Correcting partial volume effects in biexponential T2 estimation of small lesions

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Abstract

Purpose T2 mapping provides a quantitative approach for focal liver lesion characterization. For small lesions, a biexponential model should be used to account for partial volume effects (PVE). However, conventional biexponential fitting suffers from large uncertainty of the fitted parameters when noise is present. The purpose of this work is to develop a more robust method to correct for PVE affecting small lesions. Methods We developed a region of interest-based joint biexponential fitting (JBF) algorithm to estimate the T2 of lesions affected by PVE. JBF takes advantage of the lesion fraction variation among voxels within a region of interest. JBF is compared to conventional approaches using Cramér-Rao lower bound analysis, numerical simulations, phantom, and in vivo data. Results JBF provides more accurate and precise T2 estimates in the presence of PVE. Furthermore, JBF is less sensitive to region of interest drawing. Phantom and in vivo results show that JBF can be combined with a reconstruction method for highly undersampled data, enabling the characterization of small abdominal lesions from data acquired in a single breath hold. Conclusion The JBF algorithm provides more accurate and stable T2 estimates for small structures than conventional techniques when PVE is present. It should be particularly useful for the characterization of small abdominal lesions.

Original languageEnglish (US)
Pages (from-to)1632-1642
Number of pages11
JournalMagnetic Resonance in Medicine
Volume73
Issue number4
DOIs
StatePublished - Apr 1 2015

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Joints
Uncertainty
Noise
Liver

Keywords

  • lesion classification
  • MR parameter estimation
  • partial volume effect
  • T estimation

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

@article{2968976adbbe47489b721e2db96c8b37,
title = "Correcting partial volume effects in biexponential T2 estimation of small lesions",
abstract = "Purpose T2 mapping provides a quantitative approach for focal liver lesion characterization. For small lesions, a biexponential model should be used to account for partial volume effects (PVE). However, conventional biexponential fitting suffers from large uncertainty of the fitted parameters when noise is present. The purpose of this work is to develop a more robust method to correct for PVE affecting small lesions. Methods We developed a region of interest-based joint biexponential fitting (JBF) algorithm to estimate the T2 of lesions affected by PVE. JBF takes advantage of the lesion fraction variation among voxels within a region of interest. JBF is compared to conventional approaches using Cram{\'e}r-Rao lower bound analysis, numerical simulations, phantom, and in vivo data. Results JBF provides more accurate and precise T2 estimates in the presence of PVE. Furthermore, JBF is less sensitive to region of interest drawing. Phantom and in vivo results show that JBF can be combined with a reconstruction method for highly undersampled data, enabling the characterization of small abdominal lesions from data acquired in a single breath hold. Conclusion The JBF algorithm provides more accurate and stable T2 estimates for small structures than conventional techniques when PVE is present. It should be particularly useful for the characterization of small abdominal lesions.",
keywords = "lesion classification, MR parameter estimation, partial volume effect, T estimation",
author = "Chuan Huang and Jean-Philippe Galons and Graff, {Christian G.} and Clarkson, {Eric W} and Ali Bilgin and Kalb, {Bobby T} and Martin, {Diego R} and Altbach, {Maria I}",
year = "2015",
month = "4",
day = "1",
doi = "10.1002/mrm.25250",
language = "English (US)",
volume = "73",
pages = "1632--1642",
journal = "Magnetic Resonance in Medicine",
issn = "0740-3194",
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TY - JOUR

T1 - Correcting partial volume effects in biexponential T2 estimation of small lesions

AU - Huang, Chuan

AU - Galons, Jean-Philippe

AU - Graff, Christian G.

AU - Clarkson, Eric W

AU - Bilgin, Ali

AU - Kalb, Bobby T

AU - Martin, Diego R

AU - Altbach, Maria I

PY - 2015/4/1

Y1 - 2015/4/1

N2 - Purpose T2 mapping provides a quantitative approach for focal liver lesion characterization. For small lesions, a biexponential model should be used to account for partial volume effects (PVE). However, conventional biexponential fitting suffers from large uncertainty of the fitted parameters when noise is present. The purpose of this work is to develop a more robust method to correct for PVE affecting small lesions. Methods We developed a region of interest-based joint biexponential fitting (JBF) algorithm to estimate the T2 of lesions affected by PVE. JBF takes advantage of the lesion fraction variation among voxels within a region of interest. JBF is compared to conventional approaches using Cramér-Rao lower bound analysis, numerical simulations, phantom, and in vivo data. Results JBF provides more accurate and precise T2 estimates in the presence of PVE. Furthermore, JBF is less sensitive to region of interest drawing. Phantom and in vivo results show that JBF can be combined with a reconstruction method for highly undersampled data, enabling the characterization of small abdominal lesions from data acquired in a single breath hold. Conclusion The JBF algorithm provides more accurate and stable T2 estimates for small structures than conventional techniques when PVE is present. It should be particularly useful for the characterization of small abdominal lesions.

AB - Purpose T2 mapping provides a quantitative approach for focal liver lesion characterization. For small lesions, a biexponential model should be used to account for partial volume effects (PVE). However, conventional biexponential fitting suffers from large uncertainty of the fitted parameters when noise is present. The purpose of this work is to develop a more robust method to correct for PVE affecting small lesions. Methods We developed a region of interest-based joint biexponential fitting (JBF) algorithm to estimate the T2 of lesions affected by PVE. JBF takes advantage of the lesion fraction variation among voxels within a region of interest. JBF is compared to conventional approaches using Cramér-Rao lower bound analysis, numerical simulations, phantom, and in vivo data. Results JBF provides more accurate and precise T2 estimates in the presence of PVE. Furthermore, JBF is less sensitive to region of interest drawing. Phantom and in vivo results show that JBF can be combined with a reconstruction method for highly undersampled data, enabling the characterization of small abdominal lesions from data acquired in a single breath hold. Conclusion The JBF algorithm provides more accurate and stable T2 estimates for small structures than conventional techniques when PVE is present. It should be particularly useful for the characterization of small abdominal lesions.

KW - lesion classification

KW - MR parameter estimation

KW - partial volume effect

KW - T estimation

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