- Email: [email protected]
308 4D imaging and treatment planning
$140 Wednesday, October 27, 2004
Time: the fourth dimension in radiotherapy 3O8
4D imaging and treatment planning E. Rietzel1"2, G. T. Y. Chen 1, N. C. Choi 1, C. G. Wlllett 3 ~Massachusetts General Hospital, Radiation Oncology, Boston, USA 2Gesellschaft fQr Schwerionenforschung, Abteilung Biophysik, Darmstadt, Germany 3Duke University, Radiation Oncology, Durham, USA Respiratory motion can introduce significant errors in radiotherapy imaging, treatment planning, and treatment delivery. 4D Computed Tomography provides time-resolved, spatio-temporal coherent volumetric data sets of patient anatomy [1]. Target volumes can be designed incorporating patient specific tumor motion. Furthermore, the impact of internal motion on dose distributions and organs at risk can be assessed. Patients are CT scanned in axial cine mode. At each couch position data are acquired for the duration of the patient's respiratory cycle. From such data, multiple images are reconstructed per couch position, each representing a different respiratory state. Images are sorted retrospectively into temporal coherent volumes by selecting images at the same respiratory phase for each slice. The 4DCT data acquisition protocol was improved and validated in several phantom studies. Typical motion artifacts are significantly reduced. For lung cancer patients, composite target volumes are used for treatment planning at MGH. Internal motion can be inspected visually by movie loops. To ensure adequate dose coverage throughout the respiratory cycle, the union of targets contoured on volumes at different respiratory phases is generated for treatment planning. For proton therapy of liver tumors, composite target volumes are treated. Sufficient proton penetration to the distal edge of the target is guaranteed by incorporating respiration induced density variations into treatment planning. Full dose coverage under respiration can be validated by recalculation of dose distributions for 4DCT volumes at all resorted respiratory phases. To calculate total effective dose distributions under respiratory motion, CT volumes have to be registered non-rigidly to maintain the dose-to-voxel relation. This has been accomplished using a free form deformation algorithm based on B-splines [2]. Dose distributions can be mapped to CTs at different respiratory phases by applying transformations obtained for non-rigid CT-CT registration. 4DCT data represents a snapshot of respiratory motion only and does not include possible daily variations. Therefore expansions from CTV to PTV have not significantly been reduced. To validate internal motion patient specifically, fluoroscopic studies and daily gated x-ray acquisition for patient set-up have been performed for some patients. [1] Pan et al, Med Phys 2004;31:333-40. [2] Rueckert et al, IEEE Trans Med Imaging 1999;18:712-21. 309
Four-dimensional radiotherapy planning P. Keall Medical College of Virginia Hospitals, VA Commonwealth Univ, Richmond, USA Four-dimensional (4D) radiotherapy isthe explicit inclusion of the temporal changes in anatomy during the imaging, planning and delivery of radiotherapy. High precision radiation therapy
Symposia
of moving targets is becoming increasingly important in this era of image-guided therapy. We have always known that humans are four-dimensional, though our current treatment techniques are predominantly three-dimensional. Anatomy and physiology of cancerous and healthy tissues changes with time, both within and between treatments. For radiotherapy patients, the additional effects of radiation, potentially with concomitant chemotherapy and or/hormone therapy can also cause anatomical changes during treatment. Though we have known about these anatomy changes with time, due to recent technological developments in both 4D imaging (as described in the previous presentation) and 4D radiation delivery, we are in an era where anatomical changes can be explicitly accounted for. Temporal anatomic changes can occur for many reasons, though the focus of this presentation is respiration motion for lung tumors. The rationale for 4D radiotherapy is increased targeting accuracy, allowing target dose escalation and/or normal tissue dose reduction, potential leading to higher tumor control with lower treatment-related toxicity. This presentation will describe 4D radiotherapy treatment-planning methodology based on a 4D CT image set, which typically contains 8-10 complete 3D CT image sets. There are several ways to use 4D CT for planning. In the absence of any treatment methods that explicitly account for respiratory motion, the GTV for each respiratory phase can be combined to form a respiratoryintegrated tumor volume (RTV), from which margins can be added to obtain the 3D PTV used for treatment. If respiratorygated radiotherapy is available, one of the constituent 4D CT image sets could be used for planning. If motion track(ng is available (the ability to move the beam with respect to the patient in near real-time) 4D treatment planning, both 4D CRT and 4D IMRT, can occur for each constituent 4D CT image sets, provided motion constraints of the delivery system are not exceeded. 