Purpose:To evaluate the dosimetric and temporal effects of high-dose-rate respiratory-gated radiation therapy in patients with lung cancer.Methods:Treatment plans from 5 patients with lung cancer (3 nongated and 2 gated at 80EX-80IN) were retrospectively evaluated. Prescription dose for these patients varied from 8 to 18 Gy/fraction with 3 to 5 treatment fractions. Using the same treatment planning criteria, 4 new treatment plans, corresponding to 4 gating windows (20EX-20IN, 40EX-40IN, 60EX-60IN, and 80EX-80IN), were generated for each patient. Mean tumor dose, mean lung dose, and lung V20 were used to assess the dosimetric effects. A MATLAB algorithm was developed to compute treatment time.Results:Mean lung dose and lung V20 were on average reduced between −16.1% to −6.0% and −20.0% to −7.2%, respectively, for gated plans when compared to the corresponding nongated plans, and between −5.8% to −4.2% and −7.0% to −5.4%, respectively, for plans with smaller gating windows when compared to the corresponding plans gated at 80EX-80IN. Treatment delivery times of gated plans using high-dose rate were reduced on average between −19.7% (−0.10 min/100 MU) and −27.2% (−0.13 min/100 MU) for original nongated plans and −15.6% (−0.15 min/100 MU) and −20.3% (−0.19 min/100 MU) for original 80EX-80IN-gated plans.Conclusion:Respiratory-gated radiation therapy in patients with lung cancer can reduce lung dose while maintaining tumor dose. Because treatment delivery during gated therapy is discontinuous, total treatment time may be prolonged. However, this increase in treatment time can be offset by increasing the dose delivery rate. Estimation of treatment time may be helpful in selecting patients for respiratory gating and choosing appropriate gating windows.
The purpose of this study was to evaluate the dosimetric uncertainty in 4D dose calculation using three temporal probability distributions: uniform distribution, sinusoidal distribution, and patient‐specific distribution derived from the patient respiratory trace. Temporal probability, defined as the fraction of time a patient spends in each respiratory amplitude, was evaluated in nine lung cancer patients. Four‐dimensional computed tomography (4D CT), along with deformable image registration, was used to compute 4D dose incorporating the patient's respiratory motion. First, the dose of each of 10 phase CTs was computed using the same planning parameters as those used in 3D treatment planning based on the breath‐hold CT. Next, deformable image registration was used to deform the dose of each phase CT to the breath‐hold CT using the deformation map between the phase CT and the breath‐hold CT. Finally, the 4D dose was computed by summing the deformed phase doses using their corresponding temporal probabilities. In this study, 4D dose calculated from the patient‐specific temporal probability distribution was used as the ground truth. The dosimetric evaluation matrix included: 1) 3D gamma analysis, 2) mean tumor dose (MTD), 3) mean lung dose (MLD), and 4) lung V20. For seven out of nine patients, both uniform and sinusoidal temporal probability dose distributions were found to have an average gamma passing rate >95% for both the lung and PTV regions. Compared with 4D dose calculated using the patient respiratory trace, doses using uniform and sinusoidal distribution showed a percentage difference on average of −0.1%±0.6% and −0.2%±0.4% in MTD, −0.2%±1.9% and −0.2%±1.3% in MLD, 0.09%±2.8% and −0.07%±1.8% in lung V20, −0.1%±2.0% and 0.08%±1.34% in lung V10, 0.47%±1.8% and 0.19%±1.3% in lung V5, respectively. We concluded that four‐dimensional dose computed using either a uniform or sinusoidal temporal probability distribution can approximate four‐dimensional dose computed using the patient‐specific respiratory trace.PACS number: 87.55.D‐
