bluuebunny/crossref_metadata_2025 huggingface dataset:
TU‐C‐L100J‐05: A Practical Filmless Technique of Determining CT Beam Width
Authors: Rong X , Zamora D , Cody D , Stevens D
Published: July 2007

Purpose: To develop a filmless technique for the measurement of CT beam width for QA. Method and Materials: Images of pre‐patient collimated CT beams were acquired using Fuji computed radiography (CR) cassettes and direct‐exposure film (DF). CR cassettes were exposed using 80kV, 10mAs to avoid signal saturation. The DF was exposed at 80kV, 30mAs to achieve a proper optical density. The DF image was digitized then linearized. To achieve a proper signal range for CR, various plate‐reading protocols were evaluated. An IDL program was developed to automatically handle both the digitized film and a variety of CR image sizes. “Unprocessed” logarithmic CR data were linearized, which is critical to validate the FWHM. The program executes in an interactive fashion, whereby the user selects the beam to analyze. The program determines the background signal for subtraction then samples multiple cross‐beam profiles to form an averaged profile. The profile is smoothed and the FWHM is determined. Results: Under proper conditions of image acquisition, results show both DF and CR are appropriate techniques for beam width measurements. The CR technique demonstrated a high level of reproducibility with a coefficient of variation below 0.5%. Also, the CR results were within 0.3mm of specifications. Using various sizes of CR cassettes had a minimal effect on the results. However, if the properly exposed image is saturated due to an inappropriate CR plate reading protocol, the inaccuracy is substantial (>1mm). The technique worked well for annual tests of six GE scanners. Over a wide range of beam width configurations, all measurements were within 0.9mm of specifications. Conclusion: A technique for determination of CT beam width in a filmless environment was developed and tested. The results obtained using CR yield accurate measurements of CT beam profile width. The technique is effective, practical, and has proven to be robust.
TU‐C‐L100J‐06: Pediatric Organ Dose Measurements in Axial and Helical Multi‐Slice CT
Authors: McDermott A , McNitt‐Gray M , White R , Angel E , Cagnon C , DeMarco J , Cody D
Published: July 2007

Purpose: To determine radiation dose to specific organs in a pediatric phantom from a CT scan, and to determine if there is a significant difference between: axial (step and shoot) and helical acquisitions, when using very similar photon flux values (effective mAs). Method and Materials: An anthropomorphic pediatric phantom (5 year old equivalent) was used to investigate organ dose at the surface and internal to the phantom. The phantom contains four different tissue equivalent materials: soft tissue, bone, brain, and lung, and was imaged on a 64‐channel CT scanner with a head protocol [axial and two helical scans (pitch = 0.516 and 0.984)], and a chest protocol [axial and three helical scans (pitch = 0.516, 0.984, and 1.375)]. Effective mAs was kept constant (within 3%) for head and chest protocols. Dose measurements were acquired using thermoluminescent dosimeter (TLD) powder in capsules placed in the phantom sections in plug holes. The organs of interest for this study were: brain, both eyes, thyroid, sternum, both breasts, and both lungs. Results: All axial organ dose measurements were significantly higher (p<0.05) than all helical organ dose measurements. There was no significant difference (p>0.05) in organ dose values between the pitch values 0.516 and 0.984 for both head and chest scans. The chest organ dose measurements obtained using a pitch of 1.375 were significantly higher (p<0.05) than the other helical pitches used for chest scans (attributed to the automatic selection of the large focal spot). Conclusion: Communications with the vendor indicate that there are likely physical explanations for the difference observed in organ doses due to axial versus helical acquisitions. It is unclear if this difference in organ dose is unique to this scanner design, because dose measurements are not typically performed in helical scan mode and have not been investigated using other scanner models.
TU‐C‐L100J‐09: CT Doses: Changes in the Last Twenty‐Five Years
Authors: Frey G , Huda W , Groat G
Published: July 2007

Purpose. To quantify how CT patient doses, and the corresponding scan times, have changed over the last 25 years. Method. We analyzed data for five generations of CT scanners from one vendor (GE), ranging from the 9800 single slice scanner without slip ring technology used in the early 1980s to a 64 slice VCT, the current state of the art. We determined values of CTDIair and CTDIw at a constant kV/mAs. Effective doses were performed for a standard 32 cm chest CT examination performed at 120 kV using contiguous axial scanning on the 9800, and a pitch of 1 on the VCT. Scan times were computed assuming (contiguous) axial images with a 5 mm thickness.

Results. CTDIair of a VCT scanner (30 mGy/100 mAs) is 12% higher than that of a 9800 scanner, whereas the corresponding body VCT CTDIw (9.5 mGy/100 mAs) is 53% higher. The increased doses on modern scanners are a result of reduced focus‐isocenter distances to accommodate faster rotation speeds, changes in beam shaping filters, and overbeaming used on MSCT scanners. Patient effective doses for a routine chest CT examination are 5 mSv/100 mAs on a VCT and 3.2 mSv/100 mAs on a 9800. Acquisition of 64 axial images for a routine chest CT in the early 1980's took ∼5 minutes, whereas modern scanners cover the same volume in only 8 x‐ray tube rotations taking ∼3 seconds.

