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Purpose: To analyze treatment delivery errors for three-dimensional (3D) conformal therapy performed at various levels of treatment delivery automation and complexity, ranging from manual field setup to virtually complete computer-controlled treatment delivery using a computer-controlled conformal radiotherapy system (CCRS). Methods and Materials: All treatment delivery errors which occurred in our department during a 15-month period were analyzed. Approximately 34,000 treatment sessions (114,000 individual treatment segments [ports]) on four treatment machines were studied. All treatment delivery errors logged by treatment therapists or quality assurance reviews (152 in all) were analyzed. Machines “M1” and “M2” were operated in a standard manual setup mode, with no record and verify system (R/V). MLC machines “M3” and “M4” treated patients under the control of the CCRS system, which (1) downloads the treatment delivery plan from the planning system; (2) performs some (or all) of the machine set up and treatment delivery for each field; (3) monitors treatment delivery; (4) records all treatment parameters; and (5) notes exceptions to the electronically-prescribed plan. Complete external computer control is not available on M3; threfore, it uses as many CCRS features as possible, while M4 operates completely under CCRS control and performs semi-automated and automated multi-segment intensity modulated treatments. Analysis of treatment complexity was based on numbers of fields, individual segments, nonaxial and noncoplanar plans, multisegment intensity modulation, and pseudoisocentric treatments studied for a 6-month period (505 patients) concurrent with the period in which the delivery errors were obtained. Treatment delivery time was obtained from the computerized scheduling system (for manual treatments) or from CCRS system logs. Treatment therapists rotate among the machines; therefore, this analysis does not depend on fixed therapist staff on particular machines. Results: The overall reported error rate (all treatments, machines) was 0.13% per segment, or 0.44% per treatment session. The rate (per machine) depended on automation and plan complexity. The error rates per segment for machines M1 through M4 were 0.16%, 0.27%, 0.12%, 0.05%, respectively, while plan complexity increased from M1 up to machine M4. Machine M4 (the most complex plans and automation) had the lowest error rate. The error rate decreased with increasing automation in spite of increasing plan complexity, while for the manual machines, the error rate increased with complexity. Note that the real error rates on the two manual machines are likely to be higher than shown here (due to unnoticed and/or unreported errors), while (particularly on M4) virtually all random treatment delivery errors were noted by the CCRS system and related QA checks (including routine checks of machine and table readouts for each treatment). Treatment delivery times averaged from 14 min to 23 min per plan, and depended on the number of segments/plan, although this analysis is complicated by other factors. Conclusion: Use of a sophisticated computer-controlled delivery system for routine patient treatments with complex 3D conformal plans has led to a decrease in treatment delivery errors, while at the same time allowing delivery of increasingly complex and sophisticated conformal plans with little increase in treatment time. With renewed vigilance for the possibility of systematic problems, it is clear that use of complete and integrated computer-controlled delivery systems can provide improvements in treatment delivery, since more complex plans can be delivered with fewer errors, and without increasing treatment time.

Purpose : The design and implementation of a system for electronically tracking relevant plan, prescription, and treatment data for computer-controlled conformal radiation therapy is described. Methods and Materials : The electronic charting system is implemented on a computer cluster coupled by high-speed networks to computer-controlled therapy machines. A methodical approach to the specification and design of an integrated solution has been used in developing the system. The electronic chart system is designed to allow identification and access of patient-specific data including treatment-planning data, treatment prescription information, and charting of doses. An in-house developed database system is used to provide an integrated approach to the database requirements of the design. A hierarchy of databases is used for both centralization and distribution of the treatment data for specific treatment machines. Results : The basic electronic database system has been implemented and has been in use since July 1993. The system has been used to download and manage treatment data on all patients treated on our first fully computer-controlled treatment machine. To date, electronic dose charting functions have not been fully implemented clinically, requiring the continued use of paper charting for dose tracking. Conclusions : The routine clinical application of complex computer-controlled conformal treatment procedures requires the management of large quantities of information for describing and tracking treatments. An integrated and comprehensive approach to this problem has led to a full electronic chart for conformal radiation therapy treatments.

PURPOSE: A sequence processor (SP) is described as part of a larger computer-controlled conformal radiotherapy system (CCRS). The SP provides the means to accept and then translate highly sophisticated radiation therapy treatment plans into vendor specific instructions to control treatment delivery on a computer-controlled treatment machine. METHODS AND MATERIALS: The sequence processor (SP) is a small workstation computer that interfaces to the control computer of computer-controlled treatment machines, and to other parts of the larger CCRS system. The system reported here has been interfaced to a computer-controlled racetrack microtron with two treatment gantries, and also to other linear accelerator treatment machines equipped with multileaf collimators. An extensive design process has been used in defining the role of the SP within the context of the larger CCRS project. Flexibility and integration with various components of the project, including databases, treatment planning system, graphical simulator, were key factors in the development. In conjunction with the planned set of treatment fields, a procedural scripting language is used to define the sequence of treatment events that are performed, including operator interactions, communications to other systems such as dosimetry and portal imaging devices, and database management. RESULTS: A flexible system has been developed to allow investigation into procedural steps required for simulating and delivering complex radiation treatments. The system has been used to automate portions of the acceptance testing for the control system of the microtron, and is used for routine daily quality assurance testing. The sequence processor system described here has been used to deliver all clinical treatments performed on the microtron system in 2 years of clinical treatment (more than 200 patients treated to a variety of treatment sites). CONCLUSIONS: The sequence processor system has enabled the delivery of complex treatment using computer-controlled treatment machines. The flexibility of the system allows integration with secondary devices and modification of procedural steps, making it possible to develop effective techniques for insuring safe and efficient computer-controlled conformal radiation therapy treatments.

Purpose : This paper describes a new technique for manually drawing contours of anatomy over image data for the purposes of radiation therapy treatment planning. Methods and Materials : A large area rear-projectible digitizer tablet is used together with a projection TV system to display computer graphics and image data. Large images of computed tomography or magnetic resonance cross-sections are displayed and the digitizer is used to directly trace outlines of important organs. Digitizer menus allow multiple functions for selecting images and structures, for changing the grayscale level and window, and for zooming and roaming the image. Results : This device has been in clinical operation for many years and has proven to greatly increase the speed of entering cross-sectional outlines defined for serial computed tomography images sets. A small timing study of clinical usage demonstrates up to a factor of ten improvement in the speed of contour entry. Conclusion : For 3-dimensional radiation therapy, tumor, and target volumes, as well as important critical organs, must be delineated from serial sets of computed tomography or magnetic resonance images. Often 30 or more slices must be considered and the process of outlining structures on this number of slices can represent a significant fraction of the total treatment planning time. The device described in this paper greatly improve the ease and speed of manual contour entry for 3-dimensional radiation therapy planning.

Most commercially available ultrasound imaging systems currently implement the delay and sum (DAS) beamforming. Alternative beamformers have been presented, offering higher performance at the expense of computational complexity, which has so far limited their practical real-time implementation. In particular, the Filtered-Delay Multiply and Sum (F-DMAS) beamformer, which adds the computation of signed square roots, absolute values and multiplications to DAS, was recently shown to be effective in improving resolution, dynamic range and overall image quality. In this work, we present the real-time implementation of the F-DMAS beamformer on the ULA-OP 256 research system. This is obtained through a reformulation of the F-DMAS algorithm that allows reducing its computational cost. Compared to DAS, F-DMAS images of a commercial phantom captured in real-time showed higher CR (up to +7 dB), better spatial resolution (up to 30%), but lower CNR (-40%).