The relationship between local recurrence and radiotherapy treatment volume for soft tissue sarcomas treated with external beam radiotherapy and function preservation surgery

Purpose: To examine the geometric relationship between local recurrence (LR) and external beam radiotherapy (RT) volumes for soft-tissue sarcoma (STS) patients treated with function-preserving surgery and RT. Methods and Materials: Sixty of 768 (7.8%) STS patients treated with combined therapy within our institution from 1990 through 2006 developed an LR. Thirty-two received preoperative RT, 16 postoperative RT, and 12 preoperative RT plus a postoperative boost. Treatment records, RT simulation images, and diagnostic MRI/CT data sets of the original and LR disease were retrospectively compared. For LR location analysis, three RT target volumes were defined according to the International Commission on Radiation Units and Measurements 29 as follows: (1) the gross tumor or operative bed; (2) the treatment volume (TV) extending 5 cm longitudinally beyond the tumor or operative bed unless protected by intact barriers to spread and at least 1–2 cm axially (the TV was enclosed by the isodose curve representing the prescribed target absorbed dose [TAD] and accounted for target/patient setup uncertainty and beam characteristics), and (3) the irradiated volume (IRV) that received at least 50% of the TAD, including the TV. LRs were categorized as developing in field within the TV, marginal (on the edge of the IRV), and out of field (occurring outside of the IRV). Results: Forty-nine tumors relapsed in field (6.4% overall). Nine were out of field (1.1% overall), and 2 were marginal (0.3% overall). Conclusions: The majority of STS tumors recur in field, indicating that the incidence of LR may be affected more by differences in biologic and molecular characteristics rather than aberrations in RT dose or target volume coverage. In contrast, only two patients relapsed at the IRV boundary, suggesting that the risk of a marginal relapse is low when the TV is appropriately defined. These data support the accurate delivery of optimal RT volumes in the most precise way using advanced technology and image guidance.