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An analysis of the uncertainty and bias in DCE-MRI measurements using the spoiled gradient-recalled echo pulse sequence.

Publication ,  Journal Article
Subashi, E; Choudhury, KR; Johnson, GA
Published in: Med Phys
March 2014

PURPOSE: The pharmacokinetic parameters derived from dynamic contrast-enhanced (DCE) MRI have been used in more than 100 phase I trials and investigator led studies. A comparison of the absolute values of these quantities requires an estimation of their respective probability distribution function (PDF). The statistical variation of the DCE-MRI measurement is analyzed by considering the fundamental sources of error in the MR signal intensity acquired with the spoiled gradient-echo (SPGR) pulse sequence. METHODS: The variance in the SPGR signal intensity arises from quadrature detection and excitation flip angle inconsistency. The noise power was measured in 11 phantoms of contrast agent concentration in the range [0-1] mM (in steps of 0.1 mM) and in onein vivo acquisition of a tumor-bearing mouse. The distribution of the flip angle was determined in a uniform 10 mM CuSO4 phantom using the spin echo double angle method. The PDF of a wide range of T1 values measured with the varying flip angle (VFA) technique was estimated through numerical simulations of the SPGR equation. The resultant uncertainty in contrast agent concentration was incorporated in the most common model of tracer exchange kinetics and the PDF of the derived pharmacokinetic parameters was studied numerically. RESULTS: The VFA method is an unbiased technique for measuringT1 only in the absence of bias in excitation flip angle. The time-dependent concentration of the contrast agent measured in vivo is within the theoretically predicted uncertainty. The uncertainty in measuring K(trans) with SPGR pulse sequences is of the same order, but always higher than, the uncertainty in measuring the pre-injection longitudinal relaxation time (T10). The lowest achievable bias/uncertainty in estimating this parameter is approximately 20%-70% higher than the bias/uncertainty in the measurement of the pre-injection T1 map. The fractional volume parameters derived from the extended Tofts model were found to be extremely sensitive to the variance in signal intensity. The SNR of the pre-injection T1 map indicates the limiting precision with which K(trans) can be calculated. CONCLUSIONS: Current small-animal imaging systems and pulse sequences robust to motion artifacts have the capacity for reproducible quantitative acquisitions with DCE-MRI. In these circumstances, it is feasible to achieve a level of precision limited only by physiologic variability.

Duke Scholars

Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

March 2014

Volume

41

Issue

3

Start / End Page

032301

Location

United States

Related Subject Headings

  • Uncertainty
  • Time Factors
  • Reproducibility of Results
  • Probability
  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Neoplasms, Experimental
  • Neoplasm Transplantation
  • Models, Statistical
  • Mice, Nude
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Subashi, E., Choudhury, K. R., & Johnson, G. A. (2014). An analysis of the uncertainty and bias in DCE-MRI measurements using the spoiled gradient-recalled echo pulse sequence. Med Phys, 41(3), 032301. https://doi.org/10.1118/1.4865790
Subashi, Ergys, Kingshuk R. Choudhury, and G Allan Johnson. “An analysis of the uncertainty and bias in DCE-MRI measurements using the spoiled gradient-recalled echo pulse sequence.Med Phys 41, no. 3 (March 2014): 032301. https://doi.org/10.1118/1.4865790.
Subashi, Ergys, et al. “An analysis of the uncertainty and bias in DCE-MRI measurements using the spoiled gradient-recalled echo pulse sequence.Med Phys, vol. 41, no. 3, Mar. 2014, p. 032301. Pubmed, doi:10.1118/1.4865790.

Published In

Med Phys

DOI

EISSN

2473-4209

Publication Date

March 2014

Volume

41

Issue

3

Start / End Page

032301

Location

United States

Related Subject Headings

  • Uncertainty
  • Time Factors
  • Reproducibility of Results
  • Probability
  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Neoplasms, Experimental
  • Neoplasm Transplantation
  • Models, Statistical
  • Mice, Nude