bluuebunny/crossref_metadata_2025 huggingface dataset:
TU‐A‐141‐01: Multi Modal PET/CT Imaging for Therapy Response Early Prediction and Therapy Monitoring
Authors: Hatt M , Lambin P , Kinahan P
Published: July 2013

Monitoring a patient's response during treatment plays an important role in optimizing personalized treatment strategy. It may offer the possibility to predict future response early during treatment and adapt therapy. It calls for an optimal use of existing and under development imaging technologies as well as image and data processing and analyses for characterizing tumor response. This lecture will provide an overview of three complementary points related to therapy response monitoring using PET/CT. The first one concerns the growing interest and potential future role of multi modal PET/CT imaging in response to therapy studies, from a clinical point of view. This will help the audience identifying which combinations of disease, associated treatments and radiotracers are concerned. The second point is associated with the technical issues and methodological requirements associated with implementing response to therapy monitoring in clinical studies, in terms of standardization and homogeneity of acquisition protocols (reproducibility) and optimal use of existing image reconstruction methods. Finally, the third point concerns the way produced images are exploited, processed and manually or semi‐automatically analyzed then integrated in multifactorial Decision Support Systems. Current and future trends in the development of advanced methods dedicated to facilitate processing and analysis of multi modal and sequential images PET/CT (and PET/MRI) will be discussed, as well as their potential future role for response to therapy monitoring based on multi modal imaging integrated with non imaging biomarkers of predictors.

Learning Objectives

1. Review the current and future role of multi modal PET/CT imaging in early prediction and monitoring of response to therapy in several clinical oncology and radiotherapy applications.

2. Understand the requirements regarding standardization of imaging protocols and image generation in order to exploit multi modal image‐derived indices to characterize response to therapy.

3. Envision the future directions in developing semi automated methods for multi modal images analysis and multifactorial decision support systems integrating imaging and non imaging biomarkers.
TU‐A‐116‐01: Phantom Measurement of Surface and Organ Dose Using Optically Stimulated Luminescence Detectors in Diagnostic Radiology
Authors: Rodriguez M , Yukihara E , Ahmad S , Ruan C
Published: July 2013

Purpose: To measure the organ and surface dose in a phantom using aluminum oxide doped with carbon (Al2O3:C) and beryllium oxide (BeO) optically stimulated luminescence (OSL) detectors for the purpose of evaluating patient organ dose in diagnostic radiology procedures. Methods: The Al2O3 :C detectors used in this study were cut from Luxel™ tape into 4 mm diameter circles of thickness 0.3 mm. The BeO detectors used in this study were ∼4.7 mm × ∼4.7 mm × 0.5 mm chips. The liver dose was measured by placing detectors into the custom‐made detector holders and placing the holders in the 19 locations corresponding to the liver in an anthropomorphic phantom (RANDO). Each measurement was repeated three times. An AP abdomen protocol with AEC was used to determine the technical parameters for the exam. After irradiations, the BeO signal was read using a Riso TL/OSL‐DA‐15 automated reader and the Al2O3 :C signal was read using a custom‐built light emitting diode (LED)‐based reader system. The results were compared to those obtained from LiF:Mg,Ti thermoluminescence detectors (TLD). Results: The liver dose measured by BeO and Al2O3:C for a standard AP abdomen exam was found to be 208 and 222 μGy, respectively. The surface dose measured by BeO and Al2O3:C exam was both found to be 540 μGy. For comparison, the TLDs measured an organ and surface dose of 257 and 630 μGy, respectively. Conclusion: The proposed method of using BeO and Al2O3:C OSL detectors to measure organ and surface dose in an anthropomorphic phantom yielded comparable results to that of TLDs and shows improved reproducibility of the measurements when compared to TLDs. Given the flexibility and accuracy of OSL detectors for various readout techniques, OSL detectors have a great potential to allow for clinical organ dose measurement of diagnostic x‐ray exams.
TU‐A‐116‐03: CCD‐Based Dosimetry System for Use in Diagnostic Radiology
Authors: Gopan E , Hintenlang D
Published: July 2013

Purpose: To develop a new dosimetry system, for use in the diagnostic radiology energy range, which will be able to quantify dose more rapidly, effectively and consistently. The system is based on an array of cylindrical silica scintillators coupled to optical fibers and a CCD camera. Methods: An Andor Luca electron‐multiplying camera was used for readout, resulting in a strong output even from a small number of impinging photons. The camera has a cooling system to maintain a low detector temperature (−20 degrees Celsius). It was sealed in a light‐tight enclosure to shield it from background light which could contaminate the readings. A 10 mm diameter, 8 mm effective focal length aspheric lens was mounted to focus the light from the fibers onto the CCD detector. The system was evaluated for reproducibility, energy dependence and linearity, across a range of energy (40‐100 keV), current (6 to 19.5 mAs) and dose (1 to 30 mGy), validating its feasibility for future use. Results: A signal was acquired at the diagnostic radiology energy range, a Result which has not been attained by other investigators. The system showed high reproducibility, with a coefficient of variation of 1.08 % at 10 mGy. The energy dependence was fairly linear at lower energies, with a correlation coefficient of 0.995 from 40 to 80 keV, but showed greater increases between counts at higher energies. Dose (mean counts) as a function of current‐time (mAs) was also linear, with a correlation coefficient of 0.998. Conclusion: The system shows high reproducibility, linearity and immediate readout. Because the camera acts as a single readout channel, dose from multiple organs can be quantified more rapidly and consistently. The system is expected to be very useful in organ dose quantification from any imaging modality with dose to multiple organs, such as CT or CBCT.
TU‐A‐116‐04: A Method for Deriving Exam‐Specific Target Exposure Indices (TEI) in Computed Radiography as a Function of a Reference TEI
Authors: Hulme K , Kubicki V , Dong F , Davros W , Johnson P
Published: July 2013

