Faculty Bibliography

PURPOSE/OBJECTIVES/OBJECTIVE:Lung tumor motion may be impacted by heartbeat in addition to respiration. This study seeks to quantitatively analyze heart-motion-induced tumor motion and to evaluate its impact on lung cancer radiotherapy. METHODS/MATERIALS/METHODS:Fluoroscopy images were acquired for 30 lung cancer patients. Tumor, diaphragm, and heart were delineated on selected fluoroscopy frames, and their motion was tracked and converted into temporal signals based on deformable registration propagation. The clinical relevance of heart impact was evaluated using the dose volumetric histogram of the redefined target volumes. RESULTS:Correlation was found between tumor and cardiac motion for 23 patients. The heart-induced motion amplitude ranged from 0.2 to 2.6 mm. The ratio between heart-induced tumor motion and the tumor motion was inversely proportional to the amplitude of overall tumor motion. When the heart motion impact was integrated, there was an average 9% increase in internal target volumes for 17 patients. Dose coverage decrease was observed on redefined planning target volume in simulated SBRT plans. CONCLUSIONS:The tumor motion of thoracic cancer patients is influenced by both heart and respiratory motion. The cardiac impact is relatively more significant for tumor with less motion, which may lead to clinically significant uncertainty in radiotherapy for some patients.

The focus of this study is the angular dependence of two types of Metal Oxide Semiconductor Field Effect Transistor (MOSFET) dosimeters (MOSFET20 and OneDose/OneDosePlus) when used for surface dose measurements. External beam radiationat different gantry angles were delivered to a cubic solid water phantom with a MOSFET placed on the top surface at CAX. The long axis of the MOSFET was oriented along the gantry axis of rotation, with the dosimeter (bubble side) facing the radiation source. MOSFET-measured surface doses were compared against calibrated radiochromic film readings. It was found that both types of MOSFET dosimeters exhibited larger than previously reported angular dependence when measuring surface dose in beams at large oblique angles. For the MOSFET20 dosimeter the measured surface dose deviation against film readings was as high as 17% when the incident angle was 72 degrees to the norm of the phantom surface. It is concluded that some MOSFET dosimeters may have a strong angular dependence when placed on the surface of water-equivalent material, even though they may have an isotropic angular response when surrounded by uniform medium. Extra on-surface calibration maybe necessary before using MOSFET dosimeters for skin dose measurement in tangential fields.

A common approach to implementing the Monte Carlo method for the calculation of brachytherapy radiation dose deposition is to use a phase space file containing information on particles emitted from a brachytherapy source. However, the loading of the phase space file during the dose calculation consumes a large amount of computer random access memory, imposing a higher requirement for computer hardware. In this study, we propose a method to parameterize the information (e.g., particle location, direction and energy) stored in the phase space file by using several probability distributions. This method was implemented for dose calculations of a commercial Ir-192 high dose rate source. Dose calculation accuracy of the parameterized source was compared to the results observed using the full phase space file in a simple water phantom and in a clinical breast cancer case. The results showed the parameterized source at a size of 200 kB was as accurate as the phase space file represented source of 1.1 GB. By using the parameterized source representation, a compact Monte Carlo job can be designed, which allows an easy setup for parallel computing in brachytherapy planning.

PURPOSE/OBJECTIVE:Blocks have been used to protect heart from potential radiation damage in left-sided breast treatments. Since cardiac motion pattern may not be fully captured on conventional 3DCT or 4DCT simulation scans, this study was intended to investigate the optimization of the heart block design taking the cardiac motion into consideration. MATERIALS AND METHODS/METHODS:Whole breast treatment plans using two opposed tangential fields were designed based on 4DCT simulation images for 10 left-sided breast cancer patients. Using an OBI system equipped to a Varian Linac, beam-eye viewed fluoroscopy images were acquired for each of the treatment beams after patient treatment setup, and the MLC heart blocks were overlaid onto the fluoroscopy images with an in-house software package. A non-rigid image registration and tracking algorithm was utilized to track the cardiac motion on the fluoroscopy images with minimal manual delineation for initialization, and the tracked cardiac motion information was used to optimize the heart block design to minimize the radiation damage to heart while avoiding the over-shielding that may lead to underdosing certain breast tissues. RESULTS:Twenty-three sets of fluoroscopy images were acquired on 23 different days of treatment for the 10 patients. As expected, heart moved under the influences of both respiratory and cardiac motion. It was observed that for 16 out of the 23 treatments, heart moved beyond the planed heart block into treatment fields and MLC had to be adjusted to fully block heart. The adjustment was made for all but one patient. The number of the adjusted MLC leaves ranged from 1 to 16 (mean = 10), and the MLC leaf position adjustment ranged from 2 to 10 mm (mean = 6 mm). The added heart block areas ranged from 3 to 1230 mm(2) (mean = 331 mm(2)). CONCLUSION/CONCLUSIONS:In left-sided whole breast radiation treatments, simulation CT (and 4DCT) based heart block design may not provide adequate heart protection for all the treatments. A fluoroscopy-based method has been developed to adaptively optimize the heart MLC block to achieve optimal heart protection.

