Gradient flow and the renormalization group

We investigate the renormalization group (RG) structure of the gradient flow. Instead of using the original bare action to generate the flow, we propose to use the effective action at each flow time. We write down the basic equation for scalar field theory that determines the evolution of the action, and argue that the equation can be regarded as a RG equation if one makes a field-variable transformation at every step such that the kinetic term is kept to take the canonical form. We consider a local potential approximation (LPA) to our equation, and show that the result has a natural interpretation with Feynman diagrams. We make an $\varepsilon$ expansion of the LPA and show that it reproduces the eigenvalues of the linearized RG transformation around both the Gaussian and the Wilson-Fisher fixed points to the order of $\varepsilon$.Comment: 11 pages, 1 figure; v2, v3: typos corrected, some discussions improve

A first-principles study of tunneling magnetoresistance in Fe/MgAl2O4/Fe(001) magnetic tunnel junctions

We investigated the spin-dependent transport properties of Fe/MgAl2O4/Fe(001) magnetic tunneling junctions (MTJs) on the basis of first-principles calculations of the electronic structures and the ballistic conductance. The calculated tunneling magnetoresistance (TMR) ratio of a Fe/MgAl2O4/Fe(001) MTJ was about 160%, which was much smaller than that of a Fe/MgO/Fe(001) MTJ (1600%) for the same barrier thickness. However, there was an evanescent state with delta 1 symmetry in the energy gap around the Fermi level of normal spinel MgAl2O4, indicating the possibility of a large TMR in Fe/MgAl2O4/Fe(001) MTJs. The small TMR ratio of the Fe/MgAl2O4/Fe(001) MTJ was due to new conductive channels in the minority spin states resulting from a band-folding effect in the two-dimensional (2-D) Brillouin zone of the in-plane wave vector (k//) of the Fe electrode. Since the in-plane cell size of MgAl2O4 is twice that of the primitive in-plane cell size of bcc Fe, the bands in the boundary edges are folded, and minority-spin states coupled with the delta 1 evanescent state in the MgAl2O4 barrier appear at k//=0, which reduces the TMR ratio of the MTJs significantly.Comment: 5 pages, 6 figures, 1 tabl

Reproducibility of CBF using pCASL

Purpose : To determine the reproducibility of corrected quantitative cerebral blood flow (qCBF) through measurement of transit flow time using multi-delay three-dimensional pseudo-continuous arterial spin labeling (pCASL) in healthy men and women and to evaluate the differences in qCBF between not only men and women, but also the follicular and luteal phases of the women’s menstrual cycle. Methods : The participants were 16 healthy volunteers (8 men and 8 women ; mean age, 25.3 years). Two MRI were conducted for all participants ; female participants were conducted in the follicular and luteal phases. The reproducibility of qCBF values was evaluated by the intraclass correlation coefficient (ICC) and differences between the two groups were estimated by voxel-based morphometry (VBM) analysis. Results : The qCBF values were lower in men than in women, and those in females were significantly different between the follicular and luteal phases (P < 0.05). In VBM analysis, the qCBF values of the lower frontal lobes were significantly higher in women than in men (P < 0.05). The qCBF values of the frontal pole were significantly higher in the follicular phase than in the luteal phase (P < 0.01). Conclusion : Multi-delay pCASL can reveal physiological and sex differences in cerebral perfusion