Purpose: Determining appropriate target exposure index (TEI) values is one of the major barriers in the clinical efficacy of the IEC deviation index (DI). The goal of this work was to isolate the impact of exam group on TEI and thus derive TEI‐subgroups for Agfa CR that would enable target values to be more easily established from a single reference value. Methods: Data were exported from 13 Agfa NX workstations (software versions 8600 and 8700SU1) at 8 sites affiliated with Shimadzu RadSpeed radiographic rooms (generator UD150V‐40) using Agfa CR. XML files were imported into MATLAB and 147,619 dose statistics were analyzed. The DI for TEI(ref)=400 (DI(ref) = 10*log10(EI/TEI(ref))) was calculated for each data point. The distribution in DI(ref) was normal for each exam group. Variance was independent of TEI (ref). The mean ‐ DI (ref,k,i) ‐ and standard deviation ‐ SD(DI(ref,k,i) )‐were calculated for each workstation i and exam group k. DI(ref,k) was determined from the average of DI(ref,k,i) weighted by number of exams acquired for that exam group on each workstation. A bin width of ΔDI(ref) =1 was used to create TEI subgroups. Results: Exam groups were binned into seven subgroups centered on DI(ref,k) =[−2,−1,0,1,2,3,4] corresponding to linear scaling factors K(ref,k) =[0.6,0.8,1.0,1.3,1.6,2.0,2.5]. Standard error of the mean was <0.1 for all DI(ref,k) except one, which would have allowed for finer sub‐group binning. SD(DI(ref,k) ) ranged from 0.75 to 2.68, and was not correlated with DI(ref,k) (r2=0.003). Conclusion: Little guidance exists for the establishment of TEI tables as function of anatomy and view. The described methodology demonstrates how TEI values can be derived from a single reference value using measured scaling factors (TEI(k) =TEIref*K(ref,k) ). Seven TEI subgroups were established for Agfa CR. Vendor‐specific volume of interest algorithms and detector type will likely affect measured scaling factors. Determination of an appropriate TEI(ref) requires further evaluation.
TU‐A‐116‐08: A Methodology to Estimate Radiation Dose Reported On a Personal Radiation Monitor
Authors: Juneja V , Busse N , Jones A
Published: July 2013

Purpose: The purpose of this study was to estimate the expected reading on a personal radiation monitor (PRM) in a fluoroscopy procedure and to determine what information can be deduced from PRM reports. Our institution received a PRM report indicating a deep dose equivalent (DDE) exceeding our ALARA III level (1250 mrem) during a monitoring period. The employee (a radiation therapist) reported she underwent a 2 hour upper GI fluoroscopy examination and her PRM was in her purse 1 meter away during the procedure. Methods: Typical, minimum, and maximum dose area products (DAP) and x‐ray field sizes (FS) for upper GI examination were estimated based on a literature review. The ratio of DAP and FS gave an estimate of the entrance air kerma (EAK). The air kerma (K) at the location of the PRM was calculated by multiplying the EAK by the side‐scatter fraction at 1 meter. K at the PRM was corrected to 1 cm tissue depth to estimate DDE. Results: The DDE based on the scenario reported was estimated to be 12 mrem. Minimum and maximum readings were estimated as 3 and 26 mrem, respectively. If the reported DDE was due to the upper GI examination only, the EAK would be approximately 30 Gy. The PRM report also noted that imaging results were inconclusive. Shallow dose equivalent (SDE) was 5% less than DDE. Conclusions: The scenario reported by the employee is highly unlikely to have resulted in the DDE observed on the PRM. Reported beam quality from the PRM report and the relative ratio of shallow to deep dose suggest a higher energy beam (such as scatter in a radiation therapy room) to be the more likely cause.
TU‐B‐137‐01: Radiobiological Principles of Fractionated Radiotherapy and the Potential for Hypofractionation
Authors: Orton Colin G
Published: July 2013

Firstly, we will review why we fractionate at all, looking first at physical reasons then at the radiobiological aspects. Mechanisms by which radiation kills cells and ways cell damage can be repaired will be reviewed. Using the linear‐quadratic model we will show the effect of radiobiological parameters which we can control for radiotherapy including dose/fraction, number of fractions, time between fractions, overall treatment time, and dose rate. We will show that there is a “Window of Opportunity” at low doses/fraction within which we can control cancers without exceeding normal tissue tolerance. We will then show how the use of highly conformal radiotherapy widens this “Window of Opportunity” so that we can use higher doses/fraction and hence hypofractionation. Finally, we will review some potential caveats that might reduce the effectiveness of hypofractionation and, possibly, make it inappropriate for some cancers. These are the presence of significant fractions of hypoxic cancer cells, the possibility that low‐dose hyper‐radiosensitivity in normal surrounding tissue cells might reduce the effectiveness of conformal therapies, and the lengthening of treatment times when using high doses/fraction thus allowing intra‐fraction repair of cancer cells.

Learning Objectives

1. To understand why we fractionate and how the linear‐quadratic model can be used to demonstrate the effect of radiobiological parameters which we can control for radiotherapy.