Conclusion. Over the last 25 years, normalized CT patient doses (i.e., per unit mAs) have increased by ∼50%, whereas image acquisition times have been reduced by two orders of magnitude.
TU‐C‐M100J‐04: Determination of Prospective Displacement Gate Threshold for Respiratory‐Gated Radiation Delivery From Retrospective Phase‐Based Gate Threshold Selected at 4D CT Simulation
Authors: Archambault L , Vedam S , Starkschall G , Mohan R , Beddar S
Published: July 2007

Purpose: 4D‐CT imaging is based on retrospective respiratory phase sorting of an external motion monitor. Subsets of 4D‐CT images, encompassing a few respiratory phases are increasingly being used in respiratory‐gated radiotherapy to reduce internal tumor displacement. Such subset selection is equivalent to selection of a retrospective phase‐based gate threshold on the external motion monitor. Respiratory‐gated radiation delivery, however, is based on a prospective respiratory displacement threshold. We aim to establish a relationship between the retrospective phase‐based gate threshold selected at simulation and prospective displacement‐based gate threshold that should be applied during treatment delivery. Method and Materials: Over 150 external respiratory motion traces, from 90 patients, with and without audio‐visual biofeedback were analyzed. Respiratory gating phase interval was chosen from the 4D‐CT‐derived tumor motion trajectory. Retrospective displacement gate threshold for the selected phase interval was defined as the average respiratory displacement within the phase interval. By including displacement values that were both within the selected phase interval and retrospective displacement gate threshold, a prospective displacement gate duty cycle was obtained. The external respiratory displacement value that yielded the prospective displacement gate duty cycle was the prospective displacement gate threshold for gated radiation delivery. Results: Phantom motion tests yielded coincidence of retrospective and prospective gate thresholds within 0.3%. Patient data analysis indicated that the average difference between prospective and retrospective gate thresholds was 8±15% and 4±7% of the total respiratory motion range for smaller and larger phase intervals respectively. With audio‐visual biofeedback, corresponding differences were 10±14% and 9±10% respectively. Conclusion: A relationship between retrospective phase‐based gate threshold at simulation and prospective displacement gate threshold at radiation delivery was established and validated for regular and non‐regular respiratory motion. Using this relationship, the prospective external displacement gate threshold to be applied at radiation delivery can be reliably estimated from 4D‐CT simulation.
TU‐C‐M100J‐06: Accurate Prediction of Intra‐Fraction Motion Using a Modified Linear Adaptive Filter
Authors: Srivastava V , Keall P , Sawant A , Suh Y
Published: July 2007

Purpose: To predict tumor position in order to compensate for temporal latency of a target tracking‐based dynamic radiation dose delivery system. Method and Materials: A linear adaptive filter was trained for real‐time prediction of tumor target position. Signal history was first filtered by a low‐pass filter (LPF). Template matching was used in order to select training examples that were closest to the current case, using the distance metric:
urn:x-wiley:00942405:media:mp1337:mp1337-math-0001 where,
urn:x-wiley:00942405:media:mp1337:mp1337-math-0002 This algorithm was applied to 160 3D tumor motion datasets acquired from 46 patients. Algorithm parameters were selected through a comprehensive sensitivity analysis performed on 10% of the datasets that exhibited maximum peak‐to‐peak motion. The resulting parameters were used to analyze algorithm performance over the remaining 90% of the datasets. Root mean square (RMS), maximum, mean and standard deviation of errors with and without prediction were calculated. The error distribution was tested against a Gaussian distribution using the Kolmogorov‐Smirnov (KS) test. Results: Sensitivity analyses showed that a third‐order Butterworth LPF having cutoff frequency of 2 Hz was the most suitable. Examination of error indicates that it has close‐to‐zero mean for all the three dimensions and standard deviation is of the order of 0.1 mm. Moreover, the D‐statistics of KS test are close to 0.1 (indicating a distribution that closely approaches a Gaussian) except for cases where tumor motion itself is very small (less than 5 mm). Compared to no prediction, the algorithm reduced RMS and maximum errors, on average, by 74.58% and 55.39% respectively. Conclusion: We have developed a robust and highly efficient algorithm for predicting respiratory tumor motion. Future work includes integration of the algorithm with the laboratory setup of a dynamic MLC‐based target tracking system.
TU‐C‐M100J‐07: A Systematic Study On the Sources of Drift in a Turbine‐Based Spirometer Using a Breathing Simulator
Authors: Ha J , Perlow D , Yu C
Published: July 2007

Purpose: To systemically isolate and quantify the contributions of different sources of signal drift in turbine‐based spirometry. Method and Materials: To get a repeatable response from the VMM‐400 spirometer, we used a breathing simulator made of an airtight cylinder. The cylinder's piston was driven by a motor to force the air in/out of the cylinder to the spirometer. A heating blanket was used to heat the cylinder, so that the in/out air would have different temperature. The piston position, thereby the cylinder air volume, was determined using a position sensor. Results: Our data show that even when the piston was driven sinusoidally and the heating blanket was off, the spirometer exhibits a drift per cycle of 3.4% of the maximum tidal air volume due to the differential response of its turbine blade. Reversing the direction of in/out flow simply changes the drift direction. With the heating on, the drift accumulates an additional 4% per cycle. The added drift is due to the expanded air volume from the heating. The most significant drift was observed when the piston was driven in a saw‐tooth pattern, either with a fast inhale followed by a slow exhale or visa versa. The difference in the measured volume between the two breathing phases can be as large as 60% or more due to the failure of the spirometer to register the volume in the low flow‐rate phase and the air needed to be spent on reversing the blade at the end of the fast‐changing phase. Conclusions: The drift due to the blade asymmetry and temperature stays the same per breathing cycle (3.4% and 4%), and can be corrected in real‐time. The drift due to breathing asymmetry can vary between cycles because of patient irregular breathing; the correction would most likely be complex (i.e., nonlinear).
TU‐C‐M100J‐09: Application of a PARMA Algorithm to Predict Intrafraction Respiratory Motion
Authors: McCall K , George R , Keall P , Jeraj R
Published: July 2007

