THE IMPACT OF TREATMENT COMPLEXITY AND COMPUTER-CONTROL DELIVERY TECHNOLOGY ON TREATMENT DELIVERY ERRORS

Purpose: To analyze treatment delivery errors for three-dimensional (3 D) conformal therapy performed at various levels of treatment delivery automation and complexity, ranging from manual field setup to virtual ly complete computer-controlled treatment delivery using a computer-co ntrolled 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 sessio ns (114,000 individual treatment segments [ports]) on four treatment m achines were studied. All treatment delivery errors logged by treatmen t therapists or quality assurance reviews (152 in all) were analyzed. Machines ''M1'' and ''M2'' were operated in a standard manual setup mo de, with no record and verify system (RN). MLC machines ''M3'' and ''M 4'' treated patients under the control of the CCRS system, which (1) d ownloads the treatment delivery plan from the planning system; (2) per forms some (or all) of the machine set up and treatment delivery for e ach 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; thref ore, it uses as many CCRS features as possible, while M4 operates comp letely under CCRS control and performs semi-automated and automated mu lti-segment intensity modulated treatments. Analysis of treatment comp lexity was based on numbers of fields, individual segments, nonaxial a nd noncoplanar plans, multisegment intensity modulation, and pseudoiso centric treatments studied for a 6-month period (505 patients) concurr ent with the period in which the delivery errors were obtained. Treatm ent delivery time was obtained from the computerized scheduling system (for manual treatments) or from CCRS system logs. Treatment therapist s 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 aut omation and plan complexity. The error rates per segment for machines M1 through M4 were 0.16%, 0.27%, 0.12%, 0.05%, respectively, while pla n complexity increased from M1 up to machine M4. Machine M4 (the most complex plans and automation) had the lowest error rate. The error rat e decreased with increasing automation in spite of increasing plan com plexity, 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 unrep orted errors), while (particularly on M4) virtually all random treatme nt delivery errors were noted by the CCRS system and related QA checks (including routine checks of machine and table readouts for each trea tment). Treatment delivery times averaged from 14 min to 23 min per pl an, and depended on the number of segments/plan, although this analysi s is complicated by other factors. Conclusion: Use of a sophisticated computer-controlled delivery system for routine patient treatments wit h complex 3D conformal plans has led to a decrease in treatment delive ry errors, while at the same time allowing delivery of increasingly co mplex and sophisticated conformal plans with little increase in treatm ent time. With renewed vigilance for the possibility of systematic pro blems, it is clear that use of complete and integrated computer-contro lled delivery systems can provide improvements in treatment delivery, since more complex plans can be delivered with fewer errors, and witho ut increasing treatment time. (C) 1998 Elsevier Science Inc.