- Email: [email protected]
DOSIMETRIC TREATMENT COURSE SIMULATION BASED ON A PATIENT-INDIVIDUAL STATISTICAL MODEL OF DEFORMABLE ORGAN MOTION
T UESDAY, S EPTEMBER 1, 2009
179 oral THE INFLUENCE OF THE NUMBER OF IMPLANTED FIDUCIAL MARKERS ON THE LOCALIZATION ACCURACY OF THE PROSTATE J. de Boer1 , M. van Herk1 , J. J. Sonke1 1 NKI-AVL, Radiation Oncology, Amsterdam, Netherlands
Purpose: In our clinic, three fiducial markers are used to localize the prostate during radiotherapy. Implanting fiducials is uncomfortable for the patient and the markers introduce imaging artifacts in CT and MRI scans. Therefore, using fewer markers is preferred. The purpose of this study was to evaluate the influence of a reduction of the number of markers on localization accuracy of the prostate. Materials: Seven prostate cancer patients were implanted transperineally with three 0.35 x 30 mm or 0.35 x 20 mm gold markers (Visicoil; RadioMed Corp) under transrectal ultrasound guidance. The markers were aligned to the cranio-caudal axis. Cone-beam CT (CBCT) scans (7-18 per patient) were acquired as part of our correction protocol. CBCT allows thin, long markers to be used for registration, effectively introducing two fiducial points per marker, i.e., the endpoints of every marker. Rigid chamfer matching on any subset of markers was used to register each CBCT to the planning CT. Using the registration results and the positions of all endpoints, we calculated the root mean square of the target localization error (δ TRE) at the left, right, cranial, caudal, anterior and posterior side and the center of mass of the prostate. The δ TRE at a given location is the error induced by the localization error of the fiducials and is a measure of the quality of the registration. For this calculation, rigidity between the fiducial points was assumed. Seven different configurations of markers were evaluated: three markers, all combinations of two markers and each marker separately. Results: To evaluate the configurations, each marker was labeled left or right according to the lobe it was located in. Configurations with both markers in the same lobe were grouped, as were configurations with two markers in different lobes and all configurations with one marker. Table 1 shows the mean δ TRE of each location in the prostate for different numbers of markers. Compared to a registration on three markers, the relative δ TRE increase over all locations is 19% when registering to two markers in different lobes. The relative δ TRE increase of registering to two markers in the same lobe is 75%. This increase is similar to the increase in δ TRE (average 73%) when only one marker is used for the registration. Clearly, the effect of using two markers is lost when the markers are implanted close together.
P OSTER
S 65
cancer patients (5 fractions per patient) who had received breast-conserving surgery. For each BH, all captured surfaces were registered to the planning CT. Intrabeam variability was quantified by the variability (1SD) within a BH averaged (root-mean-square (RMS)) over all treatment beams, fractions and patients. Intrafraction variability was quantified by the RMS (over all fractions and patients) of SD over the average beam displacement. Furthermore, the interfraction variability before correction was quantified by the mean and SD (over fractions and patients) of the average displacement over the first BH. Interfraction variability after correction was quantified by calculating these values over the second and third BH. Since the interfraction variability after correction was retrospectively assessed by surface imaging, but online corrections were performed on the basis of bony anatomy registration (ribs) of CBCT to planning CT, a correction for the discrepancy between the setup error for the first BH assessed by surface imaging and CBCT (ribs) was taken into account. Results: The results are summarized in the table. A large interfraction variability before correction was found, clearly showing the need for a correction protocol as used. Interfraction variability after correction and intrafraction variability were of the same order of magnitude which is logical as both are mainly caused by intrafraction BH reproducibility. The intrabeam variability was found to be very small and likely dominated by small registration errors.