Purpose: Accurate motion tracking can decrease normal tissue dose, PTV margins, and shorten treatment times required for radiation therapy. A Periodic Autoregressive Moving Average (PARMA) model was developed to predict one‐dimensional respiratory motion in human subjects. Methods and Materials: A PARMA prediction algorithm was applied to clinical respiration signals from three categories: free‐breathing, audio instruction, and audio‐visual coaching. The PARMA model of the respiration motion is a dual‐component signal, a partially correlated time‐series superimposed onto a periodic pattern. The periodic component was estimated by averaging over the inhale‐exhale cycles in a 60‐second sample of the respiration signal, and the autocorrelation in the residual signal was modeled by linear autoregressive moving average equations. The PARMA predictions were compared to the system latency errors produced when tumor tracking is done without forward predictions. Results: For audio‐visual coaching, the PARMA prediction errors (1σ) were 0.09 mm, 0.23 mm and 0.99 mm at 0.1 s, 0.2 s and 0.5 s respectively. A prediction error of 0.99 mm is equivalent to 7.2% of the average end‐inhale to end‐exhale motion. By comparison, the errors were 0.60 mm, 1.20, and 2.90 mm when the lagged signal is used as an estimate of current position at 0.1 s, 0.2 s and 0.5 s respectively. For free‐breathing respiration, PARMA predictions were accurate to within 0.10 mm (1σ) at 0.1 seconds, 0.24 mm at 0.2 seconds, and 1.07mm at 0.5 seconds. The system latency errors were also similar to the coached signals. Conclusion: Tumor tracking with dynamic MLC can theoretically achieve system latency times of 0.16 seconds with accuracy of about 1 mm. The prediction errors of the PARMA algorithm was well under one‐third of the calculated system latency error for all lag times investigated.
TU‐C‐M100F‐04: Quantification of Dynamic Contrast Enhancement in Breast Cone‐Beam CT
Authors: Yeung I , Cho Y , Siewerdsen J , Kim S , Lim B , Qian B
Published: July 2007

Purpose: Contrast uptake behavior measured by dynamic contrast enhanced (DCE) MR has been shown to have diagnostic value for breast cancer. This paper is to show the feasibility of DCE breast cone beam CT (CBCT) for quantification of dynamic contrast uptake using a baseline and a single contrast enhanced CBCT. Method and Materials: A novel algorithm is proposed to determine the contrast uptake behavior for breast CBCT with a baseline image followed by a contrast enhanced acquisition synchronized with contrast injection. The method is based on the assumption that the contrast uptake curve in every voxel of the volume has a washin and a washout phase governed by a 3‐parameter equation, and the baseline along with the contrast enhanced projections are used to solve for these 3 parameters in each voxel. A computer simulation was performed based on functional CT data of cervix patients to evaluate the feasibility of the method to estimate different contrast uptake shapes. A phantom study was also done in a breast phantom with flow mechanism to compare the method against clinical CT for a fast washout and a plateau contrast uptake curve. Results: The computer simulation showed excellent accuracy of uptake characteristics for the new method that the DCE‐CBCT algorithm correctly determined the contrast uptake behavior in 14 out of 15 patients. Good agreement was also found in the phantom study in which both uptake curves (rapid washout and plateau) were accurately determined by the DCE‐CBCT method compared to those measured with clinical CT, although the former curves are more dispersed. Conclusions: Preliminary simulation and phantom data suggest the feasibility of the proposed method to determine different contrast uptake behavior in contrast enhanced breast CBCT which might have a potential for diagnosis of breast cancer.
TU‐C‐AUD‐02: Study of Neutron Exposure During Passively Scattered Proton Therapy
Authors: Zheng Y , Newhauser W , Fontenot J , Taddei P , Mohan R
Published: July 2007

