropharynx radiotherapyPhys Med Biol, 53
F Araki Y Nakaguchi (2012)
Dose verification of IMRT by use of a COMPASS transmission detectorRadiol Phys Technol, 5
(ChandrarajVStathakisSManickamREsquivelCSupeSPapanikolauNComparison of four commercial devices for RapidArc and sliding window IMRT QAJ Appl Clin Med Phys201112336721587184)
ChandrarajVStathakisSManickamREsquivelCSupeSPapanikolauNComparison of four commercial devices for RapidArc and sliding window IMRT QAJ Appl Clin Med Phys201112336721587184ChandrarajVStathakisSManickamREsquivelCSupeSPapanikolauNComparison of four commercial devices for RapidArc and sliding window IMRT QAJ Appl Clin Med Phys201112336721587184, ChandrarajVStathakisSManickamREsquivelCSupeSPapanikolauNComparison of four commercial devices for RapidArc and sliding window IMRT QAJ Appl Clin Med Phys201112336721587184
J Medin S Korreman (2009)
Dosimetric verification of RapidArc treatment deliveryActa Oncol, 48
(FogliataANicoliniGClivioAVanettiECozziLOn the dosimetric impact of inhomogeneity management in the Acuros XB algorithm for breast treatmentRadiat Oncol2011610310.1186/1748-717X-6-10321871079)
FogliataANicoliniGClivioAVanettiECozziLOn the dosimetric impact of inhomogeneity management in the Acuros XB algorithm for breast treatmentRadiat Oncol2011610310.1186/1748-717X-6-10321871079FogliataANicoliniGClivioAVanettiECozziLOn the dosimetric impact of inhomogeneity management in the Acuros XB algorithm for breast treatmentRadiat Oncol2011610310.1186/1748-717X-6-10321871079, FogliataANicoliniGClivioAVanettiECozziLOn the dosimetric impact of inhomogeneity management in the Acuros XB algorithm for breast treatmentRadiat Oncol2011610310.1186/1748-717X-6-10321871079
R Buchana A Gloi (2011)
RapidArc quality assurance through MapCHECKJ Appl Clin Med Phys, 12
(OttoKVolumetric modulated arc therapy: IMRT in a single gantry arcMed Phys20083531031710.1118/1.281873818293586)
OttoKVolumetric modulated arc therapy: IMRT in a single gantry arcMed Phys20083531031710.1118/1.281873818293586OttoKVolumetric modulated arc therapy: IMRT in a single gantry arcMed Phys20083531031710.1118/1.281873818293586, OttoKVolumetric modulated arc therapy: IMRT in a single gantry arcMed Phys20083531031710.1118/1.281873818293586
(VanettiENicoliniGNordJPeltolaJClivioAFogliataACozziLOn the role of the optimization algorithm of RapidArc(®) volumetric modulated arc therapy on plan quality and efficiencyMed Phys201138584410.1118/1.364186622047348)
VanettiENicoliniGNordJPeltolaJClivioAFogliataACozziLOn the role of the optimization algorithm of RapidArc(®) volumetric modulated arc therapy on plan quality and efficiencyMed Phys201138584410.1118/1.364186622047348VanettiENicoliniGNordJPeltolaJClivioAFogliataACozziLOn the role of the optimization algorithm of RapidArc(®) volumetric modulated arc therapy on plan quality and efficiencyMed Phys201138584410.1118/1.364186622047348, VanettiENicoliniGNordJPeltolaJClivioAFogliataACozziLOn the role of the optimization algorithm of RapidArc(®) volumetric modulated arc therapy on plan quality and efficiencyMed Phys201138584410.1118/1.364186622047348
(NakaguchiYArakiFMaruyamaMSaigaSDose verification of IMRT by use of a COMPASS transmission detectorRadiol Phys Technol20125637010.1007/s12194-011-0137-y22038312)
NakaguchiYArakiFMaruyamaMSaigaSDose verification of IMRT by use of a COMPASS transmission detectorRadiol Phys Technol20125637010.1007/s12194-011-0137-y22038312NakaguchiYArakiFMaruyamaMSaigaSDose verification of IMRT by use of a COMPASS transmission detectorRadiol Phys Technol20125637010.1007/s12194-011-0137-y22038312, NakaguchiYArakiFMaruyamaMSaigaSDose verification of IMRT by use of a COMPASS transmission detectorRadiol Phys Technol20125637010.1007/s12194-011-0137-y22038312
T Wareing O Vassiliev (2010)
Validation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beamsPhys Med Biol, 55
S Ng Z Han (2010)
Evaluation of MatriXX for IMRT and VMAT dose verifications in peripheral dose regionsMed Phys, 37
L Lee J Qian (2010)
Dose reconstruction for volumetric modulated arc therapy (VMAT) using cone beam CT and dynamic log filesPhys Med Biol, 55
(KanMLeungLYuPDosimetric impact of using the Acuros XB algorithm for intensity modulated radiation therapy and RapidArc planning in nasopharyngeal carcinomasInt J Radiat Oncol Biol Phys201285e73e8023040220)
KanMLeungLYuPDosimetric impact of using the Acuros XB algorithm for intensity modulated radiation therapy and RapidArc planning in nasopharyngeal carcinomasInt J Radiat Oncol Biol Phys201285e73e8023040220KanMLeungLYuPDosimetric impact of using the Acuros XB algorithm for intensity modulated radiation therapy and RapidArc planning in nasopharyngeal carcinomasInt J Radiat Oncol Biol Phys201285e73e8023040220, KanMLeungLYuPDosimetric impact of using the Acuros XB algorithm for intensity modulated radiation therapy and RapidArc planning in nasopharyngeal carcinomasInt J Radiat Oncol Biol Phys201285e73e8023040220
(GagneIAnsbacherWZavgorodniSPopescuCBeckhamWA Monte Carlo evaluation of RapidArc dose calculations for oropharynx radiotherapyPhys Med Biol2008537167718510.1088/0031-9155/53/24/01119033640)
GagneIAnsbacherWZavgorodniSPopescuCBeckhamWA Monte Carlo evaluation of RapidArc dose calculations for oropharynx radiotherapyPhys Med Biol2008537167718510.1088/0031-9155/53/24/01119033640GagneIAnsbacherWZavgorodniSPopescuCBeckhamWA Monte Carlo evaluation of RapidArc dose calculations for oropharynx radiotherapyPhys Med Biol2008537167718510.1088/0031-9155/53/24/01119033640, GagneIAnsbacherWZavgorodniSPopescuCBeckhamWA Monte Carlo evaluation of RapidArc dose calculations for oropharynx radiotherapyPhys Med Biol2008537167718510.1088/0031-9155/53/24/01119033640
F Lorenz R Boggula (2010)
Experimental validation of a commercial 3D dose verification system for intensity-modulated arc therapiesPhys Med Biol, 55
recording and reporting Intensity Modulated Photon Beam Therapy citation_title=Prescribing (2010)
Prescribing, recording and reporting Intensity Modulated Photon Beam Therapy (IMRT) (ICRU report 83)
