OPTIMIZING THE TIME-COURSE OF BRACHYTHERAPY AND OTHER ACCELERATED RADIOTHERAPEUTIC PROTOCOLS

Purpose: It is likely that early-responding tissues, such as tumors, repair sublethal damage more rapidly than do late-responding tissues. This difference can be exploited to design protocols with a significantly improved therapeutic advantage for accelerated radiotherapeutic regimens, including brachytherapy. Methods and Materials: The time course of potential protocols is computer optimized, maximizing the therapeutic difference between tumor-control probability (TCP), and normal-tissue complication probability (NTCP). These quantities are evaluated with the linear-quadratic model, using clinically derived parameters. The optimization is performed by individually adjusting doses in different parts of the treatment, maximizing the therapeutic advantage. In the main calculations, half times for damage repair were T-1/2(late) = 4 h, T-1/2(early) = 0.5 h. Two component (fast/slow) repair processes were also investigated. Results: Protocols determined by optimization have significantly greater therapeutic advantage than continuous low-dose rate (CLDR) protocols of the same overall dose and time. The optimized protocols are either (a) acute-dose/gap/CLDR/gap/acute-dose; or (b) a series of acute doses separated by 3-4 h. As a typical example, results are given for 60 Gy/120 h CLDR brachytherapy, which is assumed to give NTCP = 0.2 and TCP = 0.8. Under our assumptions, optimized regimes, with the same overall time and dose, produce an NTCP of similar to 0.11 and TCP of similar to 0.83, a significant therapeutic gain over CLDR. Conclusion: Difference in repair rates between early- and late-responding tissues can be exploited to produce clinically practical protocols that are significantly superior to current regimens. Such optimized protocols produce slightly better tumor control than CLDR with the same overall dose and time, significantly less late damage, and similar early normal-tissue sequellae. Temporal optimization, thus, promises to be a powerful tool in designing better treatment protocols.