Conclusions: The results show that patients are well able to perform a steady voluntarily BH. Furthermore, patients are able to perform a similar BH within a treatment fraction with a variability that is acceptable for RT of breast cancer. The uncorrected interfraction variability showed that setup verification is of great importance. Effects of interfraction BH variability on dose to the heart are subject of further study. 181 oral DOSIMETRIC TREATMENT COURSE SIMULATION BASED ON A PATIENT-INDIVIDUAL STATISTICAL MODEL OF DEFORMABLE ORGAN MOTION M. Söhn1 , B. Sobotta1 , M. Alber1 1 R ADIOONCOLOGICAL C LINIC, U NIVERSITY OF T ÜBINGEN, Section for Biomedical Physics, Tübingen, Germany Conclusions: Two instead of three Visicoil markers can be used to align the prostate, provided that both markers are implanted at a distance. Using only one marker for registration is possible, but not recommended with the safety margins in use today. 180 oral ASSESSMENT OF SETUP VARIABILITY FOR BREATH-HOLD RADIOTHERAPY FOR BREAST CANCER PATIENTS BY SURFACE IMAGING T. Alderliesten1 , J. J. Sonke1 , R. Heddes1 , A. Betgen1 , P. Remeijer1 , C. van Vliet-Vroegindewij1 1 T HE N ETHERLANDS C ANCER I NSTITUTE - A NTONI VAN L EEUWENHOEK H OSPITAL, Department of Radiation Oncology, Amsterdam, Netherlands
Purpose: Left-sided breast cancer patients treated with conventional tangential fields frequently have a significant part of heart inside the irradiation fields. These patients are at increased risk for long term heart disease. To decrease the irradiated heart volume we therefore developed a cone-beam CT (CBCT) guided voluntary deep-inspiration breath-hold (DIBH) treatment technique for these patients. The aim of this study was to quantify the intrabeam, intra- and interfraction setup variability during DIBH RT by surface imaging. Materials: In each treatment fraction, three voluntary breath-holds (BHs) were performed. During the first BH, a CBCT was acquired for online setup correction. During the second and third BH the lateral and medial fields were delivered. A 3D surface imaging system (AlignRT, Vision RT Ltd., London, UK) was used to capture surfaces (5-10 fps) during DIBH RT of 5 breast
Purpose: The complex nature of geometric uncertainties caused by deformable organ motion leads to nontrivial deviations of the actually applied tumor and OAR doses as compared to the planned dose distribution. Patientindividual assessment of such dosimetric uncertainties and potential plan adaptation at an early stage of the treatment course is vital to guarantee safe treatment in high-precision radiotherapy. We present a method to predict the dosimetric consequences of deformable organ motion for the future treatment course based on a few organ geometry samples (e.g. from onboard imaging). Materials: Based on N organ geometries and the respective deformation fields as determined from deformable registration, Principal Component Analysis (PCA) is used to create a statistical organ deformation model (Shn et al. 2005, PMB 50(24)). PCA determines the most important geometric variability in terms of Eigenmodes. These represent patient-characteristic 3Dvectorfields of correlated organ deformations around the mean geometry. Weighted sums of a few dominating Eigenmodes can be used to simulate synthetic geometries, which are statistically meaningful inter- and extrapolations of the input geometries. We present the use of PCA for Monte Carlo simulations of treatment courses to compute the probability distributions of organ equivalent uniform doses (EUDs) and other dosimetric endpoints. For this a set of random synthetic geometries is generated for each simulated treatment course, and the dose of a given treatment plan is accumulated in the moving tissue elements (dose warping). The method is applied to the example of deformable motion of prostate/bladder/rectum in prostate IMRT and investigation of its dosimetric consequences. Results: A small number of Eigenmodes (typically 3-5) suffices to capture deformable motion of prostate/bladder/rectum. Fig. 1 shows an example for dosimetric treatment course evaluation of a prostate IMRT plan, where
S 66
P OSTER
1000 treatment courses (points) with 37 fractions each were simulated using a PCA-model with 5 input geometries. Such simulations provide prediction of single-organ EUD-distributions (curves) as well as information about EUD-correlations for multiple organs in terms of joint probability distributions (scatterplot).
