bluuebunny/crossref_metadata_2025_split huggingface dataset:
MO‐E‐BRA‐03: Application of Robust Optimization in Lung Cancer Treatment
Authors: Chan TCY , Trofimov A , Vrancic C , Tsitsiklis JN , Bortfeld T 
Published: July 2007

For lung tumors, the presence of motion due to breathing is a key source of uncertainty. Motion essentially blurs the static dose distribution, which can be thought of mathematically as a convolution of the static dose distribution with a probability density function (PDF) describing the motion. The 4D IMRT optimization/inverse planning method tries to undo this blurring effect by taking the motion PDF into account during the optimization of the intensity map. Such an approach is effective as a motion compensation technique, but only when the motion is highly reproducible over the entire treatment course. In terms of the PDF, “reproducibility” corresponds to witnessing the same PDF over the course of treatment that was observed in the treatment planning stage. However, if the realized PDF during treatment differs from the planning PDF, the subsequent convolution of the static dose distribution with the realized PDF may produce undesirable hot and cold spots.Robust optimization is a concept that has gained prominence in the optimization community for its wide applicability to problems with uncertain data. Real‐world problems are rarely, if ever, accompanied by noiseless data, hence, there is a natural motivation to incorporate this uncertainty into any optimization process. The robust framework we present builds on the 4D approach by explicitly accounting for the uncertain motion represented by uncertainty in the motion PDF. Instead of basing the optimization on one PDF, robust optimization uses a family of PDFs to create a static dose distribution that is less sensitive to variations in the motion.The robust framework allows us to craft solutions in the entire spectrum between the idealized 4D method, and a conservative, ITV‐like margin approach. A given intensity map that results from the robust optimization method will balance intensity‐modulation with intensity‐homogeneity in order to effectively trade off the sparing of healthy tissues with ensuring sufficient tumor coverage. Accordingly, the robust optimization method implicitly performs multi‐objective optimization on these competing objectives.Educational Objectives:1. Understand the concept of robust optimization.2. Understand the construction of robust treatment plans based on breathing motion PDFs.3. Understand the mathematical and dosimetric differences between treatment plans of varying levels of robustness.4. Understand the multi‐objective viewpoint of robust optimization.
TU‐D‐AUD‐04: Comparison of Three Different Source Models for Head Scatter Facto Calculation
Authors: Yan G , Liu C , Li J 
Published: July 2007

Purpose: to evaluate three different source models for the calculation of head scatter factors. Method and Materials: The three different source models evaluated in this work are (1) The three‐source model (Yang et al) (2) The Gaussian analytic model (Jiang et al) (3) The numerical source model (Chui et al). These source models were developed based on different LINAC models. These source models were implemented and their results reproduced. Each of the source models was then applied to the other's measurement in order to cross‐validate accuracy. The effect of the monitor backscattering on the source model was also investigated. Finally, measurement data from a Varian Trilogy machine was used to evaluate each of the source models. The behavior of each model for different SSD data was also evaluated. Results: Measured output factors exhibit ∼1% difference at largest field sizes. The Gaussian analytic model gives 0.2% accuracy when fitting Yang's data, while the three‐source model has problem at large fields with error >15% when attempted on Jiang's data. So was the numerical model. Inclusion of the monitor backscattering effect into the source models significantly improved the agreement. When applying the models to the Trilogy measurement, the Gaussian analytic model gives the best agreement (<0.3%) while the three‐source model has trouble in asymmetric and large symmetric fields again. The numerical source model didn't fit those fields either. While the other two source models gave consistent results for data measured at different SSD, the numerical source model gave large errors (>0.5%). Conclusion: The Gaussian analytic model gave excellent fit to head scatter factor for a variety of LINAC models. Reasonable accuracy can be achieved if monitor backscatter effect were built into the other two source models.Research sponsored by Sun Nuclear Corp.
TU‐EE‐A4‐04: A New Antiscatter Grid for High‐Resolution Region‐Of‐Interest (ROI) X‐Ray Imaging
Authors: Yadava G , Rudin S , Kuhls A , Bednarek D 
Published: July 2007

