bluuebunny/crossref_metadata_2025_split huggingface dataset:
TU‐C‐230A‐01: Introduction to Medical Errors and Implications
Authors: Dunscombe P 
Published: July 2006

There has developed, over the last few years, an increased awareness of the risks patient take when submitting themselves to medical procedures all of which are prone to errors. As a medical intervention, radiation therapy is no less susceptible to errors than any other branch of health care. Indeed in the case of radiation therapy both the consequences of errors and the number of patients affected can easily exceed those experienced elsewhere. A relatively small deviation from the prescription in either dose or volume irradiated can result in severe side effects or a failure to achieve the desired therapeutic outcome. Many patients are planned and/or treated on the same equipment facilitating the possible exposure to systematic effects.In this presentation the current status of error prevention activities in radiation therapy will be reviewed. This will include initiatives in both North America and Europe. The AAPM has recently formed a working group to focus on this issue. In Europe, ESTRO is particularly active in this area through workshops, teaching courses and the ROSIS database. In addition there are less formal groups who are dealing with particular components of safety in radiation therapy.If we are to live by the maxim “First, do no harm” then we need to do better than we are doing now. The degree of ambiguity in the available literature confounds interpretation in many cases. In particular we need to speak the same language when describing safety/quality issues. We need to have a metric for describing the severity of incidents in radiation therapy. One will be suggested for discussion. Ideally we should have a causal structure, which could be linked to a high level process map, for investigating incidents. With a causal structure we have a much better chance of learning from the actual and potential incidents which do occur. The learning component is one that we are particularly weak at. With a better understanding of the probability and severity of incidents we will make more informed decisions on the allocation of safety/quality resources. Finally, patient safety in radiation therapy is too big to deal with effectively on an individual clinic basis. While local issues undoubtedly influence the local risk of incidents, we will be able to give our patients a far better guarantee of both a safe and effective treatment if we work together across professional and geographic boundaries. To do this we need a common taxonomy, a degree of commonality in causal analysis and a common commitment to effective learning strategies.Learning Objectives:1. To appreciate the current status of error reduction activities in radiation therapy.2. To identify some of the limitations of current activities.3. To consider approaches to improving error reduction strategies.
TU‐C‐224A‐05: Dosimetry Comparison of the Newly Implemented Multi‐Criteria Optimization Tool for IMRT Planning
Authors: Yang C , Peng L , Lauterbach M 
Published: July 2006

Purpose: To apply a biological model based algorithm for acquiring optimized IMRT planning solutions. This interactive planning tool will help users to select the best available plans in the IMRT solution space.Method and Materials: IMRT often is a time consuming iterative optimization process between evaluation of the dose distribution and redefinition of the object function. An IMRT planning optimization tool (Multi‐Criteria Optimization, MCO™) has been introduced for non‐clinical evaluation to acquire the best available solutions. Based on a Pareto's solution concept, this tool could search the solution space and offer users a limited set of deliverable IMRT plans. With this interactive process, users can set the target and critical structures dose constraints with the biological model (EUD) to obtain the best solution. We used Pinnacle system as the benchmark to compare the dosimetric gain from the MCO algorithm, DVH indicated excellent sparing with better PTV coverage is achievable from the MCO process in KonRad system.Results: Dosimetric findings are summarized as 1) MCO optimization testing shows that much better dose distribution can be achieved compared to the current planning results (Fig. 1 and Fig. 2). Due to the confined solution space, the optimal results are easily achievable. 2) MCO with Pareto's approach is durable in the solution searching process. It is interactive with the graphical interface which the dose distribution along with the DVH can be compared simultaneously (Fig. 3). 3) IMRT dose optimization and summary based on the MCO methodology are very conceivable. With pre‐calculated IMRT solutions, final results help users to select the best available plan from the solution domain in real time (Fig. 4). Conclusion: From this interactive MCO planning tool, we can calculate the best IMRT results in a very reasonable time frame. Human factors for determining an acceptable plan can be dramatically reduced.
TU‐E‐224A‐06: Frameless Radiosurgery Using Stereoscopic X‐Ray Guidance: System Characteristics and 2 Year Clinical Experience
Authors: MULLINS J , Li S , Pillai S , Medin P , Solberg T 
Published: July 2006

