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Title: Dynamic Contrast-Enhanced MRI in Head-and-Neck Cancer: The Impact of Region of Interest Selection on the Intra- and Interpatient Variability of Pharmacokinetic Parameters

Abstract

Purpose: Dynamic contrast-enhanced (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 (K{sup trans}), the extracellular volume fraction (v{sub e}), and the initial area under the concentration time curve (iAUC{sub 1min}). 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 betweenmore » 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 0.14-0.24, 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 (0.6-1.27 for baseline) and 0.54-0.95 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.« less

Authors:
 [1];  [1];  [2];  [3];  [1]; ;  [4];  [1];  [5]
  1. Department of Radiation Oncology, Duke University Medical Center, Durham, NC (United States)
  2. GECAD Ghana Ltd., Acra (Ghana)
  3. iCAD Inc., Nashua, NH (United States)
  4. Department of Radiology, Duke University Medical Center, Durham, NC (United States)
  5. (United States)
Publication Date:
OSTI Identifier:
22056095
Resource Type:
Journal Article
Journal Name:
International Journal of Radiation Oncology, Biology and Physics
Additional Journal Information:
Journal Volume: 82; Journal Issue: 3; Other Information: Copyright (c) 2012 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0360-3016
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; DISPERSIONS; HEAD; LYMPH NODES; NECK; NEOPLASMS; NMR IMAGING; PATIENTS; PHYSIOLOGY; RADIOTHERAPY; TRANSFER FUNCTIONS

Citation Formats

Craciunescu, Oana I., E-mail: oana.craciunescu@duke.edu, Yoo, David S., Cleland, Esi, Muradyan, Naira, Carroll, Madeline D., MacFall, James R., Barboriak, Daniel P., Brizel, David M., and Department of Surgery, Duke University Medical Center, Durham, NC. Dynamic Contrast-Enhanced MRI in Head-and-Neck Cancer: The Impact of Region of Interest Selection on the Intra- and Interpatient Variability of Pharmacokinetic Parameters. United States: N. p., 2012. Web. doi:10.1016/J.IJROBP.2011.05.059.
Craciunescu, Oana I., E-mail: oana.craciunescu@duke.edu, Yoo, David S., Cleland, Esi, Muradyan, Naira, Carroll, Madeline D., MacFall, James R., Barboriak, Daniel P., Brizel, David M., & Department of Surgery, Duke University Medical Center, Durham, NC. Dynamic Contrast-Enhanced MRI in Head-and-Neck Cancer: The Impact of Region of Interest Selection on the Intra- and Interpatient Variability of Pharmacokinetic Parameters. United States. doi:10.1016/J.IJROBP.2011.05.059.
Craciunescu, Oana I., E-mail: oana.craciunescu@duke.edu, Yoo, David S., Cleland, Esi, Muradyan, Naira, Carroll, Madeline D., MacFall, James R., Barboriak, Daniel P., Brizel, David M., and Department of Surgery, Duke University Medical Center, Durham, NC. Thu . "Dynamic Contrast-Enhanced MRI in Head-and-Neck Cancer: The Impact of Region of Interest Selection on the Intra- and Interpatient Variability of Pharmacokinetic Parameters". United States. doi:10.1016/J.IJROBP.2011.05.059.
@article{osti_22056095,
title = {Dynamic Contrast-Enhanced MRI in Head-and-Neck Cancer: The Impact of Region of Interest Selection on the Intra- and Interpatient Variability of Pharmacokinetic Parameters},
author = {Craciunescu, Oana I., E-mail: oana.craciunescu@duke.edu and Yoo, David S. and Cleland, Esi and Muradyan, Naira and Carroll, Madeline D. and MacFall, James R. and Barboriak, Daniel P. and Brizel, David M. and Department of Surgery, Duke University Medical Center, Durham, NC},
abstractNote = {Purpose: Dynamic contrast-enhanced (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 (K{sup trans}), the extracellular volume fraction (v{sub e}), and the initial area under the concentration time curve (iAUC{sub 1min}). 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 0.14-0.24, 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 (0.6-1.27 for baseline) and 0.54-0.95 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.},
doi = {10.1016/J.IJROBP.2011.05.059},
journal = {International Journal of Radiation Oncology, Biology and Physics},
issn = {0360-3016},
number = 3,
volume = 82,
place = {United States},
year = {2012},
month = {3}
}