Deep Learning for Echocardiography

Objectives: The aim of this study was to evaluate whether a deep convolutional neural network (DCNN) could detect regional wall motion abnormalities (RWMAs) and differentiate groups of coronary infarction territories from conventional 2-dimensional echocardiographic images compared with cardiologist/sonographer or resident readers. Background: An effective intervention for reduction of misreading of RWMAs is needed. We hypothesized that a DCNN trained with echocardiographic images may provide improved detection of RWMAs in the clinical setting. Methods: A total of 300 patients with history of myocardial infarction were enrolled. In this cohort, 100 each had infarctions of the left anterior descending branch (LAD), left circumflex branch (LCX), and right coronary artery (RCA). The age-matched 100 control patients with normal wall motion were selected from our database. Each case contained cardiac ultrasound images from short axis views at end-diastolic, mid-systolic and end-systolic phases. After 100 steps of training, diagnostic accuracies were calculated on the test set. We independently trained 10 versions of the same model, and performed ensemble predictions with them. Results: For detection of the presence of wall motion abnormality, the area under the receiver-operating characteristic curve (AUC) by deep learning algorithm was similar to that by cardiologist/sonographer readers (0.99 vs. 0.98, p =0.15), and significantly higher than the AUC by resident readers (0.99 vs. 0.90, p =0.002). For detection of territories of wall motion abnormality, the AUC by the deep learning algorithm was similar to the AUC by cardiologist/sonographer readers (0.97 vs. 0.95, p =0.61) and significantly higher than the AUC by resident readers (0.97 vs. 0.83, p =0.003). In a validation group from an independent site (n=40), the AUC by the DL algorithm was 0.90. Conclusions: Our results support the possibility of DCNN use for automated diagnosis of RWMAs in the field of echocardiography

The Cerebellum Is a Common Key for Visuospatial Execution and Attention in Parkinson’s Disease

Cognitive decline affects the clinical course in patients with Parkinson’s disease (PD) and contributes to a poor prognosis. However, little is known about the underlying network-level abnormalities associated with each cognitive domain. We aimed to identify the networks related to each cognitive domain in PD using resting-state functional magnetic resonance imaging (MRI). Forty patients with PD and 15 normal controls were enrolled. All subjects underwent MRI and the Mini-Mental State Examination. Furthermore, the cognitive function of patients with PD was assessed using the Montreal Cognitive Assessment (MoCA). We used independent component analysis of the resting-state functional MRI for functional segmentation, followed by reconstruction to identify each domain-related network, to predict scores in PD using multiple regression models. Six networks were identified, as follows: the visuospatial-executive-domain-related network (R2 = 0.54, p < 0.001), naming-domain-related network (R2 = 0.39, p < 0.001), attention-domain-related network (R2 = 0.86, p < 0.001), language-domain-related network (R2 = 0.64, p < 0.001), abstraction-related network (R2 = 0.10, p < 0.05), and orientation-domain-related network (R2 = 0.64, p < 0.001). Cerebellar lobule VII was involved in the visuospatial-executive-domain-related and attention-domain-related networks. These two domains are involved in the first three listed nonamnestic cognitive impairment in the diagnostic criteria for PD with dementia (PDD). Furthermore, Brodmann area 10 contributed most frequently to each domain-related network. Collectively, these findings suggest that cerebellar lobule VII may play a key role in cognitive impairment in nonamnestic types of PDD

Perfusion MRI for brain tumors

Purpose : To compare data on brain tumors derived from intravoxel incoherent motion (IVIM) and arterial spin labeling (ASL) imaging with multiple parameters obtained on dynamic susceptibility contrast (DSC) perfusion MRI and to clarify the characteristics of IVIM and ASL perfusion data from the viewpoint of cerebral blood flow (CBF) analysis. Methods : ASL-CBF and IVIM techniques as well as DSC examination were performed in 24 patients with brain tumors. The IVIM data were analyzed with the two models. The relative blood flow (rBF), relative blood volume (rBV) corrected relative blood volume (crBV), mean transit time (MTT), and leakage coefficient (K2) were obtained from the DSC MRI data. Results : The ASL-CBF had the same tendency as the perfusion parameters derived from the DSC data, but the permeability from the vessels had less of an effect on the ASL-CBF. The diffusion coefficient of the fast component on IVIM contained more information on permeability than the f value. Conclusion : ASL-CBF is more suitable for the evaluation of perfusion in brain tumors than IVIM parameters. ASL-CBF and IVIM techniques should be carefully selected and the biological significance of each parameter should be understood for the correct comprehension of the pathological status of brain tumors

Percutaneous Transcatheter Ballon Valvuloplasty of a Stenosed Bioprosthetic Tricuspid Valve

Article信州医学雑誌 67(5): 289-292(2019)journal articl