- Email: [email protected]
Validation of the path integration of 4D dose distributions with 4D phantom measurements
S608
I. J. Radiation Oncology
2449
● Biology ● Physics
Volume 60, Number 1, Supplement, 2004
Respiratory Trace Characterization: A Precursor to Feedback-Guided Breath Hold Treatment Delivery
N. Tolani, C. Nelson, P. Balter, J. Antolak, G. Starkschall, K. Prado Radiation Physics, UT M.D. Anderson Cancer Center, Houston, TX Purpose/Objective: Precise delivery of respiratory correlated treatment depends on the patient’s ability to control their breathing. For patients who may be able to effect breath-hold for extended periods of time, Feedback Guided Breath Hold Treatment (FGBHTx) may be the optimal form of treatment delivery. For patients only able to effect shorter breath-holds, explicit delineation of their Internal Target Volume (ITV) may be indicated. The purpose of this study is to quantify the respiratory criteria necessary to evaluate patients’ breathing patterns for successful patient treatment triage. Materials/Methods: The Varian Real - Time Position Management (Varian RPMTM) Respiratory Gating System enables amplitude-based respiratory gating by generating signals based on the motion of a fiducial marker relative to pre-determined limits. These signals could be coupled with a time-delay generator to ’sense’ a breath hold condition. An alternative signal, generated when both fiducial-marker position and appropriate-delay conditions are met, could be used to allow breath-hold treatment (see figure 1). To demonstrate the feasibility of this concept and preliminarily parameterize respiratory traces, the respiration of five healthy volunteers has been characterized using the Varian RPMTM gating system. A total of 6 volunteers were asked to effect free-breathing, and inspiration and expiration breath holds while receiving visual feedback from the RPMTM device. The respiratory traces obtained during these training sessions were analyzed for: length of breath hold, time to stable breath hold, position of breath hold relative to free breathing, and stability of breath hold relative to total free-breathing amplitude. Results: The lengths of breath holds of these healthy volunteers varied from about 15 to 43 seconds with times to stable breath hold varying between 1 and 3 seconds. Positions of breath holds relative to free breathing varied from about 0.7 to 1.2 with relative positions greater than 1.0 signifying excursions beyond normal breathing. Stability of breath hold relative to free-breathing amplitude varied from less than 0.1 to up to 0.3. Conclusions: Although these data have only been preliminarily analyzed, a few general conclusions can be drawn. Use of feedback-guided breath hold techniques for treatment delivery appears to be feasible, however, proper instruction on the use of the RPM monitoring device will be essential. Our volunteers received only minimal training. Their breath holds varied relatively significantly both in position as well as in stability. The variability of position relative to free breathing may be of little consequence if reproducibility as a function of time can be achieved. This has not yet been evaluated for our volunteers. The lack of stability relative to the free-breathing amplitude may be of greater significance. An unstable breath hold will lead to either residual motion (if the allowable displacement range is increased) or to a long duty cycle (if the displacement range is decreased to minimize residual motion).
2450
Validation of the Path Integration of 4D Dose Distributions with 4D Phantom Measurements
G. G. Zhang,1 T. M. Guerrero,2 K. Forster,1 G. Fischer,1 M. Fitzpatrick,1 G. Starkschall,1 G. Ibbott1 1
Radiation Physics, UT MD Anderson Cancer Center, Houston, TX, 2Radiation Oncology, UT MD Anderson Cancer Center, Houston, TX Purpose/Objective: 4D treatment planning generates a series of 3D dose distributions to represent the motion properties of the patient and/or radiation delivery system. The purpose of this study is to validate with 4D phantom measurements the use of the 3D optical flow method algorithm for the numerical path integration of 4D dose distribution data into a single 3D dose distribution. Materials/Methods: The Radiological Physics Center (RPC) thoracic phantom was placed on a programmable motion table to simulate respiratory motion. 4D CT imaging was performed on a multi-slice CT scanner (Philips Medical Systems, Anhover, MA). The CT data was binned into eight phases. The CT images were sent to a Pinnacle workstation (version 6.2b, Phillips Medical Systems, Anhover, MA) where a treatment plan was designed on the end expiration image set. The treatment plan was
Proceedings of the 46th Annual ASTRO Meeting
transposed onto the other respiratory phases and a 4D dose data set generated. The plan was delivered using a Varian 2100 linear accelerator (Varian Medical System, Palo Alto, CA). The dose delivered to the RPC thoracic phantom was recorded using radiographic film and thermoluminescent dosimeters for calibration. The 3D optical flow method (3D OFM) algorithm is a deformable image registration algorithm we have implemented. 3D OFM was used to calculate the displacement fields between the respiratory phases. The displacement fields were used to map the dose distributions from the multiple respiratory phases onto the end expiration phase. The resulting dose distributions were summed with equal weighting, performing numerical path integration. The calculated and measured dose distributions were compared with the static plan. Results: The attached figure illustrates the dose distributions. A coronal section through the static treatment plan is shown in figure A.u½pick;3197f1;0;11 The 3D OFM algorithm was applied and numerical path integration performed on the 4D dose distribution data resulting in a single 3D dose distribution. The corresponding coronal section is shown in figure B. A coronal section through the measured dose distribution is shown in figure C. The delivered dose distribution had a peak width at 90% maximum of 38.5 mm. The corresponding value for the path integrated 4D plan and the end expiration static plan were 42.6 mm and 47.0 mm. The 50% isodose line was displaced 0.5 mm when compared with the path integrated 4D plan and 8.6 mm when compared with the end expiration static plan. Conclusions: The 3D OFM algorithm provides the displacement field necessary for numerical path integration to map a 4D dose distribution data set into a single 3D dose distribution accurately. The resulting dose distribution was found to more closely represent the delivered dose versus the static plan for a moving phantom.