Purpose: A new custom‐designed antiscatter grid for high‐resolution angiographic detectors is presented that would improve the image quality without introducing substantial grid‐line artifacts. Method and Materials: The new antiscatter grid is a custom‐made, parallel‐focus, crisscross cellular grid that employs gold septa material (CREATV MicroTech, Potomac, MD). The prototype 4.25 cm × 4.25 cm field‐of‐view grid has 20 μm thick septa with interspace distance of 380 μm, height 1.95 mm, and grid‐ratio of 5. This study was performed with the Microangiographic detector (43 μm pixel, 1024×1024 pixel matrix, 4.5 cm × 4.5 cm field‐of‐view, 250‐μm‐thick structured CsI(Tl) scintillator coupled to a CCD camera via minifying taper) in simulated neurovascular angiographic conditions, where a uniform head‐equivalent phantom was used as scattering media. The air‐gap between the phantom and the detector‐with‐grid was kept at 2.5 cm as used in clinical conditions for minimal blurring, but increased scatter. The standard lead‐beam‐stop technique was employed to determine the scatter‐fraction with and without the grid. In order to evaluate the low‐contrast imaging performance of the grid, phantoms with three different bone patterns of varying thickness and three different simulated iodinated vessel inserts in acrylic were imaged with and without‐grid at 70 kVp.Results: The grid demonstrated approximately 59% scatter reduction at 70 kVp for the uniform head‐equivalent phantom without introducing substantial grid‐line artifacts following flat‐field correction. The average contrast‐improvement‐factor for the low‐contrast vessel‐phantom was found to be 1.75, whereas for the relatively higher contrast bone‐phantom it was 1.5. The primary transmission factor was measured to be 66%. Conclusion: The grid demonstrated significant scatter reduction when used in simulated neurovascular angiographic conditions even for the small FOV. Use of this grid with the Micro‐angiographic detector with reduced air‐gap can provide substantially improved image quality.(Partial support: NIH R01‐NS43924, R01‐EB002873, Toshiba Medical System Corp.)
WE‐B‐BRB‐02: Patient Motion: Adaptive RT
Authors: Bortfeld T , Trofimov A , Unkelbach J , Chan TCY , Martin B 
Published: July 2007

Organ motion blurs dose distributions. The blurring can be described in a statistical way by use of a motion probability (density) function (PDF). The motion‐blurred dose distribution is obtained by a convolution of the “sharp” (static case) dose distribution with the motion PDF. This holds true for both inter‐ and intra‐fraction motions. If intra‐fraction motion is present during an IMRT treatment, the dose distribution will also be affected by an “interplay” effect, in addition to the blurring. It has been shown that the interplay effect averages out during the course of a fractionated treatment, and that it is usually negligible after a typical number of fractions. The convolution model relies on the linear superimposition principle, which holds true for dose values but not for the biological effect. This issue has recently been addressed and will be discussed.Several investigations have now looked at the feasibility of un‐doing the motion blur through the use if intensity‐modulation. In principle it should indeed be possible to de‐convolve the motion PDF from the intensity maps, to compensate for motion effects. This approach has been called 4D optimization or 4D inverse planning. Motion de‐convolution cannot, however, compensate motion effects exactly and it cannot be applied in a naïve straight‐forward way, because that would lead to undeliverable intensity maps with sharp spikes and negative values. The method of choice is rather to include the motion PDF in the IMRT optimization process. It has been shown that this can indeed yield a surprisingly high degree of motion compensation and it can even compete with other motion compensation methods such as gated delivery. However, this is only true if the motion characteristics (the PDF) are known with great precision. If the actually realized motion PDF deviates substantially from the planned PDF, the method becomes less useful and can, in principle, make things worse.More recently, uncertainties in the knowledge of the motion characteristics have been taken into account by use of robust optimization techniques. With these one can now compensate for motion effects in an approximate way for a large class of motion characteristics. In terms of the sparing of normal structures, the results are in between the use of conventional margins and the idealistic case of perfect motion compensation. The resulting intensity maps exhibit “horns”, which can shave off a few mm from the margins.Educational Objectives:1. Understand the concepts of motion blur and PDF.2. Understand the idea of de‐blurring a dose distribution through “4D” motion optimization.3. Be able to discuss the relative potential and limitations of 4D motion optimization in comparison with margins and gating.
WE‐C‐L100J‐03: The New Solid State X‐Ray Image Intensifier (SSXII): A Demonstration of Operation Over a Range of Angiographic and Fluoroscopic Exposure Levels
Authors: Kuhls A , Yadava G , Bednarek D , Rudin S 
Published: July 2007

