title: Liver toxicity prediction with stereotactic body radiation therapy: The impact of accounting for fraction size.
abstract: OBJECTIVE
  Current liver SBRT protocols rely on the calculation of "effective volume" without accounting for the biologic effect of fraction size to estimate the risk of liver toxicity, which subsequently defines tumor prescription doses. This study compared effective volume and liver toxicity predictions with and without correction for fraction size.
  
  
  METHODS
  The effective volume was determined for 18 liver SBRT plans with and without biologic normalization using the linear quadratic formula. Lyman-Kutcher-Burman normal tissue complication probability models estimated the risk of liver toxicity. Effective volumes and corresponding toxicity predictions were compared with and without biologic normalization.
  
  
  RESULTS
  Accounting for the biologic difference of larger fraction size reduced the effective volume in all treatment plans compared with the unadjusted effective volume (median effective volume 0.21 vs 0.32). The lower effective volume with biologic normalization substantially reduced the estimated risk of liver toxicity (average risk of toxicity 32% vs 4.5%).
  
  
  CONCLUSIONS
  This study demonstrates that accounting for the biologic effect of fraction size with effective volume significantly decreases predicted hepatic toxicity, which suggests that the risk of liver toxicity may be overestimated in clinical practice if biologic normalization is omitted. The effective volume toxicity model has proven safe in prospective clinical trials, though safe dose escalation with liver SBRT may be feasible.
authors.affiliation: Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA. Electronic address: j2murphy@ucsd.edu.
authors.forename: James D
authors.initials: JD
authors.lastname: Murphy
authors.affiliation: Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA.
authors.forename: Jona
authors.initials: J
authors.lastname: Hattangadi-Gluth
authors.affiliation: Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA.
authors.forename: William Y
authors.initials: WY
authors.lastname: Song
authors.affiliation: British Columbia Cancer Agency, Vancouver, British Columbia, Canada.
authors.forename: Emily
authors.initials: E
authors.lastname: Vollans
authors.affiliation: British Columbia Cancer Agency, Vancouver, British Columbia, Canada.
authors.forename: Marie-Laure
authors.initials: ML
authors.lastname: Camborde
authors.affiliation: British Columbia Cancer Agency, Vancouver, British Columbia, Canada.
authors.forename: Robert
authors.initials: R
authors.lastname: Kosztyla
authors.affiliation: CancerCare Manitoba, Winnipeg, Manitoba, Canada.
authors.forename: Shaun K
authors.initials: SK
authors.lastname: Loewen
authors.affiliation: British Columbia Cancer Agency, Vancouver, British Columbia, Canada.
authors.forename: Catherine
authors.initials: C
authors.lastname: Crumley
authors.affiliation: Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA.
authors.forename: Vitali
authors.initials: V
authors.lastname: Moiseenko
mesh_terms: D019583:Dose Fractionation, Radiation; D006801:Humans; D008099:Liver / Q000473:pathology / Q000528:radiation effects*; D008113:Liver Neoplasms / Q000473:pathology / Q000556:secondary / Q000601:surgery*; D011832:Radiation Injuries / Q000209:etiology*; D016634:Radiosurgery / Q000009:adverse effects* / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012189:Retrospective Studies