Purpose: To evaluate targeting capabilities of a system for image guided “frameless” stereotactic irradiation. Method and Materials: System accuracy was investigated using an anthropomorphic head phantom into which a “hidden target” (radio‐opaque sphere) was inserted. The target was identified on planning CT images and the phantom was fixed to the treatment couch. To align the target to isocenter, stereoscopic kV x‐rays were fused to planning DRRs. AP and lateral verification films were exposed using a 10 mm circular collimator, and the offset of the sphere within the radiation field was recorded. The entire process was repeated 50 times in order to achieve an accurate assessment of positioning capabilities. Retrospective data was evaluated from patients having undergone nearly 600 x‐ray guided single and multi‐fraction stereotactic irradiation procedures. From this data the following were investigated: the nature and magnitude of systematic and random positioning errors present in conventional procedures, confidence limits on the reproducibility of the mask immobilization device used for multi‐fraction treatments, and the potential for replacing rigid head fixation with image guided positioning. Results: In phantom studies, a vector displacement of σ = 0.39 mm relative to the “perfect” isocenter was observed. Based on a sample population of 50, this provides assurance of accuracy at the 95% confidence level.Improvement in positioning accuracy was observed in multi‐fraction procedures; analysis of 565 fractions showed a mean vector deviation σ = 2.65 mm relative to traditional methods. The largest component of this discrepancy was in the superior/inferior direction. In comparison, a mean vector deviation σ = 1.62 mm was observed in patients for whom rigid fixation was used. Conclusions: Stereoscopic x‐ray imaging is an accurate positioning method for cranial stereotactic irradiation. The system is as accurate as rigid frame‐based methods and can improve the reproducibility of fractionated delivery.
TU‐FF‐A1‐01: Characterization of EBT Versus MD55 Gafchromic® Films for Relative Dosimetry Measurements
Authors: Alvarez P , Hernandez N , Followill D , Tailor R , Ibbott G 
Published: July 2006

Purpose: To evaluate the EBT® radio‐chromic film for relative dosimetry in comparison to MD55®. Method and Materials: For dose‐response study, EBT and MD55 films were irradiated to dose ranges 0–15 and 0–40 Gy respectively. Photon beam energies of 6 and 18 MV were used to study energy dependence. Films were scanned using a scanner from Micro‐densitometer Photoelectron Corporation. The scanner uses a CCD camera. The two diffused‐light beds using light‐emitting diodes, operating at 636 and 665 nm, were used for EBT and MD55 films respectively. For flatfield subtraction at start of a scanning session, in case of EBT, an unirradiated film was scanned employing a black mask covering the light box's area outside the film. In case of MD55, un‐masked light box without a film was scanned for the flat field subtraction. For fading study, films were read over a period 2–20 days after irradiation. For light sensitivity, un‐irradiated films were exposed to florescent light to 6 hour maximum. Results: Unlike MD55, light sensitivity of EBT is found to decrease with pre‐irradiation level. With 2Gy pre‐irradiation, it is comparable to MD55. Fading of EBT is comparable to MD55. The small energy dependence observed beyond 8Gy for EBT is considered negligible. Percent uncertainty in relative‐dose determination from two OD values is obviously expected to increase with separation between the OD values, and to be higher at lower OD levels. It is comparable for both films, and is typically estimated to be 0.8% for determination of 50% of 2Gy. Conclusions: Dosimetry characteristics of EBT are comparable to MD55. Its higher sensitivity to radiation and availability in larger size makes it preferable as a relative dosimeter for RPC use.Work supported by PHS grant CA10953 and CA81647 awarded by NCI.
TU‐FF‐A2‐01: Feasibility of Cone‐Beam CT Based Treatment Planning
Authors: Yoo S , Yin F 
Published: July 2006

