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Assessing Dynamic Cerebral Autoregulation in Patients with Sickle Cell Disease Using Near-Infrared Spectroscopy and Paced Breathing

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BLOOD 2020年 136卷 57-58页

作者： Wood, Sossena Fanta, Abeselom Dosunmu-Ogunbi, Atinuke Ruesch, Alexander Jonassaint, Jude Huppert, Theodore Novelli, Enrico M. Kainerstorfer, Jana Department of Biomedical Engineering Carnegie Mellon University Pittsburgh PA Carnegie Mellon Neuroscience Institute Carnegie Mellon University Pittsburgh PA University of Pittsburgh School of Medicine Pittsburgh PA Academic Research Center for Hematology (ARCH) University of Pittsburgh Pittsburgh PA Department of Electrical and Computer Engineering University of Pittsburgh Pittsburgh PA Heart Lung and Blood Vascular Medicine Institute University of Pittsburgh Pittsburgh PA

Introduction. Sickle cell disease (SCD) is caused by hemoglobin S polymerization leading to vaso-occlusion, small vessel disease, and reduced tissue oxygen saturation. Noninvasive assessments and screening of small vessel disease and decreased oxygen saturation in select organs, like the brain, are poorly developed. Cerebral autoregulation, a mechanism that ensures cerebral blood flow (CBF) remains constant with changes in mean arterial pressure, is impaired with and is a marker of small vessel disease. Frequency-domain near-infrared spectroscopy (FD-NIRS) can be used as a noninvasive technique to measure cerebral autoregulation by recording cerebral microvascular changes in hemoglobin concentration that are related to cerebral blood flow. Transfer function analysis is a method to noninvasively quantify the relationship between measured physiologic signals, and can be used to estimate cerebral autoregulation. In this study, we hypothesized patients with SCD have impaired cerebral autoregulation and reduced tissue oxygen saturation, which we evaluated via FD-NIRS with transfer function analysis, as compared to healthy controls. Methods. All patients provided informed consent under an IRB protocol approved by the University of Pittsburgh and Carnegie Mellon University. Patients with SCD (n = 11) and healthy, race-matched controls (n =14) were enrolled. All participants sat upright in a chair with probes of a commercial multi-distance FD-NIRS apparatus applied to their forehead in a dark room (Fig. 1A). We used paced breathing to dynamically induce controlled changes in the microvascular tone at 0.1, 0.125, and 0.1667 Hz, spanning normal to more challenging breathing rates, with a visual metronome guiding each paced breathing session (Fig.1.B). To validate each breathing pace, we recorded the participants’ respiratory rate via a belt placed around their chest, and their mean arterial pressure through a finger and arm cuff attached to a beat-to-beat finger plethysmograp

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Deep Automatic Alignment of Mpox Dermatological Hand Photography

Deep Automatic Alignment of Mpox Dermatological Hand Photogr...

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IEEE International Symposium on biomedical Imaging

作者： Bohan Jiang Andrew McNeil Yihao Liu Gaurav Rudravaram Inga Saknite Placide Mbala-Kingebeni Olivier Tshiani Mbaya Tyra Silaphet Rachel Weiss Lori E. Dodd Veronique Nussenblatt Daniel Moyer Bennett A. Landman Benoit M. Dawant Eric R. Tkaczyk Department of Electrical and Computer Engineering Vanderbilt University Nashville TN USA Department of Dermatology Vanderbilt University Medical Center Nashville TN USA Department of Veterans Affairs Dermatology Service and Research Service Nashville TN USA Biophotonics Laboratory University of Latvia Riga Latvia Institut National de Recherche Biomedicale Kinshasa Democratic Republic of the Congo Clinical Monitoring Research Program Directorate Frederick National Laboratory for Cancer Research Frederick MD USA Clinical Trials Research Section Division of Clinical Research National Institute of Allergy and Infectious Disease Bethesda MD USA Laboratory of Clinical Immunology and Microbiology National Institute of Allergy and Infectious Diseases Bethesda MD USA Department of Computer Science Vanderbilt University Nashville TN USA

