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Inclusion of systematic setup uncertainties in treatment plans
Proceedings of the 36th Annual ASTRO Meeting
241
152 IMPROVING TREATMENT PLANNING ACCURACY THROUGH MULTIPLE MODALITY IMAGING Julian Rosenman PhD, MD*?. Mitchel Soltys MS*, Tii Cullip MS*. Jun Chen MS* *Department of Radiation Oncology. tDepartment of Computer Science, University of North Carolina at Chapel Hill, North Carolina.
Purpoee/Objective: Accuracy in defining the planning target volume @TV) requires a knowledge of the gross tumor volume (GTV), extension of microscopic disease (clinical tumor volume or CTV), and patient motion, both external and internal. Although the CTV can be estimated from knowledge of the clinical disease, and patient motion from experience, the process must start from an accurate definition of the GTV. Sometimes the ulannina CT does not show the GTV. because it is of similar radiom~hic densitv cornoared to backaround. or because it has been chemically & surgically removed. We have developed a method to u& multimodality im&ing for gen&ation of planning volumes, and have identified a number of clinical situations where there technology is useful. Materials & Methods: If the GTV cannot be visualized by CT it might be seen on MR. This situation is very common in brain tumors, but also occurs in other parts of the body. A number of methods to register CT and MR of the brain have been developed, and some work outside the brain as well. In addition to registration, a way must be found to integrate the MR into the treatment planning system, and project the tumor location onto the planning CT. We have accomplished this process by extending our treatment planning system to accommodate multinle data sets. and bv tilina extracted 3D data sets (such as tumor volume) to make it available for reslicina onto the plaMingCT. In lymphoma patients with bulky disease, it is common practice to treat with chemotherapy first, and then consolidate with radiation therapy. However, after chemotherapy, the tumor may no longer be present. If a diagnostic CT was done before the chemotherapy it is possible to perform a CT/CT registration and transfer the data to the post-chemotherapy CT. If the prechemotherapy CT digital data is not available, (for example if it were done in an “outside” hospital), it is still possible to reconstmct this data from film.’ Postoperative radiation therapy is commonly done for many tumor sites. The GTV will not appear on the planning CT but can be transferred from the pm-surgical to the post-surgical CT. Since surgery alters the normal anatomy, however, image registration is more difficult_ Finally, newer imaging modalities, such as immunoscintigraphies and PET scanning wilJ be supplying the radiation oncologist with tumor localixation data. The methods developed for CT/CT and CT/MR will work here as well. Resultar Multimodality medical images can now be routinely registered with the planning CT and incorporated into our 3D treatment Planning systemCondusioaa~ Muldmodality imaging holds out the promise of improving treatment planning accuracy and thus taking maximum advantage of 3D treatment planning systems. ‘Boxwala A, Rosenman JG: Retrospective reconstruction of three dimensional radiotherapy treatment plans from two dimensional planning data. (in press], Int J Rudiut Oncol Biol Physics.
153 THE USE OF SPIRAL CT AND SPIROMETRY TO REDUCE UNCERTAINTIES IN TREATMENT PLANNING ASSOCIATED WITH BREATHING JM Balter, RK Ten Haken, K Lam, TS Lawrence, JM Robertson, AT Turrisi University of Michigan Department of Radiation Oncology, Ann Arbor, MI Purpose: The objective of this study is to investigate the effect of breathing on the integrity of treatment planning data. Treatment planning CT scans are often obtained while the patient breathes freely, under the assumption that the resulting data sets will represent an “average” patient location. This procedure may lead to a misrepresentation of the shape, position, and volume of the tumor and surrounding normal tissue structures, resulting in significant differences in the effective depth of the tumor and also in calculated NTCP for structures such as the lungs and liver. The purpose of this study is to determine the magnitude of these errors, and whether the use of CT data taken at static period of ventilation (determined by spirometry) will lead to a more accurate understanding of dosimetry in the abdomen and thorax. Mate&Is and Methods: Treatment planning CT scans were performed on three patients using a spiral scanner. In addition to the standard “free breathing” planning scan, two additional scans were acquired with the patient holding their breath at a state of normal inhale and normal exhale. Treatment planning was performed using our three-dimensional planning system. After the treatment plan was completed, the inhale and exhale CT data sets were used to redefine volumes. Three-dimensional dose matrices were calculated for each of these data sets using the planned beams. The volumes of the lungs, liver, and kidneys were calculated using all three data sets (star&n& inhale, exhale) for all patients. The locations of the liver and kidneys were determined for patients with liver cancer. For lung patients, the effective path length for each beam to the isocenter along the central axis was determined. Finally, NTCP values were calculated for the lungs of the patients treated for tumors in the thorax.