Purpose: To demonstrate the SSXII's capability to image at high angiographic to low fluoroscopic exposure levels using the built‐in adjustable gain. Method and Materials: The prototype SSXII is composed of a 1k×1k, 8μm pixel EMCCD camera system coupled to a 350 μm thick CsI(Tl) structured phosphor via a 1:1 fiber‐optic taper (FOT) and is designed for easy interchange of these front‐end components for task‐based optimization. Variable signal amplification (in solid state) from 1x to 2000x effectively eliminates image degradation due to read‐out noise over all input x‐ray intensities. Images were acquired of a stent crimped on a 1 mm diameter balloon‐tip catheter, for various x‐ray spectra, using both radiographic and fluoroscopic exposures ranging from 6 mR to 145 μR and 80 to 2.7 μR, respectively. The EMCCD gain was adjusted in order to maintain a constant output signal of ∼90% of maximum over these exposures (∼3700 digital units). Results: A series of images, obtained by halving the exposure while doubling the gain, offers a near textbook demonstration of the effect of incident SNR on the resulting image quality. Fine structures of a crimped stent are visible for the entire range of radiographic exposures tested, demonstrating the very high‐resolution capabilities of the SSXII. In pulsed fluoroscopic mode, resolving the crimped stent structures becomes difficult below 40 μR. Using high gain, the object was visible down to 2.7 μR, which corresponds to ∼0.1 incident x‐ray photons per pixel, demonstrating both tremendous sensitivity and extremely low effective instrumentation noise. Conclusion: Images obtained with the prototype SSXII, over a vast range of exposure levels, indicate this new dynamic x‐ray imager has the potential to provide significant improvements over current state‐of‐the‐art detectors (both FPDs and XIIs) for high‐resolution angiographic and low‐noise, real‐time fluoroscopic imaging.(Partial support from the UB Foundation and NIH grants R01‐EB002873, R01‐NS43924.)
WE‐C‐L100J‐04: The Solid State X‐Ray Image Intensifier (SSXII): A Next‐Generation High‐Resolution Fluoroscopic Detector System
Authors: Rudin S , Kuhls A , Keleshis C , Kim D , Yadava G , Patel V , Ionita C , Hamwi H , Cartwright A , Verevkin A , Hoffmann K , Bednarek D 
Published: July 2007

Purpose: Present the design for the new SSXII high‐resolution fluoroscope capable of overcoming lag, noise, and resolution limitations of current flat‐panel devices (FPDs). Method and Materials: The SSXII consists of an array of modules each featuring an electron multiplying (EM) CCD which views a structured phosphor through a fiber‐optic taper (FOT). The EMCCD operates like a standard frame‐transfer CCD; however, an additional row of multiplication elements enables on‐chip signal gains up to 2000X to overcome subsequent instrumentation‐noise degradation. The SSXII therefore has quantum‐limited performance at both fluoroscopic exposures with moderate gain, and radiographic exposures with low gain. The SSXII array design, through pixel binning and module selection, will enable rapid sequence and fluoroscopic imaging for either the full field‐of‐view (FOV) or high‐resolution regions‐of‐interest (ROIs). Results: A SSXII module was assembled with direct fiber‐optic coupling of the 350 micron thick CsI(Tl) phosphor and the EMCCD (Texas Instruments TC285SPD chip with 1004×1002 pixels). Operation at fluoroscopic and angiographic exposure levels was verified experimentally for gains of ∼80X and 1X, respectively, demonstrating sequences of a moving stent with no lag and bar‐pattern resolution up to 20 1p/mm with a 1:1 FOT. An array of four modules each with 6:1 FOTs will have an effective pixel size of 48 microns covering a FOV of 10×10 cm, sufficient for region‐of‐interest and neurovascular imaging. Larger arrays may be constructed to satisfy both cardiac imaging and general fluoroscopic applications. Module alignment, digital stitching, and distortion correction issues are being addressed. Conclusion: When assembled in an array of sufficient size, the new SSXII can be used in the same applications as current FPD's with advantages of high frame rates with no lag, high resolution due to the smaller pixels possible, and low‐effective‐noise, quantum‐limited fluoroscopic performance due to the on‐chip gain.(Support: UB Foundation, NIH grants R01‐EB002873, R01‐NS43924).
WE‐C‐M100J‐03: Cryoablation: Scientific Foundation, Treatment Planning and Clinical Practice
Authors: Rewcastle J 
Published: July 2007