2. To understand why hypofractionation might be possible with highly conformal radiotherapy.

3. To understand the circumstances when hypofractionation might not be appropriate.
TU‐C‐108‐01: Verification of Deformable Dose Calculation with Phantom Measurements
Authors: Adams J , Zhong H
Published: July 2013

Purpose: Dose accumulation involves many computational procedures which may introduce error. The purpose of this study is to utilize a novel deformable dosimetry phantom to experimentally verify the total dose accumulated by 4D dose calculation algorithms. Methods: Lung phantom consisting of heterogeneous sponge material and tissue‐equivalent tumor. The sponge is enclosed in a latex cylinder, compressed by a piston to simulate the diaphragm motion. TLD‐100 thermoluminescent dosimeters were placed in the sponge and inside the tumor for 4D‐dosimetry verification. Three TLDs were used at each point for better statistics. A four phase 4DCT was taken for planning purposes. A 5‐beam 6MV 3D conformal plan was developed with 95% of the ITV receiving the prescribed dose of 200 cGy, which may help to maintain a linear TLD response. The plan was delivered under the same deformation pattern with the BrainLab Novalis system, and exported to Eclipse and Pinnacle for comparison. CT phase images were registered to end‐exhale (EE) phase, when sponge is maximally compressed, using a B‐Spline‐based algorithm. The resultant displacement vector field was output for dose mapping. Dose was warped to EE phase using an in‐house developed, subvoxel projection method and accumulated for comparison with the TLD measurements. Results: The tumor dose agreed very closely to the accumulated dose and was measured to be 0.5% lower with the TLDs. Another point of measurement was ∼2 cm from the tumor, near the edge of the field, and was measured 5.4% higher with the dosimeter. A point of high field gradient ∼5 mm from the tumor was measured 12.5% higher than calculated. Larger uncertainties in the TPS are expected in this gradient region. Dose warping improved the tumor dose calculation by 29.4%. Conclusion: The deformable phantom could be a valuable tool to verify the total dose calculated by adaptive treatment plans. The research was supported by NIH/NCI R01CA140341.
TU‐C‐141‐01: The Development of a Set of Deformable Thermoplastic Materials That Mimic Tissue for Kilovoltage and Megavoltage Computed Tomography
Authors: Singhrao K , Kirby N , Pouliot J
Published: July 2013

Purpose: To construct a phantom designed to test deformable image registration algorithms, by developing a set of deformable thermoplastic materials that mimic tissue for both kilovoltage and megavoltage computed tomography. Methods: A material formulation was developed to represent muscle, water, and adipose using two polyurethanes capable of deforming in boiling water to produce anatomical deformations. The CT Hounsfield Units (HU) were tuned by doping the polyurethanes with a primary additive to increase the HU and a secondary additive to decrease it. To mimic actual bone, a plastic mixture whose HU was controlled by a tertiary additive was formulated to remain rigid in boiling water. A phantom prototype representing a central sagittal head and neck slice was constructed using the optimized materials. To ensure the phantom was anthropomorphic, its geometry was designed by contouring the major anatomical sites of a patient. The phantom was constructed so it could be opened along the sagittal midsection where a grid of 300 nonradioopaque markers were placed with 5mm spacing. The grid served as a nonradioopaque means of characterizing the 3D magnitude of a deformation with an optical camera. Results: The phantom materials were successfully tuned to be both kV and MV compatible and made to represent different tissues. The phantom constructed from these materials exhibited a similar HU contrast to an actual patient and was successfully deformed around the neck section, producing a clinically realistic deformation of several mm in magnitude. Conclusion: Using the formulated set of materials, an anthropomorphic phantom depicting different tissue types was built and deformed in 3D in a clinically realistic fashion. By measuring the positional changes of the optical markers, the constructed phantom can be used to physically verify deformable image registration algorithms. The work was supported in part by a UC Proof of Concept Program Commercialization Gap Grant.
TU‐C‐141‐08: Evaluate Deformable Image Registration for the Lungs Using Hyperpolarized Gas Tagging MRI
Authors: Liu Y , Miller W , Yin F , Cai J
Published: July 2013

Purpose: To evaluate deformable image registration for the lungs using hyperpolarized gas MR tagging technique.Method and Materials: A 3D MR grid‐tagging technique using hyperpolarized helium‐3 (HP‐He3) as gaseous contrast was developed for direct measurement of lung respiratory motion. One healthy subject was imaged at the end‐of‐inhalation (EOI) and end‐of‐exhalation (EOE) phases in a single scan using the HP He‐3 MR tagging technique, as well as a high‐resolution 3D proton MR sequence (TrueFISP) which shows rich internal lung features (pulmonary vessels). 3D displacement vectors of the lungs between the EOI and EOE phases were determined via two Methods: 1) by tracking the movements of the tags between the two phases in the HP He‐3 MR tagging images; and 2) by registering the proton MR images at two phases using deformable image registration (DIR) via commercial software. DIR‐derived 3D displacement vectors were down‐sampled to approximate the resolutions of those derived from the MR tagging method. Furthermore, 3D lung ventilation maps, where ventilation is defined as (Volume_EOE‐Volume_EOI)/Volume_EOI, were created based on the displacement vectors and compared between the two methods. Results: The HP He‐3 tagging MR images clearly revealed 3D lung respiratory motion between the EOI and EOE phases. Tags in the EOE phase were slightly blurred but traceable. 3D displacement vectors derived from the tagging and DIR methods showed distinct differences in motion pattern, amplitude and direction, for the entire lungs and on regional basis. Lung ventilation maps derived from two methods showed different mean values and uniformity: the mean (±SD) ventilation was −0.49 (±0.19) and 0.14 (±0.32) for the MR tagging and DIR methods, respectively. Conclusions: Discrepancies were found in lung respiratory motion and ventilation between the HP He‐3 MR tagging method and the DIR method. Thorough evaluation of DIR accuracy for the lungs is highly desired in future studies.
TU‐C‐103‐01: A Framework for 3D Modeling of Anthropomorphic Lesions in CT
Authors: Solomon J , Nelson R , Samei E
Published: July 2013