(BakhtiariMKumaraswamyLBaileyDde BoerSMalhotraHPodgorsakMUsing an EPID for patient specific VMAT quality assuranceMed Phys2011381366137310.1118/1.355292521520847)
BakhtiariMKumaraswamyLBaileyDde BoerSMalhotraHPodgorsakMUsing an EPID for patient specific VMAT quality assuranceMed Phys2011381366137310.1118/1.355292521520847BakhtiariMKumaraswamyLBaileyDde BoerSMalhotraHPodgorsakMUsing an EPID for patient specific VMAT quality assuranceMed Phys2011381366137310.1118/1.355292521520847, BakhtiariMKumaraswamyLBaileyDde BoerSMalhotraHPodgorsakMUsing an EPID for patient specific VMAT quality assuranceMed Phys2011381366137310.1118/1.355292521520847
S Padmanabhan SA Syamkumar (2011)
Characterization of responses of 2d array seven29 detector and its combined use with Octavius phantom for the patient-specific quality assurance in RapidArc treatment deliveryMed Dosim, 37
G Nicolini E Vanetti (2011)
On the role of the optimization algorithm of RapidArc(®) volumetric modulated arc therapy on plan quality and efficiencyMed Phys, 38
(GloiABuchanaRZugeCGoettlerARapidArc quality assurance through MapCHECKJ Appl Clin Med Phys201112325121587169)
GloiABuchanaRZugeCGoettlerARapidArc quality assurance through MapCHECKJ Appl Clin Med Phys201112325121587169GloiABuchanaRZugeCGoettlerARapidArc quality assurance through MapCHECKJ Appl Clin Med Phys201112325121587169, GloiABuchanaRZugeCGoettlerARapidArc quality assurance through MapCHECKJ Appl Clin Med Phys201112325121587169
S Stathakis V Chandraraj (2010)
Consistency and reproducibility of the VMAT plan delivery using three independent validation methodsJ Appl Clin Med Phys, 12
(SchreibmannEDhabaanAElderEFoxTPatient specific quality assurance method for VMAT treatment deliveryMed Phys2009364530453510.1118/1.321308519928084)
SchreibmannEDhabaanAElderEFoxTPatient specific quality assurance method for VMAT treatment deliveryMed Phys2009364530453510.1118/1.321308519928084SchreibmannEDhabaanAElderEFoxTPatient specific quality assurance method for VMAT treatment deliveryMed Phys2009364530453510.1118/1.321308519928084, SchreibmannEDhabaanAElderEFoxTPatient specific quality assurance method for VMAT treatment deliveryMed Phys2009364530453510.1118/1.321308519928084
(BushKTownsonRZavgorodniSMonte Carlo simulation of RapidArc radiotherapy deliveryPhys Med Biol200853N359N37110.1088/0031-9155/53/19/N0118758001)
BushKTownsonRZavgorodniSMonte Carlo simulation of RapidArc radiotherapy deliveryPhys Med Biol200853N359N37110.1088/0031-9155/53/19/N0118758001BushKTownsonRZavgorodniSMonte Carlo simulation of RapidArc radiotherapy deliveryPhys Med Biol200853N359N37110.1088/0031-9155/53/19/N0118758001, BushKTownsonRZavgorodniSMonte Carlo simulation of RapidArc radiotherapy deliveryPhys Med Biol200853N359N37110.1088/0031-9155/53/19/N0118758001
(QianJLeeLLiuWChuKMokELuxtonGLeQXingLDose reconstruction for volumetric modulated arc therapy (VMAT) using cone beam CT and dynamic log filesPhys Med Biol2010553597361010.1088/0031-9155/55/13/00220526034)
QianJLeeLLiuWChuKMokELuxtonGLeQXingLDose reconstruction for volumetric modulated arc therapy (VMAT) using cone beam CT and dynamic log filesPhys Med Biol2010553597361010.1088/0031-9155/55/13/00220526034QianJLeeLLiuWChuKMokELuxtonGLeQXingLDose reconstruction for volumetric modulated arc therapy (VMAT) using cone beam CT and dynamic log filesPhys Med Biol2010553597361010.1088/0031-9155/55/13/00220526034, QianJLeeLLiuWChuKMokELuxtonGLeQXingLDose reconstruction for volumetric modulated arc therapy (VMAT) using cone beam CT and dynamic log filesPhys Med Biol2010553597361010.1088/0031-9155/55/13/00220526034
(KorremanSMedinJKjaer-KristoffersenFDosimetric verification of RapidArc treatment deliveryActa Oncol20094818519110.1080/0284186080228711618777411)
KorremanSMedinJKjaer-KristoffersenFDosimetric verification of RapidArc treatment deliveryActa Oncol20094818519110.1080/0284186080228711618777411KorremanSMedinJKjaer-KristoffersenFDosimetric verification of RapidArc treatment deliveryActa Oncol20094818519110.1080/0284186080228711618777411, KorremanSMedinJKjaer-KristoffersenFDosimetric verification of RapidArc treatment deliveryActa Oncol20094818519110.1080/0284186080228711618777411
J Pyyry W Ulmer (2005)
A 3D photon superposition convolution algorithm and its foundation on results of Monte Carlo calculationsPhys Med Biol, 50
E Korevaar J Godart (2011)
Reconstruction of high resolution 3D dose from matrix measurements: error detection capability of the COMPASS correction kernel methodPhys Med Biol, 56
(SyamkumarSAPadmanabhanSSukumarPNagarajanVCharacterization of responses of 2d array seven29 detector and its combined use with Octavius phantom for the patient-specific quality assurance in RapidArc treatment deliveryMed Dosim201137536021741819)
SyamkumarSAPadmanabhanSSukumarPNagarajanVCharacterization of responses of 2d array seven29 detector and its combined use with Octavius phantom for the patient-specific quality assurance in RapidArc treatment deliveryMed Dosim201137536021741819SyamkumarSAPadmanabhanSSukumarPNagarajanVCharacterization of responses of 2d array seven29 detector and its combined use with Octavius phantom for the patient-specific quality assurance in RapidArc treatment deliveryMed Dosim201137536021741819, SyamkumarSAPadmanabhanSSukumarPNagarajanVCharacterization of responses of 2d array seven29 detector and its combined use with Octavius phantom for the patient-specific quality assurance in RapidArc treatment deliveryMed Dosim201137536021741819
