Literature DB >> 29751058

Imaging brain tumour microstructure.

Markus Nilsson1, Elisabet Englund2, Filip Szczepankiewicz3, Danielle van Westen4, Pia C Sundgren5.   

Abstract

Imaging is an indispensable tool for brain tumour diagnosis, surgical planning, and follow-up. Definite diagnosis, however, often demands histopathological analysis of microscopic features of tissue samples, which have to be obtained by invasive means. A non-invasive alternative may be to probe corresponding microscopic tissue characteristics by MRI, or so called 'microstructure imaging'. The promise of microstructure imaging is one of 'virtual biopsy' with the goal to offset the need for invasive procedures in favour of imaging that can guide pre-surgical planning and can be repeated longitudinally to monitor and predict treatment response. The exploration of such methods is motivated by the striking link between parameters from MRI and tumour histology, for example the correlation between the apparent diffusion coefficient and cellularity. Recent microstructure imaging techniques probe even more subtle and specific features, providing parameters associated to cell shape, size, permeability, and volume distributions. However, the range of scenarios in which these techniques provide reliable imaging biomarkers that can be used to test medical hypotheses or support clinical decisions is yet unknown. Accurate microstructure imaging may moreover require acquisitions that go beyond conventional data acquisition strategies. This review covers a wide range of candidate microstructure imaging methods based on diffusion MRI and relaxometry, and explores advantages, challenges, and potential pitfalls in brain tumour microstructure imaging.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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Year:  2018        PMID: 29751058     DOI: 10.1016/j.neuroimage.2018.04.075

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  19 in total

1.  Maxwell-compensated design of asymmetric gradient waveforms for tensor-valued diffusion encoding.

Authors:  Filip Szczepankiewicz; Carl-Fredrik Westin; Markus Nilsson
Journal:  Magn Reson Med       Date:  2019-05-31       Impact factor: 4.668

2.  Assessment of structural disconnections in gliomas: comparison of indirect and direct approaches.

Authors:  Erica Silvestri; Umberto Villani; Manuela Moretto; Maria Colpo; Alessandro Salvalaggio; Mariagiulia Anglani; Marco Castellaro; Silvia Facchini; Elena Monai; Domenico D'Avella; Alessandro Della Puppa; Diego Cecchin; Maurizio Corbetta; Alessandra Bertoldo
Journal:  Brain Struct Funct       Date:  2022-05-03       Impact factor: 3.748

Review 3.  Recent development of contrast agents for magnetic resonance and multimodal imaging of glioblastoma.

Authors:  Danping Zhuang; Huifen Zhang; Genwen Hu; Bing Guo
Journal:  J Nanobiotechnology       Date:  2022-06-16       Impact factor: 9.429

Review 4.  Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact.

Authors:  Qiuyun Fan; Cornelius Eichner; Maryam Afzali; Lars Mueller; Chantal M W Tax; Mathias Davids; Mirsad Mahmutovic; Boris Keil; Berkin Bilgic; Kawin Setsompop; Hong-Hsi Lee; Qiyuan Tian; Chiara Maffei; Gabriel Ramos-Llordén; Aapo Nummenmaa; Thomas Witzel; Anastasia Yendiki; Yi-Qiao Song; Chu-Chung Huang; Ching-Po Lin; Nikolaus Weiskopf; Alfred Anwander; Derek K Jones; Bruce R Rosen; Lawrence L Wald; Susie Y Huang
Journal:  Neuroimage       Date:  2022-02-23       Impact factor: 7.400

5.  In vivo magnetic resonance imaging and spectroscopy. Technological advances and opportunities for applications continue to abound.

Authors:  Peter van Zijl; Linda Knutsson
Journal:  J Magn Reson       Date:  2019-07-09       Impact factor: 2.229

6.  Towards unconstrained compartment modeling in white matter using diffusion-relaxation MRI with tensor-valued diffusion encoding.

Authors:  Björn Lampinen; Filip Szczepankiewicz; Johan Mårtensson; Danielle van Westen; Oskar Hansson; Carl-Fredrik Westin; Markus Nilsson
Journal:  Magn Reson Med       Date:  2020-03-06       Impact factor: 4.668

7.  Advances in Diffusion and Perfusion MRI for Quantitative Cancer Imaging.

Authors:  Mehran Baboli; Jin Zhang; Sungheon Gene Kim
Journal:  Curr Pathobiol Rep       Date:  2019-12-02

8.  Combined 18F-FET PET and diffusion kurtosis MRI in posttreatment glioblastoma: differentiation of true progression from treatment-related changes.

Authors:  Francesco D'Amore; Farida Grinberg; Jörg Mauler; Norbert Galldiks; Ganna Blazhenets; Ezequiel Farrher; Christian Filss; Gabriele Stoffels; Felix M Mottaghy; Philipp Lohmann; Nadim Jon Shah; Karl-Josef Langen
Journal:  Neurooncol Adv       Date:  2021-03-10

9.  Tensor-valued diffusion encoding for diffusional variance decomposition (DIVIDE): Technical feasibility in clinical MRI systems.

Authors:  Filip Szczepankiewicz; Jens Sjölund; Freddy Ståhlberg; Jimmy Lätt; Markus Nilsson
Journal:  PLoS One       Date:  2019-03-28       Impact factor: 3.240

Review 10.  Diagnostic value of alternative techniques to gadolinium-based contrast agents in MR neuroimaging-a comprehensive overview.

Authors:  Anna Falk Delgado; Danielle Van Westen; Markus Nilsson; Linda Knutsson; Pia C Sundgren; Elna-Marie Larsson; Alberto Falk Delgado
Journal:  Insights Imaging       Date:  2019-08-23
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