Purpose: Realistic three‐dimensional mathematical models of subtle lesions are essential for many CT studies focused on performance evaluation and optimization. The purpose of this work was to develop and apply a generic framework for creating such models informed by clinical data. Methods: A contrast profile equation was developed to describe the attenuation of a modeled lesion as a function of distance from the center of the lesion in a given direction. This equation prescribes the overall size, shape, contrast, and edge profile characteristics of the lesion in 3D. By adjusting the parameters of the contrast profile equation, the characteristics of a simulated lesion could be manipulated to emulate a realistic lesion. The simulated lesions could further be voxelized at any arbitrary resolution for comparison with real CT data. Using this framework, a trust‐region iterative minimization fitting algorithm was developed to generate a library of simulated lesions based on clinical CT data with known lesions. We first identified and segmented liver lesions, lung nodules, and renal stones from clinical cases. The fitting algorithm was then applied to the segmented pathologies. The results were evaluated for realism using an observer study and ROC analysis. Results: Based on CT image data from 22 patients; 10 liver lesion, 13 lung nodule, and 20 renal stone models were created. These models were found to have size, shape, contrast, and edge profile characteristics similar to those of real lesions. The observers could not distinguish between real and modeled lesions (AUC = 0.49). Conclusions: It is possible to create realistic 3D mathematical models of anthropomorphic lesions in CT images. These models could be instrumental in performance evaluation and optimization of CT systems. GE Healthcare, A‐56:Optimization of Protocols Employing Advanced Reconstruction Algorithms
TU‐C‐103‐08: Determination of CT Texture Variability Among Several CT Scanners
Authors: Christensen E , Hunter L , Stingo F , Klawikowski S , Court L
Published: July 2013

Purpose: Radiomics is an emerging field with the potential to use CT textures to predict clinical outcomes for cancer patients. The effect of different scanner use on CT texture variability is poorly understood. The purpose of this study was to compare the effect of scanner used on CT texture variability. Methods: A thoracic anthropomorphic phantom (Kyoto Kagaku) containing nodules mimicking lung tumors was scanned using four different CT scanners (2 GE, 2 Philips) at nearly identical settings. Nine different regions of interest (ROIs) were identified: 5 lung nodules, 3 bronchial tree regions, and the subcarinal nodal area. Each ROI was contoured using automated contouring parameters in the Pinnacle treatment planning system. Code developed and validated previously was used to extract CT texture features for each ROI. Previous work by our group identified 20 CT texture tumor features that are reproducible (CTr) between repeat scans among patients with lung cancer. These 20 CTr textures were extracted from each of the phantom ROIs. Phantom ROIs with 75% or more of the extracted texture features falling within the patient range were pooled for each machine. A one‐way ANOVA was conducted to compare the effect of CT scanner used on 20 CTr textures from pooled ROIs. Results: Five (55.5%) of the nine phantom ROIs had 75.0‐95.7% of CTr textures within the range of patient CTr textures. There was no significant effect of scanner used on any of the 20 CTr textures assessed (p > 0.18). Conclusion: Using different CT scanners at nearly identical settings does not significantly contribute to variance in CTr texture output. This phantom provides a tool with which institutions can evaluate their scanners for CT texture variances. Future studies to determine the contribution of differences in CT scanner settings, if any, to variances in CT texture will be important.
TU‐C‐103‐09: CT Model‐Based Iterative Reconstruction: How Much Dose Can We Save?
Authors: Dodge C , Rong J
Published: July 2013

Purpose: To determine the potential for dose reduction with adaptive statistical iterative reconstruction (ASiR) and model‐based iterative reconstruction (MBIR) as compared to conventional filtered back‐projection (FBP) reconstruction methods. Methods: The low‐contrast module of a Catphan 600 phantom was scanned using a GE Discovery HD750, at 120 kVp, 0.8 second rotation time, and pitch factors of 0.516, 0.984 and 1.375. The mA was selected for each of the three pitch factors to achieve CTDIvol values of 24, 18, 12, 6, 3, 2 and 1 mGy. Images were reconstructed at 2.5mm thickness with FBP; 20%, 40% and 70% ASiR; and MBIR. The 1% contrast, 15mm diameter supra‐slice object and adjacent background were selected to determine the noise and CNR. To minimize statistical variations in noise, for each scan condition, images from 10 independent acquisitions were analyzed. The results were confirmed in the anthropomorphic Kyoto Kagaku abdomen phantom at 6, 3, 2 and 1 mGy. Results: Compared to FBP, MBIR considerably reduced noise and improved CNR at all dose levels. At low doses in particular, a five‐fold decrease in noise and four‐fold increase in CNR were observed. ASiR also improved image quality compared to FBP across the range of dose values investigated, but to a lesser degree than MBIR. At 70% ASiR, up to a two‐fold increase in CNR and 50% noise reduction were achieved. The quantitative results over 3 different pitch factors were similar. By maintaining image quality at the level of 1 mGy, dose reduction was estimated for MBIR and ASiR compared to FBP. Up to 97% dose saving was achieved with MBIR and up to 15% for ASiR (70%). Conclusion: Both MBIR and ASiR maintained image quality at substantially reduced dose levels as compared to FBP. MBIR demonstrated the feasibility for low‐dose patient imaging at sub‐mGy dose levels.
TU‐C‐103‐11: Noise Reduction of 4D CT Data by a Modified Non‐Local Means Filter
Authors: Li Z , Leng S , Yu L , Manduca A , McCollough C
Published: July 2013