Purpose: Stray radiation exposures are of concern for patients receiving proton radiotherapy and vary strongly with several treatment factors such as proton energy, field size and modulation width. The purposes of this study were to conservatively estimate neutron exposures for a contemporary passive scattering proton treatment unit and to understand how they vary with treatment factors. Method and Materials: We simulated all 24 options (each range modulator and second scatterer combination is accounted for one option) for a passive scattering proton therapy unit with MCNPX. Spectral neutron fluence from simulations was then converted to neutron dose equivalent using corresponding dose conversion factors. We studied the neutron dose equivalent per therapeutic absorbed dose (H/D) as a function of treatment factors including proton energy, location in the treatment room, treatment field size, and spread‐out Bragg peak (SOBP) width using Monte Carlo simulation. Results: The H/D value at isocenter for a 250‐MeV medium field size option was estimated to be 20 mSv Gy−1. H/D decreased to about 20% from 250 Mev to 160 MeV. H/D fell off sharply with distance from the treatment unit, approximately following a power law; H/D was about 10% higher for a large field option than a medium field option for the same energy. H//D almost doubled when SOBP width was increased from a pristine peak to 16 cm. An analytical model was developed, which predicted H/D values within 28% of those obtained in simulations; this value is within typical neutron measurement uncertainties. Conclusion: The results quantified how treatment factors influence H/D values. The in‐air method with a closed aperture presented here provides a simple and straightforward approach that could be adopted for facility inter‐comparisons. In addition, an analytical model was developed to quickly estimate H/D values.
TU‐C‐AUD‐03: Comparing the Expected Effectiveness of Helical Tomotherapy and MLC‐Based IMRT Using Biological Measures
Authors: Mavroidis P , Ferreira B , Shi C , Lind B , Stathakis S , Papanikolaou N
Published: July 2007

Purpose: Presently, the radiobiological parameters of the different tumours and normal tissues are typically not taken into account during dose prescription and optimization of a treatment plan. In this study, to investigate a more comprehensive treatment plan evaluation, the biologically effective uniform dose (D̿) is applied together with the complication‐free tumour control probability (P+).

Material and Methods: Three different cancer types at different anatomical sites were investigated: head & neck, lung and prostate cancers. For each cancer type, a linac MLC‐based step‐and‐shoot IMRT plan and a Helical Tomotherapy plan were developed. By using D̿ as the common prescription point of the treatment plans and plotting the tissue response probabilities vs. D̿ for a range of prescription doses, a number of plan trials can be compared based on radiobiological measures. Results: The applied plan evaluation method shows that in the head & neck cancer case the HT treatment gives better results than the MLC‐based IMRT (P+ of 62.2% and 46.0%, D̿ to the internal target volume (ITV) of 72.3Gy and 70.7Gy, respectively). In the lung cancer and prostate cancer cases, the MLC‐based IMRT plans are better. For the lung cancer case, the HT and MLC‐based IMRT plans give a P+ of 66.9% and 72.9%, D̿ to the ITV of 64.0Gy and 66.9Gy, respectively. Similarly, for the prostate cancer case, the two radiation modalities give a P+ of 68.7% and 72.2%, D̿ to the ITV of 86.0Gy and 85.9Gy, respectively.

Discussion and Conclusions: Both MLC based‐IMRT and HT can encompass the often large ITV required while they minimize the volume of the organs at risk receiving high dose. There may exist clinical cases, which may look dosimetrically similar but in radiobiological terms may be quite different. In such situations, traditional dose based evaluation tools can be complemented by the use of P+ − D̿ diagrams to compare treatment plans.
TU‐C‐AUD‐04: Laser‐Proton Acceleration for Radiation Therapy
Authors: Ma C , Velchev I , Lin T , Fourkal E , Li J , Fan J , Orimo S , Ogura K
Published: July 2007

Purpose: Rapid developments in laser technology have facilitated proton (light ion) acceleration using laser‐induced plasmas. In this work, we investigate an experimental system for laser‐accelerated proton therapy. Method and Materials: Our system consists of a commercial 150 TW laser, custom‐made laser‐pulse compression and target chambers, particle selection and beam collimating devices, dosimetry monitoring systems and shielding constructions. We have performed initial laser‐proton acceleration experiments with thin aluminum foils as target materials. The maximum proton energy was measured using CR‐39 film and a Thomson parabola ion analyzer. We have performed particle‐in‐cell simulations to investigate the optimal laser parameters and target configurations to facilitate laser‐proton acceleration and dosimetric studies. Results: The primary particles resulting from the laser‐target interaction are protons and electrons. Our particle in cell simulation predicted protons of up to 300 MeV and electrons of 20 MeV for a laser intensity of 1021 W/cm2. The maximum number was 1011 and 1012 per pulse for protons and electron, respectively. Our initial testing with a 1018 W/cm2 laser intensity (at 10 TW) produced up to 1 MeV protons with a broad energy spectrum. Conclusion: We have developed an experimental laser‐proton accelerator for radiation therapy applications. Initial experimental studies have demonstrated proton acceleration at low laser power levels. Further studies with laser intensities up to 2 × 1020 W/cm2 are being conducted with different target materials and configurations.
TU‐C‐AUD‐06: Calculation of the Dose Distribution Around a Commercially Available 125I Brachytherapy Source Via a Multi‐Group Discrete Ordinates Method
Authors: Gifford K , Kirsner S , Horton J , Wareing T , Mourtada F
Published: July 2007

