Volume 33, Issue 6, June 2006
Index of content:
- Professional Session: Room 230A
- Professional ‐ Proffered Session
MO‐D‐230A‐01: A Nontraditional Method of Providing Radiation Protection Instruction at a Large Health Science Center33(2006); http://dx.doi.org/10.1118/1.2241427View Description Hide Description
Purpose: To test the hypothesis that the combined online/lecture format was as effective as the lecture‐only format for students who took the University of Alabama at Birmingham (UAB) radiation safety course. Method and Materials: In the 4th quarter of 2001 the University of Alabama at Birmingham (UAB) converted its traditional classroom radiation safety course, taught exclusively in a classroom setting four times each year, to a combined online‐classroom format in which the majority of the course is taught online. This change was instituted in an effort to minimize the time spent in the classroom for UAB research personnel. This format should provide the additional benefit of self‐paced instruction for course participants. A statistical analysis was performed on the average first‐attempt test scores of the tests (number of tests=334) taken during a two‐year period before the online transition (average score=75.5), and the average first‐attempt test scores of the tests (number of tests=359) taken during a two‐year period after the online transition (average score=74.1.) Results: A two‐tailed Student's t‐test was performed on the data. The t‐value was 1.73, and P(T<=t) was 0.083. At α=0.05, the null hypothesis that the two averages are equal cannot be rejected. Conclusion: The online course format appears to be as effective a method of radiation safety instruction as the more traditional, exclusively‐classroom method of instruction. This presentation also reviews steps under consideration to improve the current online course to make it a more effective tool in radiation safety instruction.
MO‐D‐230A‐02: An Immersive Virtual Environment for Training of Radiotherapy Students and Developing Clinical Experience33(2006); http://dx.doi.org/10.1118/1.2241428View Description Hide Description
Purpose:Radiotherapy equipment and techniques are rapidly developing and so efficient training is invaluable. However, the demands on clinical systems and the lack of trained personnel make it difficult to achieve. As an alternative approach we have developed virtual reality training tools, fully interactive and operating on a life size scale these can provide valuable experience for students and staff. We designed a study for 42 first year therapist students to investigate the usefulness of our training environment for learning a clinical technique that typically causes problems. Method and Materials: We have created a virtual environment that simulates an actual radiotherapy treatment machine, controlled via an actual handheld control pendant. The study was developed to simulate a “skin apposition” electron beam treatment. A virtual patient, based on the visible human female dataset, complete with rectangular markings for a range of different treatment sites, provided a range of treatment scenarios. At the Hull Immersive Visualization Environment (HIVE) we are able to project our graphics display onto a 5.3 m by 2.5 m ‘Power Wall’ utilizing stereoscopic visualization enabled via LCD shutter glasses. Such immersive interaction techniques (including the use of the Linac hand pendant) add to the user's sense of reality. To provide feedback, we have implemented a ‘scoring algorithm’ to assess how well the user has set up the beam/ patient. Results: The students reported the training environment to be realistic and following its use 93% perceived an improvement in their understanding of this clinical technique and 69% found the control system easy to master. Conclusion: Having implemented such training software and hardware we are beginning to perform academic studies to assess the impact of its use in the educational forum. We wish to understand which areas of multi‐discipline training will benefit from such an approach.
33(2006); http://dx.doi.org/10.1118/1.2241429View Description Hide Description
Purpose: The goal is to develop a dynamic automated patient management program. This software will be able to track the status of the patient's treatment plan and remind the responsible parties of intermediate deadlines. Alerts are sent each morning to the radiation oncologist, residents, dosimetrists, and physicists about the current stage of the treatment planning.Method: The patient planning management software was written in Visual Basic 7.0 and incorporates Microsoft Excel's spreadsheet. The programs display is viewable over anywhere in the department. The program shows each patient's data in a separate row and color coded according each radiation oncologist. The patient's CT and start date are entered for each patient. The deadlines included are that for the approval of the PTV and normal tissue, plan approval, and completion. The program will change the color of the patient's data from yellow (warning) and red (alarm) based upon approaching deadlines. Results: This planning software continuously updates patient information. This program eliminates the time consuming process of paging, emailing, and tracking down responsible parties to communicate completion of various tasks. Since the inception of this software the mean time interval to complete a plan has decreased by 30%. The mean time required to get target volumes approved has dropped 25%. One significant benefit is the 50% increase in time between the completion date and start date. Without an increase the overall planning time, this has allowed more time for physics checks, quality assurance, and therapist review. Conclusions: In the face of increasing patient numbers the dynamic automated patient management software has enabled our department to complete our patient's plans in a more efficient manner. This increased efficiency allows all responsible staff adequate time to complete their responsibilities for each patient.