Purpose: To evaluate the dosimetric difference between 3D and 4Dweighted dose calculation using patient specific respiratory trace and deformable image registration for stereotactic body radiation therapy in lung tumors. Methods: Two dose calculation techniques, 3D and 4D‐weighed dose calculation, were used for dosimetric comparison for 9 lung cancer patients. The magnitude of the tumor motion varied from 3 mm to 23 mm. Breath‐hold exhale CT was used for 3D dose calculation with ITV generated from the motion observed from 4D‐CT. For 4D‐weighted calculation, dose of each binned CT image from the ten breathing amplitudes was first recomputed using the same planning parameters as those used in the 3D calculation. The dose distribution of each binned CT was mapped to the breath‐hold CT using deformable image registration. The 4D‐weighted dose was computed by summing the deformed doses with the temporal probabilities calculated from their corresponding respiratory traces. Dosimetric evaluation criteria includes lung V20, mean lung dose, and mean tumor dose. Results: Comparing with 3D calculation, lung V20, mean lung dose, and mean tumor dose using 4D‐weighted dose calculation were changed by −0.67% ± 2.13%, −4.11% ± 6.94% (−0.36 Gy ± 0.87 Gy), −1.16% ± 1.36%(−0.73 Gy ± 0.85 Gy) accordingly. Conclusion: This work demonstrates that conventional 3D dose calculation method may overestimate the lung V20, MLD, and MTD. The absolute difference between 3D and 4D‐weighted dose calculation in lung tumor may not be clinically significant. This research is supported by Siemens Medical Solutions USA, Inc and Iowa Center for Research By Undergraduates
I can say without doubt that I have thoroughly enjoyed the pursuit of this degree, and this is in large part due to the extraordinary mentors that I have been fortunate to meet throughout my academic journey. I would first like to thank my thesis supervisor, Dr. Junyi Xia, for allowing me the opportunity to study under his guidance. Without his knowledge, patience, and support, this work would not have been possible. I would also like to thank Dr. Joseph Reinhardt for his academic and professional advising. I truly appreciate your willingness to help and the commitment you have always shown towards your students. Additionally, I would like to express my gratitude towards Dr. Ryan Flynn. Thank you for offering your time and input towards serving as a part of this thesis committee. Finally, I would like to thank my family and friends for their continued encouragement and support.
Purpose: To evaluate the dosimetric and temporal effects of high dose rate treatment mode for respiratory‐gated radiation therapy in lung cancer patients. Methods: Treatment plans from five lung cancer patients (3 nongated (Group 1), 2 gated at 80EX‐80IN (Group 2)) were retrospectively evaluated. The maximum tumor motions range from 6–12 mm. Using the same planning criteria, four new treatment plans, corresponding to four gating windows (20EX–20IN, 40EX–40IN, 60EX–60IN, and 80EX–80IN), were generated for each patient. Mean tumor dose (MTD), mean lung dose (MLD), and lung V20 were used to assess the dosimetric effects. A MATLAB algorithm was developed to compute treatment time by considering gantry rotation time, time to position collimator leaves, dose delivery time (scaled relative to the gating window), and communication overhead. Treatment delivery time for each plan was estimated using a 500 MU/min dose rate for the original plans and a 1500 MU/min dose rate for the gated plans. Results: Differences in MTD were less than 1Gy across plans for all five patients. MLD and lung V20 were on average reduced between −16.1% to −6.0% and −20.0% to −7.2%, respectively for non‐gated plans when compared with the corresponding gated plans, and between − 5.8% to −4.2% and −7.0% to −5.4%, respectively for plans originally gated at 80EX–80IN when compared with the corresponding 20EX‐20IN to 60EX– 60IN gated plans. Treatment delivery times of gated plans using high dose rate were reduced on average between −19.7% (−1.9min) to −27.2% (−2.7min) for originally non‐gated plans and −15.6% (−0.9min) to −20.3% (−1.2min) for originally 80EX‐80IN gated plans. Conclusion: Respiratory‐gated radiation therapy in lung cancer patients can reduce lung toxicity, while maintaining tumor dose. Using a gated high‐dose‐rate treatment, delivery time comparable to non‐gated normal‐dose‐rate treatment can be achieved. This research is supported by Siemens Medical Solutions USA, Inc
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