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23 November 2017 Assessment of a statistical AIF extraction method for dynamic PET studies with 15O water and 18F fluorodeoxyglucose in locally advanced breast cancer patients
Finbarr O’Sullivan, Janet N. O'Sullivan, Jian Huang, Robert Doot, Mark Muzi, Erin Schubert, Lanell Peterson, Lisa K. Dunnwald, David M. Mankoff
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Journal of Medical Imaging, Vol. 5, Issue 1, 011010 (November 2017). https://doi.org/10.1117/1.JMI.5.1.011010
Abstract
Blood flow-metabolism mismatch from dynamic positron emission tomography (PET) studies with O <mprescripts /> <none /> 15-labeled water ( H2O) and F <mprescripts /> <none /> 18-labeled fluorodeoxyglucose (FDG) has been shown to be a promising diagnostic for locally advanced breast cancer (LABCa) patients. The mismatch measurement involves kinetic analysis with the arterial blood time course (AIF) as an input function. We evaluate the use of a statistical method for AIF extraction (SAIF) in these studies. Fifty three LABCa patients had dynamic PET studies with H2O and FDG. For each PET study, two AIFs were recovered, an SAIF extraction and also a manual extraction based on a region of interest placed over the left ventricle (LV-ROI). Blood flow-metabolism mismatch was obtained with each AIF, and kinetic and prognostic reliability comparisons were made. Strong correlations were found between kinetic assessments produced by both AIFs. SAIF AIFs retained the full prognostic value, for pathologic response and overall survival, of LV-ROI AIFs.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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Finbarr O’Sullivan, Janet N. O'Sullivan, Jian Huang, Robert Doot, Mark Muzi, Erin Schubert, Lanell Peterson, Lisa K. Dunnwald, and David M. Mankoff "Assessment of a statistical AIF extraction method for dynamic PET studies with 15O water and 18F fluorodeoxyglucose in locally advanced breast cancer patients," Journal of Medical Imaging 5(1), 011010 (23 November 2017). https://doi.org/10.1117/1.JMI.5.1.011010
Received: 30 May 2017; Accepted: 25 October 2017; Published: 23 November 2017
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Cited by 6 scholarly publications.
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KEYWORDS
Blood
Positron emission tomography
Breast cancer
Statistical analysis
Data modeling
Tissues
Diagnostics
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