33(2006); http://dx.doi.org/10.1118/1.2241430View Description Hide Description
Purpose: To provide dedicated, integrated PET‐CT and MR simulation and imaging devices in the radiation treatment clinic for purposes of advanced oncologicimaging.Method and Materials: A planning team was established for design of radiationoncology facilities as part of a new comprehensive cancer center. Physicist input included emphasis on combined biological‐anatomical (termed “bioanatomic”™) imaging for a research program in Bioanatomic Imaging and Treatment (BAIT), provision of state‐of‐the‐art treatment devices for IMRT, radiosurgery, and HDR, and analyses of digital medical informatics. PET‐CT and MR simulator specifications were delineated at a time of rapid technology development for both modalities, and included capabilities for gated PETCT acquisition and high‐resolution MRspectroscopy.Results: Facility design includes dedicated rooms for Conventional, PET‐CT, and MR simulation. BAIT simulator devices selected are 8‐slice PET‐CT and 3.0T MR, each with “marking” lasers and virtual simulation tools. PET‐CT s“imulation includes respiratory gating. 3.0T MR simulation includes spectroscopic, diffusion, and perfusion imaging.Radiation safety aspects include shielding for ionizing radiation (PET‐CT) and radiofrequency and magnetic fields (3.0T MR). PET‐CT and MR simulators are centrally located to facilitate patient flow and physician access. PET‐CT and MR simulations are being performed under the auspices of multidisciplinary clinical and research oversight committees. Operators are paired as one imaging technologist (PET‐CT or MR) and one radiation therapist per simulator. Conclusion: Vision for the Bioanatomic Imaging and Treatment Program has been coupled with the opportunity for a new comprehensive cancer center facility to provide multi‐slice PET‐CT and 3.0T MR simulation in the radiation treatment clinic. Using a collaborative multidisciplinary approach, image‐based research protocols have been developed for specific disease sites, and experience is being gained with use of dedicated, integrated PET‐CT and MR simulation. Conflict of Interest: BAIT Program research partners include Varian Medical Systems and GE Healthcare.
33(2006); http://dx.doi.org/10.1118/1.2241431View Description Hide Description
Purpose: An error reporting program, called the Medical Error Reduction Plan, was developed in our department. The program includes errors made during the patient treatment preparation process and delivery. The purpose of this study is to understand the types of errors, error frequency and trending, correlation between errors, error severity and impact on treatment quality, and to derive an error reduction strategy based on non‐punitive principles. Method and Materials: The plan supplements all required QA processes and procedures in Radiation Oncology. After patient treatment plan approval, the Therapists Check Station performs a final comprehensive check that includes: plan revision, patient setup, data entered to R&V system, approvals and scheduling. Problems are recorded in a Discrepancy Log Book that includes also errors in simulation and incomplete directives/forms. All these data are presented, discussed and analyzed at the monthly departmental meetings. We have two full years of data combined into the following categories: simulation, planning, approvals, logistics, documentation and treatment. Errors in patient treatments have been recorded in our Department as Unintended Deviations. They are presented on graphs together with data from our error reduction plan. Results: During the past two years, 350 errors were reported. Most of them (60%) were clerical, simulation and treatment planning errors accounted for 11% and 17%, respectively. At the end of the analyzed period, there was more than 50% overall reduction of treatment errors. The introduced error reporting program increased personnel alertness to treatment process details. Conclusions: The idea of a “user friendly” error detection and reduction program has proven excellent. Despite of multiple QA procedures and the R&V system, the possibility to make errors still exists. It is imperative to detect them before treatment. This process should be ongoing in view of increasing novelty and complexity of treatments.
33(2006); http://dx.doi.org/10.1118/1.2241432View Description Hide Description
Purpose: Chart checking is key in radiation oncology QA. AAPM TG 40, Comprehensive QA…Oncology, TG53, QA for…Planning, and ACR Technical Standard... Therapy address chart checking. They recommend verifying monitor unit (MU) calculations by a second person or method before delivering 3 fractions or 10% total dose. Time‐consuming verifications are difficulty for multiple beam, heterogeneity corrected 3D and IMRT isodoses. We investigate statistical consistency reviews (SCR) of common treatments as one of several chart‐checking tools. Method and Materials: We collect data (gantry and collimator angles, SSD, field sizes, weights, fractions, dose/fraction, depths, outputs, MUs) for sites. We investigate parameter statistical consistency for the same treatment to similar patients. We report prostate four field treatments (66.6 Gy or 74 Gy/37 Fx) and IMRT five‐field (0, 75, 140, 220, 285 degrees) treatments (76 Gy/38 Fx). Results: Four field prostate treatments are surprisingly consistent. SSDs varied about 3% and MUs about 6%. Average AP SSD was 87. 9 +/− 1.9 cm (2%) requiring 47.4 +/− 2.5 (5%) MU for 45 cGy. Average lateral SSD was 80.7 +/− 2 cm (2.5%) yielding 63.3 +/− 2.5 MU (4%) for 45 cGy. IMRTtreatments MU variations were about 20%. Conclusion: How to use these data? Rather than check our historically accurate algorithm calculations against another algorithm, we review four‐field prostate MU calculations against statistical norms. A recent patient's AP 57 MU were greater than three standard deviations above the norm, 47 +/− 2.5 MU. His AP 79 cm SSD was well below the norm, 87.9 +/− 1.9 cm. A planning error? No, he was just obese, but it illustrates the value of knowing average parameters. IMRT plans appear more consistent than expected; SCR may have value for IMRT plan reviews. Statistical data will be presented for other sites (breast, head/neck, etc.) commonly treated with consistent methods.
