Vastly accelerated linear least-squares fitting with numerical optimization for dual-input delay-compensated quantitative liver perfusion mapping.

TitleVastly accelerated linear least-squares fitting with numerical optimization for dual-input delay-compensated quantitative liver perfusion mapping.
Publication TypeJournal Article
Year of Publication2018
AuthorsJafari R, Chhabra S, Prince MR, Wang Y, Spincemaille P
JournalMagn Reson Med
Volume79
Issue4
Pagination2415-2421
Date Published2018 04
ISSN1522-2594
KeywordsAlgorithms, Computer Simulation, Contrast Media, Humans, Image Processing, Computer-Assisted, Kinetics, Least-Squares Analysis, Linear Models, Liver, Liver Neoplasms, Models, Theoretical, Perfusion, Reproducibility of Results
Abstract

PURPOSE: To propose an efficient algorithm to perform dual input compartment modeling for generating perfusion maps in the liver.

METHODS: We implemented whole field-of-view linear least squares (LLS) to fit a delay-compensated dual-input single-compartment model to very high temporal resolution (four frames per second) contrast-enhanced 3D liver data, to calculate kinetic parameter maps. Using simulated data and experimental data in healthy subjects and patients, whole-field LLS was compared with the conventional voxel-wise nonlinear least-squares (NLLS) approach in terms of accuracy, performance, and computation time.

RESULTS: Simulations showed good agreement between LLS and NLLS for a range of kinetic parameters. The whole-field LLS method allowed generating liver perfusion maps approximately 160-fold faster than voxel-wise NLLS, while obtaining similar perfusion parameters.

CONCLUSIONS: Delay-compensated dual-input liver perfusion analysis using whole-field LLS allows generating perfusion maps with a considerable speedup compared with conventional voxel-wise NLLS fitting. Magn Reson Med 79:2415-2421, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

DOI10.1002/mrm.26888
Alternate JournalMagn Reson Med
PubMed ID28833534
PubMed Central IDPMC5811380
Grant ListR01 NS072370 / NS / NINDS NIH HHS / United States
S10 OD021782 / OD / NIH HHS / United States
R01 NS095562 / NS / NINDS NIH HHS / United States
R01 NS090464 / NS / NINDS NIH HHS / United States
R01 CA181566 / CA / NCI NIH HHS / United States
Related Institute: 
MRI Research Institute (MRIRI)

Weill Cornell Medicine
Department of Radiology
525 East 68th Street New York, NY 10065