Cryoablation: Scientific Foundation, Treatment Planning and Clinical Practice.Interest in and utilization of cryoablation as a primary therapy for many types of cancer has increased markedly in the past decade. The procedure has evolved significantly from a technology perspective with engineering advances yielding greater control of ice formation within the body as well as enhanced visualization. This, coupled with isotherm modeling and treatment planning, has resulted in the ability to accurately target tissue for cryoablation. The organ to which these advances are most often applied is the prostate. This is due to the prostate being a relatively difficult structure to treat. The passage of the urethra through the gland necessitates the use of multiple cryoprobes and the procedure is confounded by the sensitivity of adjacent structures including the neurovascular bundles, external sphincter and rectum. Even with these obstacles, modern prostate cryoablation has emerged both as a primary prostate cancer treatment option and as a salvage therapy following failed radiation therapy.This lecture will review the fundamentals of cryobiology and the seminal work which established clinical endpoints. The technological basis of the procedure will be discussed including both fundamentals of cryoprobe design and compatibility imaging modalities. Lastly, clinical outcomes of the prostate cryoablation will be compared to radical prostatectomy (the gold standard), external beam radiation therapy, brachytherapy and IMRT.Educational goals:1. Understand the damage mechanisms of cryoablation and how they differ from radiation damage.2. Understand the fundamentals of how prostate cryoablation is performed and the technologies used to do so, and3. Understand how the outcomes of cryoablation compare to other treatment modalities.
WE‐C‐BRB‐01: Practice Performance Improvement Introduction for Medical Physicists
Authors: Nagy P , Pawlicki T , Paliwal B , Morin R , Frey G 
Published: July 2007

Practice Performance Improvement is a key component for analyzing and improving the practice of medical physics. It is also an important component of the maintenance of Certification Process for physicists certified by the American Board of Radiology. In order to use Practice Performance Improvement effectively physicists should have training in the techniques available. This session will provide the necessary training. The session is structured as follows:IntroductionPractice Performance Improvement — Techniques and Methods.Application of Practice Performance Improvement in Radiotherapy.Examples of Practice Performance Improvement Projects from Diagnostic Radiology, Nuclear Medicine and Radiation Therapy.
WE‐C‐AUD‐05: Simulation of Neutron Dose Exposure for Pediatric Proton Therapy Patients Using Whole‐Body Age‐Dependent Voxel Phantoms
Authors: Jarlskog C Zacharatou , Lee C , Bolch W , Xu X , Paganetti H 
Published: July 2007

