Functional Magnetic Resonance Imaging in Medicine and Physiology

Moonen, Chrit; Zijl, Peter C.M. van; Frank, Joseph A.; Bihan, Denis Le; Becker, Edwin D.

doi:10.1126/science.2218514

Cited by 174 publications

(78 citation statements)

References 76 publications

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“…(2) The physiologic basis of image contrast in functional magnetic resonance imaging critically depends on the underlying microvasculature (Moonen et al, 1990;Pathak et al, 2003Pathak et al, , 2008c. (3) The cerebral vasculature is central to understanding the hemodynamics and the pharmacokinetics of novel therapies in the brain (Reichold et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Vascular phenotyping of brain tumors using magnetic resonance microscopy (μMRI)

Kim

Zhang

Hong

et al. 2011

J Cereb Blood Flow Metab

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Abnormal vascular phenotypes have been implicated in neuropathologies ranging from Alzheimer's disease to brain tumors. The development of transgenic mouse models of such diseases has created a crucial need for characterizing the murine neurovasculature. Although histologic techniques are excellent for imaging the microvasculature at submicron resolutions, they offer only limited coverage. It is also challenging to reconstruct the three-dimensional (3D) vasculature and other structures, such as white matter tracts, after tissue sectioning. Here, we describe a novel method for 3D whole-brain mapping of the murine vasculature using magnetic resonance microscopy (lMRI), and its application to a preclinical brain tumor model. The 3D vascular architecture was characterized by six morphologic parameters: vessel length, vessel radius, microvessel density, length per unit volume, fractional blood volume, and tortuosity. Region-of-interest analysis showed significant differences in the vascular phenotype between the tumor and the contralateral brain, as well as between postinoculation day 12 and day 17 tumors. These results unequivocally show the feasibility of using lMRI to characterize the vascular phenotype of brain tumors. Finally, we show that combining these vascular data with coregistered images acquired with diffusion-weighted MRI provides a new tool for investigating the relationship between angiogenesis and concomitant changes in the brain tumor microenvironment.

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Section: Introductionmentioning

confidence: 99%

Vascular phenotyping of brain tumors using magnetic resonance microscopy (μMRI)

Kim

Zhang

Hong

et al. 2011

J Cereb Blood Flow Metab

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“…4B) can be attained on a time scale of minutes, many metabolic processes will be accessible by this technique. The opportunity to measure cellular metabolism and motional parameters of metabolites and water in a well-defined homogeneous system may provide the necessary reference data for the interpretation of the many functional imaging studies that are presently possible using MR imaging (38).…”

Section: Discussionmentioning

confidence: 99%

Complete separation of intracellular and extracellular information in NMR spectra of perfused cells by diffusion-weighted spectroscopy.

Zijl

Moonen

Faustino

et al. 1991

Proc. Natl. Acad. Sci. U.S.A.

196

138

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A method is outlined that completely separates intracellular and extracellular information in NMR spectra of perfused cells. The technique uses diffusion weighting to exploit differences in motional properties between intra-and extracellular constituents. This allows monitoring of intracellular metabolism, and oftransport of small drugs and nutrients through the cell membrane, under controlled physiological conditions. As a first example, proton spectra of drug-resistant MCF-7 human breast cancer cells are studied, and uptake of phenylalanine is monitored.To rationally design and test chemotherapeutic drugs, it is important to gain an understanding of basic tumor cell metabolism and transport. Monitoring of prolonged metabolic processes under controlled conditions requires continuous perfusion of a batch of a certain cell type, a procedure currently applied to 31P magnetic resonance (MR) studies of cells embedded in an agarose gel (1, 2). This setup (Fig. 1) provides an ex vivo tumor model with actively metabolizing cells.A major problem encountered in the NMR study of cells and organs is discrimination between intra-and extracellular contributions to the spectrum. This problem is more pronounced when the extracellular fraction increases and therefore depends on cell density. In ex vivo studies, this density may be orders of magnitude lower than in vivo. For instance, for breast cancer cells embedded in agarose gel, the extracellular water volume is about a factor of 100 larger than the total intracellular one. Thus, the NMR signal from a 0.1 mM metabolite in the perfusion medium will be comparable in intensity to 10 mM of this same metabolite in the cell, complicating the interpretation of signal intensity changes in terms of intracellular metabolite concentrations. For proton studies an additional problem arises due to the presence of the intense water resonance. For the typical example above, total intra-and extracellular water has a signal intensity that is a factor of about 106 higher than that for a 10 mM metabolite. As a result, proton spectra of intracellular metabolites in perfused cell cultures have never been reported. However, proton experiments can provide information about many compounds in the free metabolite pool of the cell as well as about most drugs, and it is important to find a solution for these difficulties. Proton spectra of cell suspensions have been reported (3, 4), but separation of intra-and extracellular signals is not straightforward.Here we address the problem using the difference in motional properties ofthese components (5-10). Intracellular species diffuse in the cellular matrix with an effective diffusion constant Di, which depends on several factors-e.g., molecular size, bonding, viscosity, temperature, and possible restrictions due to compartmentation (5-9, 11, 12). When extracellular, these species have a diffusion constant De in neat medium but also flow through the perfusion vial holding cells and their support system (an agarose gel). In this paper we use these di...