T UESDAY, S EPTEMBER 1, 2009
position with 0 for presence and 1 for absence of the analyzed parameter. For these data the ANN model also based on MLP for pattern classification consisted of 160 artificial neurons in the input layer, 44 neurons in 2 hidden layers and 37 neurons in the output layer. Verification of the second model using the designated subgroup of patients proved its usefulness and allowed for certain standardization of entry (prior to) treatment plan calculation parameters. It allowed the number of beams and their beam arrangements in association with tumour localisation to be predicted. Conclusions: The ANN methods can substantially reduce time and numbers of iterations needed to obtain the desired treatment plan in stereotactic radiosurgery. 183 oral DOSE ESCALATION AND OPTIMIZATION APPROACHES FOR RAPIDARCTM. W. Crijns1 , T. Depuydt1 , T. Budiharto1 , G. Defraene1 , K. Haustermans1 , J. Verstraete1 , F. Van den Heuvel1 U NIVERSITY H OSPITAL G ASTHUISBERG, Leuven, Belgium
1
Conclusions: PCA facilitates the creation of low-order parametric statistical organ motion/deformation models, which allows efficient investigation of dose uncertainties induced by geometric uncertainties. The presented method is able to provide a prediction of dosimetric treatment course outcome based on a few geometry samples, as important for offline adaptive radiotherapy schemes or evaluation of online adaptive radiotherapy.
Posters IMRT and Stereotatic RT 182 oral APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR OPTIMISATION OF DOSE DISTRIBUTIONS IN STEREOTACTIC RADIOTHERAPY OF INTRACRANIAL CASES A. Skrobala1 1 G REAT P OLAND C ANCER C ENTRE, Medica Physics, Poznan, Poland
Purpose: In stereotactic radiosurgery and radiotherapy (SRS/SRT) for intracranial cases the large number of combinations of beams makes it difficult to develop a preliminary set-up used for further dose distribution optimisation. Different localisation of volumes and different doses in CTV, as well as variation of patients’ anatomy require that many diverse parameters have to be evaluated. A model based on the artificial neural network (ANN) should lead to more efficient and consistent treatment planning.Aim. This aim of this study was to develop a model of an artificial neuron network for a decision-making tool in treatment planning for stereotactic radiosurgery. Materials: A group of 330 patients with single intracranial lesions originally treated using the BrainLAB system was divided to form a subgroup used to develop ANN and a subgroup used later to verify the model. Treatment plans for all patients provided information on the dose (D), the number of beams (NB), volume of CTV (V(CTV)), OARs volumes (V(OAR)) and their localisation in relation to CTV (distance between the centre of OARs and beam isocentre). Six OARs were contoured, and their volumes and distances were analyzed for each patient. Eight subgroups were derived according to CTV localisation in one of eight parts of the brain (Regions). Phase 1 of the study included the choice of relevant entry parameters for ANN and phase 2 construction of an ANN model, whose exit parameters were number of beams (NB) and beam arrangement (position of gantry and table). In phase 3 the model was verified. Results: Two ANN models based on Generalized Feedforward MLP were constructed (analogue and binary). In the first, data used were in analogue form and consisted of 16 artificial neurons in the input layer, 22 neurons in 2 hidden layers and 1 neuron in the output layer. This model was abandoned in the subsequent study due to unsatisfactory results. In a second model all data were converted to binary form in the following way: entry data were transferred to numerical form (ten discrete digits 1 to 10) normalized to the maximal value. Output data (gantry and table orientations respectively) were transferred to numerical form of 36 digits digits (one dig for 100 ) plus the 37th
Purpose: This paper reports on a dose escalation treatment planning study, using radiobiological parameters to compare the outcome of IMRT and RapidArc (RA) plans. RA Patient Specific Optimization Objectives are introduced (PSOO). The aim is to use PSOO without user interaction during optimization. Materials: Twelve patients with adenocarcinoma of the prostate were included in this planning study. Target volumes and OAR were delineated on MRI. Five simultaneous integrated boost plans were created, one static gantry IMRT plan and four RA plans, applying different optimization approaches. The PSOO are created for all 12 patients, from a combination of literature plan objectives and the outcome of the IMRT plan of each patient. The four RA planning approaches were:A. Collimator jaws positioned with