Purpose: 4D (3D plus time) CT data, such as cardiac or perfusion images, are frequently affected by body motion. Additionally, these data are normally very noisy due to the use of lower scanner output settings in order to reduce patient dose. State‐of‐the‐art denoising filters can achieve efficient noise reduction of CT images, but fail to handle data containing significant body motion. The purpose of this work was to develop a filter that can overcome this limitation. Methods: A modified Partial Time Vector NonLocal Means filter (PTV‐NLM) recovers image from the original noisy data by representing a pixel using the weighted average of its neighbors in both the spatial and temporal domain. The weighting factor is determined by calculating the summed square difference of portions of the temporal profile of each pixel with its neighboring pixels. This approach does not require motion estimation, can automatically adapt to local motion and efficiently utilizes the redundant information in the images. Results: The denoised images showed better image quality than the original images, making anatomical structures easier to identify in the denoised images. After denoising, the contrast to noise ratio of simulated low‐dose perfusion data (using 25% of the full dose) was comparable to that of images acquired using the full dose. Alternatively, for applications such as cardiac CT, PTV‐NLM can be used with the full dose data to decrease image noise without introducing spatial blurring. Conclusion: In 4D data sets, the PTV‐NLM filter can maintain image quality at dramatically decreased dose levels, or provide better image quality at the same dose levels. It can be used to either reduce patient dose or improve image quality without causing blurring of moving anatomy.
TU‐C‐103‐12: An Experimental Study of the Effects of Different Beam‐Hardening Filters On CTDIvol and Low‐Contrast Image Detectability in a CT Scanner
Authors: Maghsoodpour A , Aldoohan S
Published: July 2013

Purpose: To study the effects of different beam‐hardening filters on CTDIvol and low‐contrast image detectability in a CT scanner Methods: The default Molybdenum beam‐hardening filter of GE HiSpeed CT/i scanner was replaced with three different types of filters, having K‐edges in low, middle, and high diagnostic energy range. The thickness of each filter was chosen such that it approximated Molybdenum energy‐equivalent thickness for the simulated mean energy of X‐ray spectrum generated at 120 kVp. The scanner calibration routine was run for each filter prior to image acquisition to ensure optimal image quality (optimized signal‐to‐noise ratio, optimized contrast‐to‐noise ratio, and no noticeable ring artifacts). An ACR CT phantom was imaged under a routine axial head protocol to evaluate the CNR for a wide range of mAs. Next, the head dose phantom was scanned to obtain CTDIvol for the same mAs range. The beam quality was also recorded. Filters were compared according to measured CNR, and CTDIvol for the smallest mAs providing CNR > 1 (= 200 mAs). Results: Examination of CNRs indicates no significant difference among filters. Evaluation of NPS for raw images acquired from different filters will address the image noise. CTDIvol measurements indicate that the filters attenuate the beam differently due to their K‐edge energies, and copper, having a low‐energy K‐edge (= 8.98 keV), provides the minimum CTDIvol. Conclusion: CNR is a function of CTDIvol and better addressed when accompanied by CTDIvol. The current project has the potential for selecting a new beam‐hardening filter to possibly reduce patient dose without compromising low‐contrast detectability. This work is in progress to optimize CNR by investigating other available kVps, filters, measured energy spectra, NPS, and K‐edge effect.
TU‐E‐108‐04: Preliminary Measurements Towards Radiation Therapy Involving Dynamic Couch Trajectories
Authors: Mullins J , Seuntjens J , DeBlois F , Syme A
Published: July 2013

Purpose: To assess the geometrical accuracy of treatment deliveries involving dynamic couch trajectories and to evaluate the accuracy of DMLC dose calculations in Eclipse at nonstandard SSDs. Methods: Eleven DMLC IMRT plans were recalculated as verification plans in Eclipse (AAA 10.0.28) using the collapsed gantry method, at SSDs between 85‐135 cm. Ion chamber and film measurements were performed to compare planned and delivered dose. DLG and MLC transmission were also measured as a function of SSD. Simple circular couch trajectories that simulated isocentric treatment at an SAD of 95 cm were evaluated using film and ion chamber measurements. Trajectories were implemented using Varian TrueBeam Developers Mode. Results: The relative agreement between Eclipse‐calculated dose and ion chamber measurements decreased systematically by an average of 1.5±0.3 % between 85 and 135 cm SSD. Film measurements were consistent with the ion chamber results. Following corrections for the geometric projection of the DLG, no dependence on SSD was observed, and the dependence of MLC transmission on SSD was negligible. These results are both consistent with Eclipse calculations. The standard error of ion chamber current measurements was 0.19 % for the dynamic couch trajectory at 95 cm SAD, compared to 0.17 % for static couch position. From the film measurements, the FWHM of the field delivered with dynamic couch motion was 94.6 % of the FWHM with static couch position, matching the predicted geometrical minification. Conclusion: Experiments were performed to investigate aspects of radiation therapy involving dynamic couch trajectories. The relative agreement between calculated and measured dose was found to systematically decrease with SSD, while DLG and MLC transmission were independent of SSD. Isocenter positional accuracy with dynamic couch motion was demonstrated through the consistency of ion chamber current measurements and observation of the expected decrease in field size at a shortened SAD.
TU‐E‐141‐03: A Population Based Statistical Model of Three‐Dimensional Systematic Tissue Displacement for Fractionated Radiation Therapy
Authors: Vile D , Christensen G , Ford J , Weiss E , Williamson J
Published: July 2013