Background: The accuracy of the two dose calculation engines available for RapidArc planning (both released for clinical use) is investigated in comparison to the COMPASS data. Methods: Two dose calculation algorithms (Acuros-XB and Anisotropic Analytic Algorithm (AAA)) were used to calculate RA plans and compared to calculations with the Collapsed Cone Convolution algorithm (CC) from the COMPASS system (IBA Dosimetry). CC calculations, performed on patient data, are based on experimental fluence measurements with a 2D array of ion chambers mounted on the linac head. The study was conducted on clinical cases treated with RA. Five cases for each of the following groups were included: Brain, Head and Neck, Thorax, Pelvis and stereotactic body radiation therapy for hypo-fractionated treatments with small fields. COMPASS measurements were performed with the iMatrixx-2D array. RapidArc plans were optimized for delivery using 6MV photons from a Clinac-iX (Varian, Palo Alto, USA). Accuracy of the RA calculation was appraised by means of: 1) comparison of Dose Volume histograms (DVH) metrics; 2) analysis of differential dose distributions and determination of mean dose differences per organ; 3) 3D gamma analysis with distance-to-agreement and dose difference thresholds set to 3%/3 mm or 2%/2 mm for targets, organs at risks and for the volumes encompassed by the 50 and 10% isodoses. Results: For almost all parameters, the better agreement was between Acuros-XB and COMPASS independently from the anatomical site and fractionation. The same result was obtained from the mean dose difference per organ with Acuros-CC average differences below 0.5% while for AAA-CC data, average deviations exceeded 0.5% and in the case of the pelvis 1%. Relevance of observed differences determined with the 3D gamma analysis resulted in a pass rate exceeding 99.5% for Acuros-CC and exceeding 97.5% for AAA-CC. Conclusions: This study demonstrated that i) a good agreement exists between COMPASS-CC calculations based on measured fluences with respect to dose distributions obtained with both Acuros-XB and AAA algorithms; ii) 3D dose distributions reconstructed from actual delivery coincide very precisely with the planned data; iii) a slight preference in favor of Acuros-XB was observed suggesting the preference for this algorithm in clinical applications. Keywords: Acuros-XB, Anisotropic Analytical Algorithm, RapidArc, Compass * Correspondence: Antonella.Fogliata-Cozzi@eoc.ch Department of Medical Physics, Oncology Institute of Southern Switzerland, Bellinzona, Switzerland Oncology Institute of Southern, 6504, Bellinzona, Switzerland Full list of author information is available at the end of the article © 2013 Kathirvel et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Kathirvel et al. Radiation Oncology 2013, 8:140 Page 2 of 9 http://www.ro-journal.com/content/8/1/140 Table 1 Brain (Prescription 46.4 Gy [45.0.-50.4]) Table 2 HN (Prescription 63.2 Gy [50.0.-70.5]) Parameter Acuros XB AAA CC p Parameter Acuros XB AAA CC p 3 3 PTV ( Volume [cm ] = 446.4 ± 235.2) PTV ( Volume [cm ] = 263.4 ± 213.3) Mean [%] 100.3 ± 0.3 101.8 ± 1.0 100.9 ± 0.7 a,c Mean [%] 100.2 ± 0.8 101.1 ± 1.4 100.8 ± 1.0 a,b D -D [%] 7.7 ± 1.6 7.6 ± 1.7 7.8 ± 1.7 D -D [%] 7.0 ± 2.6 7.1 ± 4.3 6.9 ± 3.6 5% 95% 5% 95% V [%] 95.9 ± 1.3 97.3 ± 2.4 96.3 ± 2.0 c V [%] 96.2 ± 2.0 96.8 ± 3.7 96.7 ± 3.0 95% 95% V [%] 0.8 ± 0.6 6.5 ± 3.6 2.5 ± 2.5 a,c V [%] 1.1 ± 1.9 4.4 ± 8.3 2.3 ± 4.7 105% 105% CI 1.2 ± 0.1 1.2 ± 0.1 1.1 ± 0.1 CI 1.9 ± 0.8 2.2 ± 1.1 2.0 ± 0.9 90% 95% 3 3 Brain Stem ( Volume [cm ] = 24.2 ± 3.9) Spinal Cord ( Volume [cm ] = 22.9 ± 4.5) D [%] 102.7 ± 2.2 104.0 ± 2.1 103.1 ± 2.7 a D [%] 61.8 ± 3.7 63.7 ± 3.5 62.5 ± 3.3 a,c 1% 1% D [%] 94.6 ± 16.7 95.6 ± 17.1 95.2 ± 17.0 a D [%] 60.0 ± 3.7 61.7 ± 3.7 60.5 ± 3.6 a,c 1.8cm3 1.8cm3 Parotids ( Volume [cm ] = 38.5 ± 19.0) V [%] 5.0 ± 11.1 5.7 ± 12.8 5.3 ± 11.9 50Gy Chiasm ( Volume [cm ] = 1.1 ± 0.4) Mean [%] 48.4 ± 11.6 49.9 ± 11.4 49.0 ± 11.6 a,b,c D [%] 95.2 ± 16.1 96.6 ± 15.4 95.7 ± 16.7 D [%] 68.0 ± 21.0 69.1 ± 19.7 68.1 ± 20.1 c 1% 33% D [%] 69.5 ± 31.6 69.3 ± 30.6 68.9 ± 30.7 D [%] 24.6 ± 10.7 26.9 ± 11.7 26.2 ± 11.6 a 1.8cm3 67% Oral Cavity ( Volume [cm ] = 76.1 ± 3.8) V [%] 11.5 ± 25.7 14.4 ± 32.2 15.1 ± 33.8 50Gy Lens ( Volume [cm ] = 0.3 ± 0.1) Mean [%] 66.7 ± 13.8 67.4 ± 14.1 67.3 ± 14.1 a Mean [%] 8.8 ± 1.9 9.4 ± 2.4 8.8 ± 2.3 c D [%] 99.6 ± 1.2 99.0 ± 1.4 99.6 ± 0.9 1% D [%] 10.5 ± 2.3 10.9 ± 2.5 10.3 ± 2.7 c D [%] 76.0 ± 12.1 76.7 ± 12.5 76.5 ± 12.4 1% 33% Larynx ( Volume [cm ] = 37.1 ± 19.9) D [%] 7.5 ± 1.9 8.1 ± 2.3 7.4 ± 2.1 c 1.8cm3 Optic Nerve ( Volume [cm ] = 1.2 ± 0.7) Mean [%] 67.8 ± 3.7 69.0 ± 3.7 69.1 ± 3.7 a,b D [%] 77.1 ± 28.6 78.1 ± 28.6 76.6 ± 28.7 a D [%] 93.1 ± 6.4 94.0 ± 7.5 92.8 ± 7.3 c 1% 1% D [%] 25.8 ± 11.6 26.6 ± 12.3 26.1 ± 12.2 D [%] 73.6 ± 4.2 74.8 ± 4.3 74.8 ± 4.3 a,b 1.8cm3 33% Retina ( Volume [cm ] = 17.7 ± 1.5) a Acuros vs AAA, b Acuros vs CC, c AAA vs CC. Mean [%] 19.5 ± 9.7 20.2 ± 9.9 19.7 ± 9.8 a,c These used for benchmark of the calculations, experimen- D [%] 48.9 ± 21.7 51.3 ± 21.9 50.2 ± 21.2 c 1% tal measurements with a plethora of different detectors D [%] 34.6 ± 19.1 35.5 ± 19.5 34.9 ± 18.6 a 1.8cm3 and established consolidated practice in the clinical rou- a Acuros vs AAA, b Acuros vs CC, c AAA vs CC. tine. As a general summary, all these studies suggested the safe and reliable consistency of calculations vs delivery ei- Background ther in simple geometrical or anthropomorphic phantoms. Volumetric Modulated Arc Therapy (VMAT) is, in the Some studies [14,15] addressed the usage of Monte Carlo variety of radiation treatment modalities, a possibly valu- methods to convert delivery information registered by the able but also challenging technique because of its intrinsic linacs during irradiation in input data for some sort of ”ac- complexity involving advanced inverse planning algo- tual” in-patient dose calculation to compare to planned rithms, dose calculation engines applied to complex fields dose distributions. Limit of this branch of investigations is and dynamic delivery with several variable parameters the need of computational tools not commercially avail- (speed of multileaf collimator, dose rate, gantry rotational able and not easily implementable in routine settings. On speed). All elements are highly interconnected and con- the same line, little has been done so far, to use measured tribute together to the generation of dose distributions of data to recalculate the ‘actual’ dose in the patients. Investi- virtually any complexity. As for all advanced treatment gations based on the usage of electronic portal imaging techniques, one fundamental aspect to monitor and to devices, used to measure transmitted dose through the pa- guarantee is the consistence between planning and deliv- tients represents the current cutting edge of the research. ery. This to prevent the risk of un-intended mistreatments Pioneering studies demonstrated the possibility to recon- with potentially severe implications for patients. The struct reliable dose in a quasi in-vivo setting by using as present study aims to contribute to the determination of patient model the Cone Beam CT data that can be ac- this accuracy in a clinical environment. The VMAT model quired daily before treatment [16]. From a different per- investigated here is the RapidArc solution (RA, Varian spective, it is possible also to use measurement devices to Medical Systems, USA) derived from the original proto- detect the fluence generated by the delivery process before type of Otto [1]. Several studies appraised the subject of entering the patient and from this, to determine the quality assurance of delivery vs calculation of RA [2-13]. ”actual” delivered dose inside a patient model. The Kathirvel et al. Radiation Oncology 2013, 8:140 Page 3 of 9 http://www.ro-journal.com/content/8/1/140 Table 3 Thorax (Prescription 46.2 Gy [39.6.-50.0]) Table 4 Pelvis (Prescription 51.6 Gy [45.0.-56.0]) Parameter Acuros XB AAA CC p Parameter Acuros XB AAA CC p 3 3 PTV ( Volume [cm ] = 516.8 ± 398.3) PTV ( Volume [cm ] = 817.6 ± 527.5) Mean [%] 100.3 ± 1.0 101.2 ± 0.4 100.9 ± 1.2 Mean [%] 98.5 ± 3.3 100.3 ± 3.3 98.9 ± 3.2 a,c D -D [%] 10.3 ± 1.6 9.8 ± 3.0 10.8 ± 2.6 c D -D [%] 6.8 ± 0.9 6.3 ± 1.0 6.7 ± 1.2 a,c 5% 95% 5% 95% V [%] 94.3 ± 2.2 95.3 ± 2.4 94.4 ± 3.3 a V [%] 80.3 ± 35.1 88.9 ± 22.2 82.5 ± 28.7 95% 95% V [%] 4.1 ± 2.4 6.8 ± 5.7 7.0 ± 5.1 V [%] 1.1 ± 1.6 4.4 ± 5.6 1.8 ± 3.8 105% 105% CI 1.8 ± 1.2 1.9 ± 1.2 2.0 ± 1.1 CI 1.2 ± 0.1 1.3 ± 0.1 1.2 ± 0.1 a,c 90% 90% 3 3 Ipsil Lung ( Volume [cm ] = 1700.2 ± 318.3) Bladder ( Volume [cm ] = 259.3 ± 114.6) Mean [%] 43.3 ± 24.7 43.3 ± 24.7 42.6 ± 24.5 Mean [%] 70.4 ± 16.4 72.2 ± 16.8 70.6 ± 16.5 a,c V [%] 48.0 ± 25.7 47.8 ± 25.7 47.5 ± 25.7 b D [%] 101.6 ± 2.5 103.6 ± 2.8 102.1 ± 2.8 a,c 20Gy 1% D [%] 104.3 ± 0.9 103.9 ± 0.9 104.5 ± 0.2 a D [%] 55.3 ± 29.0 56.7 ± 29.7 55.2 ± 29.1 a,c 1% 67% 3 3 Contr Lung ( Volume [cm ] = 2048.4 ± 42.1) Rectum ( Volume [cm ] = 101.6 ± 44.8) Mean [%] 9.6 ± 2.6 9.8 ± 2.8 9.1 ± 2.3 Mean [%] 68.4 ± 17.3 70.0 ± 17.5 68.3 ± 16.9 a,c V [%] 3.2 ± 2.6 3.2 ± 2.6 3.0 ± 2.4 D [%] 100.4 ± 4.2 101.9 ± 4.0 100.6 ± 4.1 a,c 20Gy 1% D [%] 58.2 ± 19.3 58.8 ± 19.9 57.1 ± 18.2 D [%] 53.4 ± 28.1 55.0 ± 28.5 53.3 ± 27.9 a,c 1% 67% 3 3 Lungs ( Volume [cm ] = 3382.7 ± 479.6) Femurs ( Volume [cm ] = 172.7 ± 46.3) Mean [%] 24.5 ± 7.0 24.9 ± 7.2 23.9 ± 6.9 b,c Mean [%] 38.9 ± 6.8 40.0 ± 7.0 38.7 ± 7.0 a,c V [%] 19.8 ± 7.7 19.9 ± 7.7 19.4 ± 7.7 b,c D [%] 75.8 ± 17.9 77.9 ± 18.5 76.0 ± 17.9 a,c 20Gy 1% D [%] 98.4 ± 4.5 98.4 ± 4.3 98.2 ± 4.6 D [%] 75.7 ± 18.0 77.8 ± 18.6 75.9 ± 18.0 a,c 1% 1.8cm3 3 3 Heart ( Volume [cm ] = 501.3 ± 31.4) Bowel ( Volume [cm ] = 1062.2 ± 903.1) Mean [%] 39.7 ± 27.0 40.4 ± 27.6 39.7 ± 27.3 c Mean [%] 28.0 ± 19.4 28.8 ± 19.6 27.3 ± 19.2 a,b,c D [%] 101.9 ± 3.0 103.5 ± 3.0 102.2 ± 3.9 a D [%] 68.8 ± 45.9 69.9 ± 46.3 68.5 ± 45.9 a,c 1% 1% Spinal Canal ( Volume [cm ] = 31.9 ± 3.3) D [%] 69.0 ± 48.1 69.9 ± 48.4 68.5 ± 48.0 a,b,c 1.8cm3 D [%] 67.6 ± 23.3 68.5 ± 23.5 67.9 ± 23.1 a a Acuros vs AAA, b Acuros vs CC, c AAA vs CC. 1% D [%] 63.7 ± 23.4 64.5 ± 23.5 64.1 ± 23.5 b 1.8cm3 a Acuros vs AAA, b Acuros vs CC, c AAA vs CC. Methods Patients’ selection COMPASS system (IBA Dosimetry, Germany) is a com- The study was designed to explore a wide range of clinical mercial system which allows to investigate this area. In fact, applications of RapidArc. For this reason five localisations the COMPASS consists of an experimental device, the were identified and for each of them, five patients were se- Matrix 2D array of ionization chambers which, mounted lected from the clinical database. Localisations (or groups) on the linac head, can measure the output fluence of any were: brain, head and neck (HN), thorax, pelvis; these given field. This measured fluence can be used as input to a represented conventional fractionation regimens and calculation engine based on a Collapsed Cone algorithm fields of medium to large size. A fifth group was defined (CC) which allows to compute a 3D dose distribution in a including patients treated for stereotactic body radio- phantom or in a patient CT dataset. In this way, although therapy (SBRT) with hypofractionated regimen and usage depending on the CC algorithm and the CT set used, it is of small fields to define the arcs. To increase the variability possible to generate a kind of ‘’delivered” dose distribution. of the cases, patients with different dose prescriptions The COMPASS system has been studied in terms of its in- were included in the study and, to make them comparable, trinsic accuracy compared to other measurement devices as analysis has been performed in terms of percentage doses. well as in terms of its clinical usability [17-21] for IMRT Tables 1, 2, 3, 4 and 5 report also the mean prescribed techniques. In this study, COMPASS usage will be ex- doses and ranges for each of the five groups. For all pa- tended to VMAT 3D quality assurance. tients, the planning CT and structures were shared in Aim of the study is the investigation of the accuracy of DICOM format between the planning system and the ex- the two dose calculation engines available for RA plan- perimental COMPASS system described below. For each ning (the Acuros-XB and the Anisotropic Analytical Al- patient the planning target volume (PTV) and several or- gorithm both released for clinical use) in comparison to gans at risk were considered. These depend upon the the COMPASS data for a number of cases representing localization and included: brain stem, chiasm, lenses, optic a wide spectrum of possible clinical conditions. nerves, retina, spinal cord, parotids, oral cavity, larynx, Kathirvel et al. Radiation Oncology 2013, 8:140 Page 4 of 9 http://www.ro-journal.com/content/8/1/140 Table 5 SBRT (Prescription 60.0 Gy [60.0.