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“…electron paramagnetic resonance spectroscopy or phosphorescence imaginc are currentIr being used in attempts to develop non-invasix e assax s of tumour hvpoxia (Haw kins and Phelps. 1988: Moonen et al 1990: Coleman. 1991 Wilson and Cerniglia.…”

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confidence: 99%

Fraction of radiobiologically hypoxic cells in human melanoma xenografts measured by using single-cell survival, tumour growth delay and local tumour control as end points

Rofstad

Måseide²

1998

Br J Cancer

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Summary Four human melanoma xenograft lines (A-07, D-12, R-18, U-25) grown orthotopically in Balb/c nu/nu mice were characterzed with respect to the fraction of radiobiologically hypoxic cells. The purpose of the study was to establish a firm radiobiological basis for future use of the lines in the development and evaluation of non-invasive assays of tumour hypoxia. The hypoxic fractions were assessed using three different assays. the single cell survival assay, the tumour growth delay assay and the local tumour control assay, and the means + s.e.were found to be 6 ± 30%, 3 ± 1 0 and 5 ± 2%o respectively (A-07), 26 ± 50/0, 25 ± 60/o and 22 + 6%o respectively (D-12), 55 ± 9°o 65 ± 80/o and 48 ± 7°O respectively (R-1 8) and 52 ± 8%, 59 ± 7% and 47 ± 7% respectively (U-25). The three assays gave numerical values for the hypoxic fraction that were not significantly different for any of the lines. The hypoxic fraction differed significantly among the lines; the R-18 and U-25 lines showed higher hypoxic fractions than the D-12 line (P < 0.05). which in tum showed a higher hypoxic fraction than the A-07 line (P < 0.05). regardless of the assay. The wide range of the hypoxic fractions and the signfficant differences among the lines suggest that A-07. D-12. R-18 and U-25 tumours should be useful models in future studies attempting to develop non-invasive assays of tumour hypoxia.Keywords: treatment-response assay; hypoxic fraction; melanoma xenograft; radiation biology Manv human tumours develop regions of hxpoxic cells during gro,wth (Vaupel et al. 1989: 1991: Hockel et al. 1991. The fraction of hxpoxic cells differs substantially among individual tumours of the same histological tIpe (Nordsmark et al. 1994: Brizel et al. 1995: Wong et al. 1997. Hypoxia may cause resistance to radiation therapy (Coleman. 1988: Gatenbv et al. 1988: Hockel et al. 1993: Nordsmark et al. 1996: Brizel et al. 1997: Fx-les et al. 1997 and some forms of chemotherapx (Teicher. 1994) and mav promote the development of metastatic disease (Schwickert et al. 1995: Brizel et al. 1996: Hockel et al. 1996: Walenta et al. 1997 March 1998 Correspondence to: EK Rofstad treatment resistance and malignant progression (Kim et al. 1993: Fenton et al. 1995

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Functional Magnetic Resonance Imaging in Medicine and Physiology

Cited by 174 publications

References 76 publications

Vascular phenotyping of brain tumors using magnetic resonance microscopy (μMRI)

Vascular phenotyping of brain tumors using magnetic resonance microscopy (μMRI)

Complete separation of intracellular and extracellular information in NMR spectra of perfused cells by diffusion-weighted spectroscopy.

Fraction of radiobiologically hypoxic cells in human melanoma xenografts measured by using single-cell survival, tumour growth delay and local tumour control as end points

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