4D radiotherapy can potentially reduce the magnitude of the internal margin applied to the CTV to create the PTV. However, additional geometric uncertainties introduced in the 4D radiotherapy process, including (1) limitations of the deformable image registration algorithm, (2) the correlation between the respiration signal and tumor position and (3) the response time of the motion tracking system, should also be taken into account during margin creation. As the 4D CT image set contains an order of magnitude more data than currently used for radiotherapy, automation of 4D planning processes isclearly necessary. 4D radiotherapy planning requires additional tools not available on existing treatment planning systems. These tools include (1) deformable image registration, (2) automated planning, (3) dose calculation on multiple datasets and (4) constrained optimization (for 4D IMRT). 310
Accounting for lung tumor motion C. Stevens 1, G. Starkschall 2, Z. Liao ~, T. Guerrero ~, J. Chang ~, R. Komakf, J. Cox ~, M. Jeeter~, K. Forster3 ~U.T. M.D. Anderson Cancer Center, Department of Radiation Oncology, Houston, TX, U.S.A. 2U. T. M.D. Anderson Cancer Center, Department of Radiation Physics, Houston, TX, U.S.A. 3U. T. Southwestern, Department of Radiation Oncology, Dallas, TX, U.S.A. We measured lung tumor motion in twenty-five patients. All patients had pathologically proven lung cancer, were be able to be trained to use the spirometer, and had a planned treatment course of at least 6 weeks. Patients with more than segmental atelectasis were excluded. CT images over the entire lung volume were acquired at 100% tidal volume (normal inspiration) and at 0% tidal volume (end expiration) using computerassisted occlusion spirometry. For each CT data set, the GTV
Time: the fourth dimension in radiotherapy 3O8
4D imaging and treatment planning E. Rietzel1"2, G. T. Y. Chen 1, N. C. Choi 1, C. G. Wlllett 3 ~Massachusetts General Hospital, Radiation Oncology, Boston, USA 2Gesellschaft fQr Schwerionenforschung, Abteilung Biophysik, Darmstadt, Germany 3Duke University, Radiation Oncology, Durham, USA Respiratory motion can introduce significant errors in radiotherapy imaging, treatment planning, and treatment delivery. 4D Computed Tomography provides time-resolved, spatio-temporal coherent volumetric data sets of patient anatomy [1]. Target volumes can be designed incorporating patient specific tumor motion. Furthermore, the impact of internal motion on dose distributions and organs at risk can be assessed. Patients are CT scanned in axial cine mode. At each couch position data are acquired for the duration of the patient's respiratory cycle. From such data, multiple images are reconstructed per couch position, each representing a different respiratory state. Images are sorted retrospectively into temporal coherent volumes by selecting images at the same respiratory phase for each slice. The 4DCT data acquisition protocol was improved and validated in several phantom studies. Typical motion artifacts are significantly reduced. For lung cancer patients, composite target volumes are used for treatment planning at MGH. Internal motion can be inspected visually by movie loops. To ensure adequate dose coverage throughout the respiratory cycle, the union of targets contoured on volumes at different respiratory phases is generated for treatment planning. For proton therapy of liver tumors, composite target volumes are treated. Sufficient proton penetration to the distal edge of the target is guaranteed by incorporating respiration induced density variations into treatment planning. Full dose coverage under respiration can be validated by recalculation of dose distributions for 4DCT volumes at all resorted respiratory phases. To calculate total effective dose distributions under respiratory motion, CT volumes have to be registered non-rigidly to maintain the dose-to-voxel relation. This has been accomplished using a free form deformation algorithm based on B-splines [2]. Dose distributions can be mapped to CTs at different respiratory phases by applying transformations obtained for non-rigid CT-CT registration. 4DCT data represents a snapshot of respiratory motion only and does not include possible daily variations. Therefore expansions from CTV to PTV have not significantly been reduced. To validate internal motion patient specifically, fluoroscopic studies and daily gated x-ray acquisition for patient set-up have been performed for some patients. [1] Pan et al, Med Phys 2004;31:333-40. [2] Rueckert et al, IEEE Trans Med Imaging 1999;18:712-21. 309