2451
Clinical Implementation: 4D Computed Tomography for Thoracic Tumor Treatment Planning
E. Rietzel, A. K. Liu, G. T. Chen, K. P. Doppke, N. C. Choi Radiation Oncology, Massachusetts General Hospital, Boston, MA Purpose/Objective: Respiratory motion can introduce artifacts in CT imaging. These may lead to significant errors in target delineation. 4D Computed Tomography allows temporal imaging of moving targets. Motion artifacts are significantly reduced or absent. We have established a 4DCT data acquisition protocol. Image formation and data acquisition were validated with phantom measurements. We describe our current clinical implementation of 4DCT for thoracic tumor imaging and target delineation. Materials/Methods: To date, 15 patients with thoracic tumors were 4DCT scanned. 4DCT data are acquired on a 4-slice GE Lightspeed CT scanner in axial cine mode. During several CT tube rotations, data are acquired at each couch position for the duration of the patient’s respiratory cycle. The patients’ abdominal surface motion is recorded with the Varian RPM-system, and temporally correlated to CT data acquisition. Several images per couch position are reconstructed evenly distributed over the respiratory cycle. Using GE software, images are retrospectively sorted into typically 10 spatio-temporal coherent volumes according to their correlation to surface motion. Typically, volumes at extrema of target motion are selected for contouring. It was necessary to use fusion software to contour targets at different respiratory levels referencing to the same data set for further treatment planning. Results: Two patients are shown in Figure 1. Patient A has a small lung tumor in the right upper lobe. Displayed are sagittal cuts for standard CT scanning (a), end inspiration (b), and expiration (c) of the 4DCT data. Note blurring of the tumor and artifacts at the diaphragm in the standard helical scan. Patient B has a large tumor in the left lower lung lobe. Coronal cuts for a helical scan (d), 4DCT end inspiration (e), expiration (f) are displayed. Respiratory tumor motion is clearly visible between inspiration and expiration. The helical scan shows typical motion artifacts in the tumor region. After fusion and contouring, inclusion of targets at all respiratory levels was visually validated. If needed further volumes at different respiratory phases were contoured. GTVs contoured on the helical scan are 5.5 cc (A) and 149.3 cc (B) as compared to 2.8 cc and 158 cc on average on the 4DCT volumes. In the helical scan, for patient B motion artifacts decreased the tumor volume whereas for patient A it was increased. For treatment planning targets, were expanded to include 4DCT imaging uncertainties (⬃1 slice thickness). Further GTV expansions to PTV in our 4DCT protocol are 15 mm (8 mm to CTV, 7 mm for set-up). PTV volumes were 82.2 cc (A) and 721.2 cc (B). Previously GTVs were expanded from GTV to PTV by 20 mm, resulting in 137.4 cc (A) and 797.7 cc (B). GTV centroid motion throughout the respiratory cycle was 1.4/4.2/2.9 mm (A) and 0.6/0.5/6.6 mm (B) in AP/LR/SI direction. Conclusions: 4DCT allows imaging of respiratory motion while decreasing typical motion artifacts. This facilitates generation of patient specific target volumes accounting for respiratory motion. For patient A, a significant reduction of the PTV was obtained with our 4DCT protocol. Furthermore, the magnitude of target motion is assessed to decide whether patients will be treated with 3DCRT or IMRT.