a 7mm distance to the PTV. The collimator rotation is set to 45◦ and dose rate maximum was set to 300MU/min, based on our IMRT experience.B. Like (A) with a 5◦ collimator rotation. Using this collimator rotation the MLC moves more perpendicular to the rectum, to obtain a front of leafs for better rectal protection.C. Like (A) but the prostate PTV is subdivided in three shell-like subvolumes. The first prostate subvolume is the outer first 7mm shell of the prostate. The second prostate shell is the next 7mm and the remainder forms the third shell. The seminal vesicles are divided in an outer 7mm shell and the inner part. This ’shell model’ is introduced to increase dose homogeneity, which is decreased with RA compared to IMRT.D. Like (A) but the maximum dose rate was increased up to 600MU/min. For all patients the dose of approach (A) was escalated by upscaling the delivered dose until the rectal NTCP equals that of the IMRT plan. Evaluation is based on dose constraints, NTCP, TCP, and homogeneity. Results: The majority of dose constraints are reached for all approaches. RA rectal NTCP’s are lower than those of IMRT (p=0.004). This allows a mean dose escalation of 2.44Gy ([0.98Gy,3.91Gy]). Approach B leads to a lowered maximum rectal dose. Approach C has a lowest standard deviation on the target dose, while approach D has the lowest rectal NTCP values.TCPs after dose escalation are illustrated in Figure 1.
Figure 1: TCP’s for IMRT, method A, and method A after doseescalation based on rectal NTCP-values. Dose after escalation isindicated for every patient. Conclusions: The presented PSOO methods result in lowered rectal NTCP values compared to IMRT, despite of a higher maximal rectal dose. The optimization approaches resulted in a reduced homogeneity. The presented RA methods can be used as first attempt for a RA plan. When necessary, the maximal rectal dose and the homogeneity can be improved by a second optimization with adapted PSOO’s. This way one or two optimizations lead in most cases to an acceptable treatment plan. At time of presentation we expect to increase the statistics to at least 25 patients.
179 oral THE INFLUENCE OF THE NUMBER OF IMPLANTED FIDUCIAL MARKERS ON THE LOCALIZATION ACCURACY OF THE PROSTATE J. de Boer1 , M. van Herk1 , J. J. Sonke1 1 NKI-AVL, Radiation Oncology, Amsterdam, Netherlands
Purpose: In our clinic, three fiducial markers are used to localize the prostate during radiotherapy. Implanting fiducials is uncomfortable for the patient and the markers introduce imaging artifacts in CT and MRI scans. Therefore, using fewer markers is preferred. The purpose of this study was to evaluate the influence of a reduction of the number of markers on localization accuracy of the prostate. Materials: Seven prostate cancer patients were implanted transperineally with three 0.35 x 30 mm or 0.35 x 20 mm gold markers (Visicoil; RadioMed Corp) under transrectal ultrasound guidance. The markers were aligned to the cranio-caudal axis. Cone-beam CT (CBCT) scans (7-18 per patient) were acquired as part of our correction protocol. CBCT allows thin, long markers to be used for registration, effectively introducing two fiducial points per marker, i.e., the endpoints of every marker. Rigid chamfer matching on any subset of markers was used to register each CBCT to the planning CT. Using the registration results and the positions of all endpoints, we calculated the root mean square of the target localization error (δ TRE) at the left, right, cranial, caudal, anterior and posterior side and the center of mass of the prostate. The δ TRE at a given location is the error induced by the localization error of the fiducials and is a measure of the quality of the registration. For this calculation, rigidity between the fiducial points was assumed. Seven different configurations of markers were evaluated: three markers, all combinations of two markers and each marker separately. Results: To evaluate the configurations, each marker was labeled left or right according to the lobe it was located in. Configurations with both markers in the same lobe were grouped, as were configurations with two markers in different lobes and all configurations with one marker. Table 1 shows the mean δ TRE of each location in the prostate for different numbers of markers. Compared to a registration on three markers, the relative δ TRE increase over all locations is 19% when registering to two markers in different lobes. The relative δ TRE increase of registering to two markers in the same lobe is 75%. This increase is similar to the increase in δ TRE (average 73%) when only one marker is used for the registration. Clearly, the effect of using two markers is lost when the markers are implanted close together.
