E Ehler

Patient specific 3D printed phantom for IMRT quality assurance

The purpose of this study was to test the feasibility of a patient specific phantom for patient specific dosimetric verification.Using the head and neck region of an anthropomorphic phantom as a substitute for an actual patient, a soft-tissue equivalent model was constructed with the use of a 3D printer. Calculated and measured dose in the anthropomorphic phantom and the 3D printed phantom was compared for a parallel-opposed head and neck field geometry to establish tissue equivalence. A nine-field IMRT plan was constructed and dose verification measurements were performed for the 3D printed phantom as well as traditional standard phantoms.The maximum difference in calculated dose was 1.8% for the parallel-opposed configuration. Passing rates of various dosimetric parameters were compared for the IMRT plan measurements; the 3D printed phantom results showed greater disagreement at superficial depths than other methods.A custom phantom was created using a 3D printer. It was determined that the use of patient specific phantoms to perform dosimetric verification and estimate the dose in the patient is feasible. In addition, end-to-end testing on a per-patient basis was possible with the 3D printed phantom. Further refinement of the phantom construction process is needed for routine use.

Lung 4D-IMRT treatment planning: An evaluation of three methods applied to four-dimensional data sets

PURPOSE To compare 4D-dose distributions for IMRT planning on three data sets: a single 4D-CT phase, a 4D-CT phase with a density override to the tumor motion envelope (TME) volume, and the average intensity projection (AIP). METHODS Eight planning cases were considered. IMRT inverse planning optimization was performed on each of the three data set types, for each case considered. The plans were then applied to all ten phases of the associated 4D-CT data set. The dose to the GTV in each breathing phase was compared to the TME dose from the optimized dose distribution, as well as the GTV dose determined from a model-based deformable registration algorithm. RESULTS IMRT optimization on a single 3D data set resulted in a greater equivalent uniform dose (EUD) to the GTV when applied to a 4D-CT data set than the EUD for the TME in the optimized plan. The difference was up to 5.5Gy in one case. For all cases and planning techniques considered, a maximum difference of 0.3Gy in the NTDmean to the healthy lung throughout the breathing cycle was found. CONCLUSIONS For tumors located in the periphery of the lung, optimization on the AIP image resulted in a more uniform GTV dose throughout the breathing cycle. Averages in GTV EUD and healthy lung NTDmean taken over all the breathing phases were found to be in agreement with the dose effect parameters obtained from model-based deformable registration algorithms. All planning methods yielded GTV EUD values that were larger than the prescribed dose when the full 4D data set was considered.

A method to automate the segmentation of the GTV and ITV for lung tumors.

Four-dimensional computed tomography (4D-CT) is a useful tool in the treatment of tumors that undergo significant motion. To fully utilize 4D-CT motion information in the treatment of mobile tumors such as lung cancer, autosegmentation methods will need to be developed. Using autosegmentation tools in the Pinnacle(3) v8.1t treatment planning system, 6 anonymized 4D-CT data sets were contoured. Two test indices were developed that can be used to evaluate which autosegmentation tools to apply to a given gross tumor volume (GTV) region of interest (ROI). The 4D-CT data sets had various phase binning error levels ranging from 3% to 29%. The appropriate autosegmentation method (rigid translational image registration and deformable surface mesh) was determined to properly delineate the GTV in all of the 4D-CT phases for the 4D-CT data sets with binning errors of up to 15%. The ITV was defined by 2 methods: a mask of the GTV in all 4D-CT phases and the maximum intensity projection. The differences in centroid position and volume were compared with manual segmentation studies in literature. The indices developed in this study, along with the autosegmentation tools in the treatment planning system, were able to automatically segment the GTV in the four 4D-CTs with phase binning errors of up to 15%.

SU‐E‐J‐08: Assessing and Minimizing the Dose From KV Cone Beam CT to Pediatric Patients Undergoing Radiation Therapy

PURPOSE To assess the dose from kilovoltage cone beam CT to pediatric patients undergoing image-guided radiation therapy and to compare the dose between standard and low dose protocols. METHODS Imaging dose to several pediatric patients undergoing image-guided radiation therapy, and methods to reduce it, have been assessed using a treatment planning system (TPS) and Monte Carlo (MC). The imaging dose from an Elekta XVI kV CBCT system has been added to the treatment plans to calculate total dose to patients. The maximum dose and its location, dose to isocenter and various organs, and its correlation with patient size and body mass index (BMI), have been analyzed. The calculations have been performed using standard imaging protocols and low dose and/or modified ones. The TPS calculations have been supplemented with MC to assess the dose to bone and skin which cannot be accurately calculated using the TPS. RESULTS Employing a lower dose imaging technique for pediatric patients by: 1) Choosing a pre-set imaging protocol using a lower technique that may be designated for a different anatomic region, i.e. using the Head and Neck protocol on a pelvic scan, or 2) Modifying a standard imaging protocol by reducing the mAs or number of frames, could substantially reduce the imaging dose. The image quality of the lower dose techniques has been found to be acceptable for patient position verification. Using a low dose or modified protocol could Result in an 18 fold decrease in the imaging dose. CONCLUSION In order to most accurately track exposure, dose from daily kilovoltage CBCT can be added to pediatric patient treatment plans using previously commissioned kV CBCT beams in a treatment planning system and supplemented with Monte Carlo calculations. A technique for delivering lower dose is suggested and differences between standard and low dose protocols have been quantified.