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Mpox is a viral illness with heavy cutaneous involvement. Automatic tracking of mpox lesion progression is critical in determining the resolution of evolving lesions. This work introduces a novel application of deep learning for lesion monitoring through alignment of dermatological hand photographs. By adapting the VoxelMorph framework for 2D photographic data, we explore key point alignment across serial images. We trained our neural network model on a unique dataset of 1,658 hand images and evaluated its performance on a test set of 254 images. Additionally, we validated the method's generalizability with a supplementary set of 500 images, which included extensive Mpox infection. Our findings indicate modest yet significant improvements in key points and lesion center registration across different regularization strengths. Although promising, the complexity of hand structure presents challenges, requiring cautious application and further refinement, especially in regions with intense spatial discontinuities, such as interdigital areas.

关键词： Hands Photography Deep learning Training Three-dimensional displays Image resolution Neural networks Parametric statistics Lesions Monitoring

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Identifying Materials-Level Sources of Performance Variation in Superconducting Transmon Qubits

arXiv

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arXiv 2025年

作者： Murthy, Akshay A. Bal, Mustafa Bedzyk, Michael J. Cansizoglu, Hilal Chan, Randall K. Chandrasekhar, Venkat Crisa, Francesco Datta, Amlan Deng, Yanpei Matute Diaz, Celeo D. Dravid, Vinayak P. Garcia-Wetten, David A. Garattoni, Sabrina Ghimire, Sunil Goronzy, Dominic P. de Graaf, Sebastian E. Haeuser, Sam Hersam, Mark C. Isheim, Dieter Joshi, Kamal Kim, Richard Kolachina, Saagar Kopas, Cameron J. Kramer, Matthew J. Lachman, Ella O. Lee, Jaeyel Lim, Peter G. Lunin, Andrei Mah, William Marshall, Jayss Mutus, Josh Y. Oh, Jin-Su Pappas, David P. Park, Joong-Mok Prozorov, Ruslan dos Reis, Roberto Seidman, David N. Sung, Zuhawn Tanatar, Makariy Walker, Mitchell J. Wang, Jigang Wu, Haotian Zhou, Lin Zhu, Shaojiang Grassellino, Anna Romanenko, Alexander BataviaIL60510 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Rigetti Computing BerkeleyCA94710 United States Ames National Laboratory AmesIA50011 United States Department of Physics & Astronomy Iowa State University AmesIA50011 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States The NUANCE Center Northwestern University EvanstonIL60208 United States International Institute of Nanotechnology Northwestern University EvanstonIL60208 United States National Physical Laboratory TeddingtonTW11 0LW United Kingdom Department of Chemistry Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Applied Physics Graduate Program Northwestern University EvanstonIL60208 United States Department of Materials Science and Engineering Iowa State University AmesIA50011 United States

The Superconducting Materials and Systems (SQMS) Center, a DOE National Quantum Information Science Research Center, has conducted a comprehensive and coordinated study using superconducting transmon qubit chips with known performance metrics to identify the underlying materials-level sources of device-to-device performance variation. Following qubit coherence measurements, these qubits of varying base superconducting metals and substrates have been examined with various nondestructive and invasive material characterization techniques at Northwestern University, Ames National Laboratory, and Fermilab as part of a blind study. We find trends in variations of the depth of the etched substrate trench, the thickness of the surface oxide, and the geometry of the sidewall, which when combined, lead to correlations with the T1 lifetime across different devices. In addition, we provide a list of features that varied from device to device, for which the impact on performance requires further studies. Finally, we identify two low-temperature characterization techniques that may potentially serve as proxy tools for qubit measurements. These insights provide materials-oriented solutions to not only reduce performance variations across neighboring devices, but also to engineer and fabricate devices with optimal geometries to achieve performance metrics beyond the state-of-the-art values. © 2025, CC BY.

