Literature DB >> 21251804

PET based volume segmentation with emphasis on the iterative TrueX algorithm.

Barbara Knäusl1, Albert Hirtl, Georg Dobrozemsky, Helmar Bergmann, Kurt Kletter, Robert Dudczak, Dietmar Georg.   

Abstract

PURPOSE: To assess the influence of reconstruction algorithms for positron emission tomography (PET) based volume quantification. The specifically detected activity in the threshold defined volume was investigated for different reconstruction algorithms as a function of volume size and signal to background ratio (SBR), especially for volumes smaller than 1ml. Special attention was given to the Siemens specific iterative reconstruction algorithm TrueX.
METHODS: Measurements were performed with a modified in-house produced IEC body phantom on a Siemens Biograph 64 True Point PET/CT scanner (Siemens, Medical Systems) for six different SBRs (2.1, 3.8, 4.9, 6.7, 8.9, 9.4 and without active background (BG)). The phantom consisted of a water-filled cavity with built-in plastic spheres (0.27, 0.52, 1.15, 2.57, 5.58 and 11.49ml). The following reconstruction algorithms available on the Siemens Syngo workstation were evaluated: Iterative OSEM (OSEM) (4 iterations, 21 subsets), iterative TrueX (TrueX) (4 iterations, 21 subsets) and filtered backprojection (FBP). For the threshold based volume segmentation the software Rover (ABX, Dresden) was used.
RESULTS: For spheres larger than 2.5ml a constant threshold (standard deviation (SD) 10%) level was found for a given SBR and reconstruction algorithm and therefore a mean threshold for the largest three spheres was calculated. This threshold could be approximated by a function inversely proportional to the SBR. The threshold decreased with increasing SBR for all sphere sizes. For the OSEM algorithm the threshold for small spheres with 0.27, 0.52 and 1.15ml varied between 17% and 44% (depending on sphere size). The threshold for the TrueX algorithm was substantially lower (up to 17%) than for the OSEM algorithm for all sphere sizes. The maximum activity in a specific volume yielded the true activity for the OSEM algorithm when using a SBR independent correction factor C, which depended on sphere size. For the largest three volumes a constant factor C=1.10±0.03 was found. For smaller volumes, C increased exponentially due to the partial volume effect. For the TrueX algorithm the maximum activity overestimated the true activity.
CONCLUSION: The threshold values for PET based target volume segmentation increased with increasing sphere size for all tested algorithms. True activity values of spheres in the phantom could be extracted using experimentally determined correction factors C. The TrueX algorithm has to be used carefully for quantitative comparison (e.g. follow-up) and multicenter studies. Copyright Â
© 2010. Published by Elsevier GmbH.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21251804     DOI: 10.1016/j.zemedi.2010.12.003

Source DB:  PubMed          Journal:  Z Med Phys        ISSN: 0939-3889            Impact factor:   4.820


  15 in total

1.  Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211.

Authors:  Mathieu Hatt; John A Lee; Charles R Schmidtlein; Issam El Naqa; Curtis Caldwell; Elisabetta De Bernardi; Wei Lu; Shiva Das; Xavier Geets; Vincent Gregoire; Robert Jeraj; Michael P MacManus; Osama R Mawlawi; Ursula Nestle; Andrei B Pugachev; Heiko Schöder; Tony Shepherd; Emiliano Spezi; Dimitris Visvikis; Habib Zaidi; Assen S Kirov
Journal:  Med Phys       Date:  2017-05-18       Impact factor: 4.071

Review 2.  Functional imaging in radiation therapy planning for head and neck cancer.

Authors:  Luis A Pérez Romasanta; María José García Velloso; Antonio López Medina
Journal:  Rep Pract Oncol Radiother       Date:  2013-11-09

3.  PIK3CA Mutational Status Is Associated with High Glycolytic Activity in ER+/HER2- Early Invasive Breast Cancer: a Molecular Imaging Study Using [18F]FDG PET/CT.

Authors:  Heinrich Magometschnigg; Katja Pinker; Thomas Helbich; Anita Brandstetter; Margaretha Rudas; Thomas Nakuz; Pascal Baltzer; Wolfgang Wadsak; Marcus Hacker; Michael Weber; Peter Dubsky; Martin Filipits
Journal:  Mol Imaging Biol       Date:  2019-10       Impact factor: 3.488

4.  Diagnostic accuracy of (18)F-FDG PET/CT compared with that of contrast-enhanced MRI of the breast at 3 T.

Authors:  Heinrich F Magometschnigg; Pascal A Baltzer; Barbara Fueger; Thomas H Helbich; Georgios Karanikas; Peter Dubsky; Margaretha Rudas; Michael Weber; Katja Pinker
Journal:  Eur J Nucl Med Mol Imaging       Date:  2015-06-30       Impact factor: 9.236

5.  Assessment of pulmonary melanoma metastases with 18F-FDG PET/CT: which PET-negative patients require additional tests for definitive staging?

Authors:  Marius E Mayerhoefer; Helmut Prosch; Christian J Herold; Michael Weber; Georgios Karanikas
Journal:  Eur Radiol       Date:  2012-06-01       Impact factor: 5.315

6.  Impact of the point spread function on maximum standardized uptake value measurements in patients with pulmonary cancer.

Authors:  S Gellee; J Page; B Sanghera; P Payoux; Thomas Wagner
Journal:  World J Nucl Med       Date:  2014-05

7.  The association of tumor-to-background ratios and SUVmax deviations related to point spread function and time-of-flight F18-FDG-PET/CT reconstruction in colorectal liver metastases.

Authors:  Julian Mm Rogasch; Ingo G Steffen; Frank Hofheinz; Oliver S Großer; Christian Furth; Konrad Mohnike; Peter Hass; Mathias Walke; Ivayla Apostolova; Holger Amthauer
Journal:  EJNMMI Res       Date:  2015-05-06       Impact factor: 3.138

8.  Multiparametric [18F]Fluorodeoxyglucose/ [18F]Fluoromisonidazole Positron Emission Tomography/ Magnetic Resonance Imaging of Locally Advanced Cervical Cancer for the Non-Invasive Detection of Tumor Heterogeneity: A Pilot Study.

Authors:  Katja Pinker; Piotr Andrzejewski; Pascal Baltzer; Stephan H Polanec; Alina Sturdza; Dietmar Georg; Thomas H Helbich; Georgios Karanikas; Christoph Grimm; Stephan Polterauer; Richard Poetter; Wolfgang Wadsak; Markus Mitterhauser; Petra Georg
Journal:  PLoS One       Date:  2016-05-11       Impact factor: 3.240

9.  PET image segmentation using a Gaussian mixture model and Markov random fields.

Authors:  Thomas Layer; Matthias Blaickner; Barbara Knäusl; Dietmar Georg; Johannes Neuwirth; Richard P Baum; Christiane Schuchardt; Stefan Wiessalla; Gerald Matz
Journal:  EJNMMI Phys       Date:  2015-03-12

10.  Influence of rigid coregistration of PET and CT data on metabolic volumetry: a user's perspective.

Authors:  Ingo G Steffen; Frank Hofheinz; Julian Mm Rogasch; Christian Furth; Holger Amthauer; Juri Ruf
Journal:  EJNMMI Res       Date:  2013-12-27       Impact factor: 3.138

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.