Literature DB >> 30311988

Diffusion MRI of cancer: From low to high b-values.

Lei Tang1, Xiaohong Joe Zhou2.   

Abstract

Following its success in early detection of cerebral ischemia, diffusion-weighted imaging (DWI) has been increasingly used in cancer diagnosis and treatment evaluation. These applications are propelled by the rapid development of novel diffusion models to extract biologically valuable information from diffusion-weighted MR signals, and significant advances in MR hardware that has enabled image acquisition with high b-values. This article reviews recent technical developments and clinical applications in cancer imaging using DWI, with a special emphasis on high b-value diffusion models. The article is organized in four sections. First, we provide an overview of diffusion models that are relevant to cancer imaging. The model parameters are discussed in relation to three tissue properties-cellularity, vascularity, and microstructures. An emphasis is placed on characterization of microstructural heterogeneity, given its novelty and close relevance to cancer. Second, we illustrate diffusion MR clinical applications in each of the following three categories: 1) cancer detection and diagnosis; 2) cancer grading, staging, and classification; and 3) cancer treatment response prediction and evaluation. Third, we discuss several practical issues, including selection of image acquisition parameters, reproducibility and reliability, motion management, image distortion, etc., that are commonly encountered when applying DWI to cancer in clinical settings. Lastly, we highlight a few ongoing challenges and provide some possible future directions, particularly in the area of establishing standards via well-organized multicenter clinical trials to accelerate clinical translation of advanced DWI techniques to improving cancer care on a large scale. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:23-40.
© 2018 International Society for Magnetic Resonance in Medicine.

Entities:  

Year:  2018        PMID: 30311988      PMCID: PMC6298843          DOI: 10.1002/jmri.26293

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  114 in total

1.  Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo.

Authors:  T G Reese; O Heid; R M Weisskoff; V J Wedeen
Journal:  Magn Reson Med       Date:  2003-01       Impact factor: 4.668

2.  Assessment of treatment response after lung stereotactic body radiotherapy using diffusion weighted magnetic resonance imaging and positron emission tomography: A pilot study.

Authors:  Takashi Shintani; Yukinori Matsuo; Yusuke Iizuka; Takamasa Mitsuyoshi; Shigeaki Umeoka; Yuji Nakamoto; Takashi Mizowaki; Kaori Togashi; Masahiro Hiraoka
Journal:  Eur J Radiol       Date:  2017-04-28       Impact factor: 3.528

3.  Probing tissue microstructure with restriction spectrum imaging: Histological and theoretical validation.

Authors:  Nathan S White; Trygve B Leergaard; Helen D'Arceuil; Jan G Bjaalie; Anders M Dale
Journal:  Hum Brain Mapp       Date:  2012-01-16       Impact factor: 5.038

4.  Diagnosis of Prostate Cancer with Noninvasive Estimation of Prostate Tissue Composition by Using Hybrid Multidimensional MR Imaging: A Feasibility Study.

Authors:  Aritrick Chatterjee; Roger M Bourne; Shiyang Wang; Ajit Devaraj; Alexander J Gallan; Tatjana Antic; Gregory S Karczmar; Aytekin Oto
Journal:  Radiology       Date:  2018-02-02       Impact factor: 11.105

5.  Predictive value of apparent diffusion coefficient in evaluation of colorectal carcinoma hepatic metastases' response to radiofrequency ablation.

Authors:  Edyta Szurowska; Tomasz K Nowicki; Ewa Izycka-Swieszewska; Dariusz Zadrozny; Karolina Markiet; Michal Studniarek
Journal:  J Magn Reson Imaging       Date:  2013-03-22       Impact factor: 4.813

Review 6.  Gleason grading and prognostic factors in carcinoma of the prostate.

Authors:  Peter A Humphrey
Journal:  Mod Pathol       Date:  2004-03       Impact factor: 7.842

7.  The link between diffusion MRI and tumor heterogeneity: Mapping cell eccentricity and density by diffusional variance decomposition (DIVIDE).

Authors:  Filip Szczepankiewicz; Danielle van Westen; Elisabet Englund; Carl-Fredrik Westin; Freddy Ståhlberg; Jimmy Lätt; Pia C Sundgren; Markus Nilsson
Journal:  Neuroimage       Date:  2016-07-20       Impact factor: 6.556

8.  On random walks and entropy in diffusion-weighted magnetic resonance imaging studies of neural tissue.

Authors:  Carson Ingo; Richard L Magin; Luis Colon-Perez; William Triplett; Thomas H Mareci
Journal:  Magn Reson Med       Date:  2014-02       Impact factor: 4.668

9.  Early detection of response to radiation therapy in patients with brain malignancies using conventional and high b-value diffusion-weighted magnetic resonance imaging.