Purpose: To calculate the dose distribution around a commercially available source by a multi‐group discrete ordinates code and compare with a Monte Carlo calculated dose distribution. Methods and Materials: The multi‐group discrete ordinates code, Attila™ version 6.1.1 (Transpire Inc., Gig Harbor, WA) was used to calculate the dose distribution around the IsoAid IAI‐125 (IsoAid LLC., 7824 Clark Moody Blvd, Port Richey, Florida 34668). MCNPX 2.4.k was used to benchmark the deterministic calculations. The source was constructed with Solidworks (Solidworks Corp., Concord, MA), a mechanical design software. The constructed geometry of the source, dose scoring plane and sphere were exported in Parasolid® file format so that it could be imported into Attila. MCNPX 2.4.k was used to compute the Monte Carlo dose distribution. 295 million histories were simulated resulting in standard errors of the mean of approximately 3% at a point 5 cm from the source. The source geometry was identical to that of the Attila run. Dose rate matrices were exported from both codes and imported into an in‐house data analysis software. Results: The qualitative agreement between Attila and MCNPX is excellent. The Attila calculations required approximately 13 minutes of CPU versus 1701minutes for MCNPX. Conclusions: The Attila code accurately captured the anisotropy from the IsoAid IAI‐125 source. Attila can calculated dose in an efficient manner for low energy photon sources.
TU‐C‐AUD‐07: Analysis On the Use of Megavoltage Cone‐Beam Computed‐Tomography Images for Dose Calculation
Authors: Johnson M , Reitz B , Gayou O , Parda D , Miften M
Published: July 2007

Purpose: To establish a relationship between Hounsfield Unit (HU) from a megavoltage cone‐beam CT (MV‐CBCT) system and relative electron density, and to assess the error in the dose calculation introduced by CB image artifacts. Method and Materials: A CT calibration phantom was imaged using different MV‐CBCT dose and image filtering protocols. A conversion function from HU to relative electron density relationship for MV‐CBCT was developed. The mean pixel value and standard deviation of tissue inserts with known electron densities were analyzed, with the inserts located centrally and peripherally in the phantom. Moreover, to assess the magnitude of error introduced by CB imaging artifacts on the electron densities, the data acquired from placing three tissue inserts in 17 locations throughout the phantom were analyzed using this conversion function. In addition, by simulating tissue inhomogeneities with known and calculated electron densities based on CB, the effects on dose calculations were quantified. Results: The calculated relative electron densities for the central and peripheral phantom locations were different by 13.1% for trabecular bone, 17.3% for water and 45.7% for lung (exhale). Differences in HU throughout the entire phantom corresponded to a relative electron density interpretation error of up to 17.4% for trabecular bone, 23.3% for water and 71.9% for lung (exhale) were observed. Comparing the dose calculated with known relative electron density, a maximum error of 5.1% for a 6 MV beam traversing a 5.0 cm thick section of lung (exhale) was seen. Variations in measured HU due to different patient dose imaging protocols were insignificant. Conclusion: The HU to relative electron density conversion varies within the reconstructed volume of the MV‐CBCT image. Improved image filtration is needed to reduce errors in calculated relative electron densities and therefore provide more accurate dose calculations specifically for large anatomical volumes.
TU‐C‐L100E‐01: Funding and Protecting Biomedical Research
Authors: Hendee W , Deye J , Farahani K
Published: July 2007

Biomedical research is supported principally by two sources: the National Institutes of Health (NIH) and industry. For research in medical physics, the National Cancer Institute (NCI) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB) are the two principal supporting agencies within the NIH. These agencies have a number of funding programs that are designed for specific purposes. Applications for support from them are prepared according to specific guidelines and must match the intent of a specific program. Writing a winning application is an art as well as a science, and counsel from experienced grantees is invaluable during the preparation of an application. It is also important to understand the review process that ensues after an application is submitted, and the criteria by which a final decision about funding of the application is reached.

The second source of support, industry, is much less structured and usually requires a personal relationship between the investigator and the company providing the research funding. Negotiating a research agreement between the investigator, the investigator's institution, and the company can be challenging, because it involves issues such as the publication of research results, ownership of intellectual property, and indemnification of each party against wrongdoing by the other. At times these negotiations break down because the parties cannot agree on the issues, often because one party (frequently the institution) assumes an unreasonable position. Successful negotiating an industry research agreement requires diplomacy and sensitivity as well as objectivity and focus.

In all research grants and agreements, the protection of intellectual property (IP) is of overriding importance, especially now that institutions are viewed increasingly as engines for economic development through technology licenses and the formation of start‐up companies. IP protection is less arcane than it may seem, but it does require dedicated time and effort by the investigator and a willingness to work with attorneys and the institution's technology transfer office.
TU‐D‐L100J‐01: Partial Volume Correction of Lung Nodules Using PET/CT
Authors: Bradley W , Wendt R , Pan T , Erasmus J , White R , Mawlawi O
Published: July 2007

Purpose: Partial voluming in PET imaging leads to underestimation in activity concentration. The aim of this abstract is to correct for partial volume artifacts in PET/CT scans. Method and Materials: A Jaszczak phantom with hollow spheres of varying sizes (4.95 – 31.27 mm inner diameter (ID)) was filled with F‐18 water using 3 different sphere‐to‐background ratios (SBR), ranging from 3:1 to 10:1. For each SBR, several acquisitions were conducted. All PET data was reconstructed using OSEM (2 iterations, 21 subsets). Regions were drawn on the CT images to obtain accurate sphere volume and location. A software tool was written to correct for partial voluming by incorporating the sphere size and the non‐stationary response function of the scanner. The original maximum (OM), original average (OA), corrected maximum (CM), and corrected average (CA) activity concentrations (AC) were measured and compared. Results: For all SBRs, spheres larger than 19 mm the measured OM and OA AC were 111 and 77% of the true value, respectively. Following correction, these values changed to 128 (CM) and 102% (CA), respectively. For the smallest sphere size (4.95 mm), the measured OM and OA AC were both 20% of the true value. Following correction, these values changed to 121 (CM) and 104% (CA) of the true value. The CM, however, did vary between 83 and 176% of the true AC. An analytical relationship between the lesion size (obtained from CT) and the amount of correction needed to recover the true AC based on the multiple acquisitions was generated. Conclusions: To determine the true AC of a lesion from a PET/CT scan, the corrected average is more accurate than the original maximum, and should be used for clinical assessment.
TU‐D‐L100F‐01: MR Biomarkers: Current Applications and Unmet Needs
Authors: Jackson E
Published: July 2007

