title: The tumor radiobiology of SRS and SBRT: are more than the 5 Rs involved?
abstract: Stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT), also known as stereotactic ablative radiation therapy (SABR), are rapidly becoming accepted practice for the radiation therapy of certain tumors. Typically, SRS and SBRT involve the delivery of 1 or a few large-dose fractions of 8 to 30 Gy per fraction: a major paradigm shift from radiation therapy practice over the past 90 years, when, with relatively large amounts of normal tissues receiving high doses, the goal was to maximize tumor response for an acceptable level of normal tissue injury. The development of SRS and SBRT have come about because of technologic advances in image guidance and treatment delivery techniques that enable the delivery of large doses to tumors with reduced margins and high gradients outside the target, thereby minimizing doses to surrounding normal tissues. Because the results obtained with SRS and SBRT have been impressive, they have raised the question whether classic radiobiological modeling, and the linear-quadratic (LQ) model, are appropriate for large doses per fraction. In addition to objections to the LQ model, the possibility of additional biological effects resulting from endothelial cell damage, enhanced tumor immunity, or both have been raised to account for the success of SRS and SBRT. In this review, we conclude that the available preclinical and clinical data do not support a need to change the LQ model or to invoke phenomena over and above the classic 5 Rs of radiobiology and radiation therapy, with the likely exception that for some tumors high doses of irradiation may produce enhanced antitumor immunity. Thus, we suggest that for most tumors, the standard radiobiology concepts of the 5 Rs are sufficient to explain the clinical data, and the excellent results obtained from clinical studies are the result of the much larger biologically effective doses that are delivered with SRS and SBRT.
authors.affiliation: Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California. Electronic address: mbrown@stanford.edu.
authors.forename: J Martin
authors.initials: JM
authors.lastname: Brown
authors.affiliation: Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut.
authors.forename: David J
authors.initials: DJ
authors.lastname: Carlson
authors.affiliation: Center for Radiological Research, Columbia University Medical Center, New York, New York.
authors.forename: David J
authors.initials: DJ
authors.lastname: Brenner
mesh_terms: D000465:Algorithms; D000818:Animals; D002453:Cell Cycle / Q000528:radiation effects; D015687:Cell Hypoxia / Q000502:physiology / Q000528:radiation effects; D049109:Cell Proliferation / Q000528:radiation effects; D002470:Cell Survival / Q000502:physiology / Q000528:radiation effects; D004249:DNA Damage; D004260:DNA Repair; D019583:Dose Fractionation, Radiation; D042783:Endothelial Cells / Q000528:radiation effects; D006801:Humans; D016014:Linear Models; D008545:Melanoma / Q000276:immunology / Q000601:surgery; D051379:Mice; D008954:Models, Biological; D009369:Neoplasms / Q000098:blood supply / Q000473:pathology / Q000503:physiopathology / Q000532:radiotherapy / Q000601:surgery*; D010101:Oxygen Consumption; D011836:Radiation Tolerance / Q000528:radiation effects; D011853:Radiobiology; D016634:Radiosurgery / Q000379:methods / Q000706:statistics & numerical data / Q000639:trends; D012062:Relative Biological Effectiveness