Authors:  Yael Mardor; Raphael Pfeffer; Roberto Spiegelmann; Yiftach Roth; Stephan E Maier; Ouzi Nissim; Raanan Berger; Ami Glicksman; Jacob Baram; Arie Orenstein; Jack S Cohen; Thomas Tichler
Journal:  J Clin Oncol       Date:  2003-03-15       Impact factor: 44.544

10.  On a fractional order calculus model in diffusion weighted breast imaging to differentiate between malignant and benign breast lesions detected on X-ray screening mammography.

Authors:  Sebastian Bickelhaupt; Franziska Steudle; Daniel Paech; Anna Mlynarska; Tristan Anselm Kuder; Wolfgang Lederer; Heidi Daniel; Martin Freitag; Stefan Delorme; Heinz-Peter Schlemmer; Frederik Bernd Laun
Journal:  PLoS One       Date:  2017-04-28       Impact factor: 3.240

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  19 in total

Review 1.  Abbreviated MRI for Hepatocellular Carcinoma Screening and Surveillance.

Authors:  Julie Y An; Miguel A Peña; Guilherme M Cunha; Michael T Booker; Bachir Taouli; Takeshi Yokoo; Claude B Sirlin; Kathryn J Fowler
Journal:  Radiographics       Date:  2020 Nov-Dec       Impact factor: 5.333

2.  Machine Learning Based on MRI DWI Radiomics Features for Prognostic Prediction in Nasopharyngeal Carcinoma.

Authors:  Qiyi Hu; Guojie Wang; Xiaoyi Song; Jingjing Wan; Man Li; Fan Zhang; Qingling Chen; Xiaoling Cao; Shaolin Li; Ying Wang
Journal:  Cancers (Basel)       Date:  2022-06-30       Impact factor: 6.575

3.  Cervical Carcinoma: Evaluation Using Diffusion MRI With a Fractional Order Calculus Model and its Correlation With Histopathologic Findings.

Authors:  Xian Shao; Li An; Hui Liu; Hui Feng; Liyun Zheng; Yongming Dai; Bin Yu; Jin Zhang
Journal:  Front Oncol       Date:  2022-04-05       Impact factor: 5.738

Review 4.  Choosing The Right Animal Model for Renal Cancer Research.

Authors:  Paweł Sobczuk; Anna Brodziak; Mohammed Imran Khan; Stuti Chhabra; Michał Fiedorowicz; Marlena Wełniak-Kamińska; Kamil Synoradzki; Ewa Bartnik; Agnieszka Cudnoch-Jędrzejewska; Anna M Czarnecka
Journal:  Transl Oncol       Date:  2020-02-22       Impact factor: 4.243

5.  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

6.  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

Review 7.  Current and Emerging Magnetic Resonance-Based Techniques for Breast Cancer.

Authors:  Apekshya Chhetri; Xin Li; Joseph V Rispoli
Journal:  Front Med (Lausanne)       Date:  2020-05-12

Review 8.  Preclinical Molecular Imaging for Precision Medicine in Breast Cancer Mouse Models.

Authors:  M F Fiordelisi; L Auletta; L Meomartino; L Basso; G Fatone; M Salvatore; M Mancini; A Greco
Journal:  Contrast Media Mol Imaging       Date:  2019-09-22       Impact factor: 3.161

9.  Evaluation of Multiple Prognostic Factors of Hepatocellular Carcinoma with Intra-Voxel Incoherent Motions Imaging by Extracting the Histogram Metrics.

Authors:  Gaofeng Shi; Xue Han; Qi Wang; Yan Ding; Hui Liu; Yunfei Zhang; Yongming Dai
Journal:  Cancer Manag Res       Date:  2020-07-20       Impact factor: 3.989

Review 10.  Medical physics challenges in clinical MR-guided radiotherapy.

Authors:  Christopher Kurz; Giulia Buizza; Guillaume Landry; Florian Kamp; Moritz Rabe; Chiara Paganelli; Guido Baroni; Michael Reiner; Paul J Keall; Cornelis A T van den Berg; Marco Riboldi
Journal:  Radiat Oncol       Date:  2020-05-05       Impact factor: 3.481

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