Literature DB >> 25952739

Quantitative Evaluation of Segmentation- and Atlas-Based Attenuation Correction for PET/MR on Pediatric Patients.

Ilja Bezrukov1, Holger Schmidt2, Sergios Gatidis2, Frédéric Mantlik3, Jürgen F Schäfer2, Nina Schwenzer2, Bernd J Pichler4.   

Abstract

UNLABELLED: Pediatric imaging is regarded as a key application for combined PET/MR imaging systems. Because existing MR-based attenuation-correction methods were not designed specifically for pediatric patients, we assessed the impact of 2 potentially influential factors: inter- and intrapatient variability of attenuation coefficients and anatomic variability. Furthermore, we evaluated the quantification accuracy of 3 methods for MR-based attenuation correction without (SEGbase) and with bone prediction using an adult and a pediatric atlas (SEGwBONEad and SEGwBONEpe, respectively) on PET data of pediatric patients.
METHODS: The variability of attenuation coefficients between and within pediatric (5-17 y, n = 17) and adult (27-66 y, n = 16) patient collectives was assessed on volumes of interest (VOIs) in CT datasets for different tissue types. Anatomic variability was assessed on SEGwBONEad/pe attenuation maps by computing mean differences to CT-based attenuation maps for regions of bone tissue, lungs, and soft tissue. PET quantification was evaluated on VOIs with physiologic uptake and on 80% isocontour VOIs with elevated uptake in the thorax and abdomen/pelvis. Inter- and intrapatient variability of the bias was assessed for each VOI group and method.
RESULTS: Statistically significant differences in mean VOI Hounsfield unit values and linear attenuation coefficients between adult and pediatric collectives were found in the lungs and femur. The prediction of attenuation maps using the pediatric atlas showed a reduced error in bone tissue and better delineation of bone structure. Evaluation of PET quantification accuracy showed statistically significant mean errors in mean standardized uptake values of -14% ± 5% and -23% ± 6% in bone marrow and femur-adjacent VOIs with physiologic uptake for SEGbase, which could be reduced to 0% ± 4% and -1% ± 5% using SEGwBONEpe attenuation maps. Bias in soft-tissue VOIs was less than 5% for all methods. Lung VOIs showed high SDs in the range of 15% for all methods. For VOIs with elevated uptake, mean and SD were less than 5% except in the thorax.
CONCLUSION: The use of a dedicated atlas for the pediatric patient collective resulted in improved attenuation map prediction in osseous regions and reduced interpatient bias variation in femur-adjacent VOIs. For the lungs, in which intrapatient variation was higher for the pediatric collective, a patient- or group-specific attenuation coefficient might improve attenuation map accuracy. Mean errors of -14% and -23% in bone marrow and femur-adjacent VOIs can affect PET quantification in these regions when bone tissue is ignored.
© 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Entities:  

Keywords:  PET/MR; atlas; attenuation correction; segmentation

Mesh:

Substances:

Year:  2015        PMID: 25952739     DOI: 10.2967/jnumed.114.149476

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  11 in total

1.  Progressing Toward a Cohesive Pediatric 18F-FDG PET/MR Protocol: Is Administration of Gadolinium Chelates Necessary?

Authors:  Christopher Klenk; Rakhee Gawande; Vy Thao Tran; Jennifer Trinh Leung; Kevin Chi; Daniel Owen; Sandra Luna-Fineman; Kathleen M Sakamoto; Alex McMillan; Andy Quon; Heike E Daldrup-Link
Journal:  J Nucl Med       Date:  2015-10-15       Impact factor: 10.057

2.  How PET/MR Can Add Value For Children With Cancer.

Authors:  Heike Daldrup-Link
Journal:  Curr Radiol Rep       Date:  2017-02-21

Review 3.  [Simultaneous whole-body PET-MRI in pediatric oncology : More than just reducing radiation?].

Authors:  S Gatidis; B Gückel; C la Fougère; J Schmitt; J F Schäfer
Journal:  Radiologe       Date:  2016-07       Impact factor: 0.635

4.  Prognostic Value of Hybrid PET/MR Imaging in Patients with Differentiated Thyroid Cancer.

Authors:  Leandra Piscopo; Carmela Nappi; Fabio Volpe; Valeria Romeo; Emanuele Nicolai; Rosj Gallicchio; Alessia Giordano; Giovanni Storto; Leonardo Pace; Carlo Cavaliere; Marco Salvatore; Alberto Cuocolo; Michele Klain
Journal:  Cancers (Basel)       Date:  2022-06-15       Impact factor: 6.575

5.  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

Review 6.  One-stop local and whole-body staging of children with cancer.

Authors:  Heike E Daldrup-Link; Ashok J Theruvath; Lucia Baratto; Kristina Elizabeth Hawk
Journal:  Pediatr Radiol       Date:  2021-04-30

7.  A concept for holistic whole body MRI data analysis, Imiomics.

Authors:  Robin Strand; Filip Malmberg; Lars Johansson; Lars Lind; Magnus Sundbom; Håkan Ahlström; Joel Kullberg
Journal:  PLoS One       Date:  2017-02-27       Impact factor: 3.240

8.  Feasibility of Deep Learning-Based PET/MR Attenuation Correction in the Pelvis Using Only Diagnostic MR Images.

Authors:  Tyler J Bradshaw; Gengyan Zhao; Hyungseok Jang; Fang Liu; Alan B McMillan
Journal:  Tomography       Date:  2018-09

Review 9.  A decade of multi-modality PET and MR imaging in abdominal oncology.

Authors:  Lisa A Min; Francesca Castagnoli; Wouter V Vogel; Jisk P Vellenga; Joost J M van Griethuysen; Max J Lahaye; Monique Maas; Regina G H Beets Tan; Doenja M J Lambregts
Journal:  Br J Radiol       Date:  2021-08-13       Impact factor: 3.629

Review 10.  PET/MRI attenuation estimation in the lung: A review of past, present, and potential techniques.

Authors:  Joseph Lillington; Ludovica Brusaferri; Kerstin Kläser; Karin Shmueli; Radhouene Neji; Brian F Hutton; Francesco Fraioli; Simon Arridge; Manuel Jorge Cardoso; Sebastien Ourselin; Kris Thielemans; David Atkinson
Journal:  Med Phys       Date:  2020-01-01       Impact factor: 4.071

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