S609
I. J. Radiation Oncology
2449
● Biology ● Physics
Volume 60, Number 1, Supplement, 2004
Respiratory Trace Characterization: A Precursor to Feedback-Guided Breath Hold Treatment Delivery
N. Tolani, C. Nelson, P. Balter, J. Antolak, G. Starkschall, K. Prado Radiation Physics, UT M.D. Anderson Cancer Center, Houston, TX Purpose/Objective: Precise delivery of respiratory correlated treatment depends on the patient’s ability to control their breathing. For patients who may be able to effect breath-hold for extended periods of time, Feedback Guided Breath Hold Treatment (FGBHTx) may be the optimal form of treatment delivery. For patients only able to effect shorter breath-holds, explicit delineation of their Internal Target Volume (ITV) may be indicated. The purpose of this study is to quantify the respiratory criteria necessary to evaluate patients’ breathing patterns for successful patient treatment triage. Materials/Methods: The Varian Real - Time Position Management (Varian RPMTM) Respiratory Gating System enables amplitude-based respiratory gating by generating signals based on the motion of a fiducial marker relative to pre-determined limits. These signals could be coupled with a time-delay generator to ’sense’ a breath hold condition. An alternative signal, generated when both fiducial-marker position and appropriate-delay conditions are met, could be used to allow breath-hold treatment (see figure 1). To demonstrate the feasibility of this concept and preliminarily parameterize respiratory traces, the respiration of five healthy volunteers has been characterized using the Varian RPMTM gating system. A total of 6 volunteers were asked to effect free-breathing, and inspiration and expiration breath holds while receiving visual feedback from the RPMTM device. The respiratory traces obtained during these training sessions were analyzed for: length of breath hold, time to stable breath hold, position of breath hold relative to free breathing, and stability of breath hold relative to total free-breathing amplitude. Results: The lengths of breath holds of these healthy volunteers varied from about 15 to 43 seconds with times to stable breath hold varying between 1 and 3 seconds. Positions of breath holds relative to free breathing varied from about 0.7 to 1.2 with relative positions greater than 1.0 signifying excursions beyond normal breathing. Stability of breath hold relative to free-breathing amplitude varied from less than 0.1 to up to 0.3. Conclusions: Although these data have only been preliminarily analyzed, a few general conclusions can be drawn. Use of feedback-guided breath hold techniques for treatment delivery appears to be feasible, however, proper instruction on the use of the RPM monitoring device will be essential. Our volunteers received only minimal training. Their breath holds varied relatively significantly both in position as well as in stability. The variability of position relative to free breathing may be of little consequence if reproducibility as a function of time can be achieved. This has not yet been evaluated for our volunteers. The lack of stability relative to the free-breathing amplitude may be of greater significance. An unstable breath hold will lead to either residual motion (if the allowable displacement range is increased) or to a long duty cycle (if the displacement range is decreased to minimize residual motion).
2450
Validation of the Path Integration of 4D Dose Distributions with 4D Phantom Measurements
G. G. Zhang,1 T. M. Guerrero,2 K. Forster,1 G. Fischer,1 M. Fitzpatrick,1 G. Starkschall,1 G. Ibbott1 1
Radiation Physics, UT MD Anderson Cancer Center, Houston, TX, 2Radiation Oncology, UT MD Anderson Cancer Center, Houston, TX Purpose/Objective: 4D treatment planning generates a series of 3D dose distributions to represent the motion properties of the patient and/or radiation delivery system. The purpose of this study is to validate with 4D phantom measurements the use of the 3D optical flow method algorithm for the numerical path integration of 4D dose distribution data into a single 3D dose distribution. Materials/Methods: The Radiological Physics Center (RPC) thoracic phantom was placed on a programmable motion table to simulate respiratory motion. 4D CT imaging was performed on a multi-slice CT scanner (Philips Medical Systems, Anhover, MA). The CT data was binned into eight phases. The CT images were sent to a Pinnacle workstation (version 6.2b, Phillips Medical Systems, Anhover, MA) where a treatment plan was designed on the end expiration image set. The treatment plan was
Proceedings of the 46th Annual ASTRO Meeting
transposed onto the other respiratory phases and a 4D dose data set generated. The plan was delivered using a Varian 2100 linear accelerator (Varian Medical System, Palo Alto, CA). The dose delivered to the RPC thoracic phantom was recorded using radiographic film and thermoluminescent dosimeters for calibration. The 3D optical flow method (3D OFM) algorithm is a deformable image registration algorithm we have implemented. 3D OFM was used to calculate the displacement fields between the respiratory phases. The displacement fields were used to map the dose distributions from the multiple respiratory phases onto the end expiration phase. The resulting dose distributions were summed with equal weighting, performing numerical path integration. The calculated and measured dose distributions were compared with the static plan. Results: The attached figure illustrates the dose distributions. A coronal section through the static treatment plan is shown in figure A.u½pick;3197f1;0;11 The 3D OFM algorithm was applied and numerical path integration performed on the 4D dose distribution data resulting in a single 3D dose distribution. The corresponding coronal section is shown in figure B. A coronal section through the measured dose distribution is shown in figure C. The delivered dose distribution had a peak width at 90% maximum of 38.5 mm. The corresponding value for the path integrated 4D plan and the end expiration static plan were 42.6 mm and 47.0 mm. The 50% isodose line was displaced 0.5 mm when compared with the path integrated 4D plan and 8.6 mm when compared with the end expiration static plan. Conclusions: The 3D OFM algorithm provides the displacement field necessary for numerical path integration to map a 4D dose distribution data set into a single 3D dose distribution accurately. The resulting dose distribution was found to more closely represent the delivered dose versus the static plan for a moving phantom.