Purpose: To investigate the feasibility of cone‐beam computed tomography (CBCT)‐based treatment planning. Methods: HU of material disks in Catphan, HU profiles for homogeneous and inhomogeneous phantoms, and HU values in different tissue areas of brain, thorax and prostate patients were compared in CBCT and CT images. Plans with one beam based on CBCT and CT of phantoms and patients were compared using MU/cGy values and isodose distributions. For patient cases, 3D plans and IMRT plans based on CT images were generated, and then verification plans based on CBCT were generated. The isodose distributions and dose values at the isocenter were compared between two plans. Results: HU values of CBCT are very close to those of CT in Catphan. However, HU profiles of homogeneous and inhomogeneous phantoms in CBCT show inhomogeneous distribution compared to those in CT with large scatter. Large scatter contribution becomes greater in patient cases. The lung or fatty tissue appears with even lower HU values in CBCT than in CT. Resulting MU/cGy differences are generally within 2%, but a beam passing through a significant amount of the lung or bone shows 2 – 3% of MU/cGy difference. The isodose distributions of CBCT‐based verification plans and CT‐based plans for brain and prostate patients are very similar with the dose values less than 2% different. The dose value is about 4% higher in CBCT‐based verification plan than in CT‐based plan for the thorax patient and the isodose distributions in the high dose area inside of the lung shows disagreement between the two plans. Conclusion: This study validates CBCT‐based treatment planning by comparing with the gold standard CT‐based treatment planning. CBCT‐based plans could be used for most cases. However, beams should be selected with a consideration to avoid a large part of lung.Research partially sponsored by Varian Medical System.
TU‐FF‐A4‐01: Instrumentation Noise Equivalent Exposure (INEE) Representation for High Sensitivity X‐Ray Imaging Detectors
Authors: Yadava G , Rudin S , Kuhls A , Patel V , Bednarek D , Hoffmann K 
Published: July 2006

Purpose: For modern high‐sensitivity digital imaging detectors operating at fluoroscopic exposure rates, the additive instrumentation readout noise may prevent desirable optimal quantum‐limited performance. A formalism and experimental validation of the representation of instrumentation noise in terms of the equivalent x‐ray entrance exposure to the detector is presented as a more practical noise measure than the equipment‐invasive measurement of electrons per pixel. Method and Materials: The instrumentation noise in terms of exposure equivalent is added in quadrature to the quantum noise to give the total measurable noise. Experimental validation was done using two different CCD‐based detectors: a high‐sensitivity microangiographic fluoroscope (MAF) and a less sensitive microangiographic detector (MA). Both detectors have a CsI(Tl) phosphor coupled to a fiber‐optic taper followed by a CCD camera (the MAF additionally has a variable‐gain light amplifier between the taper and the CCD). To determine the INEE for both detectors, a least‐squares regression technique was used to fit the measured data to the theoretical equation relating the signal‐to‐noise ratio squared SNR2 to the detector entrance exposure. Results: The SNR2 versus exposure plot deviates from linear behavior at lower exposures as expected, and closely follows the modeled equation used to derive the INEE. The measured INEE for the high‐sensitivity MAF was 0.034 μR and that for the MA was 10.8 μR. Conclusion: A formal treatment of the instrumentation noise in terms of the detector entrance exposure was developed and validated by using two different CCD based systems of different sensitivity. This study demonstrates that the INEE is a practical way to gauge the range of quantum‐limited performance for clinical x‐ray imaging detectors, with the implication that detector performance at exposures below the INEE will be instrumentation‐noise limited rather than quantum‐noise limited.(Partial support from NIH Grants R01EB002873, R01NS43924, and Toshiba Medical Systems Corporation).
TU‐FF‐A4‐05: Temporal Subtraction of Lateral Chest Radiographs
Authors: Engelmann R , Armato S , Doshi D , Sensakovic W , Starkey A , MacMahon H 
Published: July 2006