33(2006); http://dx.doi.org/10.1118/1.2241433View Description Hide Description
Purpose: To measure couch sag and couch deflection in several EXACT Couches. Method and Materials: Couch sag was evaluated for EXACT Couches at three positions: tip, center and base with the couch fully extended in treatment position. In each case, measurements were made with no weight and with 84, 142, and 319 lbs uniformly distributed over the couch surface. Couch deflection was evaluated with SSD readings to the couch surface using the mechanical backpointer at isocenter and digital read out. Measurement were repeated with the couch at nominal SSDs of 100 cm, 110 cm and 120 cm and with rails closed together in the middle. Same measurements were performed with Picker CT couch for comparison. Results: We found 9 mm deflection from the tip to the base of couch (fully extended) with no weight on the surface. According to Varian service personnel, design of EXACT Couches follows IEC specification and Exact Couch manufacturers provided a +5mm deflection to counter weight the patient's weight. Our couch was shimmed and brought the sag down to +5mm. EXACT Couch deflection with no weight on surface varied between 5ndash;9mm at five different centers. Sag was same at nominal SSDs. Up to 7mm sag variation was noticed depending upon the weight.
With rails closed together in the middle, about 1mm decrease was noted for the above values. Upto 4mm sag was noticed in CT couch. Unlike Exact couch, CT couch sag decreased at the base. Conclusions: Study demonstrated that the +5mm deflection does not completely counter weight the patient's weight for having leveled surface at the isocenter.
2–5mm sag at tip and up to −7mm at base relative to the amount of weight on couch was noticed. In time +5mm‐shimmed deflection was deteriorated to +7mm. Same results were obtained when couch was loaded.
33(2006); http://dx.doi.org/10.1118/1.2241434View Description Hide Description
Purpose: To create a tool for collecting physician referral data, identifying strengths and weaknesses in physician referral patterns, and for predicting future referrals in real‐time. Methods and Materials: Since January 2001, the referring physician was recorded for each patient that was seen for consultation in a radiation oncology department. In addition to the physician, the referring physician group was also recorded. The total referrals for each month were summed for each individual referring physician and physician group. In addition to referral data, physician hospital in‐patient admitting data for oncology related diagnoses were obtained from the state's medical statistics. For physicians that have privileges at multiple hospitals, the “Market Share” was calculated. The number of referrals received each month was predicted using a locally weighted regression (LWR) model. The regularization parameters of the LWR model were determined through a continuous genetic algorithm that minimized the mean squared error using data not used in the LWR model. To protect confidentiality, a sample data set was crafted to simulate possible radiation oncology scenarios. Results: The results of this study are confidential business data, and so, a sample dataset is used to demonstrate referral pattern tracking. The results concluded that 95% of patient referrals originate from one of five specialties, the largest being medicaloncology (43%). The top referring group in each medical specialty was responsible for 65% of patient referrals, and refer >95% of their patients inside the same health system. The remaining 35% of the hypothetical radiation oncology's referrals are physicians who practice in multiple health systems. The LWRmodel accurately predicted the number of referrals with a mean squared error of 2.2%. Conclusions: The collection and analysis of physician referral data provides a useful tool for maximizing radiation oncology growth and efficiency through known parameters.
33(2006); http://dx.doi.org/10.1118/1.2241435View Description Hide Description
The Mammography Quality Standards Act (MQSA) of 1992 requires that all mammography facilities in the United States (including those using full field digital mammography [FFDM] equipment) be accredited by an approved body, certified by the U.S. Department of Health and Human Services (HHS), and receive an on‐site inspection by a state agency acting on behalf of the HHS (or by HHS inspectors). The FDA approved the first premarket approval application for a FFDM unit in January 2000. Immediately accrediting these units presented a dilemma for the American College of Radiology (ACR) since, historically, programs are only developed for mature, widely‐available technologies, so that reasonable standards may be developed based on expert experience. Consequently, the ACR could not have an accreditation program available for this new technology at the time FDA approved it to be sold in the US. To provide time for accreditation development, the FDA provided a process to exempt FFDM units from the MQSA accreditation requirement if an accreditation program was not yet available for the specific FFDM model. The FDA approved the ACR to accredit the General Electric Senographe 2000D, the Fischer SenoScan and the Lorad Selenia FFDM units in 2003; the General Electric Senographe DS in 2004 and the Siemens Mammomat Novation in 2005. Although some of the accreditation instructions and submissions are different for digital accreditation, each unit is still required to pass clinical image quality, phantom image quality and dose. Data since 2003 shows that the deficiency rate for FFDM units making their first attempt at accreditation is lower than with screen‐film applicants (approximately 7% vs. 11%). Accreditation results from over 1200 units at 900 facilities will be presented.