On Correlated Sources of Uncertainty in Four Dimensional Computed Tomography Data Sets

The purpose of this work is to estimate the degree of uncertainty inherent to a given four dimensional computed tomography (4D-CT) imaging modality and to test for interaction of the investigated factors (i.e., object displacement, velocity, and the period of motion) when determining the object motion coordinates, motion envelope, and the confomality in which it can be defined within a time based data series. A motion phantom consisting of four glass spheres imbedded in low density foam on a one dimensional moving platform was used to investigate the interaction of uncertainty factors in motion trajectory that could be used in comparison of trajectory definition, motion envelope definition and conformality in an optimal 4D-CT imaging environment. The motion platform allowed for a highly defined motion trajectory that could be as the ground truth in the comparison with observed motion in 4D-CT data sets. 4D-CT data sets were acquired for 9 different motion patterns. Multifactor analysis of variance (ANOVA) was performed where the factors considered were the phantom maximum velocity, object volume, and the image intensity used to delineate the high density objects. No statistical significance was found for three factor interaction for definition of the motion trajectory, motion envelope, or Dice Similarity Coefficient (DSC) conformality. Two factor interactions were found to be statistically significant for the DSC for the interactions of 1) object volume and the HU threshold used for delineation and 2) the object velocity and object volume. Moreover, a statistically significant single factor direct proportionality was observed between the maximum velocity and the mean tracking error. In this work multiple factors impacting on the uncertainty in 4D data sets have been considered and some statistically significant two-factor interactions have been identified. Therefore, the detailed evaluation of errors and uncertainties in 4D imaging modalities is recommended in order to assess the clinical implications of interaction among the various uncertainty factors.

3D printing technology will eventually eliminate the need of purchasing commercial phantoms for clinical medical physics QA procedures

3D printing is not a new concept. The recent advances in printing speed, technology, and material selection are promoting its significant impacts in several industries, including health care. For our medical physics field, researchers are also finding its applications in various clinical aspects. However, the interests still remain in a few academic centers who have the luxuries of owning such an unconventional device in the radiation oncology department, or collaborating with a local 3D printing lab. As the 3D printing technology is becoming an unstoppable driving force in manufacturing revolution, are we also envisioning a future that 3D printing will become as common as a block‐cutting machine in a radiation oncology department? In this debate, we invited two researchers who are experienced in studying the clinical use of 3D printing in medical physics field. Dr. Eric Ehler is arguing for the proposition that “3D printing technology will eventually eliminate the need of purchasing commercial phantoms for clinical medical physics QA procedures” and Dr. Daniel Craft is arguing against. Dr. Eric Ehler is an Assistant Professor in the Department of Radiation Oncology at the University of Minnesota. He is the medical physics residency program director at the University of Minnesota Medical Center. His education and research interests are 3D printing, pediatric radiotherapy, radiation dosimetry, and machine learning. Dr. Daniel Craft is currently a medical physics resident at The Mayo Clinic in Phoenix, AZ. Prior to the beginning of his residency, Dr. Craft was a graduate research assistant and PhD student at the University of Texas MD Anderson Cancer Center in Houston Texas, where he studied techniques to deliver postmastectomy radiation therapy using 3D printed patient‐specific tissue compensators. He completed his Ph.D. in Medical Physics in May, 2018, and also holds an undergraduate degree in Physics from Brigham Young University.

SU‐F‐BRE‐04: Construction of 3D Printed Patient Specific Phantoms for Dosimetric Verification Measurements

PURPOSE To validate a method to create per patient phantoms for dosimetric verification measurements. METHODS Using a RANDO phantom as a substitute for an actual patient, a model of the external features of the head and neck region of the phantom was created. A phantom was used instead of a human for two reasons: to allow for dosimetric measurements that would not be possible in-vivo and to avoid patient privacy issues. Using acrylonitrile butadiene styrene thermoplastic as the building material, a hollow replica was created using the 3D printer filled with a custom tissue equivalent mixture of paraffin wax, magnesium oxide, and calcium carbonate. A traditional parallel-opposed head and neck plan was constructed. Measurements were performed with thermoluminescent dosimeters in both the RANDO phantom and in the 3D printed phantom. Calculated and measured dose was compared at 17 points phantoms including regions in high and low dose regions and at the field edges. On-board cone beam CT was used to localize both phantoms within 1mm and 1° prior to radiation. RESULTS The maximum difference in calculated dose between phantoms was 1.8% of the planned dose (180 cGy). The mean difference between calculated and measured dose in the anthropomorphic phantom and the 3D printed phantom was 1.9% ± 2.8% and -0.1% ± 4.9%, respectively. The difference between measured and calculated dose was determined in the RANDO and 3D printed phantoms. The differences between measured and calculated dose in each respective phantom was within 2% for 12 of 17 points. The overlap of the RANDO and 3D printed phantom was 0.956 (Jaccard Index). CONCLUSION A custom phantom was created using a 3D printer. Dosimetric calculations and measurements showed good agreement between the dose in the RANDO phantom (patient substitute) and the 3D printed phantom.