Purpose: Radiologists routinely compare multiple radiographs of the same patient to identify interval change in anatomy and pathology. The temporal subtraction images that facilitate this comparison have been limited to posteroanterior radiographs. Since the lateral view provides diagnostically important information, the purpose of this study was to develop an automated method for the subtraction of temporally sequential lateral chest radiographs and to evaluate the quality of the resulting images. Method and Materials: An automated method was developed to digitally subtract pairs of lateral chest radiographs. First, multiple rotated versions of the “previous” lateral radiograph were generated. For each of the rotated previous images, the apex of the lungs was identified through gray‐level profile analysis. A 251 × 215 mm subimage was then extracted near the apex and used as a template for cross‐correlation with the “current” radiograph. The translation and rotation parameters that yielded the highest correlation were used to rigidly transform the “previous” radiograph, which was then subtracted from the current radiograph to yield the temporal subtraction image. 30 pairs of lateral chest radiographs were subtracted. An observer rated the quality of each temporal subtraction image using a 1 (“very poor”) to 5 (“excellent”) scale. Results: The average registration accuracy rating was 4.0. 83% (25/30) of the subtraction images were rated as “acceptable” or better (3.0 or higher). Conclusion: Our technique for the automated subtraction of temporally sequential lateral chest radiographs generates a high percentage of subtraction images with acceptable registration accuracy. Such a method is expected to provide a valuable supplement to the conventional posteroanterior temporal subtraction images that have proven beneficial in the diagnostic evaluation of interval change in chest radiography.S.A. and H.M. hold warrants to shares in R2 Technology, Inc.; H.M. consultant for Riverain Medical and Median Technologies.
WE‐A‐330A‐01: Breast CAD in the Digital Era
Authors: Giger M 
Published: July 2006

Use of output from a computerized analysis of a breast image by radiologists may help them in the tasks of detection or diagnostic, and potentially improve the overall interpretation of breast images and the subsequent patient care. Many factors motivate the attempts to aid or automate radiological diagnosis. Inadequacies in interpretation performance may be due to the presence of image noise or normal anatomical structure as well as to known limitations in the human search and perception process. Developments in breast CAD have led to clinically‐used detection systems in screening mammography and preclinical classification systems for diagnostic breast imaging. Diagnostic breast CAD systems provide output for the characterization of lesions on special‐view mammography, breast sonography, and breast MRI in order to aid in patient management decisions, such as biopsy decisions. As imaging continues to expand in the digital era, computer‐aided diagnosis (CAD) may become an integrated tool in the online diagnostic workup of suspect breast lesions using multi‐modality images and advanced PACS. This presentation reviews research in computerized analysis of mammographic, sonographic, and magnetic resonance breast images for detection and diagnosis. It will include the characterization of lesions and the estimation of the probability of malignancy for use in the diagnostic workup of suspect lesions. CAD systems in diagnostic workup usually involve having the computer extract the margin of the lesion from the surrounding parenchyma, extract characteristics (features) of the lesions, merge these computer‐extracted features into an estimate of the probability of malignancy, and as an option, retrieve automatically similar lesions from an online reference library. The aim of CAD in diagnostic workup is to increase classification sensitivity and specificity as well as to reduce intra‐and inter‐observer variability. While the breadth and depth of CAD is increasing, continued and expanded efforts are needed for collecting and confirming databases, establishing methods for evaluation, integrating effectively and efficiently with PACS and RIS systems, and providing means for clinical evaluation.Learning objectives:1. To appreciate the development of CAD in multi‐modality imaging for detection and diagnosis of breast cancer.2. To understand the benefits and challenges as CAD moves into the digital era and is integrated with PACS and HIS.3. To recognize the necessary steps for advancing and integrating CAD clinically.COI: Maryellen Giger is a shareholder and consultant, and receives research funding from R2 Technology, Inc.
WE‐A‐330D‐01: PET Scanner Quality Assurance
Authors: Kemp B 
Published: July 2006