-60.0]) referred to the original publications [17,18]. Its principle Parameter Acuros XB AAA CC p can be summarized as follows. A detector is mounted on the linac gantry (typically at the accessory mount holder) PTV ( Volume [cm ] = 68.9 ± 50.2) and it is used to measure the fluence produced by the Mean [%] 102.2 ± 2.4 102.9 ± 3.4 102.0 ± 2.7 linac for a given field (static or dynamic, modulated or D -D [%] 19.2 ± 4.0 18.1 ± 2.5 20.2 ± 3.6 b 5% 95% plain). The measured fluence is used then as input data V [%] 91.9 ± 3.0 93.2 ± 4.0 91.0 ± 3.1 b,c 95% for a 3D convolution algorithm (Collapsed Cone) which V [%] 35.0 ± 16.9 41.2 ± 21.4 35.2 ± 17.0 105% allows to reconstruct the dose ‘’delivered” by the linac in CI 1.1 ± 0.2 1.2 ± 0.2 1.1 ± 0.2 b,c a CT dataset (which could be a phantom or a patient 90% set, even a Cone Beam CT). In the present case, the Ipsil Lung ( Volume [cm ] = 1202.5 ± 421.1) same CT sets were used for RA planning and for COM- Mean [%] 14.7 ± 12.7 14.8 ± 12.6 14.8 ± 12.5 PASS calculations. The dose calculation was performed V [%] 15.1 ± 17.4 15.0 ± 17.3 15.3 ± 17.1 20Gy with a resolution of 2.5 mm. The detector used for flu- D [%] 74.8 ± 43.5 75.2 ± 43.8 74.9 ± 43.7 1% ence measurements is the Matrixx 2D array of ion Contr Lung ( Volume [cm ] = 1164.7 ± 601.0) chambers with a spatial resolution of 7.6 mm (center-to- Mean [%] 2.4 ± 2.0 2.4 ± 2.0 2.2 ± 1.9 center distance of the chambers). Fine interpolation of V [%] 5.4 ± 10.5 5.1 ± 9.9 4.9 ± 9.4 data to build an high resolution fluence is part of the 5Gy COMPASS algorithm itself. In this study, the entire D [%] 7.9 ± 4.9 8.0 ± 4.9 7.7 ± 5.0 b,c 1% 3 COMPASS system can be considered as a pre-treatment Ribs ( Volume [cm ] = 213.5 ± 327.2) quality assurance tool (since it was used in absence of D [%] 83.3 ± 15.0 85.1 ± 15.7 83.7 ± 14.7 a 1% the patient) and it was used to benchmark the accuracy V [%] 19.0 ± 18.7 20.1 ± 19.9 19.1 ± 18.8 30Gy of the Eclipse calculations vs. recalculation from actual Liver ( Volume [cm ] = 1135.0 ± 489.9) fluence delivery. In the present study no assessment of Mean [%] 14.7 ± 4.3 15.0 ± 4.3 14.5 ± 4.3 a,b,c the intrinsic accuracy of CC is provided and readers are D [%] 88.6 ± 33.1 90.1 ± 33.8 89.0 ± 33.3 referred to Korrevaar et al [17] for an appraisal. 1% V [%] 11.6 ± 6.2 11.8 ± 6.2 11.6 ± 6.1 21Gy Analysis and evaluation tools a Acuros vs AAA, b Acuros vs CC, c AAA vs CC. To appraise the accuracy of the algorithms from Eclipse heart, ipsi- and contra-lateral lungs, ribs, liver, rectum, with respect of the calculations of COMPASS, three bladder, bowels, femoral heads. Tables 1, 2, 3, 4 and 5 levels of tests were designed. report the volumes of each of these targets and organs The first level of investigation was based on the con- at risk. ventional analysis of parameters derived from Dose Vol- ume Histograms (DVH). To avoid possible biases in the Dose calculation algorithms and experimental construction of DVHs, the 3D dose matrices from instrumentation COMPASS were imported in Eclipse so that only one RapidArc plans were optimized using the Progressive engine was applied to build them. The analysis included Resolution Optimiser algorithm (PRO 10.0.28) [22] imple- for target volumes (PTV) the mean dose, the coverage mented in the Eclipse planning system (Varian Medical expressed as the volume receiving 95% or 105% of the Systems, USA) and dose calculations were performed prescription dose (V and V ), the homogeneity 95% 105% using for each case both the Anisotropic Analytical Algo- expressed as the difference between the dose to 5% and rithm (AAA) [23] and the Acuros-XB algorithm [24] (ver- to 95% of it (D -D ) and the conformality expressed 5% 95% sion 10.0.28 for both) using a spatial resolution of 2.5 mm as the ratio between the volume of the 95% isodose and in the x and y directions. All plans were optimized and the PTV (conformity index, CI ). For organs at risk, 95% calculated for 6MV photon beams generated by a Clinac various parameters were quantified depending on the iX equipped with a Millennium 120 Multileaf Collimator. specificity of each of them in the spirit of ICRU 83 rec- Given the variability of the clinical cases, RA plans in- ommendations [25]. These included: mean doses, max- cluded full, partial, single and multiple arcs to cover the imum significant doses (e.g. D or D ), doses to a 1% 1.8cm3 spectrum of routine application of the treatment given volume (D ) and volumes receiving given dose x% technique. levels (V ). x% The COMPASS system (IBA Dosimetry, Germany), in The second level of investigation was aiming to quan- its version 2.0.7, was used to generate independent data tify global differences in the dose distributions between for the verification of the accuracy of the two Eclipse al- the different algorithms and conditions. This was better gorithms with respect to actual delivery. For a detailed expressed in terms of mean dose difference for each description of the COMPASS system, readers are PTV or organ at risk (depending on the groups) for the Kathirvel et al. Radiation Oncology 2013, 8:140 Page 5 of 9 http://www.ro-journal.com/content/8/1/140 Figure 1 Graphical summary of the average percentage dose difference between the various algorithms for various significant volumes or organs. Data, obtained from 3D dose distributions, are presented separately for the five groups: brain, head and neck, thorax, pelvis and SBRT clinical cases. couples AAA – Acuros, CC - AAA and CC – Acuros. clinically relevant objects. To appraise also the accuracy Positive differences indicated a dose over-estimation of in the low dose range, the test was applied