关键词： Qubits

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Compressibility-Near-Zero Acoustic Radiation

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Physical Review Applied 2021年第2期15卷 024022-024022页

作者： Curtis Rasmussen Andrea Alù Department of Mechanical Engineering The University of Texas at Austin Austin Texas 78712 USA Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Photonics Initiative CUNY Advanced Science Research Center New York New York 10031 USA Physics Program Graduate Center City University of New York New York New York 10026 USA

A hallmark of near-zero-index materials is the uniform phase profile that the waves experience as they propagate with staticlike properties in these media. This feature is exploited in electromagnetics for several applications, including for the realization of compact highly directive antennas illuminated by a single source. Here, we discuss the promise of near-zero metamaterials for acoustic radiation, based on the cutoff of a higher-order mode in a waveguide with small holes. We show that the near-zero nature of this phenomenon ensures unusual robustness to disorder, which is analyzed using a statistical description of the radiation patterns for randomly generated location of the holes. The radiation pattern can be made more directive by simply increasing the overall radiating aperture, without having to worry about the specific location of individual holes and their relative distance. The proposed zero-compressibility material offers a promising alternative to traditional acoustic directive sources due to its design simplicity, inherent robustness, and compact profile.

关键词： Acoustic metamaterials Acoustic wave phenomena Disordered systems Acoustic techniques Cavity resonators Green's function methods

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Epipolar Geometry on Drones Cameras for Swarm Robotics Applications

Epipolar Geometry on Drones Cameras for Swarm Robotics Appli...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Andres Erazo Eduardo Tayupanta Seok-Bum Ko Division of Biomedical Engineering University of Saskatchewan Member IEEE Saskatoon Canada Department of Electrical and Electronic Engineering Universidad de las Fuerzas Armadas − ESPE Quito Ecuador Department of Electrical and Computer Engineering and Division of Biomedical Engineering University of Saskatchewan Senior Member IEEE Saskatoon Canada

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

Nowadays, Convolutional Neural Networks are commonly used in classification of images due to their accuracy and performance. In robotics, cameras are used as the main sensor to be able to gather information of the environment; however, image processing could require great amounts of resources. An approach for object detection for 3D environment navigation was implemented, using onboard 2D cameras of mini-drones. A TensorFlow network was fine-tuned for specific object classification and epipolar geometry used to obtain measures of distance between three drones and the detected items. An average measurement accuracy of 0.6094 was obtained, with an average projection error of the cameras of 0.08779. The processing time for object prediction was approximately 0.02 seconds, which correspond to the 37% of the total time needed for a Node's iteration.

关键词： Cameras Drones Robots Optical distortion Three-dimensional displays Image reconstruction IP networks

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Fully Integrated Si-Rich Silicon Nitride Wavelength Converter Based on Bragg Scattering Intermodal Four-Wave Mixing 49

Fully Integrated Si-Rich Silicon Nitride Wavelength Converte...

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49th European Conference on Optical Communications, ECOC 2023

作者： Vitali, Valerio Dominguez Bucio, Thalia Liu, Hao Manuel Luque Gonzalez, Jose Jurado-Romero, Francisco Ortega-Monux, Alejandro Churchill, Glenn C. Gates, James Hillier, James Kalfagiannis, Nikolaos Melati, Daniele Schmid, Jens H. Cristiani, Ilaria Cheben, Pavel Wanguemert-Perez, J. Gonzalo Inigo Molina-Fernandez Gardes, Frederic Lacava, Cosimo Petropoulos, Periklis Optoelectronics Research Centre University of Southampton SouthamptonSO17 1BJ United Kingdom Electrical Computer and Biomedical Engineering Department University of Pavia Pavia27100 Italy Universidad de Malaga CEI Andalucia TECH E.T.S.I. Telecomunicacion Malaga29010 Spain School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom Centre de Nanosciences et de Nanotechnologies Universit e Paris-Saclay CNRS Palaiseau91120 France Advanced Electronics and Photonics Research Center National Research Council Canada 1200 Montreal Road OttawaONK1A 0R6 Canada

ISBN: (纸本)9781839539954

We report the demonstration of an integrated silicon-rich silicon nitride wavelength converter based on Bragg scattering intermodal four-wave mixing process. The system integrates mode conversion, multiplexing and de-multiplexing functionalities on chip. Broadband signal conversion with a 3dB bandwidth exceeding 70 nm is demonstrated. © The Institution of engineering & Technology 2023.

