title: Pretreatment diffusion-weighted and dynamic contrast-enhanced MRI for prediction of local treatment response in squamous cell carcinomas of the head and neck.
abstract: OBJECTIVE
  The objective of our study was to predict response to chemoradiation therapy in patients with head and neck squamous cell carcinoma (HNSCC) by combined use of diffusion-weighted imaging (DWI) and high-spatial-resolution, high-temporal-resolution dynamic contrast-enhanced MRI (DCE-MRI) parameters from primary tumors and metastatic nodes.
  
  
  METHODS
  Thirty-two patients underwent pretreatment DWI and DCE-MRI using a modified radial imaging sequence. Postprocessing of data included motion-correction algorithms to reduce motion artifacts. The median apparent diffusion coefficient (ADC), volume transfer constant (K(trans)), extracellular extravascular volume fraction (v(e)), and plasma volume fraction (v(p)) were computed from primary tumors and nodal masses. The quality of the DCE-MRI maps was estimated using a threshold median chi-square value of 0.10 or less. Multivariate logistic regression and receiver operating characteristic curve analyses were used to determine the best model to discriminate responders from nonresponders.
  
  
  RESULTS
  Acceptable χ(2) values were observed from 84% of primary tumors and 100% of nodal masses. Five patients with unsatisfactory DCE-MRI data were excluded and DCE-MRI data for three patients who died of unrelated causes were censored from analysis. The median follow-up for the remaining patients (n = 24) was 23.72 months. When ADC and DCE-MRI parameters (K(trans), v(e), v(p)) from both primary tumors and nodal masses were incorporated into multivariate logistic regression analyses, a considerably higher discriminative accuracy (area under the curve [AUC] = 0.85) with a sensitivity of 81.3% and specificity of 75% was observed in differentiating responders (n = 16) from nonresponders (n = 8).
  
  
  CONCLUSIONS
  The combined use of DWI and DCE-MRI parameters from both primary tumors and nodal masses may aid in prediction of response to chemoradiation therapy in patients with HNSCC.
authors.affiliation: Department of Radiology, University of Pennsylvania, 423 Guardian Dr, B6 Blockley Hall, Philadelphia, PA 19104, USA.
authors.forename: Sanjeev
authors.initials: S
authors.lastname: Chawla
authors.forename: Sungheon
authors.initials: S
authors.lastname: Kim
authors.forename: Lawrence
authors.initials: L
authors.lastname: Dougherty
authors.forename: Sumei
authors.initials: S
authors.lastname: Wang
authors.forename: Laurie A
authors.initials: LA
authors.lastname: Loevner
authors.forename: Harry
authors.initials: H
authors.lastname: Quon
authors.forename: Harish
authors.initials: H
authors.lastname: Poptani
mesh_terms: D002294:Carcinoma, Squamous Cell / Q000175:diagnosis* / Q000628:therapy; D059248:Chemoradiotherapy; D003287:Contrast Media; D038524:Diffusion Magnetic Resonance Imaging; D005260:Female; D006258:Head and Neck Neoplasms / Q000175:diagnosis* / Q000628:therapy; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008207:Lymphatic Metastasis; D018810:Magnetic Resonance Angiography; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media