MR coil sensitivity inhomogeneity correction for plaque characterization in carotid arteries

We are involved in a comprehensive program to characterize atherosclerotic disease using multiple MR images having different contrast mechanisms (T1W, T2W, PDW, magnetization transfer, etc.) of human carotid and animal model arteries. We use specially designed intravascular and surface array coils that give high signal-to-noise but suffer from sensitivity inhomogeneity. With carotid surface coils, challenges include: (1) a steep bias field with an 80% change; (2) presence of nearby muscular structures lacking high frequency information to distinguish bias from anatomical features; (3) many confounding zero-valued voxels subject to fat suppression, blood flow cancellation, or air, which are not subject to coil sensitivity; and (4) substantial noise. Bias was corrected using a modification of the adaptive fuzzy c-mean method reported by Pham et al. (IEEE TMI, 18:738-752), whereby a bias field modeled as a mechanical membrane was iteratively improved until cluster means no longer changed. Because our images were noisy, we added a noise reduction filtering step between iterations and used approximate to5 classes. In a digital phantom having a bias field measured from our MR system, variations across an area comparable to a carotid artery were reduced from 50% t

Decoupling a Cooper-pair box to enhance the lifetime to 0.2 ms

We present a circuit QED experiment in which a separate transmission line is used to address a quasi-lumped element superconducting microwave resonator which is in turn coupled to an Al/AlO$_{x}$/Al Cooper-pair box (CPB) charge qubit. In our measurements we find a strong correlation between the measured lifetime of the CPB and the coupling between the qubit and the transmission line. By monitoring perturbations of the resonator's 5.44 GHz resonant frequency, we have measured the spectrum, lifetime ($T_{1}$), Rabi, and Ramsey oscillations of the CPB at the charge degeneracy point while the CPB was detuned by up to 2.5 GHz . We find a maximum lifetime of the CPB was $T_{1} = 200\ \mu$s for $f = 4$ to 4.5 GHz. Our measured $T_{1}$'s are consistent with loss due to coupling to the transmission line, spurious microwave circuit resonances, and a background decay rate on the order of $5\times 10^{3}$ s$^{-1}$ of unknown origin, implying that the loss tangent in the AlO$_{x}$ junction barrier must be less than about $4\times 10^{-8}$ at 4.5 GHz, about 4 orders of magnitude less than reported in larger area Al/AlO$_{x}$/Al tunnel junctions

Large collective Lamb shift of two distant superconducting artificial atoms

Virtual photons can mediate interaction between atoms, resulting in an energy shift known as a collective Lamb shift. Observing the collective Lamb shift is challenging, since it can be obscured by radiative decay and direct atom-atom interactions. Here, we place two superconducting qubits in a transmission line terminated by a mirror, which suppresses decay. We measure a collective Lamb shift reaching 0.8% of the qubit transition frequency and exceeding the transition linewidth. We also show that the qubits can interact via the transmission line even if one of them does not decay into it.Comment: 7+5 pages, 4+2 figure

CT attenuation analysis of carotid intraplaque hemorrhage

Background and Purpose: Intraplaque hemorrhage is considered a leading parameter of carotid plaque vulnerability. Our purpose was to assess the CT characteristics of intraplaque hemorrhage with histopathologic correlation to identify features that allow for confirming or ruling out the intraplaque hemorrhage. MATERIALS AND METHODS: This retrospective study included 91 patients (67 men; median age, 657 years; age range, 41-83 years) who underwent CT angiography and carotid endarterectomy from March 2010 to May 2013. Histopathologic analysis was performed for the tissue characterization and identification of intraplaque hemorrhage. Two observers assessed the plaque's attenuation values by using an ROI (≤1 and ≥2 mm2). Receiver operating characteristic curve, Mann-Whitney, and Wilcoxon analyses were performed. RESULTS: A total of 169 slices were assessed (59 intraplaque hemorrhage, 63 lipid-rich necrotic core, and 47 fibrous); the average values of the intraplaque hemorrhage, lipid-rich necrotic core, and fibrous tissue were 17.475 Hounsfield units (HU) and 18.407 HU, 39.476 HU and 48.048 HU, and 91.66 HU and 93.128 HU, respectively, before and after the administration of contrast medium. The Mann-Whitney test showed a statistically significant difference of HU values both in basal and after the administration of contrast material phase. Receiver operating characteristic analysis showed a statistical association between intraplaque hemorrhage and low HU values, and a threshold of 25 HU demonstrated the presence of intraplaque hemorrhage with a sensitivity and specificity of 93.22% and 92.73%, respectively. The Wilcoxon test showed that the attenuation of the plaque before and after administration of contrast material is different (intraplaque hemorrhage, lipid-rich necrotic core, and fibrous tissue had P values of .006, .0001, and .018, respectively). CONCLUSIONS: The results of this preliminary study suggest that CT can be used to identify the presence of intraplaque hemorrhage according to the attenuation. A threshold of 25 HU in the volume acquired after the administration of contrast medium is associated with an optimal sensitivity and specificity. Special care should be given to the correct identification of the ROI

A review on a deep learning perspective in brain cancer classification

AWorld Health Organization (WHO) Feb 2018 report has recently shown that mortality rate due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It is of critical importance that cancer be detected earlier so that many of these lives can be saved. Cancer grading is an important aspect for targeted therapy. As cancer diagnosis is highly invasive, time consuming and expensive, there is an immediate requirement to develop a non-invasive, cost-effective and efficient tools for brain cancer characterization and grade estimation. Brain scans using magnetic resonance imaging (MRI), computed tomography (CT), as well as other imaging modalities, are fast and safer methods for tumor detection. In this paper, we tried to summarize the pathophysiology of brain cancer, imaging modalities of brain cancer and automatic computer assisted methods for brain cancer characterization in a machine and deep learning paradigm. Another objective of this paper is to find the current issues in existing engineering methods and also project a future paradigm. Further, we have highlighted the relationship between brain cancer and other brain disorders like stroke, Alzheimer’s, Parkinson’s, andWilson’s disease, leukoriaosis, and other neurological disorders in the context of machine learning and the deep learning paradigm