also to the the first algorithm with respect to the second, and vice- volume of patients encompassed by the 50% and 10% versa. Objective was to identify and quantify possible isodoses. All tests were repeated using two sets of systematic trends. thresholds: a conventional dose difference and distance The third level of analysis was aiming to determine to agreement (DTA) of 3%/3 mm, used in routine clin- the possible relevance of observed discrepancies. The ical practice for quality assurance purposes, and a more adopted tool was the 3D gamma analysis based on a restrictive 2%/2 mm aiming to stress the algorithms at generalization of the gamma of Low concept [26]. The the limit of their calculation resolution. Results were computational methods here adopted has been described expressed in terms of pass rates, i.e. the percentage of in Fogliata et al. [27]. The 3D gamma test was applied to voxels in a volume passing the gamma test. As a general each of the volumes listed above representing the concept, in the comparison between AAA (or Acuros) Kathirvel et al. Radiation Oncology 2013, 8:140 Page 6 of 9 http://www.ro-journal.com/content/8/1/140 Figure 2 Graphical summary of the failure rate after 3D gamma analysis (with thresholds set to 3%/3 mm (a) or to 2%/2 mm (b)). Data, presented for various significant volumes or organs at risk, are presented separately for the five groups: head and neck, thorax, pelvis and SBRT clinical cases. Kathirvel et al. Radiation Oncology 2013, 8:140 Page 7 of 9 http://www.ro-journal.com/content/8/1/140 Table 6 Gamma agreement index are on average in better agreement with a more variable Group AAA_Acuros CC_Acuros CC_AAA p pattern of over- and under- estimation of the doses. The average overestimation of AAA respect to Acuros for GAI [%] with criteria 3 %/3 mm the analyzed organs is 0.70 ± 0.69% and of AAA respect Brain 99.1 ± 2.1 99.2 ± 2.1 99.7 ± 0.6 b to COMPASS-CC is 0.88 ± 0.46%. The average difference H&N 99.0 ± 1.4 99.4 ± 0.9 99.4 ± 1.0 a,b between Acuros and COMPASS-CC is −0.02 ± 0.51%. In Thorax 99.6 ± 0.8 99.9 ± 0.2 99.7 ± 0.33 - all cases for brain, head and neck, thorax and SBRT, Pelvis 99.4 ± 1.4 99.9 ± 0.3 98.9 ± 3.1 a,c average differences did not exceeded 1.3%, for pelvis SBRT 99.6 ± 1.4 100.0 ± 0.0 99.5 ± 2.1 - these reached 1.8%. In most of the cases the observed differences resulted statistically significant with the ex- GAI [%] with criteria 2 %/2 mm ception of the chiasm in the brain, the larynx in head Brain 97.0 ± 4.5 98.0 ± 3.6 98.7 ± 3.4 a,b and neck, the lungs in the thorax and the PTV and liver H&N 91.1 ± 7.3 96.9 ± 3.2 96.2 ± 5.5 a,b in SBRT, where no significance was determined. Thorax 96.4 ± 5.7 99.2 ± 1.3 97.9 ± 2.4 a,c Figure 2 is the graphical summary of the 3D gamma Pelvis 92.2 ± 11.3 98.8 ± 2.3 91.9 ± 14.4 a,c analysis. Results are shown in terms of the residual fail- SBRT 97.8 ± 4.8 99.9 ± 0.2 98.5 ± 4.9 a ure rate expressed as percentage of voxels in the vol- a AAA_Acuros vs CC_ Acuros, b AAA_ Acuros vs CC_AAA, c CC_ Acuros umes under analysis not passing the gamma test with vs CC_AAA. thresholds set to 3%/3 mm (a) or to 2%/2 mm (b). As for the previous results, data are presented for the five and COMPASS-CC, low pass rates would suggest the groups separately and for the same volumes of interest. risk of relevant discrepancies between the dose delivered The average pass rates (expressed as Gamma Agreement to a patient and the intended plan, outside the ‘’recov- Index, i.e. the percentage of voxels in the organ passing ery” tolerances of the gamma measure. In the absence of the 3D gamma test) are summarized in Table 6. In gen- any consensus on acceptability levels, it is assumed here eral, with the conventional thresholds of 3%/3 mm, all that any pass rate higher than 97% corresponds to com- algorithms did agree with a maximum failure of ~3% pletely satisfactory agreement while, conversely, pass (larynx and rectum). With the tighter thresholds, Acuros rates inferior to 90% would recommend some care and COMPASS-CC remained highly consistent with suggesting possible clinical risks. average failure rate inferior to ~3% with only one excep- For all comparisons, statistical significance at 5% was tion for the low isodose and larynx case in the head and assessed by means of Fisher’s signed test. neck (~6% and ~4% respectively). High failure rates were observed for AAA compared to Acuros or COMPASS- Results CC, particularly for PTVs. A general better agreement Tables 1, 2, 3, 4 and 5 present a summary of the quanti- between AAA and COMPASS-CC was observed than tative comparison of DVH obtained from the dose distri- between AAA and Acuros. butions computed with Acuros-XB and AAA and from the CC based calculations on the experimental COM- Discussion and conclusion PASS. Data are presented separately for the four groups The aim of the present study was the assessment of the showing for each parameter the mean over the patients degree of agreement between 3D dose distributions in the group and the standard deviation; in the p column calculated for clinical RA plans against independent are identified the cases where significant differences calculations based on actual fluence delivered by the lin- were observed. For each organ at risk or target volume it ear accelerators, before entering in the patient. These is reported also the mean volume and its standard devi- fluences were used to calculate the dose ‘delivered’ to ation. All data are reported in % because of the different the patients using the planning CT dataset. In this way, dose prescriptions. Although sometimes statistically sig- the object of the study is in practice the appraisal of the nificant, no macroscopic discrepancies were observed accuracy of the planning calculation engines in simu- between all algorithm for all parameters. lating the real delivery by the linear accelerator. In fact, Figure 1 contains the graphical summary of the a- errors and issues attributable to changes in patient pos- verage