Technical aspects of perfusion-weighted imaging

MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129, USA.
Neuroimaging Clinics of North America (Impact Factor: 1.53). 09/2005; 15(3):623-37, xi. DOI: 10.1016/j.nic.2005.08.009
Source: PubMed


There is increasing interest in using diffusion-weighted (DWI) MR imaging and perfusion-weighted MR imaging (PWI) to assist clinical decision-making in the management of acute stroke patients. Larger PWI than DWI lesions have been speculated to represent potentially salvageable tissue that is at risk of infarction unless nutritive flow is restored and presence of these mismatches have been proposed as inclusion criteria for identifying patients most likely to benefit from therapeutic intervention. Understanding the technical aspects of PWI may improve comprehension of the capabilities and limitations of this technique.

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    • "pMRI was acquired with a gradient echo echo-planar imaging (EPI) sequence and dynamic susceptibility contrast-enhanced (DSC) technique as previously described [21]. Relative cerebral blood volume (rCBV) maps were calculated based on established tracer kinetic models applied to first pass data using commercial perfusion analysis software (Nordic Ice, Nordic NeuroLab, Bergen, Norway) [9, 22, 23]. "
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    ABSTRACT: Perfusion and diffusion magnetic resonance imaging (pMRI, dMRI) are valuable diagnostic tools for assessing brain tumors in the clinical setting. The aim of this study was to determine the correlation of pMRI and dMRI with (11)C-methionine positron emission tomography (MET PET) in suspected low-grade gliomas (LGG) prior to surgery. Twenty-four adults with suspected LGG were enrolled in an observational study and examined by MET PET, pMRI and dMRI. Histological tumor diagnosis was confirmed in 23/24 patients (18 gliomas grade II, 5 gliomas grade III). The maximum relative cerebral blood volume (rCBVmax) and the minimum mean diffusivity (MDmin) were measured in tumor areas with highest MET uptake (hotspot) on PET by using automated co-registration of MRI and PET scans. A clearly defined hotspot on PET was present in all 23 tumors. Regions with rCBVmax corresponded with hotspot regions in all tumors, regions with MDmin corresponded with hotspot regions in 20/23 tumors. The correlation between rCBVmax (r = 0.19, P = 0.38) and MDmin (r = -0.41, P = 0.053) with MET uptake in the hotspot was not statistically significant. Taken into account the difficulties of measuring perfusion abnormalities in non-enhancing gliomas, this study demonstrates that co-registered MET PET and pMRI facilitates the identification of regions with rCBVmax. Furthermore, the lack of a clear positive correlation between tumor metabolism in terms of MET uptake and tumor vascularity measured as rCBVmax suggests that combined pMRI/PET provides complementary baseline imaging data in these tumors.
    Journal of Neuro-Oncology 06/2013; 114(2). DOI:10.1007/s11060-013-1178-3 · 3.07 Impact Factor
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    • "Perfusion and diffusion MRI are most commonly used stroke imaging techniques, providing information about disrupted hemodynamic and cellular structural status [17, 47-51]. Whereas MR angiogram can detect the location and severity of occlusion, the downstream tissue hemodynamic status can be better characterized with dynamic susceptibility contrast (DSC), dynamic contrast enhance (DCE) and arterial spin labeling (ASL) techniques, providing quantitative parameters such as cerebral blood flow (CBF), volume (CBV) and mean transit time (MTT), etc [52, 53]. Particularly, ASL MRI employs arterial water as an endogenous tracer, and is completely non-invasive and very popular in pre-clinical studies [54, 55]. "
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    ABSTRACT: Magnetic resonance imaging (MRI) and spectroscopy (MRS) are versatile diagnostic techniques capable of characterizing the complex stroke pathophysiology, and hold great promise for guiding stroke treatment. Particularly, tissue viability and salvageability are closely associated with its metabolic status. Upon ischemia, ischemic tissue metabolism is disrupted including altered metabolism of glucose and oxygen, elevated lactate production/accumulation, tissue acidification and eventually, adenosine triphosphate (ATP) depletion and energy failure. Whereas metabolism impairment during ischemic stroke is complex, it may be monitored non-invasively with magnetic resonance (MR)-based techniques. Our current article provides a concise overview of stroke pathology, conventional and emerging imaging and spectroscopy techniques, and data analysis tools for characterizing ischemic tissue damage.
    The Open Neuroimaging Journal 11/2011; 5(Suppl 1):66-73. DOI:10.2174/1874440001105010066
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    • "For example, in major vasculopathy cases, contrast agents may arrive earlier in the tissue than in the chosen AIF, leading errors in the estimation. Following previous studies [15], [16], [30], we use circulant (by means of a block-circulant version of matrix) instead of linear deconvolution to avoid such causality problems. The accuracy of the estimation of residue function by cTSVD is sensitive to the choice of the regularization parameter . "
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    ABSTRACT: Perfusion imaging is a useful adjunct to anatomic imaging in numerous diagnostic and therapy-monitoring settings. One approach to perfusion imaging is to assume a convolution relationship between a local arterial input function and the tissue enhancement profile of the region of interest via a ??residue function?? and subsequently solve for this residue function. This ill-posed problem is generally solved using singular-value decomposition based approaches, and the hemodynamic parameters are solved for each voxel independently. In this paper, we present a formulation which incorporates both spatial and temporal correlations, and show through simulations that this new formulation yields higher accuracy and greater robustness with respect to image noise. We also show using rectal cancer tumor images that this new formulation results in better segregation of normal and cancerous voxels.
    IEEE Transactions on Medical Imaging 06/2010; 29(5-29):1182 - 1191. DOI:10.1109/TMI.2010.2043536 · 3.39 Impact Factor
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