242
Radiation
Oncology,
Biology, Physics
Volume 30, Supplement
1
The volume of tbe liver and kidneys was conserved to within 3% on abdominal breath hold CT SCBI~S, while it varied by over 15% Resuk between the Bee breathing CT and tbe static spiral data. While tbe position of tbe center of the liver and kidneys extracted from the planning data falls between the positions from tbe inbale and exhale studies, tbe shape of the liver and kidneys are not conserved on the phuming CT. Both the liver and kidneys exhibited movement on the order of 1 cm. Lung volume changes of up to 50% have been observed between inspiration and expiration. These volume changes, combined with radiation path length changes of over 2 cm, resulted in a change in predicted NTCP of over 30% for some patients. Conclnalon: Conveutioual treatment planning CT data sets may not represent the true state of organs tbat are affected by ventilatory motion. Static (breath hold) volumes present a more consistent organ shape itt the abdomen, and more accurately represent the status of the patient at a given stage of the breatbiug cycle. Knowledge of tbe status of tbeae organs, when correlated witb lung volume and/or time course of breatbing measurements, will allow for more accurate dosimetry in the abdomen and thorax. Future work will focus on modelliug breathing and estimating the benefit of gating treatment to account for ventilatory motion. Work supported in part by NJH grant no. POl-CA59827
154 INCLUSION OF SYSTEMATIC SETUP UNCERTAINTIES IN TREATMENT PLANS G.J. Kutcher, G.S. Mageras, C. Chui, Z. Fuks, A. Georgiades, S.M. Leibel, T. LoSasso, and R. Mohan MemoriaJ Sloan-Kettering Cancer Center, New York, NY 10021 Purpose: The purpose of this presentation is to present a methodology for including systematic setup uncertainties in treatment plans. The seminal role of such calculations in the evaluation of treatment techniques, and their potential use for designing strategies for correcting setup errors will be presented with clinical examples. Methods and Materials: The methodology is based upon the observation that setup errors can be measured for a patient population (by site and institution) and grouped into 2 fundamental distributions: random and systematic. The latter is sampled to obtain the 3 translation and rotation coordinates of the oatient which is modeled bv an oooosite motion of the radiation field. For each of a quasi-random sample of organ points, cumulative dose frequency distributions’& generated. This vields a dose volume histoeram (DVH) for soecified percentiles (confidence limits) in do&. The method a&permits recalculation of the radiological pathlengths for sampled positions of the radiation field in instances where large inhomogeneities are present. This approach has been applied to 3D treatment plans of the prostate and nasopharynx. Results: Shown in the figure is one example of 3 DVHs for the rectal wall for a 6-field treatment of the prostate: a nominal DVH (i.e. one without setup error) and 15% and 85% confidence limit DVHs for systematic translation setup errors with standard deviations of 0.5 cm. The DVHs were obtained by sampling the in translation setup error distributions 50 times each using 500 organ dose points. Doubling tbe number of sample or organ points or including radiological pathlength recalculation leads to no change in the DVHs for this site(figure not shown). Examples of prostate and rectal plans with translation and rotation errors will be present& these show striking differences from DVHs without setup errors or with only random errors included. Furthermore, the use of these calculations to design protocols for correcting setup errors, e.g. with on-line imaging, will be addressed. We will also discuss how to extend this technique to include correlated motion. Conclusions: We believe that systematic errors are present in routine clinical practice, and - while our aim should be to reduce them - they should also be included in treatment plans. The described method for including systematic errors is fast and efficient and can readily be extended to include organ motion. ‘Ibese calculations have utility in assessing the dosimetric consequences of setup errors so that a more rational approach to their reduction should be possible.
