Literature DB >> 1997487

Precision and accuracy considerations of physiological quantitation in PET.

R E Carson1.   

Abstract

The ability to differentiate regional patterns of flow and metabolism between various patient populations depends upon the signal-to-noise characteristics of the data. The approach chosen for producing quantitative data will affect the detection sensitivity of a method. Methods based on mathematical models can reduce intersubject variability by accounting for factors unrelated to the physiological measure of interest, in particular, differences in the input function. However, errors in the model and in the implementation of a model-based method can increase variability compared to simpler, empirical methods. Normalization of physiological measures can significantly reduce intersubject variation; however, interpretation of normalized results can be more complex. The advantages and disadvantages of various approaches for physiological quantitation are considered.

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Year:  1991        PMID: 1997487     DOI: 10.1038/jcbfm.1991.36

Source DB:  PubMed          Journal:  J Cereb Blood Flow Metab        ISSN: 0271-678X            Impact factor:   6.200


  7 in total

1.  Dual time point method for the quantification of irreversible tracer kinetics: A reference tissue approach applied to [18F]-FDOPA brain PET.

Authors:  I Lopes Alves; Sanne K Meles; Antoon Tm Willemsen; Rudi A Dierckx; Ana M Marques da Silva; Klaus L Leenders; Michel Koole
Journal:  J Cereb Blood Flow Metab       Date:  2016-12-19       Impact factor: 6.200

2.  Comparative evaluation of Logan and relative-equilibrium graphical methods for parametric imaging of dynamic [18F]FDDNP PET determinations.

Authors:  Koon-Pong Wong; Vladimir Kepe; Magnus Dahlbom; Nagichettiar Satyamurthy; Gary W Small; Jorge R Barrio; Sung-Cheng Huang
Journal:  Neuroimage       Date:  2011-12-16       Impact factor: 6.556

3.  Relationship between impulsivity, prefrontal anticipatory activation, and striatal dopamine release during rewarded task performance.

Authors:  Barbara J Weiland; Mary M Heitzeg; David Zald; Chelsea Cummiford; Tiffany Love; Robert A Zucker; Jon-Kar Zubieta
Journal:  Psychiatry Res       Date:  2014-06-05       Impact factor: 3.222

4.  Clinical characteristics of cognitive impairment in patients with Parkinson's disease and its related pattern in 18 F-FDG PET imaging.

Authors:  Lei Wu; Feng-Tao Liu; Jing-Jie Ge; Jue Zhao; Yi-Lin Tang; Wen-Bo Yu; Huan Yu; Tim Anderson; Chuan-Tao Zuo; Ling Chen; Jian Wang
Journal:  Hum Brain Mapp       Date:  2018-07-12       Impact factor: 5.038

5.  Reproducibility of compartmental modelling of 18F-FDG PET/CT to evaluate lung inflammation.

Authors:  Laurence D Vass; Sarah Lee; Frederick J Wilson; Marie Fisk; Joseph Cheriyan; Ian Wilkinson
Journal:  EJNMMI Phys       Date:  2019-12-16

6.  Application of machine learning to pretherapeutically estimate dosimetry in men with advanced prostate cancer treated with 177Lu-PSMA I&T therapy.

Authors:  Song Xue; Andrei Gafita; Chao Dong; Yu Zhao; Giles Tetteh; Bjoern H Menze; Sibylle Ziegler; Wolfgang Weber; Ali Afshar-Oromieh; Axel Rominger; Matthias Eiber; Kuangyu Shi
Journal:  Eur J Nucl Med Mol Imaging       Date:  2022-06-30       Impact factor: 10.057

7.  Voxel-based NK1 receptor occupancy measurements with [(18)F]SPA-RQ and positron emission tomography: a procedure for assessing errors from image reconstruction and physiological modeling.

Authors:  Esa Wallius; Mikko Nyman; Vesa Oikonen; Jarmo Hietala; Ulla Ruotsalainen
Journal:  Mol Imaging Biol       Date:  2007 Sep-Oct       Impact factor: 3.484

  7 in total

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