The application of MR imaging biomarkers in pre‐clinical studies as well as Phase I/II clinical trials has greatly expanded over the past few years. Such MR biomarkers include measures obtained from dynamic contrast agent enhanced MRI (DCE‐MRI), dynamic susceptibility change MRI (DSC‐MRI), diffusion MRI, blood oxygen level dependent (BOLD) MRI, and in vivo spectroscopy. The symposium session will introduce each of these techniques and provide representative pre‐clinical and clinical trial results using each technique. In addition, more novel applications, such as MR molecular imaging techniques, will be introduced. Finally, a summary of unmet needs of MR imaging biomarkers, specifically the need for standardization, quality control, and change assessment criteria, will be presented. These needs must be addressed in order to

Educational Objectives:

1. To understand the physical basis, applications, and current limitations of DCE‐MRI, DSC‐MRI, diffusion MRI, BOLD MRI, and MR spectroscopy techniques currently employed to obtain non‐invasive MR biomarkers.

2. To understand the need for standardization, quality control, and change assessment tools/criteria development.
TU‐D‐M100F‐06: Temporal Precision of Gated Step‐And‐Shoot Intensity Modulated Radiation Therapy
Authors: Wiersma RD , Xing L
Published: July 2007

Purpose: The use of gating in the delivery of radiation therapy (RT) has been shown as an effective means of treating tumors susceptible to motion. However, due to electronic and mechanical limitations of the radiation delivery equipment, the precision of gated IMRT is susceptible to equipment process time delays. The purpose of this study is to investigate the temporal accuracies of gated RT using a simple and inexpensive method that doesn't require complex or fast sampling equipment to measure response times. Method and Materials: Using a Varian Trilogy treatment delivery system together with a Varian RPM respiratory gating system, the response times of both normal RT and step‐and‐shoot (SS) IMRT gated deliveries are investigated. Radiation dosage profiles, recorded using radiographic films, are digitalized to allow extraction of temporal data. In addition the same response time technique is used with an electronic portal imagining device (EPIDs). Results: Static to dynamic comparison of specific MLC patterns is used to extract the gating response time. It is found that the time, from when an object enters into the specified phase to when the radiation beam is actually turned on, is approximately 0.15 s. This time error is found to be systematic in nature and is approximately the same for both normal and SS‐IMRT gated deliveries. Conclusion: A general and simple procedure has been developed that will allow the response time of a LINAC based gating systems to be made. The ∼150 ms systematic timing error found to occur in the Trilogy/RPM system can be corrected by modification of the gating software provided if the patients breathing is regular and periodic.
TU‐D‐M100F‐08: Quality Assurance Protocol of the HiArt Tomotherapy MLC: Design and Implementation
Authors: Shi C , Sarkar V , Lin L , Papanikolaou N
Published: July 2007

Purpose: To develop a comprehensive protocol and software tool for the quality assurance of the HiArt Tomotherapy MLC system. Method and Materials: Seven MLC test patterns were designed and an in‐house software called “Tomo MLC QA” was developed to generate the sinogram for the test patterns and analyzed the test results. The seven test patterns are: box in box, modified checkerboard, leakage test, IEC‐X gradient, IEC‐Y gradient, complex field A, and complex field B. Kodak EDR2 ReadyPak films were used for all the measurements with our test patterns. Results: The films from the measurements were analyzed with the “Tomo MLC QA” tool. Pass and Fail criteria were specified for each test according to published QA data. Most tests passed the set criteria, although some failures were detected and corrected. Conclusion: In this study, seven test patterns were designed as part of a QA toolkit for the MLC of a helical tomotherapy unit. A software platform called “Tomo MLC QA” was developed to facilitate the analysis of the seven tomotherapy MLC QA tests. The software can be easily adapted to any treatment center with a helical tomotherapy unit to perform customized tomotherapy MLC QA or to standardize testing. Additional test patterns can be developed based on the “Tomo MLC QA” platform. The seven designed test patterns for tomotherapy MLC QA are not aimed to test all characteristics of the tomotherapy MLC. However, the patterns allow the users to test some of the mechanical and dosimetric properties of the tomotherapy MLC. The analysis results based on the seven test patterns from our institution were reported. All tests passed at the inhouse set criteria, indicating that our unit's MLC is operating according to specifications. The analysis revealed some minor problems regarding beam angle position that require further investigation.
TU‐D‐BRA‐03: Laser‐Accelerated Electrons for Radiation Therapy
Authors: Malka V , Fuchs T , Oelfke U , Szymanowski H , Faure J , Glinec Y , Rechatin C
Published: July 2007

