Literature DB >> 20575076

Predicting and monitoring cancer treatment response with diffusion-weighted MRI.

Harriet C Thoeny1, Brian D Ross.   

Abstract

An imaging biomarker that would provide for an early quantitative metric of clinical treatment response in cancer patients would provide for a paradigm shift in cancer care. Currently, nonimage based clinical outcome metrics include morphology, clinical, and laboratory parameters, however, these are obtained relatively late following treatment. Diffusion-weighted MRI (DW-MRI) holds promise for use as a cancer treatment response biomarker as it is sensitive to macromolecular and microstructural changes which can occur at the cellular level earlier than anatomical changes during therapy. Studies have shown that successful treatment of many tumor types can be detected using DW-MRI as an early increase in the apparent diffusion coefficient (ADC) values. Additionally, low pretreatment ADC values of various tumors are often predictive of better outcome. These capabilities, once validated, could provide for an important opportunity to individualize therapy thereby minimizing unnecessary systemic toxicity associated with ineffective therapies with the additional advantage of improving overall patient health care and associated costs. In this report, we provide a brief technical overview of DW-MRI acquisition protocols, quantitative image analysis approaches and review studies which have implemented DW-MRI for the purpose of early prediction of cancer treatment response. (c) 2010 Wiley-Liss, Inc.

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Year:  2010        PMID: 20575076      PMCID: PMC2918419          DOI: 10.1002/jmri.22167

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


  65 in total

1.  Prospective early response imaging biomarker for neoadjuvant breast cancer chemotherapy.

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Journal:  Clin Cancer Res       Date:  2007-01-15       Impact factor: 12.531

2.  [Use of diffusion-weighted MRI in monitoring response of lymph node metastatic bladder cancer treated with chemotherary].

Authors:  Takayuki Nakayama; Soichiro Yoshida; Yasuhisa Fujii; Fumitaka Koga; Kazutaka Saito; Hitoshi Masuda; Tsuyoshi Kobayashi; Satoru Kawakami; Kazunori Kihara
Journal:  Nihon Hinyokika Gakkai Zasshi       Date:  2008-11

Review 3.  MRI: use of the inversion recovery pulse sequence.

Authors:  G M Bydder; J V Hajnal; I R Young
Journal:  Clin Radiol       Date:  1998-03       Impact factor: 2.350

4.  Proton and sodium MRI assessment of emerging tumor chemotherapeutic resistance.

Authors:  Victor D Schepkin; Kuei C Lee; Kyle Kuszpit; Mukilan Muthuswami; Timothy D Johnson; Thomas L Chenevert; Alnawaz Rehemtulla; Brian D Ross
Journal:  NMR Biomed       Date:  2006-12       Impact factor: 4.044

Review 5.  Diffusion imaging for evaluation of tumor therapies in preclinical animal models.

Authors:  B A Moffat; D E Hall; J Stojanovska; P J McConville; J B Moody; T L Chenevert; A Rehemtulla; B D Ross
Journal:  MAGMA       Date:  2004-12-01       Impact factor: 2.310

6.  Evaluation of the functional diffusion map as an early biomarker of time-to-progression and overall survival in high-grade glioma.

Authors:  Daniel A Hamstra; Thomas L Chenevert; Bradford A Moffat; Timothy D Johnson; Charles R Meyer; Suresh K Mukherji; Douglas J Quint; Stephen S Gebarski; Xiaoying Fan; Christina I Tsien; Theodore S Lawrence; Larry Junck; Alnawaz Rehemtulla; Brian D Ross
Journal:  Proc Natl Acad Sci U S A       Date:  2005-11-02       Impact factor: 11.205

7.  Diffusion-weighted magnetic resonance imaging for predicting and detecting early response to chemoradiation therapy of squamous cell carcinomas of the head and neck.

Authors:  Sungheon Kim; Laurie Loevner; Harry Quon; Eric Sherman; Gregory Weinstein; Alex Kilger; Harish Poptani
Journal:  Clin Cancer Res       Date:  2009-02-01       Impact factor: 12.531

8.  Advanced pancreatic cancer: the use of the apparent diffusion coefficient to predict response to chemotherapy.

Authors:  T Niwa; M Ueno; S Ohkawa; T Yoshida; T Doiuchi; K Ito; T Inoue
Journal:  Br J Radiol       Date:  2009-01       Impact factor: 3.039

9.  Diffusion-weighted MRI in cervical cancer.

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10.  Test liquids for quantitative MRI measurements of self-diffusion coefficient in vivo.

