title: Physiological imaging-defined, response-driven subvolumes of a tumor.
abstract: OBJECTIVE
  To develop an image analysis framework to delineate the physiological imaging-defined subvolumes of a tumor in relating to treatment response and outcome.
  
  
  METHODS
  Our proposed approach delineates the subvolumes of a tumor based on its heterogeneous distributions of physiological imaging parameters. The method assigns each voxel a probabilistic membership function belonging to the physiological parameter classes defined in a sample of tumors, and then calculates the related subvolumes in each tumor. We applied our approach to regional cerebral blood volume (rCBV) and Gd-DTPA transfer constant (K(trans)) images of patients who had brain metastases and were treated by whole-brain radiation therapy (WBRT). A total of 45 lesions were included in the analysis. Changes in the rCBV (or K(trans))-defined subvolumes of the tumors from pre-RT to 2 weeks after the start of WBRT (2W) were evaluated for differentiation of responsive, stable, and progressive tumors using the Mann-Whitney U test. Performance of the newly developed metrics for predicting tumor response to WBRT was evaluated by receiver operating characteristic (ROC) curve analysis.
  
  
  RESULTS
  The percentage decrease in the high-CBV-defined subvolumes of the tumors from pre-RT to 2W was significantly greater in the group of responsive tumors than in the group of stable and progressive tumors (P<.007). The change in the high-CBV-defined subvolumes of the tumors from pre-RT to 2W was a predictor for post-RT response significantly better than change in the gross tumor volume observed during the same time interval (P=.012), suggesting that the physiological change occurs before the volumetric change. Also, K(trans) did not add significant discriminatory information for assessing response with respect to rCBV.
  
  
  CONCLUSIONS
  The physiological imaging-defined subvolumes of the tumors delineated by our method could be candidates for boost target, for which further development and evaluation is warranted.
authors.affiliation: Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.
authors.forename: Reza
authors.initials: R
authors.lastname: Farjam
authors.forename: Christina I
authors.initials: CI
authors.lastname: Tsien
authors.forename: Felix Y
authors.initials: FY
authors.lastname: Feng
authors.forename: Diana
authors.initials: D
authors.lastname: Gomez-Hassan
authors.forename: James A
authors.initials: JA
authors.lastname: Hayman
authors.forename: Theodore S
authors.initials: TS
authors.lastname: Lawrence
authors.forename: Yue
authors.initials: Y
authors.lastname: Cao
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001810:Blood Volume / Q000502:physiology / Q000528:radiation effects*; D001932:Brain Neoplasms / Q000098:blood supply / Q000378:metabolism / Q000473:pathology / Q000532:radiotherapy* / Q000556:secondary; D002560:Cerebrovascular Circulation; D016371:Cranial Irradiation / Q000379:methods; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011446:Prospective Studies; D011879:Radiotherapy Dosage; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*; D018709:Statistics, Nonparametric; D016896:Treatment Outcome; D047368:Tumor Burden / Q000528:radiation effects*