Literature DB >> 11337577

Quantification of regional myocardial blood flow using dynamic H2(15)O PET and factor analysis.

J Y Ahn1, D S Lee, J S Lee, S K Kim, G J Cheon, J S Yeo, S A Shin, J K Chung, M C Lee.   

Abstract

UNLABELLED: Because the use of factor analysis has been proposed for extracting pure physiologic temporal or spatial information from dynamic nuclear medicine images, factor analysis should be capable of robustly estimating regional myocardial blood flow (rMBF) using H2(15)O PET without additional C15O PET, which is a cumbersome procedure for patients. Therefore, we measured rMBF using time-activity curves (TACs) obtained from factor analysis of dynamic myocardial H2(15)O PET images without the aid of C15O PET.
METHODS: H2(15)O PET of six healthy dogs at rest and during stress was performed simultaneously with microsphere studies using 85Sr, 46Sc, and 113SN: We performed factor analysis in two steps after reorienting and masking the images to include only the cardiac region. The first step discriminated each factor in the spatial distribution and acquired the input functions, and the second step extracted regional-tissue TACS: Image-derived input functions obtained by factor analysis were compared with those obtained by the sampling method. rMBF calculated using a compartmental model with tissue TACs from the second step of the factor analysis was compared with rMBF measured by microsphere studies.
RESULTS: Factor analysis was successful for all the dynamic H2(15)O PET images. The input functions obtained by factor analysis were nearly equal to those obtained by arterial blood sampling, except for the expected delay. The correlation between rMBF obtained by factor analysis and rMBF obtained by microsphere studies was good (r = 0.95). The correlation between rMBF obtained by the region-of-interest method and rMBF obtained by microsphere studies was also good (r = 0.93).
CONCLUSION: rMBF can be measured robustly by factor analysis using dynamic myocardial H2(15)O PET images without additional C15O blood-pool PET.

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Year:  2001        PMID: 11337577

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


  14 in total

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Authors:  Hendrik J Harms; Paul Knaapen; Stefan de Haan; Rick Halbmeijer; Adriaan A Lammertsma; Mark Lubberink
Journal:  Eur J Nucl Med Mol Imaging       Date:  2011-01-27       Impact factor: 9.236

2.  Alignment of 3-dimensional cardiac structures in O-15-labeled water PET emission images with mutual information.

Authors:  Anu Juslin; Jyrki Lötjönen; Sergey V Nesterov; Kari Kalliokoski; Juhani Knuuti; Ulla Ruotsalainen
Journal:  J Nucl Cardiol       Date:  2007-01       Impact factor: 5.952

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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

Review 4.  Recent advances in parametric neuroreceptor mapping with dynamic PET: basic concepts and graphical analyses.

Authors:  Seongho Seo; Su Jin Kim; Dong Soo Lee; Jae Sung Lee
Journal:  Neurosci Bull       Date:  2014-09-28       Impact factor: 5.203

5.  Simultaneous evaluation of myocardial blood flow, cardiac function and lung water content using [15O]H2O and positron emission tomography.

Authors:  Alexandru Naum; Helena Tuunanen; Erik Engblom; Vesa Oikonen; Hannu Sipilä; Patricia Iozzo; Pirjo Nuutila; Juhani Knuuti
Journal:  Eur J Nucl Med Mol Imaging       Date:  2006-10-24       Impact factor: 9.236

6.  Direct comparison between 2-dimensional and 3-dimensional PET acquisition modes for myocardial blood flow absolute quantification with O-15 water and N-13 ammonia.

Authors:  Véronique Roelants; Anne Bol; Xavier Bernard; Ann Coppens; Jacques Melin; Bernhard Gerber; Jean-Louis Vanoverschelde
Journal:  J Nucl Cardiol       Date:  2006 Mar-Apr       Impact factor: 5.952

7.  Sparsity Constrained Mixture Modeling for the Estimation of Kinetic Parameters in Dynamic PET.

Authors:  Yanguang Lin; Justin P Haldar; Quanzheng Li; Peter S Conti; Richard M Leahy
Journal:  IEEE Trans Med Imaging       Date:  2013-11-07       Impact factor: 10.048

8.  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

9.  Segmental quantitative myocardial perfusion with PET for the detection of significant coronary artery disease in patients with stable angina.

Authors:  Valentina Berti; Roberto Sciagrà; Danilo Neglia; Mikko Pietilä; Arthur J Scholte; Stephan Nekolla; François Rouzet; Alberto Pupi; Juhani Knuuti
Journal:  Eur J Nucl Med Mol Imaging       Date:  2016-03-18       Impact factor: 9.236

10.  Myocardial perfusion and glucose uptake coupling in CAD patients.

Authors:  Alejandro N Mazzadi; Pierre Croisille; Xavier André-Fouët; Stéphane Fol; Jérôme Duisit; Michel Ovize; Dominique Comar; Marc F Janier
Journal:  Int J Cardiovasc Imaging       Date:  2003-10       Impact factor: 2.357

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