P OSTER
S 65
cancer patients (5 fractions per patient) who had received breast-conserving surgery. For each BH, all captured surfaces were registered to the planning CT. Intrabeam variability was quantified by the variability (1SD) within a BH averaged (root-mean-square (RMS)) over all treatment beams, fractions and patients. Intrafraction variability was quantified by the RMS (over all fractions and patients) of SD over the average beam displacement. Furthermore, the interfraction variability before correction was quantified by the mean and SD (over fractions and patients) of the average displacement over the first BH. Interfraction variability after correction was quantified by calculating these values over the second and third BH. Since the interfraction variability after correction was retrospectively assessed by surface imaging, but online corrections were performed on the basis of bony anatomy registration (ribs) of CBCT to planning CT, a correction for the discrepancy between the setup error for the first BH assessed by surface imaging and CBCT (ribs) was taken into account. Results: The results are summarized in the table. A large interfraction variability before correction was found, clearly showing the need for a correction protocol as used. Interfraction variability after correction and intrafraction variability were of the same order of magnitude which is logical as both are mainly caused by intrafraction BH reproducibility. The intrabeam variability was found to be very small and likely dominated by small registration errors.
Conclusions: The results show that patients are well able to perform a steady voluntarily BH. Furthermore, patients are able to perform a similar BH within a treatment fraction with a variability that is acceptable for RT of breast cancer. The uncorrected interfraction variability showed that setup verification is of great importance. Effects of interfraction BH variability on dose to the heart are subject of further study. 181 oral DOSIMETRIC TREATMENT COURSE SIMULATION BASED ON A PATIENT-INDIVIDUAL STATISTICAL MODEL OF DEFORMABLE ORGAN MOTION M. Söhn1 , B. Sobotta1 , M. Alber1 1 R ADIOONCOLOGICAL C LINIC, U NIVERSITY OF T ÜBINGEN, Section for Biomedical Physics, Tübingen, Germany Conclusions: Two instead of three Visicoil markers can be used to align the prostate, provided that both markers are implanted at a distance. Using only one marker for registration is possible, but not recommended with the safety margins in use today. 180 oral ASSESSMENT OF SETUP VARIABILITY FOR BREATH-HOLD RADIOTHERAPY FOR BREAST CANCER PATIENTS BY SURFACE IMAGING T. Alderliesten1 , J. J. Sonke1 , R. Heddes1 , A. Betgen1 , P. Remeijer1 , C. van Vliet-Vroegindewij1 1 T HE N ETHERLANDS C ANCER I NSTITUTE - A NTONI VAN L EEUWENHOEK H OSPITAL, Department of Radiation Oncology, Amsterdam, Netherlands
Purpose: Left-sided breast cancer patients treated with conventional tangential fields frequently have a significant part of heart inside the irradiation fields. These patients are at increased risk for long term heart disease. To decrease the irradiated heart volume we therefore developed a cone-beam CT (CBCT) guided voluntary deep-inspiration breath-hold (DIBH) treatment technique for these patients. The aim of this study was to quantify the intrabeam, intra- and interfraction setup variability during DIBH RT by surface imaging. Materials: In each treatment fraction, three voluntary breath-holds (BHs) were performed. During the first BH, a CBCT was acquired for online setup correction. During the second and third BH the lateral and medial fields were delivered. A 3D surface imaging system (AlignRT, Vision RT Ltd., London, UK) was used to capture surfaces (5-10 fps) during DIBH RT of 5 breast