Four-dimensional radiotherapy planning P. Keall Medical College of Virginia Hospitals, VA Commonwealth Univ, Richmond, USA Four-dimensional (4D) radiotherapy isthe explicit inclusion of the temporal changes in anatomy during the imaging, planning and delivery of radiotherapy. High precision radiation therapy
Symposia
of moving targets is becoming increasingly important in this era of image-guided therapy. We have always known that humans are four-dimensional, though our current treatment techniques are predominantly three-dimensional. Anatomy and physiology of cancerous and healthy tissues changes with time, both within and between treatments. For radiotherapy patients, the additional effects of radiation, potentially with concomitant chemotherapy and or/hormone therapy can also cause anatomical changes during treatment. Though we have known about these anatomy changes with time, due to recent technological developments in both 4D imaging (as described in the previous presentation) and 4D radiation delivery, we are in an era where anatomical changes can be explicitly accounted for. Temporal anatomic changes can occur for many reasons, though the focus of this presentation is respiration motion for lung tumors. The rationale for 4D radiotherapy is increased targeting accuracy, allowing target dose escalation and/or normal tissue dose reduction, potential leading to higher tumor control with lower treatment-related toxicity. This presentation will describe 4D radiotherapy treatment-planning methodology based on a 4D CT image set, which typically contains 8-10 complete 3D CT image sets. There are several ways to use 4D CT for planning. In the absence of any treatment methods that explicitly account for respiratory motion, the GTV for each respiratory phase can be combined to form a respiratoryintegrated tumor volume (RTV), from which margins can be added to obtain the 3D PTV used for treatment. If respiratorygated radiotherapy is available, one of the constituent 4D CT image sets could be used for planning. If motion track(ng is available (the ability to move the beam with respect to the patient in near real-time) 4D treatment planning, both 4D CRT and 4D IMRT, can occur for each constituent 4D CT image sets, provided motion constraints of the delivery system are not exceeded. 4D radiotherapy can potentially reduce the magnitude of the internal margin applied to the CTV to create the PTV. However, additional geometric uncertainties introduced in the 4D radiotherapy process, including (1) limitations of the deformable image registration algorithm, (2) the correlation between the respiration signal and tumor position and (3) the response time of the motion tracking system, should also be taken into account during margin creation. As the 4D CT image set contains an order of magnitude more data than currently used for radiotherapy, automation of 4D planning processes isclearly necessary. 4D radiotherapy planning requires additional tools not available on existing treatment planning systems. These tools include (1) deformable image registration, (2) automated planning, (3) dose calculation on multiple datasets and (4) constrained optimization (for 4D IMRT). 310
Accounting for lung tumor motion C. Stevens 1, G. Starkschall 2, Z. Liao ~, T. Guerrero ~, J. Chang ~, R. Komakf, J. Cox ~, M. Jeeter~, K. Forster3 ~U.T. M.D. Anderson Cancer Center, Department of Radiation Oncology, Houston, TX, U.S.A. 2U. T. M.D. Anderson Cancer Center, Department of Radiation Physics, Houston, TX, U.S.A. 3U. T. Southwestern, Department of Radiation Oncology, Dallas, TX, U.S.A. We measured lung tumor motion in twenty-five patients. All patients had pathologically proven lung cancer, were be able to be trained to use the spirometer, and had a planned treatment course of at least 6 weeks. Patients with more than segmental atelectasis were excluded. CT images over the entire lung volume were acquired at 100% tidal volume (normal inspiration) and at 0% tidal volume (end expiration) using computerassisted occlusion spirometry. For each CT data set, the GTV