- 作者：Oana I. Craciunescu ; Ph.D.&lowast ; ; oana.craciunescu@duke.edu ; David S. Yoo ; M.D. ; Ph.D.&lowast ; ; Esi Cleland ; M.S.&dagger ; ; Naira Muradyan ; Ph.D.&Dagger ; ; Madeline D. Carroll ; M.S.A.&lowast ; ; James R. MacFall ; Ph.D.§ ; ; Daniel P. Barboriak ; M.D.§ ; ; David M. Brizel ; M.D.&lowast ; ; ¶ ;
- 关键词：DCE-MRI ; Head and neck cancer ; Pharmacokinetic analysis ; ROI
- 刊名：International Journal of Radiation Oncology*Biology*Physics
- 出版年：2012
- 出版时间：1 March 2012
- 年：2012
- 卷：82
- 期：3
- 页码：e345-e350
- 全文大小：623 K
Purpose
Dynamic contrast¨Cenhanced (DCE) MRI-extracted parameters measure tumor microvascular physiology and are usually calculated from an intratumor region of interest (ROI). Optimal ROI delineation is not established. The valid clinical use of DCE-MRI requires that the variation for any given parameter measured within a tumor be less than that observed between tumors in different patients. This work evaluates the impact of tumor ROI selection on the assessment of intra- and interpatient variability.Method and Materials
Head and neck cancer patients received initial targeted therapy (TT) treatment with erlotinib and/or bevacizumab, followed by radiotherapy and concurrent cisplatin with synchronous TT. DCE-MRI data from Baseline and the end of the TT regimen (Lead-In) were analyzed to generate the vascular transfer function (Ktrans), the extracellular volume fraction (ve), and the initial area under the concentration time curve (iAUC1 min). Four ROI sampling strategies were used: whole tumor or lymph node (Whole), the slice containing the most enhancing voxels (SliceMax), three slices centered in SliceMax (Partial), and the 5 % most enhancing contiguous voxels within SliceMax (95Max). The average coefficient of variation (aCV) was calculated to establish intrapatient variability among ROI sets and interpatient variability for each ROI type. The average ratio between each intrapatient CV and the interpatient CV was calculated (aRCV).
Results
Baseline primary/nodes aRCVs for different ROIs not including 95Max were, for all three MR parameters, in the range of 0.14?.24, with Lead-In values between 0.09 and 0.2, meaning a low intrapatient vs. interpatient variation. For 95Max, intrapatient CVs approximated interpatient CVs, meaning similar data dispersion and higher aRCVs (0.6?.27 for baseline) and 0.54?.95 for Lead-In.
Conclusion
Distinction between different patient¡¯s primary tumors and/or nodes cannot be made using 95Max ROIs. The other three strategies are viable and equivalent for using DCE-MRI to measure head and neck cancer physiology.