2451
Clinical Implementation: 4D Computed Tomography for Thoracic Tumor Treatment Planning
E. Rietzel, A. K. Liu, G. T. Chen, K. P. Doppke, N. C. Choi Radiation Oncology, Massachusetts General Hospital, Boston, MA Purpose/Objective: Respiratory motion can introduce artifacts in CT imaging. These may lead to significant errors in target delineation. 4D Computed Tomography allows temporal imaging of moving targets. Motion artifacts are significantly reduced or absent. We have established a 4DCT data acquisition protocol. Image formation and data acquisition were validated with phantom measurements. We describe our current clinical implementation of 4DCT for thoracic tumor imaging and target delineation. Materials/Methods: To date, 15 patients with thoracic tumors were 4DCT scanned. 4DCT data are acquired on a 4-slice GE Lightspeed CT scanner in axial cine mode. During several CT tube rotations, data are acquired at each couch position for the duration of the patient’s respiratory cycle. The patients’ abdominal surface motion is recorded with the Varian RPM-system, and temporally correlated to CT data acquisition. Several images per couch position are reconstructed evenly distributed over the respiratory cycle. Using GE software, images are retrospectively sorted into typically 10 spatio-temporal coherent volumes according to their correlation to surface motion. Typically, volumes at extrema of target motion are selected for contouring. It was necessary to use fusion software to contour targets at different respiratory levels referencing to the same data set for further treatment planning. Results: Two patients are shown in Figure 1. Patient A has a small lung tumor in the right upper lobe. Displayed are sagittal cuts for standard CT scanning (a), end inspiration (b), and expiration (c) of the 4DCT data. Note blurring of the tumor and artifacts at the diaphragm in the standard helical scan. Patient B has a large tumor in the left lower lung lobe. Coronal cuts for a helical scan (d), 4DCT end inspiration (e), expiration (f) are displayed. Respiratory tumor motion is clearly visible between inspiration and expiration. The helical scan shows typical motion artifacts in the tumor region. After fusion and contouring, inclusion of targets at all respiratory levels was visually validated. If needed further volumes at different respiratory phases were contoured. GTVs contoured on the helical scan are 5.5 cc (A) and 149.3 cc (B) as compared to 2.8 cc and 158 cc on average on the 4DCT volumes. In the helical scan, for patient B motion artifacts decreased the tumor volume whereas for patient A it was increased. For treatment planning targets, were expanded to include 4DCT imaging uncertainties (⬃1 slice thickness). Further GTV expansions to PTV in our 4DCT protocol are 15 mm (8 mm to CTV, 7 mm for set-up). PTV volumes were 82.2 cc (A) and 721.2 cc (B). Previously GTVs were expanded from GTV to PTV by 20 mm, resulting in 137.4 cc (A) and 797.7 cc (B). GTV centroid motion throughout the respiratory cycle was 1.4/4.2/2.9 mm (A) and 0.6/0.5/6.6 mm (B) in AP/LR/SI direction. Conclusions: 4DCT allows imaging of respiratory motion while decreasing typical motion artifacts. This facilitates generation of patient specific target volumes accounting for respiratory motion. For patient A, a significant reduction of the PTV was obtained with our 4DCT protocol. Furthermore, the magnitude of target motion is assessed to decide whether patients will be treated with 3DCRT or IMRT.
S609