241
152 IMPROVING TREATMENT PLANNING ACCURACY THROUGH MULTIPLE MODALITY IMAGING Julian Rosenman PhD, MD*?. Mitchel Soltys MS*, Tii Cullip MS*. Jun Chen MS* *Department of Radiation Oncology. tDepartment of Computer Science, University of North Carolina at Chapel Hill, North Carolina.
Purpoee/Objective: Accuracy in defining the planning target volume @TV) requires a knowledge of the gross tumor volume (GTV), extension of microscopic disease (clinical tumor volume or CTV), and patient motion, both external and internal. Although the CTV can be estimated from knowledge of the clinical disease, and patient motion from experience, the process must start from an accurate definition of the GTV. Sometimes the ulannina CT does not show the GTV. because it is of similar radiom~hic densitv cornoared to backaround. or because it has been chemically & surgically removed. We have developed a method to u& multimodality im&ing for gen&ation of planning volumes, and have identified a number of clinical situations where there technology is useful. Materials & Methods: If the GTV cannot be visualized by CT it might be seen on MR. This situation is very common in brain tumors, but also occurs in other parts of the body. A number of methods to register CT and MR of the brain have been developed, and some work outside the brain as well. In addition to registration, a way must be found to integrate the MR into the treatment planning system, and project the tumor location onto the planning CT. We have accomplished this process by extending our treatment planning system to accommodate multinle data sets. and bv tilina extracted 3D data sets (such as tumor volume) to make it available for reslicina onto the plaMingCT. In lymphoma patients with bulky disease, it is common practice to treat with chemotherapy first, and then consolidate with radiation therapy. However, after chemotherapy, the tumor may no longer be present. If a diagnostic CT was done before the chemotherapy it is possible to perform a CT/CT registration and transfer the data to the post-chemotherapy CT. If the prechemotherapy CT digital data is not available, (for example if it were done in an “outside” hospital), it is still possible to reconstmct this data from film.’ Postoperative radiation therapy is commonly done for many tumor sites. The GTV will not appear on the planning CT but can be transferred from the pm-surgical to the post-surgical CT. Since surgery alters the normal anatomy, however, image registration is more difficult_ Finally, newer imaging modalities, such as immunoscintigraphies and PET scanning wilJ be supplying the radiation oncologist with tumor localixation data. The methods developed for CT/CT and CT/MR will work here as well. Resultar Multimodality medical images can now be routinely registered with the planning CT and incorporated into our 3D treatment Planning systemCondusioaa~ Muldmodality imaging holds out the promise of improving treatment planning accuracy and thus taking maximum advantage of 3D treatment planning systems. ‘Boxwala A, Rosenman JG: Retrospective reconstruction of three dimensional radiotherapy treatment plans from two dimensional planning data. (in press], Int J Rudiut Oncol Biol Physics.
153 THE USE OF SPIRAL CT AND SPIROMETRY TO REDUCE UNCERTAINTIES IN TREATMENT PLANNING ASSOCIATED WITH BREATHING JM Balter, RK Ten Haken, K Lam, TS Lawrence, JM Robertson, AT Turrisi University of Michigan Department of Radiation Oncology, Ann Arbor, MI Purpose: The objective of this study is to investigate the effect of breathing on the integrity of treatment planning data. Treatment planning CT scans are often obtained while the patient breathes freely, under the assumption that the resulting data sets will represent an “average” patient location. This procedure may lead to a misrepresentation of the shape, position, and volume of the tumor and surrounding normal tissue structures, resulting in significant differences in the effective depth of the tumor and also in calculated NTCP for structures such as the lungs and liver. The purpose of this study is to determine the magnitude of these errors, and whether the use of CT data taken at static period of ventilation (determined by spirometry) will lead to a more accurate understanding of dosimetry in the abdomen and thorax. Mate&Is and Methods: Treatment planning CT scans were performed on three patients using a spiral scanner. In addition to the standard “free breathing” planning scan, two additional scans were acquired with the patient holding their breath at a state of normal inhale and normal exhale. Treatment planning was performed using our three-dimensional planning system. After the treatment plan was completed, the inhale and exhale CT data sets were used to redefine volumes. Three-dimensional dose matrices were calculated for each of these data sets using the planned beams. The volumes of the lungs, liver, and kidneys were calculated using all three data sets (star&n& inhale, exhale) for all patients. The locations of the liver and kidneys were determined for patients with liver cancer. For lung patients, the effective path length for each beam to the isocenter along the central axis was determined. Finally, NTCP values were calculated for the lungs of the patients treated for tumors in the thorax.