Purpose: The complex nature of geometric uncertainties caused by deformable organ motion leads to nontrivial deviations of the actually applied tumor and OAR doses as compared to the planned dose distribution. Patientindividual assessment of such dosimetric uncertainties and potential plan adaptation at an early stage of the treatment course is vital to guarantee safe treatment in high-precision radiotherapy. We present a method to predict the dosimetric consequences of deformable organ motion for the future treatment course based on a few organ geometry samples (e.g. from onboard imaging). Materials: Based on N organ geometries and the respective deformation fields as determined from deformable registration, Principal Component Analysis (PCA) is used to create a statistical organ deformation model (Shn et al. 2005, PMB 50(24)). PCA determines the most important geometric variability in terms of Eigenmodes. These represent patient-characteristic 3Dvectorfields of correlated organ deformations around the mean geometry. Weighted sums of a few dominating Eigenmodes can be used to simulate synthetic geometries, which are statistically meaningful inter- and extrapolations of the input geometries. We present the use of PCA for Monte Carlo simulations of treatment courses to compute the probability distributions of organ equivalent uniform doses (EUDs) and other dosimetric endpoints. For this a set of random synthetic geometries is generated for each simulated treatment course, and the dose of a given treatment plan is accumulated in the moving tissue elements (dose warping). The method is applied to the example of deformable motion of prostate/bladder/rectum in prostate IMRT and investigation of its dosimetric consequences. Results: A small number of Eigenmodes (typically 3-5) suffices to capture deformable motion of prostate/bladder/rectum. Fig. 1 shows an example for dosimetric treatment course evaluation of a prostate IMRT plan, where
S 66
P OSTER
1000 treatment courses (points) with 37 fractions each were simulated using a PCA-model with 5 input geometries. Such simulations provide prediction of single-organ EUD-distributions (curves) as well as information about EUD-correlations for multiple organs in terms of joint probability distributions (scatterplot).
T UESDAY, S EPTEMBER 1, 2009
position with 0 for presence and 1 for absence of the analyzed parameter. For these data the ANN model also based on MLP for pattern classification consisted of 160 artificial neurons in the input layer, 44 neurons in 2 hidden layers and 37 neurons in the output layer. Verification of the second model using the designated subgroup of patients proved its usefulness and allowed for certain standardization of entry (prior to) treatment plan calculation parameters. It allowed the number of beams and their beam arrangements in association with tumour localisation to be predicted. Conclusions: The ANN methods can substantially reduce time and numbers of iterations needed to obtain the desired treatment plan in stereotactic radiosurgery. 183 oral DOSE ESCALATION AND OPTIMIZATION APPROACHES FOR RAPIDARCTM. W. Crijns1 , T. Depuydt1 , T. Budiharto1 , G. Defraene1 , K. Haustermans1 , J. Verstraete1 , F. Van den Heuvel1 U NIVERSITY H OSPITAL G ASTHUISBERG, Leuven, Belgium
1
Conclusions: PCA facilitates the creation of low-order parametric statistical organ motion/deformation models, which allows efficient investigation of dose uncertainties induced by geometric uncertainties. The presented method is able to provide a prediction of dosimetric treatment course outcome based on a few geometry samples, as important for offline adaptive radiotherapy schemes or evaluation of online adaptive radiotherapy.
