Literature DB >> 33344067

Advances in Diffusion and Perfusion MRI for Quantitative Cancer Imaging.

Mehran Baboli1, Jin Zhang1, Sungheon Gene Kim1.   

Abstract

PURPOSE OF REVIEW: This article is to review recent technical developments and their clinical applications in cancer imaging quantitative measurement of cellular and vascular properties of the tumors. RECENT
FINDINGS: Rapid development of fast Magnetic Resonance Imaging (MRI) technologies over last decade brought new opportunities in quantitative MRI methods to measure both cellular and vascular properties of tumors simultaneously.
SUMMARY: Diffusion MRI (dMRI) and dynamic contrast enhanced (DCE)-MRI have become widely used to assess the tissue structural and vascular properties, respectively. However, the ultimate potential of these advanced imaging modalities has not been fully exploited. The dependency of dMRI on the diffusion weighting gradient strength and diffusion time can be utilized to measure tumor perfusion, cellular structure, and cellular membrane permeability. Similarly, DCE-MRI can be used to measure vascular and cellular membrane permeability along with cellular compartment volume fractions. To facilitate the understanding of these potentially important methods for quantitative cancer imaging, we discuss the basic concepts and recent developments, as well as future directions for further development.

Entities:  

Keywords:  Cancer imaging; DCE-MRI; Diffusion MRI; Microstructure; Perfusion; Water Exchange

Year:  2019        PMID: 33344067      PMCID: PMC7747414          DOI: 10.1007/s40139-019-00204-7

Source DB:  PubMed          Journal:  Curr Pathobiol Rep        ISSN: 2167-485X


  93 in total

Review 1.  Fundamentals of quantitative dynamic contrast-enhanced MR imaging.

Authors:  Michael J Paldino; Daniel P Barboriak
Journal:  Magn Reson Imaging Clin N Am       Date:  2009-05       Impact factor: 2.266

2.  Shutter-speed dynamic contrast-enhanced MRI: Is it fit for purpose?

Authors:  David L Buckley
Journal:  Magn Reson Med       Date:  2018-09-19       Impact factor: 4.668

3.  Dynamic T1-weighted magnetic resonance imaging and positron emission tomography in patients with lung cancer: correlating vascular physiology with glucose metabolism.

Authors:  G J Hunter; L M Hamberg; N Choi; R K Jain; T McCloud; A J Fischman
Journal:  Clin Cancer Res       Date:  1998-04       Impact factor: 12.531

4.  Diffusion-weighed MR imaging of pancreatic carcinoma.

Authors:  M Matsuki; Y Inada; G Nakai; F Tatsugami; M Tanikake; I Narabayashi; D Masuda; Y Arisaka; K Takaori; N Tanigawa
Journal:  Abdom Imaging       Date:  2007 Jul-Aug

5.  Quantification of endothelial permeability, leakage space, and blood volume in brain tumors using combined T1 and T2* contrast-enhanced dynamic MR imaging.

Authors:  X P Zhu; K L Li; I D Kamaly-Asl; D R Checkley; J J Tessier; J C Waterton; A Jackson
Journal:  J Magn Reson Imaging       Date:  2000-06       Impact factor: 4.813

6.  Learning a variational network for reconstruction of accelerated MRI data.

Authors:  Kerstin Hammernik; Teresa Klatzer; Erich Kobler; Michael P Recht; Daniel K Sodickson; Thomas Pock; Florian Knoll
Journal:  Magn Reson Med       Date:  2017-11-08       Impact factor: 4.668

7.  Apparent diffusion coefficient in pancreatic cancer: characterization and histopathological correlations.

Authors:  Noriaki Muraoka; Hidemasa Uematsu; Hirohiko Kimura; Yoshiaki Imamura; Yasuhiro Fujiwara; Makoto Murakami; Akio Yamaguchi; Harumi Itoh
Journal:  J Magn Reson Imaging       Date:  2008-06       Impact factor: 4.813

8.  Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI.

Authors:  Li Feng; Robert Grimm; Kai Tobias Block; Hersh Chandarana; Sungheon Kim; Jian Xu; Leon Axel; Daniel K Sodickson; Ricardo Otazo
Journal:  Magn Reson Med       Date:  2013-10-18       Impact factor: 4.668

9.  Intratumor mapping of intracellular water lifetime: metabolic images of breast cancer?

Authors:  Charles S Springer; Xin Li; Luminita A Tudorica; Karen Y Oh; Nicole Roy; Stephen Y-C Chui; Arpana M Naik; Megan L Holtorf; Aneela Afzal; William D Rooney; Wei Huang
Journal:  NMR Biomed       Date:  2014-05-05       Impact factor: 4.044

10.  Apparent exchange rate for breast cancer characterization.

Authors:  Samo Lasič; Stina Oredsson; Savannah C Partridge; Lao H Saal; Daniel Topgaard; Markus Nilsson; Karin Bryskhe
Journal:  NMR Biomed       Date:  2016-02-29       Impact factor: 4.044

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