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Evaluation of intravoxel incoherent motion fitting methods in low‐perfused tissue
Author(s) -
Meeus Emma M.,
Novak Jan,
Withey Stephanie B.,
Zarinabad Niloufar,
Dehghani Hamid,
Peet Andrew C.
Publication year - 2017
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.25730
Subject(s) - intravoxel incoherent motion , reproducibility , robustness (evolution) , nuclear medicine , mathematics , computer science , diffusion mri , magnetic resonance imaging , medicine , statistics , chemistry , radiology , biochemistry , gene
Purpose To investigate the robustness of constrained and simultaneous intravoxel incoherent motion (IVIM) fitting methods and the estimated IVIM parameters ( D, D* and f ) for applications in brain and low‐perfused tissues. Materials and Methods Model data simulations relevant to brain and low‐perfused tumor tissues were computed to assess the accuracy, relative bias, and reproducibility (CV%) of the fitting methods in estimating the IVIM parameters. The simulations were performed at a series of signal‐to‐noise ratio (SNR) levels to assess the influence of noise on the fitting. Results The estimated IVIM parameters from model simulations were found significantly different ( P < 0.05) using simultaneous and constrained fitting methods at low SNR. Higher accuracy and reproducibility were achieved with the constrained fitting method. Using this method, the mean error (%) for the estimated IVIM parameters at a clinically relevant SNR = 40 were D 0.35, D * 41.0 and f 4.55 for the tumor model and D 1.87, D * 2.48, and f 7.49 for the gray matter model. The most robust parameters were the IVIM‐ D and IVIM‐ f . The IVIM‐ D * was increasingly overestimated at low perfusion. Conclusion A constrained IVIM fitting method provides more accurate and reproducible IVIM parameters in low‐perfused tissue compared with simultaneous fitting. Level of Evidence : 3 J. MAGN. RESON. IMAGING 2017;45:1325–1334