Omission of serial arterial blood sampling in neuroreceptor imaging with independent component analysis

Naganawa, Mika; Kimura, Yuichi; Nariai, Tadashi; Ishii, Kenji; Oda, Kazuhiro; Manabe, Yoshitsugu; Chihara, Kazuo; Ishiwata, Kiichi

doi:10.1016/j.neuroimage.2005.02.025

Cited by 27 publications

(19 citation statements)

References 17 publications

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“…Some IDIF methods for neuroreceptor tracers described in the literature estimated only the wholeblood curve from images, and the percentage of unchanged parent was obtained at each time point by correcting the image input using HPLC (high-performance liquid chromatography) analysis from arterial blood sampling (Mourik et al, 2008a(Mourik et al, , 2009, thus diminishing the practical utility of the method. In some other studies, the problem of individual metabolite correction was not taken into account (Litton, 1997;Naganawa et al, 2005b). Naganawa et al (2005b) calculated [ 11 C]-MPDX whole-blood time-activity curve using independent component analysis and suggested that these curves could be used for absolute V T quantification, because the metabolite fraction for this tracer was negligible.…”

Section: The Issue Of Metabolite And/or Plasma Versus Whole-blood Cormentioning

confidence: 99%

Image-Derived Input Function for Brain PET Studies: Many Challenges and Few Opportunities

Zanotti‐Fregonara

Chen

Liow

et al. 2011

J Cereb Blood Flow Metab

195

189

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Quantitative positron emission tomography (PET) brain studies often require that the input function be measured, typically via arterial cannulation. Image-derived input function (IDIF) is an elegant and attractive noninvasive alternative to arterial sampling. However, IDIF is also a very challenging technique associated with several problems that must be overcome before it can be successfully implemented in clinical practice. As a result, IDIF is rarely used as a tool to reduce invasiveness in patients. The aim of the present review was to identify the methodological problems that hinder widespread use of IDIF in PET brain studies. We conclude that IDIF can be successfully implemented only with a minority of PET tracers. Even in those cases, it only rarely translates into a less-invasive procedure for the patient. Finally, we discuss some possible alternative methods for obtaining less-invasive input function.

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Section: The Issue Of Metabolite And/or Plasma Versus Whole-blood Cormentioning

confidence: 99%

Image-Derived Input Function for Brain PET Studies: Many Challenges and Few Opportunities

Zanotti‐Fregonara

Chen

Liow

et al. 2011

J Cereb Blood Flow Metab

195

189

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“…EPICA was found to be a promising tool for non-invasive input extraction in [ 18 F]FDG and [ 11 C]MPDX studies [12]. However, the ICA only deals with relative radioactivity values, while absolute figures are lost in the process.…”

Section: Discussionmentioning

confidence: 99%

“…*Address correspondence to this author at the Institute of Clinical Physiology, National Research Council, 56100 Pisa, Italy; E-mail: patricia.iozzo@ifc.cnr.it Methods to derive arterial time-activity curves (TACs) directly from a PET image have been suggested [12][13][14][15][16][17][18][19][20][21][22][23][24][25]. Independent Component Analysis based methods (EPICAextraction of the plasma TAC using Independent Component Analysis) have been used to obtain input curves from [ 18 F]FDG and [ 11 C]MPDX human brain data [12,13].…”

Section: Introductionmentioning

confidence: 99%

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Non-Invasive Estimation of Subcutaneous and Visceral Adipose Tissue Blood Flow by Using [15O]H2O PET with Image Derived Input Functions

Liukko¹,

Oikonen²,

Tolvanen³

et al. 2007

TOMIJ

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Subcutaneous adipose tissue blood flow is finely regulated, and tuned with fat metabolism; little is known about visceral fat, which is less accessible in humans. In estimating blood flow with positron emission tomography (PET) and oxygen-15-labelled water ([ 15 (FBP). Location, diameter, and inner radioactivity levels of the abdominal aorta were automatically determined. Image derived arterial curves (IDI) were compared to measured arterial blood data, as obtained by an online blood sampler (OSI). Blood flow in three adipose tissue depots was estimated using the autoradiographic method with OSI vs the FBP image derived input (F-IDI) function. Correlations between blood flow results obtained with OSI and IDI were significant (r 0.87, p<0.0001) in all regions. Estimates of the aortic diameter ranged between 10.7-17.2 mm. A good agreement was found between area under the curve (AUC) values of F-IDI and OSI curves; the AUC F-IDI /AUC OSI ratio was 0.97±0.10. Our results support the implementation of the current method for the non-invasive detection of the abdominal aorta input function from a dynamic [15 O]H 2 O PET image in the quantification of regional blood flow in low flow tissues. This method allows simultaneously examine subcutaneous and intraabdominal fat depots.

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“…Alternative non-invasive methods for estimation of the input function have been described based on cluster analysis [1], based on linear decomposition methods such as independent component analysis (ICA) [2] [3], and by non-negative matrix factorization (NMF) of the signals in a region of interest [4] and on whole brain data [5]. The linear decomposition methods are preferred because they do not assume that voxels are dominated by the vascular signal, where the NMF method is attractive because of the relative straightforward estimation procedure.…”

Section: Introductionmentioning

confidence: 99%

NMF on Positron Emission Tomography

Bödvarsson

Hansen

Svarer

et al. 2007

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07

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In positron emission tomography, kinetic modelling of brain tracer uptake, metabolism or binding requires knowledge of the cerebral input function. Traditionally, this is achieved with arterial blood sampling in the arm or as shown in [1] by non-invasive K-means clustering. We propose another method to estimate time-activity curves (TAC) extracted directly from dynamic positron emission tomography (PET) scans by nonnegative matrix factorization (NMF). Since the scaling of the basis curves is lost in the NMF the estimated TAC is scaled by a vector a which is calculated from the NMF solution. The method is tested on a [18F]-Altanserin tracer ligand data set consisting of 5 healthy subjects. The results from using Kmeans clustering and NMF are compared to a sampled arterial TAC. The comparison is done by calculating the correlation with the arterial sampled TAC.

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Omission of serial arterial blood sampling in neuroreceptor imaging with independent component analysis

Cited by 27 publications

References 17 publications

Image-Derived Input Function for Brain PET Studies: Many Challenges and Few Opportunities

Image-Derived Input Function for Brain PET Studies: Many Challenges and Few Opportunities

Non-Invasive Estimation of Subcutaneous and Visceral Adipose Tissue Blood Flow by Using [15O]H2O PET with Image Derived Input Functions

NMF on Positron Emission Tomography

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