PURPOSE/OBJECTIVE:To investigate the dosimetric difference due to the different point A definitions in cervical cancer low-dose-rate (LDR) intracavitary brachytherapy. MATERIAL AND METHODS/METHODS:Twenty CT-based LDR brachytherapy plans of 11 cervical patients were retrospectively reviewed. Two plans with point As following the modified Manchester system which defines point A being 2 cm superior to the cervical os along the tandem and 2 cm lateral (Aos), and the American Brachytherapy Society (ABS) guideline definition in which the point A is 2 cm superior to the vaginal fornices instead of os (Aovoid) were generated. Using the same source strength, two plans prescribed the same dose to Aos and Aovoid. Dosimetric differences between plans including point A dose rate, treatment volume encompassed by the prescription isodose line (TV), and dose rate of 2 cc of the rectum and bladder to the prescription dose were measured. RESULTS:On average Aovoid was 8.9 mm superior to Aos along the tandem direction with a standard deviation of 5.4 mm. With the same source strength and arrangement, Aos dose rate was 19% higher than Aovoid dose rate. The average TV(Aovoid) was 118.0 cc, which was 30% more than the average TV(Aos) of 93.0 cc. D2cc/D(Aprescribe) increased from 51% to 60% for rectum, and increased from 89% and 106% for bladder, if the prescription point changed from Aos to Aovoid. CONCLUSIONS:Different point A definitions lead to significant dose differences. Careful consideration should be given when changing practice from one point A definition to another, to ensure dosimetric and clinical equivalency from the previous clinical experiences.

PURPOSE/OBJECTIVE:In the presence of random uncertainties, delivered radiation treatment doses in patient likely exhibit a statistical distribution. The expected dose and variance of this distribution are unknown and are most likely not equal to the planned value since the current treatment planning systems cannot exactly model and simulate treatment machine. Relevant clinical questions are 1) how to quantitatively estimate the expected delivered dose and extrapolate the expected dose to the treatment dose over a treatment course and 2) how to evaluate the treatment dose relative to the corresponding planned dose. This study is to present a systematic approach to address these questions and to apply this approach to patient-specific IMRT (PSIMRT) plan verifications. METHODS:The expected delivered dose in patient and variance are quantitatively estimated using Student T distribution and Chi Distribution, respectively, based on pre-treatment QA measurements. Relationships between the expected dose and the delivered dose over a treatment course and between the expected dose and the planned dose are quantified with mathematical formalisms. The requirement and evaluation of the pre-treatment QA measurement results are also quantitatively related to the desired treatment accuracy and to the to-be-delivered treatment course itself. The developed methodology was applied to PSIMRT plan verification procedures for both QA result evaluation and treatment quality estimation. RESULTS:Statistically, the pre-treatment QA measurement process was dictated not only by the corresponding plan but also by the delivered dose deviation, number of measurements, treatment fractionation, potential uncertainties during patient treatment, and desired treatment accuracy tolerance. For the PSIMRT QA procedures, in theory, more than one measurement had to be performed to evaluate whether the to-be-delivered treatment course would meet the desired dose coverage and treatment tolerance. CONCLUSION/CONCLUSIONS:By acknowledging and considering the statistical nature of multi-fractional delivery of radiation treatment, we have established a quantitative methodology to evaluate the PSIMRT QA results. Both the statistical parameters associated with the QA measurement procedure and treatment course need to be taken into account to evaluate the QA outcome and to determine whether the plan is acceptable and whether additional measures should be taken to reduce treatment uncertainties. The result from a single QA measurement without the appropriate statistical analysis can be misleading. When the required number of measurements is comparable to the planned number of fractions and the variance is unacceptably high, action must be taken to either modify the plan or adjust the beam delivery system.

Clinical objective IMRT QA is a new approach to conduct patient specific IMRT QA by evaluating the QA result based on metrics like the structure dose volume histograms (DVH) on the planning CT image. Different from traditional 2D planar dose based IMRT QA in which all the measurements and evaluations were based on a phantom, clinical objective IMRT QA reveals the direct clinical impact of any measured variation based on the predicted delivered dose to the patient target volumes and critical organs. In this study, we proposed a method to implement the clinical objective IMRT QA procedure by using generally available dosimetry equipment in a radiation oncology clinic. The proposed procedure was tested and validated on five IMRT plans by using a solid water phantom, which served as a test patient, along with total 30 ion chamber measurements. The result showed that the proposed QA procedure successfully achieved the goal of clinical objective IMRT QA. Based on the ion chamber measurements, the QA procedure predicted that the average variations between the planned and the delivered doses were within 1.9%. This method may hold potentials to help radiation oncology clinics to move from the traditional IMRT QA to the clinical objective IMRT QA.

PURPOSE/OBJECTIVE:The management of thoracic malignancies with radiation therapy is complicated by continuous target motion. In this study, a real time motion analysis approach is proposed to improve the accuracy of patient setup. METHODS:For 11 lung cancer patients a long training fluoroscopy was acquired before the first treatment, and multiple short testing fluoroscopies were acquired weekly at the pretreatment patient setup of image guided radiotherapy (IGRT). The data analysis consisted of three steps: first a 4D target motion model was constructed from 4DCT and projected to the training fluoroscopy through deformable registration. Then the manifold learning method was used to construct a 2D subspace based on the target motion (kinetic) and location (static) information in the training fluoroscopy. Thereafter the respiratory phase in the testing fluoroscopy was determined by finding its location in the subspace. Finally, the phase determined testing fluoroscopy was registered to the corresponding 4DCT to derive the pretreatment patient position adjustment for the IGRT. The method was tested on clinical image sets and numerical phantoms. RESULTS:The registration successfully reconstructed the 4D motion model with over 98% volume similarity in 4DCT, and over 95% area similarity in the training fluoroscopy. The machine learning method derived the phase values in over 98% and 93% test images of the phantom and patient images, respectively, with less than 3% phase error. The setup approach achieved an average accumulated setup error less than 1.7 mm in the cranial-caudal direction and less than 1 mm in the transverse plane. All results were validated against the ground truth of manual delineations by an experienced radiation oncologist. The expected total time for the pretreatment setup analysis was less than 10 s. CONCLUSIONS:By combining the registration and machine learning, the proposed approach has the potential to improve the accuracy of pretreatment setup for patients with thoracic malignancy.