Quantitative susceptibility mapping (QSM) is an advanced MRI technique for evaluating the distribution of magnetic susceptibility related to substances such as iron, hemosiderin, and deoxyhemoglobi... Quantitative susceptibility mapping (QSM), one of the advanced MRI techniques for evaluating magnetic susceptibility, offers precise quantitative measurements of spatial distributions of magnetic s...

Background and Purpose—: The oxygen extraction fraction (OEF) is an effective metric to evaluate metabolic reserve in chronic ischemia. However, OEF is considered to be accurately measured only when using positron emission tomography (PET). Thus, we investigated whether OEF maps generated by magnetic resonance quantitative susceptibility mapping (QSM) at 7 Tesla enabled detection of OEF changes when compared with those obtained with PET. Methods—: Forty-one patients with chronic stenosis/occlusion of the unilateral internal carotid artery or middle cerebral artery were examined using 7 Tesla-MRI and PET scanners. QSM images were obtained from 3-dimensional T2*-weighted images, using a multiple dipole-inversion algorithm. OEF maps were generated based on susceptibility differences between venous structures and brain tissues on QSM images. OEF ratios of the ipsilateral middle cerebral artery territory against the contralateral side were calculated on the QSM-OEF and PET-OEF images, using an anatomic template. Results—: The OEF ratio in the middle cerebral artery territory showed significant correlations between QSM-OEF and PET-OEF maps ( r =0.69; P 1.09, as determined by receiver operating characteristic analysis, showed a sensitivity and specificity of 0.82 and 0.86, respectively, for the substantial increase in the PET-OEF ratio. Absolute QSM-OEF values were significantly correlated with PET-OEF values in the patients with increased PET-OEF. Conclusions—: OEF ratios on QSM-OEF images at 7 Tesla showed a good correlation with those on PET-OEF images in patients with unilateral steno-occlusive internal carotid artery/middle cerebral artery lesions, suggesting that noninvasive OEF measurement by MRI can be a substitute for PET.

We examined the presence of maximum information preservation, which may be a fundamental principle of information transmission in all sensory modalities, in the Drosophila antennal lobe using an experimentally grounded network model and physiological data. Recent studies have shown a nonlinear firing rate transformation between olfactory receptor neurons (ORNs) and second-order projection neurons (PNs). As a result, PNs can use their dynamic range more uniformly than ORNs in response to a diverse set of odors. Although this firing rate transformation is thought to assist the decoder in discriminating between odors, there are no comprehensive, quantitatively supported studies examining this notion. Therefore, we quantitatively investigated the efficiency of this firing rate transformation from the viewpoint of information preservation by computing the mutual information between odor stimuli and PN responses in our network model. In the Drosophila olfactory system, all ORNs and PNs are divided into unique functional processing units called glomeruli. The nonlinear transformation between ORNs and PNs is formed by intraglomerular transformation and interglomerular interaction through local neurons (LNs). By exploring possible nonlinear transformations produced by these two factors in our network model, we found that mutual information is maximized when a weak ORN input is preferentially amplified within a glomerulus and the net LN input to each glomerulus is inhibitory. It is noteworthy that this is the very combination observed experimentally. Furthermore, the shape of the resultant nonlinear transformation is similar to that observed experimentally. These results imply that information related to odor stimuli is almost maximally preserved in the Drosophila olfactory circuit. We also discuss how intraglomerular transformation and interglomerular inhibition combine to maximize mutual information.

Quantitative susceptibility mapping (QSM) is a new magnetic resonance imaging (MRI) technique for noninvasively estimating the magnetic susceptibility of biological tissue. Several methods for QSM have been proposed. One of these methods can estimate susceptibility with high accuracy in tissues whose contrast is consistent between magnitude images and susceptibility maps, such as deep gray-matter nuclei. However, the susceptibility of small veins is underestimated and not well depicted by using the above approach, because the contrast of small veins is inconsistent between a magnitude image and a susceptibility map. In order to improve the estimation accuracy and visibility of small veins without streaking artifacts, a method with multiple dipole-inversion combination with k-space segmentation (MUDICK) has been proposed. In the proposed method, k-space was divided into three domains (low-frequency, magic-angle, and high-frequency). The k-space data in low-frequency and magic-angle domains were obtained by L1-norm regularization using structural information of a pre-estimated susceptibility map. The k-space data in high-frequency domain were obtained from the pre-estimated susceptibility map in order to preserve small-vein contrasts. Using numerical simulation and human brain study at 3 Tesla, streaking artifacts and small-vein susceptibility were compared between MUDICK and conventional methods (MEDI and TKD). The numerical simulation and human brain study showed that MUDICK and MEDI had no severe streaking artifacts and MUDICK showed higher contrast and accuracy of susceptibility in small-veins compared to MEDI. These results suggest that MUDICK can improve the accuracy and visibility of susceptibility in small-veins without severe streaking artifacts.