Literature DB >> 7658236

Factor analysis for extraction of blood time-activity curves in dynamic FDG-PET studies.

H M Wu1, C K Hoh, Y Choi, H R Schelbert, R A Hawkins, M E Phelps, S C Huang.   

Abstract

UNLABELLED: Arterial sampling in dynamic PET studies can be eliminated by using left ventricular or aortic time-activity curves (TAC) obtained from user drawn regions of interest (ROIs) after appropriate spillover correction. In this study, we evaluated the feasibility of extracting the "pure" arterial TAC from dynamic PET images using factor analysis of dynamic structures (FADS).
METHODS: Computer simulations were used to study the performance of the FADS algorithm with positivity constraints. Ten canine 13N-ammonia and two human FDG-PET dynamic studies were used to extract the blood TACs from FADS. Plasma samples and compartmental model fittings were used to validate the accuracy of the FADS-generated blood factors.
RESULTS: We found that FADS with positivity constraints was sufficient to extract the blood factor from the composite dynamic images. The "pure" blood-pool TACs that matched well with the arterialized well counter measurements were generated from FADS in the canine and human studies.
CONCLUSION: FADS has the potential to accurately extract "pure" blood TAC from dynamic PET images, allowing reliable quantitation of biological information from PET studies without blood sampling, ROI drawing or spillover correction.

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Year:  1995        PMID: 7658236

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  29 in total

1.  Left atrial versus left ventricular input function for quantification of the myocardial blood flow with nitrogen-13 ammonia and positron emission tomography.

Authors:  Jens D Hove; Hidehiro Iida; Klaus F Kofoed; Jacob Freiberg; Søren Holm; Henning Kelbaek
Journal:  Eur J Nucl Med Mol Imaging       Date:  2003-10-10       Impact factor: 9.236

Review 2.  Quantification of myocardial blood flow and flow reserve: Technical aspects.

Authors:  Ran Klein; Rob S B Beanlands; Robert A deKemp
Journal:  J Nucl Cardiol       Date:  2010-08       Impact factor: 5.952

3.  An internet-based "kinetic imaging system" (KIS) for MicroPET.

Authors:  Sung-Cheng Huang; David Truong; Hsiao-Ming Wu; Arion F Chatziioannou; Weber Shao; Anna M Wu; Michael E Phelps
Journal:  Mol Imaging Biol       Date:  2005 Sep-Oct       Impact factor: 3.488

4.  Hybrid image and blood sampling input function for quantification of small animal dynamic PET data.

Authors:  Kooresh I Shoghi; Michael J Welch
Journal:  Nucl Med Biol       Date:  2007-09-19       Impact factor: 2.408

Review 5.  Image-derived input function for brain PET studies: many challenges and few opportunities.

Authors:  Paolo Zanotti-Fregonara; Kewei Chen; Jeih-San Liow; Masahiro Fujita; Robert B Innis
Journal:  J Cereb Blood Flow Metab       Date:  2011-08-03       Impact factor: 6.200

6.  Simultaneous estimation of input functions: an empirical study.

Authors:  R Todd Ogden; Francesca Zanderigo; Stephen Choy; J John Mann; Ramin V Parsey
Journal:  J Cereb Blood Flow Metab       Date:  2009-12-09       Impact factor: 6.200

Review 7.  What is the current status of quantification and nuclear medicine in cardiology?

Authors:  G Hör
Journal:  Eur J Nucl Med       Date:  1996-07

8.  Clustering-initiated factor analysis application for tissue classification in dynamic brain positron emission tomography.

Authors:  Rostyslav Boutchko; Debasis Mitra; Suzanne L Baker; William J Jagust; Grant T Gullberg
Journal:  J Cereb Blood Flow Metab       Date:  2015-04-22       Impact factor: 6.200

Review 9.  Dynamic whole-body PET imaging: principles, potentials and applications.

Authors:  Arman Rahmim; Martin A Lodge; Nicolas A Karakatsanis; Vladimir Y Panin; Yun Zhou; Alan McMillan; Steve Cho; Habib Zaidi; Michael E Casey; Richard L Wahl
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-09-29       Impact factor: 9.236

10.  Blind source separation of hemodynamics from magnetic resonance perfusion brain images using independent factor analysis.

Authors:  Yen-Chun Chou; Chia-Feng Lu; Wan-Yuo Guo; Yu-Te Wu
Journal:  Int J Biomed Imaging       Date:  2010-04-21
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