Literature DB >> 22469243

Magnetic resonace-based attenuation correction for micro-single-photon emission computed tomography.

Vincent Keereman1, Yves Fierens, Christian Vanhove, Tony Lahoutte, Stefaan Vandenberghe.   

Abstract

Attenuation correction is necessary for quantification in micro-single-photon emission computed tomography (micro-SPECT). In general, this is done based on micro-computed tomographic (micro-CT) images. Derivation of the attenuation map from magnetic resonance (MR) images is difficult because bone and lung are invisible in conventional MR images and hence indistinguishable from air. An ultrashort echo time (UTE) sequence yields signal in bone and lungs. Micro-SPECT, micro-CT, and MR images of 18 rats were acquired. Different tracers were used: hexamethylpropyleneamine oxime (brain), dimercaptosuccinic acid (kidney), colloids (liver and spleen), and macroaggregated albumin (lung). The micro-SPECT images were reconstructed without attenuation correction, with micro-CT-based attenuation maps, and with three MR-based attenuation maps: uniform, non-UTE-MR based (air, soft tissue), and UTE-MR based (air, lung, soft tissue, bone). The average difference with the micro-CT-based reconstruction was calculated. The UTE-MR-based attenuation correction performed best, with average errors ≤ 8% in the brain scans and ≤ 3% in the body scans. It yields nonsignificant differences for the body scans. The uniform map yields errors of ≤ 6% in the body scans. No attenuation correction yields errors ≥ 15% in the brain scans and ≥ 25% in the body scans. Attenuation correction should always be performed for quantification. The feasibility of MR-based attenuation correction was shown. When accurate quantification is necessary, a UTE-MR-based attenuation correction should be used.

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Year:  2012        PMID: 22469243

Source DB:  PubMed          Journal:  Mol Imaging        ISSN: 1535-3508            Impact factor:   4.488


  5 in total

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Authors:  Thomas Beyer; Martin L Lassen; Ronald Boellaard; Gaspar Delso; Maqsood Yaqub; Bernhard Sattler; Harald H Quick
Journal:  MAGMA       Date:  2016-01-06       Impact factor: 2.310

2.  Transforming UTE-mDixon MR Abdomen-Pelvis Images Into CT by Jointly Leveraging Prior Knowledge and Partial Supervision.

Authors:  Pengjiang Qian; Jiamin Zheng; Qiankun Zheng; Yuan Liu; Tingyu Wang; Rose Al Helo; Atallah Baydoun; Norbert Avril; Rodney J Ellis; Harry Friel; Melanie S Traughber; Ajit Devaraj; Bryan Traughber; Raymond F Muzic
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2021-02-03       Impact factor: 3.710

3.  Using Magnetic Resonance for Predicting Femoral Strength: Added Value with respect to Bone Densitometry.

Authors:  Olivia Louis; Yves Fierens; Maria Strantza; Robert Luypaert; Johan de Mey; Erik Cattrysse
Journal:  Biomed Res Int       Date:  2015-08-27       Impact factor: 3.411

Review 4.  The role of preclinical SPECT in oncological and neurological research in combination with either CT or MRI.

Authors:  Monique R Bernsen; Pieter E B Vaissier; Roel Van Holen; Jan Booij; Freek J Beekman; Marion de Jong
Journal:  Eur J Nucl Med Mol Imaging       Date:  2014-05       Impact factor: 9.236

5.  SUV-quantification of physiological lung tissue in an integrated PET/MR-system: Impact of lung density and bone tissue.

Authors:  Ferdinand Seith; Holger Schmidt; Sergios Gatidis; Ilja Bezrukov; Christina Schraml; Christina Pfannenberg; Christian la Fougère; Konstantin Nikolaou; Nina Schwenzer
Journal:  PLoS One       Date:  2017-05-31       Impact factor: 3.240

  5 in total

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