Purpose: To introduce and validate a model of systematic tissue displacement based upon population statistics for prostate cancer patients undergoing fractionated external‐beam radiotherapy. Methods: Our dataset consisted of 19 patients, each with 9–14 pelvic fan‐beam CTs taken throughout treatment, all manually contoured and aligned to bone. Each patient's fractional images were deformably registered to his planning image using intensity and contour matching. The resulting displacement vector fields (DVFs) were averaged to find the patient‐specific tissue systematic error, which maps the patient's mean treatment anatomy to his planning anatomy. Then, each patient's prostate, rectum, and bladder were mapped from his planning image to its counterpart on an average reference image set using contour‐driven deformable registration. These planning‐to‐reference DVFs were used to transport the 19 systematic DVFs (limited to the space occupied by the organs) into the common reference frame. A principal component analysis (PCA) was performed to determine the principal modes of systematic DVF variability. A leave‐one‐out approach was used to test the hypothesis that systematic errors for patients not included in the training set can be accurately represented as a linear combination of PCA eigenvectors. The known average anatomy and the PCA reconstructed anatomy was compared using the Dice similarity coefficient. Results: The PCA showed that 92% of systematic error variations can be accounted for using 7 eigenmodes. Using the leave‐one‐out approach to reconstruct the patient's average anatomy, the mean (standard deviation) Dice for the prostate, bladder, and rectum were 0.91±0.03, 0.93±0.03, and 0.84±0.05 respectively. Conclusion: The PCA population modeling of systematic errors can accurately represent systematic error DVFs for arbitrary patients. Our model can be used to create an ensemble of randomly sampled systematic pelvic organ DVFs for use in probabilistic planning when the patient's actual systematic error is unknown a priori. Supported by NIH Grant P01 CA 116602; Supported by NIH Grant P01 CA 116602
TU‐E‐141‐06: Estimation of Dose Distributions with the Dental Artifact Correction in Radiation Treatment Plans for Head‐And‐Neck Cancers
Authors: Lee M , Suh T , Park J , Lee J , Park H , Lee B
Published: July 2013

Purpose: Metal artifacts generated by dental implants cause dose discrepancy in intensity‐modulated radiation therapy (IMRT) of head‐and‐neck cancer cases due to the inaccurate predicted doses. To determine the effective metal artifact reduction (MAR) method presenting minimum dose errors with delivered dose, dosimetric impact of different MAR methods were evaluated in radiation treatment plans. Methods: MAR was implemented using Euler elastic and curvature based sinogram inpainting (EECSI) algorithm, volume clustering with Hounsfield unit (HU) overriding (VCU), and multimodal image‐based correction (MIC). When delivered doses were calculated on the corrected computed tomography (CT) images by employing the same plan parameters in the reference IMRT plan (Planref), dose errors were analyzed with dose‐volume histograms (DVHs), monitor unit, and dose conformity of target volumes. Dosimetric impacts were also estimated using the biophysical evaluation parameters in three oropharyngeal patients. Results: Optimized fluence in the Planref resulted in overdose up to 5% in the salivary glands and spinal cords on the corrected CT images, while the overdose in target volumes increased tumor control probability of 3–7%. Target doses in peripheral regions affected by the surrounded dark pixels were deformed and decreased conformity. The DVHs of organs at risk (OAR) and target volumes also showed the 5–8% volume gap in the prescription dose range. As the efficient MAR is employed into the head‐and‐neck IMRT plans, more accurate predicted doses of primary structures would be achieved, even if the dose differences of each MAR method are small less than 2–3%. Conclusion: EEECSI and VCU were useful methods to reduce the metal artifacts and to predict more accurate delivered doses. Since dental artifacts cause dose variation in peripheral region of target volumes and OAR, dose calculation on corrected CT images using efficient MAR techniques and dose verification would be encouraged in head‐and‐neck IMRT plans.
TU‐E‐141‐08: Dosimetric Impact of Partial Volume Correction On PET‐Based Targeted Radionuclide Therapy Planning
Authors: Titz B , Grudzinski JJ , Barbee DL , Weichert JP
Published: July 2013

