title: Dynamic contrast-enhanced perfusion processing for neuroradiologists: model-dependent analysis may not be necessary for determining recurrent high-grade glioma versus treatment effect.
abstract: OBJECTIVE
  Dynamic contrast-enhanced perfusion MR imaging has proved useful in determining whether a contrast-enhancing lesion is secondary to recurrent glial tumor or is treatment-related. In this article, we explore the best method for dynamic contrast-enhanced data analysis.
  
  
  METHODS
  We retrospectively reviewed 24 patients who met the following conditions: 1) had at least an initial treatment of a glioma, 2) underwent a half-dose contrast agent (0.05-mmol/kg) diagnostic-quality dynamic contrast-enhanced perfusion study for an enhancing lesion, and 3) had a diagnosis by pathology within 30 days of imaging. The dynamic contrast-enhanced data were processed by using model-dependent analysis (nordicICE) using a 2-compartment model and model-independent signal intensity with time. Multiple methods of determining the vascular input function and numerous perfusion parameters were tested in comparison with a pathologic diagnosis.
  
  
  RESULTS
  The best accuracy (88%) with good correlation compared with pathology (P = .005) was obtained by using a novel, model-independent signal-intensity measurement derived from a brief integration beginning after the initial washout and by using the vascular input function from the superior sagittal sinus for normalization. Modeled parameters, such as mean endothelial transfer constant > 0.05 minutes(-1), correlated (P = .002) but did not reach a diagnostic accuracy equivalent to the model-independent parameter.
  
  
  CONCLUSIONS
  A novel model-independent dynamic contrast-enhanced analysis method showed diagnostic equivalency to more complex model-dependent methods. Having a brief integration after the first pass of contrast may diminish the effects of partial volume macroscopic vessels and slow progressive enhancement characteristic of necrosis. The simple modeling is technique- and observer-dependent but is less time-consuming.
authors.affiliation: From the Department of Diagnostic Radiology, Section of Neuroimaging (J.D.H., C.I., N.E.L., L.K., A.J.K.) Radiology Partners Houston (J.D.H.), Houston, Texas Jackson.hamilton@radpartners.com.
authors.forename: J D
authors.initials: JD
authors.lastname: Hamilton
authors.affiliation: Department of Imaging Physics, Section of MRI Physics (J.L., E.F.J.) Rice University (J.L.), Houston, Texas Baylor College of Medicine (J.L.), Houston, Texas.
authors.forename: J
authors.initials: J
authors.lastname: Lin
authors.affiliation: From the Department of Diagnostic Radiology, Section of Neuroimaging (J.D.H., C.I., N.E.L., L.K., A.J.K.).
authors.forename: C
authors.initials: C
authors.lastname: Ison
authors.affiliation: From the Department of Diagnostic Radiology, Section of Neuroimaging (J.D.H., C.I., N.E.L., L.K., A.J.K.).
authors.forename: N E
authors.initials: NE
authors.lastname: Leeds
authors.affiliation: Department of Imaging Physics, Section of MRI Physics (J.L., E.F.J.).
authors.forename: E F
authors.initials: EF
authors.lastname: Jackson
authors.affiliation: Department of Pathology, Section of Neuropathology (G.N.F.), The University of Texas M.D. Anderson Cancer Center, Houston, Texas.
authors.forename: G N
authors.initials: GN
authors.lastname: Fuller
authors.affiliation: From the Department of Diagnostic Radiology, Section of Neuroimaging (J.D.H., C.I., N.E.L., L.K., A.J.K.).
authors.forename: L
authors.initials: L
authors.lastname: Ketonen
authors.affiliation: From the Department of Diagnostic Radiology, Section of Neuroimaging (J.D.H., C.I., N.E.L., L.K., A.J.K.).
authors.forename: A J
authors.initials: AJ
authors.lastname: Kumar
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001921:Brain / Q000473:pathology; D001932:Brain Neoplasms / Q000175:diagnosis*; D003287:Contrast Media; D005260:Female; D005910:Glioma / Q000175:diagnosis*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D009364:Neoplasm Recurrence, Local / Q000175:diagnosis*; D010477:Perfusion; D012189:Retrospective Studies
chemical_list: D003287:Contrast Media