percentage dose difference between the three al- ition, anatomy and shape are not accounted for because gorithms for the target volumes and organs at risk for all calculations were performed on the same planning the five groups. Data, obtained from 3D dose distribu- CT, a single snapshot in time. The study as presented tions of the plan differences, are presented separately for here, cannot provide an absolute determination of the the five groups. The error bars represent one standard accuracy of the clinical algorithms because, in the ex- deviation. As a general trend, AAA over-estimate the perimental arm, another algorithm (CC) is used by the dose compared to Acuros and to CC. Acuros and CC COMPASS system. This kind of loop is unavoidable Kathirvel et al. Radiation Oncology 2013, 8:140 Page 8 of 9 http://www.ro-journal.com/content/8/1/140 (and present also in the Monte Carlo based methods or on the fact that, in the absence of any perturbation due to in the EPID based [16] methods) because whatever the patient positioning or organs motion, Acuros-XB repro- strategy, it is always necessary to convert some kind of duces almost perfectly the delivery suggesting its lower measurement into a 3D dose distribution inside the pa- sensitivity to the two above elements if compared to AAA. tient. Validation of the CC algorithm was not subject of In conclusion, this study demonstrated that i) a good this study and was addressed by its developers in their agreement exists between COMPASS-CC calculations founding studies. Here CC accuracy was considered to based on measured fluences with respect to dose distri- be adequate for quality assurance purpose as determined butions obtained with both Acuros-XB and AAA algo- by Korevaar [17] or Nakaguchi [19] and comparable to rithms; ii) 3D dose distributions reconstructed from what achievable with films or other dosimetry devices actual delivery coincide very precisely with the planned (Mapcheck). Within the frame of validity defined above, data; iii) a slight preference in favor of Acuros-XB was the two algorithms available for clinical calculation of observed suggesting the preference for this algorithm in RA plans, Acuros-XB and AAA were compared against clinical applications. benchmark data from COMPASS for a total of 25 pa- Competing interests tients, divided in 5 groups representing different treat- The corresponding author states: Dr. L. Cozzi acts as a scientific advisor to ment sites, dose prescription and plan complexity. From Varian Medical Systems and is Head of Research and Technological Development to Oncology Institute of Southern Switzerland, IOSI, Bellinzona. the three different analyses performed on the data it is possible to extract some general consideration. Based on Authors’ contributions DVH analysis, both Acuros-XB and AAA resulted in good VSS and LC coordinated the entire study. Data collection was conducted by agreement with COMPASS-CC calculations. Acuros-XB MK. VSS, VS, ST. Analysis tools were developed and data processing was done by AFC, GN, EV, AC. LC wrote the manuscript. All authors reviewed and showed smaller differences than AAA for basically all pa- approved the final version. rameters usually used for plan evaluation and for dose reporting as recommended by ICRU [25]. This fact is re- Author details 1 2 Yashoda Super Speciality Hospital, Hyderabad, India. Department of assuring because it suggests that, for RA, the calculation Medical Physics, Oncology Institute of Southern Switzerland, Bellinzona, engines, with all their inherent approximations, are any- 3 Switzerland. All Indian Institute of Medical Sciences, New Delhi, India. way adequate to model the real delivery within acceptable Research and Development Centre, Bharathiar University, Coimbatore, India. Oncology Institute of Southern, 6504, Bellinzona, Switzerland. levels. In fact the differences reported in Tables 1, 2, 3, 4 and 5 would not be considered clinically alarming and Received: 18 April 2013 Accepted: 2 June 2013 could be well ascribed to the intrinsic variation between Published: 11 June 2013 different algorithms. In this respect it is important to no- References tice that for most of the patients, the anatomical sites 1. Otto K: Volumetric modulated arc therapy: IMRT in a single gantry arc. studied included highly heterogeneous tissues which are Med Phys 2008, 35:310–317. differently managed and modeled by the different algo- 2. Korreman S, Medin J, Kjaer-Kristoffersen F: Dosimetric verification of RapidArc treatment delivery. Acta Oncol 2009, 48:185–191. rithms as demonstrated in earlier studies [28-30]. The 3. Nicolini G, Vanetti E, Clivio A, Fogliata A, Korreman S, Bocanek J, Cozzi L: The same results suggest also that even if 3D dose reconstruc- GLAaS algorithm for portal dosimetry and quality assurance of RapidArc, tion in patients are available as part of advanced quality an intensity modulated rotational therapy. Radiat Oncol 2008, 3:24. 4. Schreibmann E, Dhabaan A, Elder E, Fox T: Patient specific quality assurance assurance procedures, an analysis based only on DVH pa- method for VMAT treatment delivery. Med Phys 2009, 36:4530–4535. rameters could be insufficient to determine possibly clin- 5. Teke T, Bergman A, Kwa W, Gill B, Duzenli C, Popescu A: Monte Carlo ical relevant features. More interesting results were in fact based patient specific RapidArc QA using Linac log files. Med Phys 2010, 37:116–123. obtained from the inspection of 3D dose differences per 6. Qian J, Lee L, Liu W, Chu K, Mok E, Luxton G, Le Q, Xing L: Dose organ. In this case, it was possible to demonstrate the sys- reconstruction for volumetric modulated arc therapy (VMAT) using cone tematic difference between Acuros-XB and AAA with re- beam CT and dynamic log files. Phys Med Biol 2010, 55:3597–3610. 