Quality assurance of PET scanners must be performed on a regular basis to maintain and confirm proper scanner performance. These procedures should track system stability and be sensitive to changes in scanner operation. The quality control and calibration of a PET scanner includes detector and electronic characterizations such as adjustment of PMT gain, definition of crystal and energy maps and coincidence timing calibration. These characterizations are applied to the PET data during acquisition. A PET quality control regimen includes system corrections such as normalization, calibration and, in the case of non‐PET/CT systems, blank scans. The calibration correction is used to convert the reconstructed image pixel values into activity concentration and it may be used to compensate for the axial sensitivity variation of the scanner. These characterizations are applied to the PET data after acquisition.The NEMA PET NU2‐2001 standard should be followed for acceptance testing. This standard uses a polyethylene phantom of 700mm axial length with a line source to measure scatter fraction, count losses and randoms. The measurement of sensitivity is conducted with a line source surrounded by known absorbers, and the sensitivity with no absorbers can be found by extrapolation. The intent of the image quality measurement is to mimic a whole body scan using a torso phantom containing hot and cold spheres of various diameters (representing lesions) in a warm background.This presentation will focus on the calibrations and corrections required to maintain proper system performance. The presentation will also describe the rationale and methodology of the NEMA NU2‐2001 performance standards.Educational Objectives:1. Describe the calibrations required to properly detect the location of a coincident event.2. Describe the post acquisition corrections required to minimize image artifacts.3. Describe NEMA NU2‐2001 PET performance standards.
WE‐A‐ValB‐01: Multi‐Slice CT Image Reconstruction
Authors: Hsieh J 
Published: July 2006

Over the past decade, x‐ray computed tomography has experienced tremendously technological advancements: the introduction of helical/spiral and multi‐slice/volumetric acquisition. These advancements not only allow improved image quality and enable new clinical applications, but also significantly increase the technical challenges associated with image reconstruction.The first part of this lecture will cover the fundamentals of image reconstruction. For the ease of understanding, we start with an explanation of the central slice theorem (Fourier slice theorem). Both theoretical and intuitive approaches are used to illustrate the concept. The reconstruction algorithm is then extended to fan beam geometry by mathematical derivation and graphic description.Using the central slice theorem as the foundation, reconstruction algorithms for helical acquisition are discussed in the second part of the lecture. We analyze, for single slice, the major difference between helical and step‐andshoot acquisitions. Implications of different reconstruction approaches on image quality and computational complexity are also discussed.Cone beam reconstruction discussion will start with one of the most popular algorithms: FDK algorithm. The derivation of the algorithm from the fan‐beam case is first described and its extension to helical/spiral acquisition is then presented. The lecture ends with a discussion on some of the most recent advances in cone beam reconstruction, including both approximate and exact methods.Jiang Hsieh is an employee of GE Healthcare Technologies.Educational Objectives:1. Learn the fundamentals of x‐ray CT reconstruction.2. Understand recent advancements in reconstruction algorithms.
WE‐A‐224A‐01: IMRT Modeling Influence On Planning
Authors: Dempsey J 
Published: July 2006

The quality of an intensity modulated radiation therapy (IMRT) treatment plan can be strongly influenced by the physical and mathematical models underlying a clinical planning system. This lecture provides an overview of the models that are commonly employed for purposes of treatment planning for megavoltage (MV) photon‐beam IMRT achieved through multi‐leaf collimator (MLC) delivery. IMRT treatment planning models will be examined which include models of: ionizing‐radiation dose computation; fluence‐map optimization; MLC delivery sequence optimization; dosimetric plan evaluation; and “biologic” plan evaluation. Models will be studied with focus on the assumptions, merits, and limitations involved with different models. The differences between reality and the models will be explored. Emphasis will be placed on plan characteristics that exist in reality but are not reflected in the model of the IMRT delivery. The influence of the algorithms employed to implement the models will also be discussed including methods that involve discretization, rounding, and limited numerical precision. Practical examples that demonstrate the influence of modeling differences on IMRT plan quality will be presented.Educational Objectives:1. Understand the influence of the choice of physical models employed in clinical IMRT.2. Understand the assumptions, merits, and limitations involved with different IMRT planning models.3. Review the conditions where IMRT modeling is suspect and requires careful scrutiny in clinical implementation.