242
Radiation
Oncology,
Biology, Physics
Volume 30, Supplement
1
The volume of tbe liver and kidneys was conserved to within 3% on abdominal breath hold CT SCBI~S, while it varied by over 15% Resuk between the Bee breathing CT and tbe static spiral data. While tbe position of tbe center of the liver and kidneys extracted from the planning data falls between the positions from tbe inbale and exhale studies, tbe shape of the liver and kidneys are not conserved on the phuming CT. Both the liver and kidneys exhibited movement on the order of 1 cm. Lung volume changes of up to 50% have been observed between inspiration and expiration. These volume changes, combined with radiation path length changes of over 2 cm, resulted in a change in predicted NTCP of over 30% for some patients. Conclnalon: Conveutioual treatment planning CT data sets may not represent the true state of organs tbat are affected by ventilatory motion. Static (breath hold) volumes present a more consistent organ shape itt the abdomen, and more accurately represent the status of the patient at a given stage of the breatbiug cycle. Knowledge of tbe status of tbeae organs, when correlated witb lung volume and/or time course of breatbing measurements, will allow for more accurate dosimetry in the abdomen and thorax. Future work will focus on modelliug breathing and estimating the benefit of gating treatment to account for ventilatory motion. Work supported in part by NJH grant no. POl-CA59827
154 INCLUSION OF SYSTEMATIC SETUP UNCERTAINTIES IN TREATMENT PLANS G.J. Kutcher, G.S. Mageras, C. Chui, Z. Fuks, A. Georgiades, S.M. Leibel, T. LoSasso, and R. Mohan MemoriaJ Sloan-Kettering Cancer Center, New York, NY 10021 Purpose: The purpose of this presentation is to present a methodology for including systematic setup uncertainties in treatment plans. The seminal role of such calculations in the evaluation of treatment techniques, and their potential use for designing strategies for correcting setup errors will be presented with clinical examples. Methods and Materials: The methodology is based upon the observation that setup errors can be measured for a patient population (by site and institution) and grouped into 2 fundamental distributions: random and systematic. The latter is sampled to obtain the 3 translation and rotation coordinates of the oatient which is modeled bv an oooosite motion of the radiation field. For each of a quasi-random sample of organ points, cumulative dose frequency distributions’& generated. This vields a dose volume histoeram (DVH) for soecified percentiles (confidence limits) in do&. The method a&permits recalculation of the radiological pathlengths for sampled positions of the radiation field in instances where large inhomogeneities are present. This approach has been applied to 3D treatment plans of the prostate and nasopharynx. Results: Shown in the figure is one example of 3 DVHs for the rectal wall for a 6-field treatment of the prostate: a nominal DVH (i.e. one without setup error) and 15% and 85% confidence limit DVHs for systematic translation setup errors with standard deviations of 0.5 cm. The DVHs were obtained by sampling the in translation setup error distributions 50 times each using 500 organ dose points. Doubling tbe number of sample or organ points or including radiological pathlength recalculation leads to no change in the DVHs for this site(figure not shown). Examples of prostate and rectal plans with translation and rotation errors will be present& these show striking differences from DVHs without setup errors or with only random errors included. Furthermore, the use of these calculations to design protocols for correcting setup errors, e.g. with on-line imaging, will be addressed. We will also discuss how to extend this technique to include correlated motion. Conclusions: We believe that systematic errors are present in routine clinical practice, and - while our aim should be to reduce them - they should also be included in treatment plans. The described method for including systematic errors is fast and efficient and can readily be extended to include organ motion. ‘Ibese calculations have utility in assessing the dosimetric consequences of setup errors so that a more rational approach to their reduction should be possible.