Reduction of treatment delivery variances with a computer-controlled treatment delivery system

Purpose: To analyze treatment delivery variances for 3-D conformal therapy performed at various levels of treatment delivery automation, ranging from manual field setup to virtually complete computer-controlled treatment delivery using a computer-controlled conformal radiotherapy system. Materials and Methods: All external beam treatments performed in our department during six months of 1996 were analyzed to study treatment delivery variances versus treatment complexity. Treatments for 505 patients (40,641 individual treatment ports) on four treatment machines were studied. All treatment variances noted by treatment therapists or quality assurance reviews (39 in all) were analyzed. Machines 'M1' (CLinac (6(100))) and 'M2' (CLinac 1800) were operated in a standard manual setup mode, with no record and verify system (R/V). Machines 'M3' (CLinac 2100CD/MLC) and ''M4'' (MM50 racetrack microtron system with MLC) treated patients under the control of a computer-controlled conformal radiotherapy system (CCRS) 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, so 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 (ports), non-axial and non-coplanar plans, multi-segment intensity modulation, and pseudo-isocentric treatments (and other plans with computer-controlled table motions). Treatment delivery time was obtained from the computerized scheduling system (for manual treatments) or from CCRS system logs. Treatment therapists rotate among the machines, so this analysis does not depend on fixed therapist staff on particular machines. Results: The overall reported variance rate (all treatments, machines) was < 0.1 % per port or 0.33 % per treatment session. The rate (per machine) depended on automation and plan complexity (see table). Machine M4 (most complex plans and most automation) had the lowest variance rate. The variance rate decreased with increasing automation in spite of increasing plan complexity, while for the manual machines the variance rate increased with complexity. Note that the real variance rates on the two manual machines must be higher than shown here, while (particularly on M4) virtually all random treatment delivery errors were noted by the CCRS system and its QA checks. Treatment delivery times averaged from 14 to 23 minutes per plan, and depended on ports/plan, although this analysis is complicated by other factors. Conclusion: Use of a sophisticated computer-controlled delivery system for routine patient treatments with complex 3-D conformal plans has led to a significant decrease in treatment delivery variances, while at the same time allowing delivery of increasingly complex and sophisticated conformal plans without a significant 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 significant improvements in treatment delivery, since better plans can be delivered with significantly fewer errors, and without significantly increasing treatment time