Posters IMRT and Stereotatic RT 182 oral APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR OPTIMISATION OF DOSE DISTRIBUTIONS IN STEREOTACTIC RADIOTHERAPY OF INTRACRANIAL CASES A. Skrobala1 1 G REAT P OLAND C ANCER C ENTRE, Medica Physics, Poznan, Poland
Purpose: In stereotactic radiosurgery and radiotherapy (SRS/SRT) for intracranial cases the large number of combinations of beams makes it difficult to develop a preliminary set-up used for further dose distribution optimisation. Different localisation of volumes and different doses in CTV, as well as variation of patients’ anatomy require that many diverse parameters have to be evaluated. A model based on the artificial neural network (ANN) should lead to more efficient and consistent treatment planning.Aim. This aim of this study was to develop a model of an artificial neuron network for a decision-making tool in treatment planning for stereotactic radiosurgery. Materials: A group of 330 patients with single intracranial lesions originally treated using the BrainLAB system was divided to form a subgroup used to develop ANN and a subgroup used later to verify the model. Treatment plans for all patients provided information on the dose (D), the number of beams (NB), volume of CTV (V(CTV)), OARs volumes (V(OAR)) and their localisation in relation to CTV (distance between the centre of OARs and beam isocentre). Six OARs were contoured, and their volumes and distances were analyzed for each patient. Eight subgroups were derived according to CTV localisation in one of eight parts of the brain (Regions). Phase 1 of the study included the choice of relevant entry parameters for ANN and phase 2 construction of an ANN model, whose exit parameters were number of beams (NB) and beam arrangement (position of gantry and table). In phase 3 the model was verified. Results: Two ANN models based on Generalized Feedforward MLP were constructed (analogue and binary). In the first, data used were in analogue form and consisted of 16 artificial neurons in the input layer, 22 neurons in 2 hidden layers and 1 neuron in the output layer. This model was abandoned in the subsequent study due to unsatisfactory results. In a second model all data were converted to binary form in the following way: entry data were transferred to numerical form (ten discrete digits 1 to 10) normalized to the maximal value. Output data (gantry and table orientations respectively) were transferred to numerical form of 36 digits digits (one dig for 100 ) plus the 37th
Purpose: This paper reports on a dose escalation treatment planning study, using radiobiological parameters to compare the outcome of IMRT and RapidArc (RA) plans. RA Patient Specific Optimization Objectives are introduced (PSOO). The aim is to use PSOO without user interaction during optimization. Materials: Twelve patients with adenocarcinoma of the prostate were included in this planning study. Target volumes and OAR were delineated on MRI. Five simultaneous integrated boost plans were created, one static gantry IMRT plan and four RA plans, applying different optimization approaches. The PSOO are created for all 12 patients, from a combination of literature plan objectives and the outcome of the IMRT plan of each patient. The four RA planning approaches were:A. Collimator jaws positioned with a 7mm distance to the PTV. The collimator rotation is set to 45◦ and dose rate maximum was set to 300MU/min, based on our IMRT experience.B. Like (A) with a 5◦ collimator rotation. Using this collimator rotation the MLC moves more perpendicular to the rectum, to obtain a front of leafs for better rectal protection.C. Like (A) but the prostate PTV is subdivided in three shell-like subvolumes. The first prostate subvolume is the outer first 7mm shell of the prostate. The second prostate shell is the next 7mm and the remainder forms the third shell. The seminal vesicles are divided in an outer 7mm shell and the inner part. This ’shell model’ is introduced to increase dose homogeneity, which is decreased with RA compared to IMRT.D. Like (A) but the maximum dose rate was increased up to 600MU/min. For all patients the dose of approach (A) was escalated by upscaling the delivered dose until the rectal NTCP equals that of the IMRT plan. Evaluation is based on dose constraints, NTCP, TCP, and homogeneity. Results: The majority of dose constraints are reached for all approaches. RA rectal NTCP’s are lower than those of IMRT (p=0.004). This allows a mean dose escalation of 2.44Gy ([0.98Gy,3.91Gy]). Approach B leads to a lowered maximum rectal dose. Approach C has a lowest standard deviation on the target dose, while approach D has the lowest rectal NTCP values.TCPs after dose escalation are illustrated in Figure 1.
Figure 1: TCP’s for IMRT, method A, and method A after doseescalation based on rectal NTCP-values. Dose after escalation isindicated for every patient. Conclusions: The presented PSOO methods result in lowered rectal NTCP values compared to IMRT, despite of a higher maximal rectal dose. The optimization approaches resulted in a reduced homogeneity. The presented RA methods can be used as first attempt for a RA plan. When necessary, the maximal rectal dose and the homogeneity can be improved by a second optimization with adapted PSOO’s. This way one or two optimizations lead in most cases to an acceptable treatment plan. At time of presentation we expect to increase the statistics to at least 25 patients.