The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) offers unique possibilities. In this paper we aim to exploit the high spatial resolution of MRI to enhance the reconstruction of simultaneously acquired PET data. We propose a new prior to incorporate structural side information into a maximum a posteriori reconstruction. The new prior combines the strengths of previously proposed priors for the same problem: it is very efficient in guiding the reconstruction at edges available from the side information and it reduces locally to edge-preserving total variation in the degenerate case when no structural information is available. In addition, this prior is segmentation-free, convex and no a priori assumptions are made on the correlation of edge directions of the PET and MRI images. We present results for a simulated brain phantom and for real data acquired by the Siemens Biograph mMR for a hardware phantom and a clinical scan. The results from simulations show that the new prior has a better trade-off between enhancing common anatomical boundaries and preserving unique features than several other priors. Moreover, it has a better mean absolute bias-to-mean standard deviation trade-off and yields reconstructions with superior relative l-error and structural similarity index. These findings are underpinned by the real data results from a hardware phantom and a clinical patient confirming that the new prior is capable of promoting well-defined anatomical boundaries.
Although xenon is classically taught to be a "perfusion-limited" gas, (129)Xe in its hyperpolarized (HP) form, when detected by magnetic resonance (MR), can probe diffusion limitation. Inhaled HP (129)Xe diffuses across the pulmonary blood-gas barrier, and, depending on its tissue environment, shifts its resonant frequency relative to the gas-phase reference (0 ppm) by 198 ppm in tissue/plasma barrier and 217 ppm in red blood cells (RBCs). In this work, we hypothesized that in patients with idiopathic pulmonary fibrosis (IPF), the ratio of (129)Xe spectroscopic signal in the RBCs vs. barrier would diminish as diffusion-limitation delayed replenishment of (129)Xe magnetization in RBCs. To test this hypothesis, (129)Xe spectra were acquired in 6 IPF subjects as well as 11 healthy volunteers to establish a normal range. The RBC:barrier ratio was 0.55 ± 0.13 in healthy volunteers but was 3.3-fold lower in IPF subjects (0.16 ± 0.03, P = 0.0002). This was caused by a 52% reduction in the RBC signal (P = 0.02) and a 58% increase in the barrier signal (P = 0.01). Furthermore, the RBC:barrier ratio strongly correlated with lung diffusing capacity for carbon monoxide (DLCO) (r = 0.89, P < 0.0001). It exhibited a moderate interscan variability (8.25%), and in healthy volunteers it decreased with greater lung inflation (r = -0.78, P = 0.005). This spectroscopic technique provides a noninvasive, global probe of diffusion limitation and gas-transfer impairment and forms the basis for developing 3D MR imaging of gas exchange.
Key points The blood–brain barrier (BBB) is an important and dynamic structure which contributes to homeostasis in the central nervous system.BBB permeability changes occur in health and disease but measurement of BBB permeability in humans is not straightforward.Dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) can be used to model the movement of gadolinium contrast into the brain, expressed as the influx constant K i.Here evidence is provided that K i as measured by DCE‐MRI behaves as expected for a marker of overall BBB leakage.These results support the use of DCE‐MRI for in vivo studies of human BBB permeability in health and disease. AbstractBlood–brain barrier (BBB) leakage can be measured using dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) as the influx constant K i. To validate this method we compared measured K i with biological expectations, namely (1) higher K i in healthy individual grey matter (GM) versus white matter (WM), (2) GM/WM cerebral blood volume (CBV) ratio close to the histologically established GM/WM vascular density ratio, (3) higher K i in visibly enhancing multiple sclerosis (MS) lesions versus MS normal appearing white matter (NAWM), and (4) higher K i in MS NAWM versus healthy individual NAWM. We recruited 13 healthy individuals and 12 patients with MS and performed whole‐brain 3D DCE‐MRI at 3 T. K i and CBV were calculated using Patlak modelling for manual regions of interest (ROI) and segmented tissue masks. K i was higher in control GM versus WM (P = 0.001). CBV was higher in GM versus WM (P = 0.005, mean ratio 1.9). K i was higher in visibly enhancing MS lesions versus MS NAWM (P = 0.002), and in MS NAWM versus controls (P = 0.014). Bland–Altman analysis showed no significant difference between ROI and segmentation methods (P = 0.638) and an intra‐class correlation coefficient showed moderate single measure consistency (0.610). K i behaves as expected for a compound marker of permeability and surface area. The GM/WM CBV ratio measured by this technique is in agreement with the literature. This adds evidence to the validity of K i measured by DCE‐MRI as a marker of overall BBB leakage.
Abstract. In this paper. a method is presented to enable automatic classification of the degree of abnormality of susceptibility-weighted images (SWI) acquired from babies with hypoxic-ischemic encephalopathy (HIE), in order to more accurately predict eventual cognitive and motor outcomes in these infants. SWI images highlight the cerebral venous vasculature and can reflect abnormalities in blood flow and oxygenation, which may be linked to adverse outcomes. A qualitative score based on magnetic resonance imaging (MRI) analyses is assigned to SWIs by specialists to determine the severity of abnormality in an HIE patient. The method allows the detection of image ridges, representing the vessels in SWIs, and the histogram of the ridges grey scales. A curve with only four parameters is fitted to the histograms. These parameters are then used to estimate the SWI abnormality score. The images are classified by using a kNNand multiple SVM classifiers based on the parameters of the fitting curves. The algorithm is tested on an SWI-MRI dataset consisting of 10 healthy infants and 48 infants with HIE with a range of SWI abnormality scores between 1 and 7. The accuracy of classifying babies with HIE vs. those without (ie: healthy controls) using our algorithm with a leave-one-out strategy is measured as 91.38%. Our method is fast and could increase the prognostic value of these scans, thereby improving management of the condition, as well as elucidating the disease mechanisms of HIE.
Background Systemic infl ammation can aff ect disease expression in multiple sclerosis. The mechanism might involve blood-brain barrier disruption. We aimed to assess the eff ects of systemic infl ammation on disease progression in multiple sclerosis and the role of blood-brain barrier disruption. Methods We recruited adults with relapsing-remitting multiple sclerosis and healthy controls from the general population. Three-dimensional dynamic-contrast enhanced MRI was used to measure blood-brain barrier permeability in the normal-appearing white matter (NAWM). Urinary neopterin, a product of activated macrophages, was measured to provide a readout of systemic infl ammation. All study activities were performed in University Hospital Southampton after ethics approval (REC 12/SC/0176).
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