Laser plasma accelerators provide electron beams with parameters of interest in many fields and in particular for radiotherapy. A short review of progress achieved recently including bubble [1] and colliding [2] schemes will be presented. Using the last improvements of laser‐plasma accelerators, we performed dose deposition simulations using a quasi‐monoenergetic electron beam in the 200 MeV range [3]. It is shown that electron beam properties offer advantageous dosimetric characteristics compare to those calculated with high energy photons. The depth dose curve shows a broad maximum at large depths (> 20 cm). The lateral penumbra of treatment fields for focused electron beams is smaller compared to 6 MeV photons at depths smaller than 10 cm. These advantages result in an improvement of the quality of a clinically approved prostate treatment plan. While the target coverage is the same or even slightly better for 250 MeV electrons compared to photons the dose sparing of sensitive structures is improved. E.g. the dose to the rectum is reduced by 19% for 250 MeV, focused electrons. These findings agree with previous results regarding very high energy electrons as a treatment modality [4, 5, 6].

The lack of compact and cost‐efficient electron accelerators could be overcome by laser‐plasma systems.

Educational Objectives:

1. Understand the origin electron injection in plasma.

2. Understand the acceleration process and to motivate this approach which uses extremely high electric field.

3. Understand the issues related to clinical application for radiotherapy.
TU‐EE‐A3‐01: Evaluating the Impact of Probe Depression On Prostate Displacement in Ultrasound‐Guided Prostate IMRT Treatment
Authors: Ding C , Li X , Yang Y , Heron D , Huq M
Published: July 2007

Purpose: The prostate displacement under the mechanical pressure of abdominal ultrasound probe may compromise the accuracy of ultrasound‐guided prostate IMRT treatment. The purpose of this study is to investigate the impact of ultrasound probe depression on the prostate displacement by finite element method (FEM). Method and Materials: An ultrasound system (Restitu™, Resonant Medical System, Montreal, Canada) integrated with a CT‐Sim was used to acquire a full set of 3‐D ultrasound (US)‐CT images for a typical prostate cancer patient. The patient's structures, such as body, bone, bladder, and prostate, were contoured on the CT images. These structures were utilized to generate a 3D finite element model. The mechanical properties of the patient's tissues and ultrasound probe, including elastic module (E) and Poisson's ratio (v), were set as: body (E=55kPa, v=0.45), bone (E=10GPa, v=0.45), bladder (E=10kPa, v=0.45), prostate (E=100kPa, v=0.45), and probe (E=3GPa, v=0.35), respectively. The corresponding displacement of prostate centroid during ultrasound localization was calculated by a FEM software (Ansys). Results: When the depression of ultrasound probe increased from 10mm to 50mm with an increment of 10mm on the patient's abdomen at an angle of 45 degree to horizontal plane, the displacement of prostate centroid was increased from 0.5mm to 4.9mm in the inferior direction and 0.4mm to 3.6mm in the posterior direction. There was no significant left‐right displacement of the prostate. The 3D vector displacement of prostate centroid is increased from 0.6mm to 6.1mm based on FEM calculation. Conclusion: The displacement of prostate was non‐negligible when the depression of ultrasound probe was more than 20mm on the patient's abdomen. This displacement should be considered in the 3‐D US—CT image‐registration and US‐guided radiation therapy.
TU‐EE‐A1‐04: Dimension Reduction Analysis of Dose Volume Histogram And Its Potential Application In Predicting Normal Tissue Complication Probability
Authors: Zhou S , Das S , Chen S , Zhang J , Marks L
Published: July 2007

Purpose: Radiation pneumonitis (RP) is a major concern for patients receiving radiotherapy for lung cancer. The present study assesses the possibility of using multiple dose‐volume‐histogram (DVH) based metrics to predict the likelihood of grade ⩾ 2 RP. MATERIALS AND METHODS: The lung DVH and clinical outcome data from 235 patients were studied. Two linear and four nonlinear statistical dimension reduction analysis methods were applied to the lung DVH to map the data from the original feature space into a 2D or 3D manifold. Then, the question of whether the lung DVH could uniquely predict the likelihood of grade ⩾ 2 RP was mapped to the feasibility of separating the populations with and without RP in the 2D/3D manifold. Results: None of the statistical dimension reduction techniques which preserve the local geometric properties of the original DVH curves was able to clearly separate the patients with and without grade ⩾ 2 RP in the 2D/3D manifold. Among the techniques tested, the Local Tangent Space Alignment (LTSA) performed the best. It could almost reduce the original DVH data into a one dimension manifold. Unfortunately the order the LTSA assigned to the lung DVH curves did show clear correlation with patient RP grades. Conclusions: The dimension reduction analysis like LTSA which preserve the distance information between DVH curves can be useful in characterizing the complexity of patient DVH data from a lung toxicity study. The lack of clear segmentation between the grade ⩾ 2 RP patients and other patients in the dimension‐reduced manifold indicates that using lung DVH data only can not generate a satisfactory result in predicting the occurrence of grade ⩾ 2 RP among the lung cancer patients after 3D‐CRT radiotherapy treatment.

