Literature DB >> 19009568

Monitoring of gliomas in vivo by diffusion MRI and (1)H MRS during gene therapy-induced apoptosis: interrelationships between water diffusion and mobile lipids.

Timo Liimatainen1, Juhana M Hakumäki, Risto A Kauppinen, Mika Ala-Korpela.   

Abstract

The measurement of water diffusion by diffusion-weighted MRI (DWI) in vivo offers a non-invasive method for assessing tissue responses to anti-cancer therapies. The pathway of cell death after anti-cancer treatment is often apoptosis, which leads to accumulation of mobile lipids detectable by (1)H MRS in vivo. However, it is not known how these discrete MR markers of cell death relate to each other. In a rodent tumour model [i.e. ganciclovir-treated herpes simplex thymidine kinase (HSV-tk) gene-transfected BT4C gliomas], we studied the interrelationships between water diffusion (Trace{D}) and mobile lipids during apoptosis. Water diffusion and water-referenced concentrations of mobile lipids showed clearly increasing and interconnected trends during treatment. Of the accumulating (1)H MRS-visible lipids, the fatty acid --CH==CH-- groups and cholesterol compounds showed the strongest associations with water diffusion (r(2) = 0.30; P < 0.05 and r(2) = 0.48; P < 0.01, respectively). These results indicate that the tumour histopathology and apoptotic processes during tumour shrinkage can be interrelated in vivo by DWI of tissue water and (1)H MRS of mobile lipids, respectively. However, there is considerable individual variation in the associations, particularly at the end of the treatment period, and in the relative compositions of the accumulating NMR-visible lipids. The findings suggest that the assessment of individual treatment response in vivo may benefit from combining DWI and (1)H MRS. Absolute and relative changes in mobile lipids may indicate initiation of tumour shrinkage even when changes in tissue water diffusion are still small. Conversely, greatly increased water diffusion probably indicates that substantial cell decomposition has taken place in the tumour tissue when the (1)H MRS resonances of mobile lipids alone can no longer give a reliable estimate of tissue conditions.

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Year:  2009        PMID: 19009568     DOI: 10.1002/nbm.1320

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  16 in total

Review 1.  Diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy.

Authors:  Anwar R Padhani; Aftab Alam Khan
Journal:  Target Oncol       Date:  2010-04-11       Impact factor: 4.493

2.  In vivo characterization of several rodent glioma models by 1H MRS.

Authors:  Sabrina Doblas; Ting He; Debra Saunders; Jessica Hoyle; Nataliya Smith; Quentin Pye; Megan Lerner; Randy L Jensen; Rheal A Towner
Journal:  NMR Biomed       Date:  2011-09-23       Impact factor: 4.044

3.  Glioma cell density in a rat gene therapy model gauged by water relaxation rate along a fictitious magnetic field.

Authors:  Timo Liimatainen; Alejandra Sierra; Timothy Hanson; Dennis J Sorce; Seppo Ylä-Herttuala; Michael Garwood; Shalom Michaeli; Olli Gröhn
Journal:  Magn Reson Med       Date:  2011-06-30       Impact factor: 4.668

4.  MRI detection of bacterial brain abscesses and monitoring of antibiotic treatment using bacCEST.

Authors:  Jing Liu; Renyuan Bai; Yuguo Li; Verena Staedtke; Shuixing Zhang; Peter C M van Zijl; Guanshu Liu
Journal:  Magn Reson Med       Date:  2018-03-25       Impact factor: 4.668

Review 5.  Lipid metabolism emerges as a promising target for malignant glioma therapy.

Authors:  Deliang Guo; Erica Hlavin Bell; Arnab Chakravarti
Journal:  CNS Oncol       Date:  2013-05

Review 6.  MR-visible lipids and the tumor microenvironment.

Authors:  E James Delikatny; Sanjeev Chawla; Daniel-Joseph Leung; Harish Poptani
Journal:  NMR Biomed       Date:  2011-04-27       Impact factor: 4.044

7.  Prospective analysis of parametric response map-derived MRI biomarkers: identification of early and distinct glioma response patterns not predicted by standard radiographic assessment.

Authors:  Craig J Galbán; Thomas L Chenevert; Charles R Meyer; Christina Tsien; Theodore S Lawrence; Daniel A Hamstra; Larry Junck; Pia C Sundgren; Timothy D Johnson; Stefanie Galbán; Judith S Sebolt-Leopold; Alnawaz Rehemtulla; Brian D Ross
Journal:  Clin Cancer Res       Date:  2011-04-28       Impact factor: 12.531

8.  Metabolomics of human breast cancer: new approaches for tumor typing and biomarker discovery.

Authors:  Carsten Denkert; Elmar Bucher; Mika Hilvo; Reza Salek; Matej Orešič; Julian Griffin; Scarlet Brockmöller; Frederick Klauschen; Sibylle Loibl; Dinesh Kumar Barupal; Jan Budczies; Kristiina Iljin; Valentina Nekljudova; Oliver Fiehn
Journal:  Genome Med       Date:  2012-04-30       Impact factor: 11.117

9.  NMR spectroscopy of macrophages loaded with native, oxidized or enzymatically degraded lipoproteins.

Authors:  Paul Ramm Sander; Markus Peer; Margot Grandl; Ulrich Bogdahn; Gerd Schmitz; Hans Robert Kalbitzer
Journal:  PLoS One       Date:  2013-02-15       Impact factor: 3.240

10.  Development of a Multiparametric Voxel-Based Magnetic Resonance Imaging Biomarker for Early Cancer Therapeutic Response Assessment.

Authors:  Craig J Galbán; Benjamin Lemasson; Benjamin A Hoff; Timothy D Johnson; Pia C Sundgren; Christina Tsien; Thomas L Chenevert; Brian D Ross
Journal:  Tomography       Date:  2015-09
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