Purpose: Partial volume effects have been shown to introduce a significant error in positron emission tomography (PET) quantitation. In this study, we investigated the impact of PET partial volume correction (PVC) on the dosimetry of PET‐based targeted radionuclide therapy (TRT) planning. Methods: Five tumor‐bearing nude mice were injected with ∼230 μCi of a 124I‐CLR1404, a small‐molecule, phospholipid ether analog featuring selective retention and accumulation in malignant cells. PET/CT data were acquired at 1, 6, 12, 24, 36, 48, 60, 72, 96, 120, 168, and 240 hours post injection and reconstructed with and without PVC using an OSEM3D algorithm. Assuming identical uptake between 124I‐CLR1404 and its therapeutic analog, 131I‐CLR1404, absorbed doses of 131I‐CLR1404 were modeled by applying a piecewise trapezoidal integration to the 124I‐CLR1404 kinetics. Dose volume histograms (DVHs) and normalized differential DVHs (dDVHs) were used to quantify the impact of PVC on PET‐based TRT planning. Results: Partial volume corrected PET images showed higher tumor uptake, increased the recovery of tumor heterogeneity structures, and a generally improved recovery of small normal tissue structures such as the heart ventricles. In tumors, the mean and maximum 124I‐CLR1404 standardized uptake value at peak drug concentration increased by 1.95±0.86% and 34.97±9.36%, respectively. DVHs of planned 131I‐CLR1404 doses showed an increase in maximum tumor dose levels by 15.63±3.53% due to PVC. Tumor dDVHs confirmed a shift towards higher therapeutic doses with an average increase of 13.09±1.21 mGy per mCi of injected 131I‐CLR1404 activity. Conclusion: PVC of PET data more accurately recovered the biodistribution of 124I‐CLR1404 and thus further improved TRT planning and delivery by increasing the quantitative accuracy. PVC will especially benefit the identification of cold spots in the target volume and the dose estimation in dose limiting organs. JJG and JPWare affiliated with Novelos Therapeutics, Inc., which owns the licensing rights to CLR1404 and related compounds.
TU‐E‐116‐01: Clinical Implementation for Advanced Brachytherapy Dose Calculation Algorithms Beyond the TG‐43 Formalism
Authors: Thomson R , Ballester F , Beaulieu L
Published: July 2013

With the recent introduction of heterogeneity correction algorithms for brachytherapy, the AAPM community is still unclear on how to commission and implement these into clinical practice. The recently‐published AAPM TG‐186 report discusses important issues for clinical implementation of these algorithms. In this practical medical physics course, specific examples on how to perform the commissioning process are presented, as well as descriptions of the clinical impact from recent literature reporting comparisons of TG‐43 and heterogeneity‐based dosimetry. A proposed commissioning flowchart will be discussed, guiding the audience through the clinical process. Further, QA tests specific to these new heterogeneity correction algorithms for brachytherapy will be explained. Potential changes in brachytherapy dose prescriptions will be discussed, with pitfalls identified to minimize likelihood for errors.

Learning Objectives:

1. Identify key clinical applications needing advanced dose calculation in brachytherapy.

2. Review TG‐186 guidelines, commission process, and dosimetry benchmarks.

3. Evaluate clinical cases using a commercially available system and compare to TG‐43 dosimetry
TU‐F‐500‐01: Point and Counter Point Debate: Brachytherapy Is Better Than External Beam Therapy for Partial Breast Irradiation
Authors: Todor D , Becker S
Published: July 2013

Partial breast irradiation (PBI) by either brachytherapy or external beam (EB) therapy is frequently used for the treatment of certain populations of breast cancer patients. The claim that brachytherapy is better than EB for PBI is the Proposition debated here.

Advantages claimed for brachytherapy for PBI include:

• brachytherapy is associated with smaller treatment volumes, lower integral doses, and smaller doses/fraction to normal tissues

• dosimetric parameters which affect toxicity have been thoroughly investigated for brachytherapy

• brachytherapy is supported by over ten years of study with excellent local control and minimal toxicity

• with brachytherapy, evidence‐based treatment planning guidelines have been published.

Advantages claimed for EB therapy include:

• all clinics have linacs, whereas not all have an HDR unit or LDR facilities

• brachytherapy requires specific skills and training that not all radiation oncologists have

• brachytherapy is an invasive procedure

• a brachytherapy program requires greater effort and staff to commission and maintain

• brachytherapy is performed BID, which is inconvenient to patients

• not all patients are appropriate for brachytherapy treatment

Arguing FOR the Proposition is Dorin Todor, Ph.D. Dr. Todor obtained his Ph.D. in Physics from Old Dominion University, Norfolk, VA followed by a one‐year Research Fellowship at Memorial Sloan Kettering Cancer Center, New York. Since then he has worked at the Virginia Commonwealth University where he is currently an Associate Professor. His major research interests include real‐time 3D HDR source position detection and tracking, and dual fusion imaging for intraoperative planning, execution and evaluation of brachytherapy implants.

Arguing against the Proposition is Stewart Becker, Ph.D. Dr. Becker obtained his M.S. and Ph.D. degrees in Medical Physics from the University of Wisconsin, Madison after which he moved to the Department of Radiation Oncology, New York University Medical Center, where he is currently Senior Physicist and Assistant Professor. His major research interests include image‐guided radiotherapy, and whole and accelerated partial breast radiotherapy.

