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Research ArticleAdult Brain
Open Access

Estimating Local Cellular Density in Glioma Using MR Imaging Data

E.D.H. Gates, J.S. Weinberg, S.S. Prabhu, J.S. Lin, J. Hamilton, J.D. Hazle, G.N. Fuller, V. Baladandayuthapani, D.T. Fuentes and D. Schellingerhout
American Journal of Neuroradiology January 2021, 42 (1) 102-108; DOI: https://doi.org/10.3174/ajnr.A6884
E.D.H. Gates
aFrom the Departments of Imaging Physics (E.D.H.G., J.S.L., J.D.H., D.T.F.)
fThe University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences (E.D.H.G.), Houston, Texas
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J.S. Weinberg
bNeurosurgery (J.S.W., S.S.P.)
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S.S. Prabhu
bNeurosurgery (J.S.W., S.S.P.)
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J.S. Lin
aFrom the Departments of Imaging Physics (E.D.H.G., J.S.L., J.D.H., D.T.F.)
gBaylor College of Medicine (J.S.L.), Houston, Texas
hDepartment of Bioengineering (J.S.L.), Rice University, Houston, Texas
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J. Hamilton
cNeuroradiology (J.H., D.S.)
iRadiology Partners (J.H.), Houston, Texas
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J.D. Hazle
aFrom the Departments of Imaging Physics (E.D.H.G., J.S.L., J.D.H., D.T.F.)
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G.N. Fuller
dPathology (G.N.F.)
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V. Baladandayuthapani
jDepartment of Computational Medicine and Bioinformatics (V.B.), University of Michigan School of Public Health, Ann Arbor, Michigan
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D.T. Fuentes
aFrom the Departments of Imaging Physics (E.D.H.G., J.S.L., J.D.H., D.T.F.)
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D. Schellingerhout
cNeuroradiology (J.H., D.S.)
eCancer Systems Imaging (D.S.), University of Texas MD Anderson Cancer Center, Houston, Texas
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Article Information

vol. 42 no. 1 102-108
DOI 
https://doi.org/10.3174/ajnr.A6884
PubMed 
33243897

Published By 
American Journal of Neuroradiology
Print ISSN 
0195-6108
Online ISSN 
1936-959X
History 
  • Received April 13, 2020
  • Accepted after revision August 22, 2020
  • Published online January 11, 2021.

Copyright & Usage 
© 2021 by American Journal of Neuroradiology Indicates open access to non-subscribers at www.ajnr.org

Author Information

  1. E.D.H. Gatesa,f,
  2. J.S. Weinbergb,
  3. S.S. Prabhub,
  4. J.S. Lina,g,h,
  5. J. Hamiltonc,i,
  6. J.D. Hazlea,
  7. G.N. Fullerd,
  8. V. Baladandayuthapanij,
  9. D.T. Fuentesa and
  10. D. Schellingerhoutc,e
  1. aFrom the Departments of Imaging Physics (E.D.H.G., J.S.L., J.D.H., D.T.F.)
  2. bNeurosurgery (J.S.W., S.S.P.)
  3. cNeuroradiology (J.H., D.S.)
  4. dPathology (G.N.F.)
  5. eCancer Systems Imaging (D.S.), University of Texas MD Anderson Cancer Center, Houston, Texas
  6. fThe University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences (E.D.H.G.), Houston, Texas
  7. gBaylor College of Medicine (J.S.L.), Houston, Texas
  8. hDepartment of Bioengineering (J.S.L.), Rice University, Houston, Texas
  9. iRadiology Partners (J.H.), Houston, Texas
  10. jDepartment of Computational Medicine and Bioinformatics (V.B.), University of Michigan School of Public Health, Ann Arbor, Michigan
  1. Please address correspondence to Dawid Schellingerhout, MD, Neuroradiology and Cancer Systems Imaging, UT MD Anderson Cancer Center, 1400 Pressler St, Unit 1482, Houston, TX, 77030; e-mail: Dawid.Schellingerhout{at}mdanderson.org
View Full Text

