SP-0426: Quality management for contemporary and emerging RT technologies

not received SP-0425 Molecular imaging as biomarker in future clinical trials: The proof of the pudding is in the eating J.H.A.M. Kaanders, B.A.W. Hoeben, E.G.C. Troost, J. Bussink, W.J.G. Oyen Radboud University Nijmegen Medical Centre, Radiation Oncology, Nijmegen, The Netherlands Maastro Clinic, Radiation Oncology, Maastricht, The Netherlands Radboud University Nijmegen Medical Centre, Nuclear Medicine, Nijmegen, The Netherlands Integration of molecular imaging techniques into therapy selection strategies and radiation treatment planning can serve several purposes. First, pretreatment assessments can steer decisions about radiotherapy modifications or combinations with other modalities. Second, biology-based objective functions can be introduced to the radiation treatment planning process by co-registration of functional imaging with planning CT-scans. Thus, customized heterogeneous dose distributions can be generated with escalating doses to tumor areas where radiotherapy resistance mechanisms are most prevalent. Third, monitoring of temporal and spatial variations in these radiotherapy resistance mechanisms early during the treatment can discriminate responders from non-responders. With such information available shortly after the start of the treatment, modifications can be implemented or the radiation treatment plan can be adapted tailing the biological response pattern. Currently, these strategies are in various phases of clinical testing, mostly in single-center studies but more and more also in multi-center set-up. Ultimately, this should result in availability for routine clinical practice requiring stable production and accessibility of tracers, reproducibilty and standardization of imaging and analysis methods and general availability of knowledge and expertise. Small studies employing adaptive radiotherapy based on functional dynamics and early response mechanisms demonstrate promising results. This approach is closest to large scale clinical testing with good prospects for success. SYMPOSIUM: METHODS FOR QUALITY MANAGEMENT SP-0426 Quality management for contemporary and emerging RT technologies S. Mutic Washington University Medical Center, Radiation Oncology, St. Louis, USA The definition of quality in radiation therapy largely remains poorly defined, understood and often confused with the issues of safety. While safety and quality are on many levels inseparable, there is a clear distinction and there can be delivery of safe treatments according to physician prescription in radiation therapy which are of insufficient quality to meet the treatment goals. High quality clinical operations can be defined as those which minimize variations and uncertainty in patient treatments and result in consistent outcomes. In radiation therapy, treatment consists of multiple components (consultation, treatment selection, immobilization, imaging for planning, contouring, planning, etc.). Relatively large variation and uncertainty in any one of these steps contribute to the overall degradation of treatment quality. The degradation of quality results in uncertainty in patient outcomes. Figure 1 a) shows an example distribution of patient treatments. On one end of the spectrum is overdose of critical structures, in middle are the majority of patient treatments which result in clinical benefit without unexpected side effects,and on the other side of the spectrum is under dose of target volumes. The over dose and under dose is clearly bad, but the two regions between clinical benefit and over dose and under dose, respectively, have clinical uncertainty. Patients falling in these uncertainty regions may or may not have clinical complications or poor tumor control. Patients falling in extreme over or under dose regions are typically infrequent and these are extreme cases that typically are widely publicized. However, it is unclear how many patients fall in the uncertainty regions and potentially have compromised outcomes. It is important to note that the outcomes in the uncertainty region are often considered as expected and accepted treatment outcomes, though possibly avoidable. S164 2 ESTRO Forum 2013 Figure1. a) Clinical system with large uncertainty and overall poor quality, b) Clinical system with reduced uncertainty and improved clinical benefit (quality) for the majority of treated patients. Figure 1 b) shows an outcome distribution for a system with improved quality. In this situation, the vast majority of patients fall in the clinical benefit region and the overall uncertainty of clinical outcomes is reduced. The quality improvement in radiation therapy can be defined as an effort to move a clinical system from the situation in Figure 1 a) to that shown in Figure 1 b). This quality improvement and consistent operational level can be achieved through systems management, standardization, benchmarking, and a variety of industrial tools. High level of quality and reliability cannot be achieved without a systematic approach to operations and clinical management. In many aspects, Figure 1 is overly simplistic representation of the actual clinical operations and other concerns like timely and efficient care, cost,and the overall employee and patient satisfaction are not considered in this example. Systematic approach to clinical decisions and operational management can lead to improvements in all of these areas. In fact, most modern radiotherapy operations are very complex, have a relatively high risk for catastrophic failures, and involve significant cost and as such meet the very definition of operations which require systems approach. Direct translation of industrial methods to clinical environment is typically inappropriate and requires adaptation to result in meaningful improvements in clinical operations. This presentation will discuss: 1) The role of quality and safety in radiation therapy 2) Modern approaches to quality management which are adoptable to radiation therapy operations 3) The role of automation, decision support, and knowledge based tools for management of safety and quality in radiation therapy SP-0427 The use of Statistical Process Control (SPC) to monitor processes K. Gerard-Herlevin, V. Marchesi, N. Villani, O. Mougel, I. Buchheit Alexis Vautrin Cancer Center, Medical Physics Unit, Nancy, France Over the past few years, due to the development of new radiotherapy equipments and complex techniques such as IMRT, IGRT and IMAT, the amount of quality controls (QC) required to check the equipment performance and the patient-specific treatment plans has increased and could be a barrier to the development of these techniques. Although we can find reports or guidelines regarding the procedures, protocols and detectors that are best adapted for each control, it remains difficult to find discussions on how to improve the dose delivery process by reducing variability and by defining action levels. In this purpose, we suggest that the quality control results should not only be analyzed in an individual manner by checking if the result is within predefined tolerances, but should also be analyzed from a process behaviour point of view. This is done by evaluating the position of the current result compared to all of the previous similar results. This will help to detect a potential drift of the whole process that could be missed when evaluating each result individually. As a consequence, this will help to increase quality. To perform this process analysis, an industrial method: the Statistical Process Control (SPC) has been used. SPC aims at controlling and improving the quality of a process through statistical analysis, by using two main tools: control charts and performance indices. Control charts (see Figure 1) are graphics that monitor the process over time, by using statistical control limits that distinguish random (natural) variations (i.e values within the control limits) from significant changes (special causes) that disturb the process. Thanks to the statistical control limits, the effects of special causes can be detected, and then actions can be undertaken to reduce or eliminate their effects. A process that is only subject to random causes of variation around the target value (i.e the perfect value to which each result should tend to, for instance having 0% of deviation between calculation and measurement) is statistically under control and thus statistically predictable. Performance indices quantify the ability of a process to produce data that are within predefined tolerances, at a precise moment. They give a value showing how far the results are from these tolerances and/or from the target. So, contrary to control charts, performance indices depend on the tolerances that are often chosen empirically, based on practice and experience, and thus on the QC’s method. In the presentation, we will show how SPC can be used to monitor the IMRT pre-treatment quality controls and to make the dose delivery process under control. The aim is to increase the security of each patient’s treatment while controlling the whole dose delivery process, without increasing time devoted to the analysis. We are convinced that SPC should help to secure and to improve quality of many processes in radiotherapy and could serve as a common language to evaluate processes’ performance. Moreover, the ultimate goal of SPC is, considering a process is under control, to streamline the amount of QC in a safe statistical environment by taking objective decisions to balance resources and quality. Figure 1: Example of a control chart displaying three potential special causes. This process is out of control. SP-0428 Monitoring of quality in radiotherapy using external audits M. Tomsej CHU Charleroi Hôpital André Vésale, Medical Physics, Montigny-le-