Literature DB >> 11303885

FDG-PET standardized uptake values in normal anatomical structures using iterative reconstruction segmented attenuation correction and filtered back-projection.

C D Ramos1, Y E Erdi, M Gonen, E Riedel, H W Yeung, H A Macapinlac, R Chisin, S M Larson.   

Abstract

Filtered back-projection (FBP) is the most commonly used reconstruction method for PET images, which are usually noisy. The iterative reconstruction segmented attenuation correction (IRSAC) algorithm improves image quality without reducing image resolution. The standardized uptake value (SUV) is the most clinically utilized quantitative parameter of [fluorine-18]fluoro-2-deoxy-D-glucose (FDG) accumulation. The objective of this study was to obtain a table of SUVs for several normal anatomical structures from both routinely used FBP and IRSAC reconstructed images and to compare the data obtained with both methods. Twenty whole-body PET scans performed in consecutive patients with proven or suspected non-small cell lung cancer were retrospectively analyzed. Images were processed using both IRSAC and FBP algorithms. Nonquantitative or gaussian filters were used to smooth the transmission scan when using FBP or IRSAC algorithms, respectively. A phantom study was performed to evaluate the effect of different filters on SUV. Maximum and average SUVs (SUVmax and SUVavg) were calculated in 28 normal anatomical structures and in one pathological site. The phantom study showed that the use of a nonquantitative smoothing filter in the transmission scan results in a less accurate quantification and in a 20% underestimation of the actual measurement. Most anatomical structures were identified in all patients using the IRSAC images. On average, SUVavg and SUVmax measured on IRSAC images using a gaussian filter in the transmission scan were respectively 20% and 8% higher than the SUVs calculated from conventional FBP images. Scatterplots of the data values showed an overall strong relationship between IRSAC and FBP SUVs. Individual scatterplots of each site demonstrated a weaker relationship for lower SUVs and for SUVmax than for higher SUVs and SUVavg. A set of reference values was obtained for SUVmax and SUVavg of normal anatomical structures, calculated with both IRSAC and FBP image reconstruction algorithms. The use of IRSAC and a gaussian filter for the transmission scan seems to give more accurate SUVs than are obtained from conventional FBP images using a nonquantitative filter for the transmission scan.

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Year:  2001        PMID: 11303885     DOI: 10.1007/s002590000421

Source DB:  PubMed          Journal:  Eur J Nucl Med        ISSN: 0340-6997


  28 in total

1.  FDG-PET: procedure guidelines for tumour imaging.

Authors:  Emilio Bombardieri; Cumali Aktolun; Richard P Baum; Angelika Bishof-Delaloye; John Buscombe; Jean François Chatal; Lorenzo Maffioli; Roy Moncayo; Luc Mortelmans; Sven N Reske
Journal:  Eur J Nucl Med Mol Imaging       Date:  2003-12       Impact factor: 9.236

2.  Effects of ROI definition and reconstruction method on quantitative outcome and applicability in a response monitoring trial.

Authors:  Nanda C Krak; R Boellaard; Otto S Hoekstra; Jos W R Twisk; Corneline J Hoekstra; Adriaan A Lammertsma
Journal:  Eur J Nucl Med Mol Imaging       Date:  2004-10-15       Impact factor: 9.236

3.  Clinical value and limitations of [11C]-methionine PET for detection and localization of suspected parathyroid adenomas.

Authors:  Ken Herrmann; Toshiki Takei; Kakuko Kanegae; Tohru Shiga; Andreas K Buck; Jennifer Altomonte; Markus Schwaiger; Tibor Schuster; Kenichi Nishijima; Yuji Kuge; Nagara Tamaki
Journal:  Mol Imaging Biol       Date:  2009-04-02       Impact factor: 3.488

4.  A fuzzy locally adaptive Bayesian segmentation approach for volume determination in PET.

Authors:  Mathieu Hatt; Catherine Cheze le Rest; Alexandre Turzo; Christian Roux; Dimitris Visvikis
Journal:  IEEE Trans Med Imaging       Date:  2009-01-13       Impact factor: 10.048

5.  Respiratory-induced errors in tumor quantification and delineation in CT attenuation-corrected PET images: effects of tumor size, tumor location, and respiratory trace: a simulation study using the 4D XCAT phantom.

Authors:  Parham Geramifar; Mojtaba Shamsaie Zafarghandi; Pardis Ghafarian; Arman Rahmim; Mohammad Reza Ay
Journal:  Mol Imaging Biol       Date:  2013-12       Impact factor: 3.488

Review 6.  A review on segmentation of positron emission tomography images.

Authors:  Brent Foster; Ulas Bagci; Awais Mansoor; Ziyue Xu; Daniel J Mollura
Journal:  Comput Biol Med       Date:  2014-04-28       Impact factor: 4.589

7.  Attenuation correction in 4D-PET using a single-phase attenuation map and rigidity-adaptive deformable registration.

Authors:  Faraz Kalantari; Jing Wang
Journal:  Med Phys       Date:  2017-02-03       Impact factor: 4.071

8.  Quantification of tumour (18) F-FDG uptake: Normalise to blood glucose or scale to liver uptake?

Authors:  Georgia Keramida; Sabina Dizdarevic; Janice Bush; A Michael Peters
Journal:  Eur Radiol       Date:  2015-04-22       Impact factor: 5.315

Review 9.  Methodological considerations in quantification of oncological FDG PET studies.

Authors:  Dennis Vriens; Eric P Visser; Lioe-Fee de Geus-Oei; Wim J G Oyen
Journal:  Eur J Nucl Med Mol Imaging       Date:  2009-11-20       Impact factor: 9.236

10.  Iodine-124 PET dosimetry in differentiated thyroid cancer: recovery coefficient in 2D and 3D modes for PET(/CT) systems.

Authors:  Walter Jentzen; Reiner Weise; Jürgen Kupferschläger; Lutz Freudenberg; Wolfgang Brandau; Ronald Bares; Wolfgang Burchert; Andreas Bockisch
Journal:  Eur J Nucl Med Mol Imaging       Date:  2007-10-10       Impact factor: 9.236

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