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  127 in total

1.  Evaluation of diffusion-weighted MRI and geometric distortion on a 0.35T MR-LINAC at multiple gantry angles.

Authors:  Benjamin Lewis; Anamaria Guta; Stacie Mackey; H Michael Gach; Sasa Mutic; Olga Green; Taeho Kim
Journal:  J Appl Clin Med Phys       Date:  2021-01-15       Impact factor: 2.102

2.  Preliminary study of apparent diffusion coefficient assessment after ion beam therapy for hepatocellular carcinoma.

Authors:  Masayuki Kanamoto; Tosiaki Miyati; Kazuki Terashima; Daisaku Suga; Nobukazu Fuwa
Journal:  Radiol Phys Technol       Date:  2016-04-07

3.  A study of the relationship of metabolic MR parameters to estrogen dependence in breast cancer xenografts.

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4.  Treatment-related changes in neuroendocrine tumors as assessed by textural features derived from 68Ga-DOTATOC PET/MRI with simultaneous acquisition of apparent diffusion coefficient.

Authors:  Manuel Weber; Lukas Kessler; Benedikt Schaarschmidt; Wolfgang Peter Fendler; Harald Lahner; Gerald Antoch; Lale Umutlu; Ken Herrmann; Christoph Rischpler
Journal:  BMC Cancer       Date:  2020-04-16       Impact factor: 4.430

5.  Multimodal imaging for early functional response assessment of (90)Y-/ (177)Lu-DOTATOC peptide receptor targeted radiotherapy with DW-MRI and (68)Ga-DOTATOC-PET/CT.

Authors:  Sarah Wulfert; Clemens Kratochwil; Peter L Choyke; Ali Afshar-Oromieh; Walter Mier; Hans-Ulrich Kauczor; Jens-Peter Schenk; Uwe Haberkorn; Frederik L Giesel
Journal:  Mol Imaging Biol       Date:  2014-08       Impact factor: 3.488

6.  Assessing reproducibility of diffusion-weighted magnetic resonance imaging studies in a murine model of HER2+ breast cancer.

Authors:  Jennifer G Whisenant; Gregory D Ayers; Mary E Loveless; Stephanie L Barnes; Daniel C Colvin; Thomas E Yankeelov
Journal:  Magn Reson Imaging       Date:  2013-12-14       Impact factor: 2.546

7.  Uveal melanoma: quantitative evaluation of diffusion-weighted MR imaging in the response assessment after proton-beam therapy, long-term follow-up.

Authors:  Pietro Valerio Foti; Antonio Longo; Michele Reibaldi; Andrea Russo; Giuseppe Privitera; Corrado Spatola; Luigi Raffaele; Vincenzo Salamone; Renato Farina; Stefano Palmucci; Andrea Musumeci; Rosario Caltabiano; Marco Ragusa; Cesare Mariotti; Teresio Avitabile; Pietro Milone; Giovanni Carlo Ettorre
Journal:  Radiol Med       Date:  2016-10-17       Impact factor: 3.469

8.  Phenethyl isothiocyanate hampers growth and progression of HER2-positive breast and ovarian carcinoma by targeting their stem cell compartment.

Authors:  Ada Koschorke; Simona Faraci; Debora Giani; Claudia Chiodoni; Egidio Iorio; Rossella Canese; Mario P Colombo; Alessia Lamolinara; Manuela Iezzi; Michael Ladomery; Claudio Vernieri; Filippo de Braud; Massimo Di Nicola; Elda Tagliabue; Lorenzo Castagnoli; Serenella M Pupa
Journal:  Cell Oncol (Dordr)       Date:  2019-08-02       Impact factor: 6.730

9.  Serial diffusion MRI to monitor and model treatment response of the targeted nanotherapy CRLX101.

Authors:  Thomas S C Ng; David Wert; Hargun Sohi; Daniel Procissi; David Colcher; Andrew A Raubitschek; Russell E Jacobs
Journal:  Clin Cancer Res       Date:  2013-03-26       Impact factor: 12.531

10.  Diffusion MRI with Semi-Automated Segmentation Can Serve as a Restricted Predictive Biomarker of the Therapeutic Response of Liver Metastasis.

Authors:  Renu M Stephen; Abhinav K Jha; Denise J Roe; Theodore P Trouard; Jean-Philippe Galons; Matthew A Kupinski; Georgette Frey; Haiyan Cui; Scott Squire; Mark D Pagel; Jeffrey J Rodriguez; Robert J Gillies; Alison T Stopeck
Journal:  Magn Reson Imaging       Date:  2015-08-15       Impact factor: 2.546

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