MO-A-9A-01: Innovation in Medical Physics Practice: 3D Printing Applications

3D printing, also called additive manufacturing, has great potential to advance the field of medicine. Many medical uses have been exhibited from facial reconstruction to the repair of pulmonary obstructions. The strength of 3D printing is to quickly convert a 3D computer model into a physical object. Medical use of 3D models is already ubiquitous with technologies such as computed tomography and magnetic resonance imaging. Thus tailoring 3D printing technology to medical functions has the potential to impact patient care. This session will discuss applications to the field of Medical Physics. Topics discussed will include introduction to 3D printing methods as well as examples of real-world uses of 3D printing spanning clinical and research practice in diagnostic imaging and radiation therapy. The session will also compare 3D printing to other manufacturing processes and discuss a variety of uses of 3D printing technology outside the field of Medical Physics. LEARNING OBJECTIVES 1. Understand the technologies available for 3D Printing 2. Understand methods to generate 3D models 3. Identify the benefits and drawbacks to rapid prototyping / 3D Printing 4. Understand the potential issues related to clinical use of 3D Printing.

Step and shoot IMRT to mobile targets and techniques to mitigate the interplay effect.

The purpose of this work is to evaluate a method to mitigate temporal dose variation due to the interplay effect as well as investigate the effect of randomly varying motion patterns. The multi-leaf collimator (MLC) settings from 5, 9 and 11 field step and shoot intensity modulated radiation therapy (IMRT) of non-small cell lung cancer (NSCLC) treatment plans with tumor motion of 1.53, 1.03 and 1.95 cm, respectively, were used. Static planar dose distributions were determined for each treatment field using the Planar Dose Module in the Pinnacle(3) treatment planning system. The MotionSIM XY/4D robotic diode array was used to recreate the tumor motion orthogonal to each treatment beam. Dose rate modulation was investigated as a method to mitigate temporal dose variation due to the interplay effect. Computer simulation was able to identify individual fields where interplay effects are greatest. Computer simulation and physical measurement have shown that temporal dose variation can be mitigated by the selection of the dose rate or by selective dose rate modulation within a given IMRT treatment field. Selective dose rate modulation within a given IMRT treatment field reduced temporal dose variation to levels comparable to whole field dose rate reduction, while also producing shorter radiation delivery times in six of the seven cases investigated. For the cases considered, the interplay effect did not appear to have a greater effect on hypofractionation compared to traditional fractionation even though fewer fractions were delivered. Randomized motion kernel variation was also considered. For this portion of the study, a nine field step and shoot IMRT configuration was considered with a 1.03 cm tumor motion rather than the five field case. In general, if the extent of the variant motion pattern was mostly contained within the target volume, limited impact on the temporal dose variation was observed. In cases where the variant motion kernels increasingly exceeded the target volume limits, increases in temporal dose variation were observed.

TH‐E‐ValA‐01: On the Dose Delivered to a Moving Target When Employing Different IMRT Delivery Mechanisms

Purpose: To investigate the influence of target motion on dose distributions generated using unmodulated open fields, solid intensity modulator (SIM), Step and Shoot MLC (SMLC) and dynamic MLC (DMLC). Method and Materials: For two lungcancer cases, four treatment plans were generated using Pinnacle3 7.9t consisting of an open field, SIM, SMLC and DMLC delivery on a Varian Clinac 600C/D equipped with a 120 leaf Millennium MLC. The coordinates (x, y, z, t) of the 4D motion trace for each of the tumors were determined using 4D‐CT from which a 4D motion kernel was generated. For each beam used in the experiment, the beams‐eye view tumor motion due to breathing was simulated using a computerized 2D tabletop apparatus. A MAPcheck diode array was incorporated into the apparatus for dose distribution analysis. Each of the four static treatment plans was delivered to the breathing MAPcheck ten times at various points of the breathing cycle. Results: The variation in diode dose readings within the tumor motion envelope was compared for the open field, solid, segmented, and dynamic IMRT deliveries. The open field provided the most uniform dose to the entire set of tumor mimicking diodes followed by SIM, SMLC, and DMLC IMRT, respectively. On an individual diode by diode basis over ten trials, the open field had the smallest average coefficient of variation of 0.122% followed by SIM (0.98%), SMLC (2.22%) and DMLC (3.88%) IMRT delivery, respectively. Conclusion: For the three IMRT delivery methods (SIM, SMLC, and DMLC), SIM consistently provided a more uniform dose to the tumor over many trials. SMLC performed as well as the solid modulators in many cases or was slightly out performed by SIM. DMLC consistently delivered the least uniform dose to the tumor over many trials.