title: Using susceptibility-weighted imaging to determine response to combined anti-angiogenic, cytotoxic, and radiation therapy in patients with glioblastoma multiforme.
abstract: BACKGROUND
  The goal of this study was to investigate whether the amount of hypointense signal on susceptibility-weighted imaging within the contrast-enhancing lesion (%SWI-h) on the pretreatment scan could determine response in patients with newly diagnosed glioblastoma multiforme who received external beam radiation therapy with concomitant anti-angiogenic therapy (enzastaurin) and cytotoxic chemotherapy (temozolomide).
  
  
  METHODS
  Twenty-five patients were imaged before therapy (postsurgical resection) and scanned serially every 2 months until progression. Standard clinical MR imaging and SWI were performed on a 3T scanner. %SWI-h was quantified for each patient's pretreatment scan. Time to progression and death were used to characterize patients into non-, immediate-, and sustained-response groups for both events. Cox proportional hazards models were used to assess the association between %SWI-h and both progression-free survival (PFS) and overall survival (OS). Classification and regression tree analysis were used to determine optimal cutoffs on which to split %SWI-h.
  
  
  RESULTS
  For both death- and progression-based response categories, %SWI-h was significantly higher in sustained responders than in nonresponders. Cox model coefficients showed an association between %SWI-h and PFS and OS, both in univariate analysis (PFS: hazard ratio [HR] = 0.966, 95% confidence interval [CI] = 0.942-0.988; and OS: HR = 0.945, 95% CI = 0.915-0.976) and when adjusting for baseline KPS, age, sex, and resection extent (PFS: HR = 0.968, 95% CI = 0.940 -0.994; and OS: HR = 0.943, 95% CI = 0.908 -0.976). A cutoff value of 38.1% significantly differentiated patients into 2 groups based on censored OS and into non- and intermediate-response categories based on time to progression.
  
  
  CONCLUSIONS
  These early differences suggest that SWI may be able to predict which patients would benefit most from similar combination therapies and may assist clinicians in making important decisions about patient care.
authors: Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94158. janine.lupo@ucsf.edu
authors: Janine M
authors: JM
authors: Lupo
authors: Emma
authors: E
authors: Essock-Burns
authors: Annette M
authors: AM
authors: Molinaro
authors: Soonmee
authors: S
authors: Cha
authors: Susan M
authors: SM
authors: Chang
authors: Nicholas
authors: N
authors: Butowski
authors: Sarah J
authors: SJ
authors: Nelson
mesh_terms: D000328:Adult; D000368:Aged; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use*; D001932:Brain Neoplasms / Q000401:mortality* / Q000473:pathology / Q000628:therapy; D059248:Chemoradiotherapy; D003606:Dacarbazine / Q000008:administration & dosage / Q000031:analogs & derivatives; D005260:Female; D005500:Follow-Up Studies; D005909:Glioblastoma / Q000401:mortality* / Q000473:pathology / Q000628:therapy; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007211:Indoles / Q000008:administration & dosage; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D011379:Prognosis; D015996:Survival Rate; D000077204:Temozolomide
chemical_list: D007211:Indoles; D003606:Dacarbazine; C504878:enzastaurin; D000077204:Temozolomide
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