7. Han Z, Ng S, Bhagwat M, Lyatskaya Y, Zygmanski P: Evaluation of MatriXX spect to COMPASS-CC and the smaller discrepancies for IMRT and VMAT dose verifications in peripheral dose regions. Med when Acuros-XB is used. In addition, it was possible to Phys 2010, 37:3704–3714. demonstrate that calculations based on AAA have a sys- 8. Chandraraj V, Stathakis S, Manickam R, Esquivel C, Supe S, Papanikolau N: Consistency and reproducibility of the VMAT plan delivery using three tematic trend of over-estimation of the dose actually deliv- independent validation methods. J Appl Clin Med Phys 2010, 12:3373. ered to the patients. Although the absolute values are 9. Bakhtiari M, Kumaraswamy L, Bailey D, de Boer S, Malhotra H, Podgorsak M: small (below 2%), this could have some clinical impact Using an EPID for patient specific VMAT quality assurance. Med Phys 2011, 38:1366–1373. (e.g. with AAA more plans might be considered not ac- 10. Chandraraj V, Stathakis S, Manickam R, Esquivel C, Supe S, Papanikolau N: ceptable then Acuros-XB due to dosimetric constraints vi- Comparison of four commercial devices for RapidArc and sliding olations). Finally, the application of more complex tools window IMRT QA. J Appl Clin Med Phys 2011, 12:3367. 11. Gloi A, Buchana R, Zuge C, Goettler A: RapidArc quality assurance through like the 3D gamma, allowed to determine that Acuros-XB MapCHECK. J Appl Clin Med Phys 2011, 12:3251. is more robust and accurate than AAA with also tight 12. Syamkumar SA, Padmanabhan S, Sukumar P, Nagarajan V: Characterization thresholds (2%/2 mm). The clinical relevance of this relies of responses of 2d array seven29 detector and its combined use with Kathirvel et al. Radiation Oncology 2013, 8:140 Page 9 of 9 http://www.ro-journal.com/content/8/1/140 Octavius phantom for the patient-specific quality assurance in RapidArc treatment delivery. Med Dosim 2011, 37:53–60. 13. Fakir H, Gaede S, Mulligan M, Chen J: Development of a novel ArcCheck insert for routine quality assurance of VMAT delivery including dose calculation with inhomogeneities. Med Phys 2012, 39:4203–4208. 14. Bush K, Townson R, Zavgorodni S: Monte Carlo simulation of RapidArc radiotherapy delivery. Phys Med Biol 2008, 53:N359–N371. 15. Gagne I, Ansbacher W, Zavgorodni S, Popescu C, Beckham W: A Monte Carlo evaluation of RapidArc dose calculations for oropharynx radiotherapy. Phys Med Biol 2008, 53:7167–7185. 16. van Elmpt W, Petit S, De Ruysscher D, Lambin P, Dekker A: 3D dose delivery verification using repeated cone beam imaging and EPID dosimetry for stereotactic body radiotherapy of non small cell lung cancer. Radiother Oncol 2010, 94:188–194. 17. Korevaar E, Wauben D, van der Hulst P, Lagendijk J, van’tVeld A: Clinical introduction of a linac head mounted 2D detector array based quality assurance system in head and neck IMRT. Radiother Oncol 2011, 100:446–453. 18. Godart J, Korevaar E, Visser R, Wauben D, van’t Veld A: Reconstruction of high resolution 3D dose from matrix measurements: error detection capability of the COMPASS correction kernel method. Phys Med Biol 2011, 56:5029–5043. 19. Nakaguchi Y, Araki F, Maruyama M, Saiga S: Dose verification of IMRT by use of a COMPASS transmission detector. Radiol Phys Technol 2012, 5:63–70. 20. Boggula R, Jahnke L, Wertz H, Lohr F, Wenz F: Patient-specific 3D pretreatment and potential 3D online dose verification of Monte Carlo- calculated IMRT prostate treatment plans. Int J Radiat Oncol Biol Phys 2011, 81:1168–1175. 21. Boggula R, Lorenz F, Müller L, Birkner M, Wertz H, Stieler F, Steil V, Lohr F, Wenz F: Experimental validation of a commercial 3D dose verification system for intensity-modulated arc therapies. Phys Med Biol 2010, 55:5619–5633. 22. Vanetti E, Nicolini G, Nord J, Peltola J, Clivio A, Fogliata A, Cozzi L: On the role of the optimization algorithm of RapidArc(®) volumetric modulated arc therapy on plan quality and efficiency. Med Phys 2011, 38:5844. 23. Ulmer W, Pyyry J, Kaissl W: A 3D photon superposition convolution algorithm and its foundation on results of Monte Carlo calculations. Phys Med Biol 2005, 50:1767–1790. 24. Vassiliev O, Wareing T, McGhee J, Failla G, Salehpour M, Mourtada F: Validation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beams. Phys Med Biol 2010, 55:581–598. 25. ICRU report 83: Prescribing, recording and reporting Intensity Modulated Photon Beam Therapy (IMRT) (ICRU report 83). Washington, DC: International Commission on Radiation Units and Measurements; 2010. 26. Low DA, Harms WB, Mutic S, Purdy JA: A technique for quantitative evaluation of dose distributions. Med Phys 2008, 25:656–661. 27. Fogliata A, Nicolini G, Vanetti E, Clivio A, Winkler P, Cozzi L: The impact of photon dose calculation algorithms on expected dose distributions in lungs under different respiratory phases. Phys Med Biol 2008, 53:2375–2390. 28. Fogliata A, Nicolini G, Clivio A, Vanetti E, Cozzi L: On the dosimetric impact of inhomogeneity management in the Acuros XB algorithm for breast treatment. Radiat Oncol 2011, 6:103. 29. Fogliata A, Nicolini G, Clivio A, Vanetti E, Cozzi L: Critical appraisal of Acuros XB and Anisotropic Analytical Algorithm dose calculation in advanced non-small cell lung cancer treatments. Int J Radiat Oncol Biol Phys 2012, 83:1587–1595. 30. Kan M, Leung L, Yu P: Dosimetric impact of using the Acuros XB algorithm for intensity modulated radiation therapy and RapidArc planning in nasopharyngeal carcinomas. Int J Radiat Oncol Biol Phys 2012, Submit your next manuscript to BioMed Central 85:e73–e80. and take full advantage of: doi:10.1186/1748-717X-8-140 Cite this article as: Kathirvel et al.: Critical appraisal of the accuracy of • Convenient online submission Acuros-XB and Anisotropic Analytical Algorithm compared to • Thorough peer review measurement and calculations with the compass system in the delivery • No space constraints or color ﬁgure charges of RapidArc clinical plans. Radiation Oncology 2013 8:140. • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit
Radiation Oncology – Springer Journals
Published: Dec 1, 2013
Keywords: cancer research; oncology; radiotherapy; imaging / radiology
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