Learning Objectives

1. To understand why brachytherapy might be better than external beam therapy for partial breast irradiation

2. To understand why external beam therapy might be better than brachytherapy for partial breast irradiation

3. To know how brachytherapy and external beam therapy differ when applied to partial breast irradiation
TU‐G‐108‐02: Left Atrium Dose‐Volume Parameters Predict for Clinically Significant Radiation Pneumonitis
Authors: Huang E , Folkert M , Bradley J , Apte A , Deasy J
Published: July 2013

Purpose: To detect and quantify the association between cardiac substructure irradiation and the risk of developing radiation pneumonitis (RP) within a multivariate framework for patients treated with conventional external beam radiotherapy for non‐small‐cell lung cancer (NSCLC). Methods: All evaluable 3‐D conformal radiation therapy (3D‐CRT) treatment plans for patients with registered outcomes treated for NSCLC between 1991 and 2001 were eligible for this study (N=209). RP events occurred in 49 (23.4%) patients, with events defined as requiring steroid management or more intensive intervention (CTCAE v.4.0 Grade 2 or greater). Cardiac substructures including the left ventricle, right ventricle, left atrium, right atrium, ascending aorta, and descending aorta were contoured and individually reviewed by a single physician. Cross‐validation methods were used to build a multivariate model included clinical factors (age, gender, race, performance status, weight loss, smoking history, and histology); dosimetric parameters for cardiac substructures and normal lung [D5–D100, V10–V80, mean dose, maximum dose, and minimum dose ]; other treatment factors (chemotherapy, treatment time, fraction size); and the center of mass of the GTV within the lung, in the superior‐inferior dimension (GTV_COMSI). An optimal multivariate model was obtained by step‐wise variable selection and logistic regression. Results: Statistically significant variables (p less than 0.05) with the highest univariate Spearman rank correlations (Rs) included: Left atrium D5 (Rs,0.235), left atrium D10 (Rs,0.228), right ventricle Dmax (Rs,0.2), right atrium Dmax (Rs,0.197), and GTV_COMSI (Rs,0.22). The optimal logistic model used four variables, incorporating the left atrium D20 and V30, the lung D35, and the GTV_COMSI; (Rs=0.31) with an area under the receiver‐operator curve of 0.75. The best model using only whole‐heart variables had an Rs=0.26. Conclusion: Left atrium dose‐volume parameters had greater predictive power than other heart substructures and previously derived lung parameters to predict RP, and were incorporated into a robust prognostic multiparametric model.
TU‐G‐WAB‐01: Advanced Applications in Deformable Registration
Authors: Brock K , Dong L , Hawkes D
Published: July 2013

The field of deformable image registration has seen many technical advances over the past decade, with increases in accuracy, the speed of the algorithms, and the flexibility of the algorithm to handle complex, multi‐modality images. These technical advances have enabled further advances in the applications of deformable image registration. This symposium will cover exciting new applications of deformable registration, ranging from population models, to image‐guided treatments outside of external beam radiotherapy, to image validation through correlative pathology. Deformable registration is generally thought of to be between two images of the same patient, for purposes of aiding the patient's radiotherapy treatment. However, novel applications are using deformable registration in applications outside of this space. Examples will include the investigation of population based information, such as the determination of a risk‐based CTV. The use of deformable registration for image validation through correlative pathology will be described including challenges and results of early studies. Exciting advances of hybrid registration technology for robust and efficient deformable registration for image‐guided surgery will also be illustrated.

Learning Objectives:

1. Describe the use of deformable registration for advanced image‐guided treatments.

2. Understand the application of deformable registration for population‐based models.

3. Describe the use of deformable registration for image validation in correlative pathology.

Dr. Brock has financial interest in deformable registration technology through a licensing agreement with Ray Search Laboratories.
TU‐G‐141‐02: Evaluation of Respiration Motion‐Corrected Cone‐Beam CT: Prospective Study in Lung
Authors: Dzyubak O , Kincaid R , Hertanto A , Hu Y , Pham H , Rimner A , Yorke E , Zhang Q , Mageras G
Published: July 2013

Purpose: Respiratory motion adversely affects the ability of cone‐beam computerized tomography (CBCT) to guide radiation treatment, due to blurring and streaking artifacts. In a prospective patient study, we evaluate respiratory motion‐corrected (RMC) CBCT efficacy in reducing motion artifacts and improving localization accuracy and whether a correction model derived from a respiration‐correlated CT (RCCT) at simulation is still valid at treatment. Methods: In an IRB‐approved study, lung cancer patients receive an RCCT at simulation, and on one treatment day receive an RCCT, respiratory‐gated CBCT, and a one‐minute CBCT. A respiration monitor of abdominal displacement is used during all imaging. One‐minute CBCT projections are sorted into 10 bins based on abdominal displacement and reconstructed. Each binned CBCT is deformed to the end expiration state using a model derived from RCCT and added to produce an RMC‐CBCT. Comparison is made between uncorrected CBCT (NoCorr), RMC(sim) CBCT using simulation RCCT, and RMC(tx) CBCT using treatment RCCT. The gated CBCT, gated at end expiration, serves as the criterion standard for comparison. Each CBCT is registered twice to the gated CBCT, first to align to spine, second to tumor in lung. Localization accuracy is defined as the difference between tumor and spine registration. Agreement in tumor shape with the gated CBCT is evaluated by calculating normalized cross‐correlation (NCC) of pixel intensities within the local tumor region. Results: NCC from RMC(tx) is higher in 12/13 cases compared to NoCorr, and in 7/13 compared to RMC(sim). Tumor position in RMC(tx) is in closer agreement with gated CBCT than for NoCorr in 11/13 cases. Tumor position between RMC(tx) and RMC(sim) agrees within 2mm in all cases. Conclusion: This correction method reduces motion artifacts and improves localization accuracy in nearly all cases. Motion correction based on the simulation day RCCT or on the treatment day RCCT yields similar results. NIH/NCI award R01 CA126993 and research grant from Varian.