Literature DB >> 31437602

Attenuation correction of a flat table top for radiation therapy in hybrid PET/MR using CT- and 68Ge/68Ga transmission scan-based μ-maps.

Stephan Witoszynskyj1, Piotr Andrzejewski2, Dietmar Georg2, Marcus Hacker1, Tufve Nyholm3, Ivo Rausch4, Barbara Knäusl5.   

Abstract

Hybrid PET/MR offers new opportunities in radiation oncology for tissue/tumour characterisation and response assessment. Attenuation correction (AC) is an important issue especially in the presence of immobilization devices and flat table tops (FTT). The goal of this study was to compare two methods of AC using CT- and 68Ge/68Ga transmission scan-based attenuation maps (μ-maps) for a custom-designed FTT. Measurements were performed in the mMR PET/MR and TrueV PET/CT Biograph Siemens scanners with three different phantoms, namely the Siemens MR-QA, a cubic canister and the NEMA IEC body phantom. The study revealed that the MR image quality is not hampered by the presence of the FTT. For cubic canister applying the scanner's inherent AC alone resulted in inaccuracies in PET images, with up to -4.0% underestimation of the activity. The mean NEMA sphere activity measurements without FTT, agreed within 3.5% with the respective inserted activity. Placing the FTT in the PET/MR scanner resulted in a difference to the injected activity of 4.5% when the table was not corrected for. By introducing the μ-maps the discrepancy between the used activity and the measurements decreased down to 2.6%. To improve the AC of the FTT the creation of a dedicated μ-map was necessary while the CT-based μ-map performed equally good as the source transmission scan-based one.
Copyright © 2019 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Attenuation correction; PET/MR; Radiation oncology; μ-Map

Mesh:

Substances:

Year:  2019        PMID: 31437602     DOI: 10.1016/j.ejmp.2019.08.005

Source DB:  PubMed          Journal:  Phys Med        ISSN: 1120-1797            Impact factor:   2.685


  1 in total

Review 1.  Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods.

Authors:  Tonghe Wang; Yang Lei; Yabo Fu; Walter J Curran; Tian Liu; Jonathon A Nye; Xiaofeng Yang
Journal:  Phys Med       Date:  2020-07-29       Impact factor: 2.685

  1 in total

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