Funding

  • Greenspun neurosurgical research fund

  • National Cancer Institute

    P30 CA016672

Altmetrics

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E.D.H. Gates, J.S. Weinberg, S.S. Prabhu, J.S. Lin, J. Hamilton, J.D. Hazle, G.N. Fuller, V. Baladandayuthapani, D.T. Fuentes, D. Schellingerhout
Estimating Local Cellular Density in Glioma Using MR Imaging Data
American Journal of Neuroradiology Jan 2021, 42 (1) 102-108; DOI: 10.3174/ajnr.A6884

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Estimating Local Cellular Density in Glioma Using MR Imaging Data
E.D.H. Gates, J.S. Weinberg, S.S. Prabhu, J.S. Lin, J. Hamilton, J.D. Hazle, G.N. Fuller, V. Baladandayuthapani, D.T. Fuentes, D. Schellingerhout
American Journal of Neuroradiology Jan 2021, 42 (1) 102-108; DOI: 10.3174/ajnr.A6884
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Cited By...

  • Cellular Density in Adult Glioma, Estimated with MR Imaging Data and a Machine Learning Algorithm, Has Prognostic Power Approaching World Health Organization Histologic Grading in a Cohort of 1181 Patients
  • Crossref (11)
  • Google Scholar

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

  • Emerging role of artificial intelligence in diagnosis, classification and clinical management of glioma
    Jiefeng Luo, Mika Pan, Ke Mo, Yingwei Mao, Donghua Zou
    Seminars in Cancer Biology 2023 91
  • Simultaneous quantification of perfusion, permeability, and leakage effects in brain gliomas using dynamic spin-and-gradient-echo echoplanar imaging MRI
    Francesco Sanvito, Catalina Raymond, Nicholas S. Cho, Jingwen Yao, Akifumi Hagiwara, Joey Orpilla, Linda M. Liau, Richard G. Everson, Phioanh L. Nghiemphu, Albert Lai, Robert Prins, Noriko Salamon, Timothy F. Cloughesy, Benjamin M. Ellingson
    European Radiology 2023 34 5
  • Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study
    Corentin Martens, Laetitia Lebrun, Christine Decaestecker, Thomas Vandamme, Yves-Rémi Van Eycke, Antonin Rovai, Thierry Metens, Olivier Debeir, Serge Goldman, Isabelle Salmon, Gaetan Van Simaeys
    Tomography 2021 7 4
  • The intra-tumoral heterogeneity in glioblastoma — a limitation for prognostic value of epigenetic markers?
    Sippl Christoph, Saenz Alicia, Teping Fritz, Trenkpohl Vanessa, Ketter Ralf, Kim Yoo Jin, Linsler Stefan, Oertel Joachim
    Acta Neurochirurgica 2023 165 6
  • Liquid biopsies for early diagnosis of brain tumours: in silico mathematical biomarker modelling
    Johanna A. Blee, Xia Liu, Abigail J. Harland, Kavi Fatania, Stuart Currie, Kathreena M. Kurian, Sabine Hauert
    Journal of The Royal Society Interface 2022 19 193
  • Cellular Density in Adult Glioma, Estimated with MR Imaging Data and a Machine Learning Algorithm, Has Prognostic Power Approaching World Health Organization Histologic Grading in a Cohort of 1181 Patients
    E.D.H. Gates, D. Suki, A. Celaya, J.S. Weinberg, S.S. Prabhu, R. Sawaya, J.T. Huse, J.P. Long, D. Fuentes, D. Schellingerhout
    American Journal of Neuroradiology 2022 43 10
  • Convolutional Neural Networks for Glioma Segmentation and Prognosis: A Systematic Review
    Janette Herr, Radka Stoyanova, Eric Albert Mellon
    Critical Reviews™ in Oncogenesis 2024 29 3
  • Tracking glioblastoma progression after initial resection with minimal reaction-diffusion models
    Duane C. Harris, Giancarlo Mignucci-Jiménez, Yuan Xu, Steffen E. Eikenberry, C. Chad Quarles, Mark C. Preul, Yang Kuang, Eric J. Kostelich
    Mathematical Biosciences and Engineering 2022 19 6
  • Consideration of transmembrane water exchange in pharmacokinetic model significantly improves the accuracy of DCE-MRI in estimating cellular density: A pilot study in glioblastoma multiforme
    Zhenfeng Pang, Zejun Wang, Bao Wang, Kaiyue Guo, Cheng Meng, Yingchao Liu, Xueqian Kong, Ruiliang Bai
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