Purpose: With the average age of radiation therapy patients decreasing due to early cancer detection and a larger proportion of patients being cured and thus at risk for treatment complications, there has to be a growing concern for the risk of developing cancer due to radiation treatments, in particular for pediatric and young patients. Age and gender specific whole‐body phantoms have been implemented in Geant4 in order to determine the dose from secondary radiation in patients undergoing proton treatment. Method and Materials: In a systematic study, we have used three methods to calculate the neutron organ equivalent dose to 14 organs distal to the target volume for six circular fields of varying diameters and range/modulation width combinations and for two patient fields that were previously used to treat two pediatric patients at the F. H. Burr Proton Therapy Center of Massachusetts General Hospital for brain lesions. Results using an adult phantom as well as phantoms of a 9‐month old male, a 4‐year old female, an 8‐year old female, an 11‐year old male and a 14‐year old male were analyzed. Results: The relative contribution to organ dose from secondary radiation from the treatment head and secondary radiation generated within the patient was evaluated. We found that the organ equivalent dose has a marked dependence on the phantom age, the distance between the organ and the PTV as well as on field characteristics. Overall, the organ equivalent doses were below 3 mSv per treatment Gy. Conclusions: The organ equivalent neutron dose for proton treatments of brain lesions in organs distal to the target was calculated for six age‐dependent phantoms. We found that the dose decreases with patient age and also depends on field size, beam energy and modulation.Work supported by NIH/NCI RO1 CA 116743.
WE‐C‐AUD‐08: Sensitivity Analysis of a Non‐Cylindrically Symmetric Monte Carlo Beam Model of a Siemens Primus Accelerator
Authors: Schreiber E , Chen J , Sawkey D , Faddegon B 
Published: July 2007

Purpose: To facilitate the development and commissioning of radiotherapy accelerator beam models by studying the impact of the variation of geometric and electron beam parameters on photon dose and fluence output for a Siemens Primus accelerator. In particular, the impact of lateral offsets of linac components and lateral and angular offsets of the electron beam were examined. Method and Materials: We have performed a sensitivity study examining the effect of varying beam and geometric parameters of a Monte Carlo model of a Siemens Primus accelerator. The accelerator and dose output were modeled using BEAMnrc and DOSXYZnrc, respectively. The BEAMnrc package was modified to allow for linear offsets of individual accelerator components, and lateral and angular offsets of the incident electron beam. Dose distributions were studied for 40 × 40 cm2 fields. Flatness, symmetry, OAR, and profile slope were studied. Results: The electron beam parameters having the greatest effect on the resulting dose distributions were found to be electron energy and angle of incidence, as high as 5% for a 0.25° deflection, with lateral offset of the electron beam and spot size having a smaller impact. Variations in target thickness were found to have a lesser effect than found in previous studies for electron beams. Small (∼2 mm) lateral offsets of the flattening filter altered the OAR by 5% for 6 MV and as much as 25% for 18 MV. Conclusion: Using large fields allows treatment head details to be more easily extracted. Lateral and angular offsets of beam and accelerator components have strong effects on dose distributions, and need to be included in any high‐accuracy beam model. Having a table cataloging the impact of model parameters on dose output can greatly facilitate beam model commissioning.Support from NIH R01 CA104777‐01A2.
WE‐C‐BRA‐01: Introduction
Authors: Nahum A 
Published: July 2007

Advances in technology and in computing have given us computer‐controlled linear accelerators equipped with multileaf collimators and wonderful 3D graphics workstations to perform treatment planning; additionally we have conceptual advances such as stereotaxy (cranial and extra‐cranial) intensity modulation (IMRT), helical tomotherapy and protons. But the bottom line in radiotherapy is radiobiology, radiobiology, radiobiology. If we don't know how to convert ‘physics’, i.e. dose distributions, into estimates of clinical outcome then these wonderful technological advances will remain ‘toys’ for physicists to play with.Radiobiology has traditionally concerned itself with determining surviving fraction vs. (uniform) dose curves for human tumour cell lines. However, in the 3D era we need models which connect dose distributions (and fractionation regimens) in tumours and normal tissues (generally in the form of dose‐volume histograms) with the probabilities of tumour (local) control — TCP — and of complications — NTCP. Such models now exist and their active use in treatment planning ushers in the era of Conformal Radiobiology.Educational Objectives:1. Appreciate the limitations of technology‐driven dose‐based radiotherapy.2. Appreciate the limitations of ‘classical’ radiobiology in the conformal era.3. Understand what is meant by ‘Conformal Radiobiology’.