This work was partially funded by NIH grants R01 CA69579 and R01 CA115748.
TU‐EE‐A2‐01: Comparison of HDR Brachytherapy Optimization Using Physical Dose and Biological Response Models
Authors: Amadon S , Hu Z , Turian J , Zusag T , Chu J
Published: July 2007

Purpose: Comparison of optimized HDR treatment plans using biological and physical objective functions. Methods and Materials: For a gynecological cancer case, treatment plans were generated using physical and biological optimization models. Optimization was done using adaptive simulated annealing. The target and critical structure volumes were determined from CT images. Target volumes were planned to receive 80Gy using a uniform external beam dose of 0 or 45Gy. The physical model objective function uses a least square fitting. The biological model objective function uses EUD to maximize the target and minimize critical structures dose. Plan evaluation is done by comparing the isodose distribution and calculating tumor control probability (TCP), normal tissue complication probability (NTCP), equivalent uniform dose (EUD), coverage index (CI), homogeneity index (HI), and overdose index (OI). Results: The physical model produced excellent dose uniformity and target coverage. The biological model was able to increase EUD to the target, lower EUD to the rectum and sigmoid, but increased EUD to the bladder. When external beam dose is added, the differences in EUD were in the same direction, but smaller. The biological plan was less uniform (lower HI and higher OI) with the same CI as the physical model, but when an external beam was added, CI was the same, HI became smaller, and OI was larger compared to the physical model. TCP was larger for the biological model. NTCP are zero for plans without external beam dose. When external beam dose was added, TCP and NTCP increased for both plans. TCP became higher for the physical model and NTCP followed the same trend as the EUD calculations. Conclusion: The biological model is able to spare dose to critical structures, but has less homogeneity and greater overdose than the physical model. When an external beam dose is included, plans look almost identical.
WE‐C‐L100J‐08: Charge Trapping in a Prototype Active Matrix Flat Panel Dosimeter and Its Implications
Authors: Chen Y , Moran J , Roberts D , El‐Mohri Y , Antonuk L , Fraass B
Published: July 2007

Purpose: This work models charge trapping behavior of a prototype Active Matrix Flat Panel Dosimeter (AMFPD) using three parameters and explains a number of published observations. An understanding of charge trapping and release is necessary to estimate non‐linearities in the AMFPD response due to trapping and to correct artifacts in the resulting dose image. Method and Materials: The AMFPD consisted of an amorphous silicon flat panel imaging array operated without a phosphor screen. Fluoroscopic and radiographic modes were used to obtain a series of fixed field dosimetric measurements at different doses and dose rates. Data were acquired in order to test the assumptions upon which the model was based:

(1) Trapped charge density in the metastable defects can be described by a stretched exponential function, .

(2) Trapped charge starts to release from the trapping centers when the photodiode is recharged.

(3) Charge release is not affected by subsequent irradiations when the dose per frame is small.

(4) The charge trapping rate depends on bias voltage and varies slowly with dose when the dose is small.

Model stretch parameter β, time constant τ, and the charge trapping rate p were determined from a fit to the pixel signal decay following irradiation. These parameters were then applied to simulate results for the AMFPD operated in fluoroscopic mode based on the above assumptions. Results: The simulated results agreed well with the measurements. It was determined that β is constant for a detector array, τ depends on bias voltage, and the charge trapping rate depends on bias voltage and dose. Furthermore, the model qualitatively explains observations reported in published papers on charge trapping. Conclusion: A three parameter model was found to successfully describe the behavior of charge trapping and release at different values of bias voltage, frame rate, dose rate and dose.
WE‐C‐AUD‐10: A Comparison of DPM and VMC++ Mont Carlo Codes Applied to Heterogeneous Media
Authors: Cui J , Davidson S , Lindsay P , Followill D , El Naqa I , Deasy J
Published: July 2007

Purpose: Monte Carlo (MC) techniques are physically sound to provide accurate dose distributions. However, they take a large amount of CPU time compared to EGS4. Several fast MC algorithms have been developed, including VMC++ (Voxel Monte Carlo) and DPM (Dose Planning Method). For these fast MC codes, the simplifications of the underlying physics, variance reduction, and random number generation may not be equivalent. Moreover, implementation issues are complex and therefore testing and quality assurance is important. We compared these two codes as applied to heterogeneous media a quality assurance check. Methods and Materials: In this research, we conducted calculations for both codes on a standard open field water phantom, a water phantom with an air cavity, and a 5‐beam conformal therapy plan computed based on a CT‐scan of a heterogeneous anthropomorphic thorax phantom. The results were either compared with BEAM results, the Treatment Planning System (TPS; Pinnacle 7.6c), film or TLD measurements. The MC codes were integrated with CERR to facilitate CT‐based calculations. Results: In the water phantom, for 6MV 5×5cm2 field size at 100cm SSD, DPM and VMC++ agreed within 1%, except in the penumbra region. For 0.5×0.5cm2 field size of the air cavity test, they differed at the interface of air and water. For the 5‐beam 3D conformal plan on a thorax phantom, they agreed within 1% RMS ([STD of the difference larger than 5%Dmax]/Dmax); Most regions had a difference much less than 3% except at the buildup region for the two beams. Conclusions Carefully designed tests were conducted comparing DPM and VMC++. Water phantom results were almost identical. The air‐cavity‐heterogeneity results gave agreement within 1% except for the water‐air‐cavity interface. DPM appeared to be somewhat more sensitive to local material changes in the thorax phantom results.