关键词： Four wave mixing

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Idealized aortic annuloplasty FSI digital twin of 3D-printed phantoms with 4D-flow MRI comparison

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computers in Biology and Medicine 2025年第Pt B期192卷 110398-110398页

作者： Bontempi, Luca Zattoni, Marta Ramella, Anna Migliavacca, Francesco Ringgaard, Steffen Kim, Won Yong Johansen, Peter Colombo, Monika Department of Mechanical and Production Engineering Aarhus University Aarhus Denmark Department of Chemistry Materials and Chemical Engineering "Giulio Natta" Politecnico di Milano Milan Italy Department of Biomedical Engineering Thoraxcenter Erasmus MC Rotterdam Netherlands Department of Clinical Medicine Aarhus University Denmark Department of MR Research Centre Aarhus University Hospital Denmark Department of Cardiology Aarhus University Hospital Denmark Department of Electrical and Computer Engineering Aarhus University Denmark Department of Cardiothoracic and Vascular Surgery Aarhus University Hospital Denmark

Background: Aortic annuloplasty, involving the implantation of an external ring around the aortic root to reduce annular dimensions, is a promising treatment for aortic valve insufficiency. However, its hemodynamic effects remain underexplored due to the absence of computational models validated by experimental and clinical data. Methods: This study introduces a computational fluid-structure interaction (FSI) model of supra valvular aortic annuloplasty using 4D-flow magnetic resonance imaging (MRI). Native and post-annuloplasty conditions of idealized aortic root phantoms, including the aortic valve, were CAD-modelled and 3D-printed with elastic resin. These phantoms were tested in a mock circulatory flow-loop providing normal pulsatile physiologic conditions using a glycerol-water mixture to simulate blood viscosity. Flow and pressure data collected from sensors were used as boundary conditions for FSI simulations. Experimental velocity fields from 4D-flow MRI were compared to computational results to assess model accuracy. Results: MRI scans of the annuloplasty model showed an increased peak systolic velocity (up to 145.4 cm/s) and localized flow alterations, corresponding to a higher pressure gradient across the valve. During regurgitation, the annuloplasty model showed broader velocity distributions compared to the native condition. The FSI simulations closely matched 4D-flow MRI data, with strong correlation coefficients (r > 0.93) and minimal Bland-Altman differences, particularly during systolic phases. Conclusions: This study establishes an integrative methodology combining in-vitro, in-silico, and clinical imaging techniques to evaluate aortic annuloplasty hemodynamics. The in-vitro validated digital twin framework offers a pathway for patient-specific modelling, enabling prediction of surgical outcomes and optimization of aortic valve repair strategies. © 2025 The Authors

关键词： Theranostics

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Spinal functional Magnetic Resonance Imaging (fMRI) on Human Studies: A Literature Review

Spinal functional Magnetic Resonance Imaging (fMRI) on Human...

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2019 Advances in Science and engineering Technology International Conferences, ASET 2019

作者： Al-Momani, Sajedah Dhou, Salam Biomedical Engineering Graduate Program American University of Sharjah Sharjah United Arab Emirates Department of Computer Science and Engineering Biomedical Engineering Graduate Program Biosciences and Bioengineering Research Institute American University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9781538682715

Spinal functional Magnetic Resonance Imaging (fMRI) is a newly emerging non-invasive imaging technique that has been introduced to study the Blood Oxygenation Level Dependent (BOLD) changes in the spinal cord associated with a certain activity or even at rest. Spinal fMRI is also used to assess the treatment of many dysfunctions affect the spinal cord such as spinal cord injury (SCI) and Multiple sclerosis (MS). The purpose of this paper is to propose a literature review of spinal fMRI studies performed on healthy human volunteers. The studies reviewed are divided based on the paradigm being performed during image acquisition into (1) studies under activities and stimulus which are further classified according to the type of the stimuli, and (2) studies at resting state. Moreover, the limitations of spinal fMRI and how to tackle them are discussed. © 2019 IEEE.

关键词： Magnetic resonance imaging

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Differentiating COVID-19 Cases from Others by an Anatomy Similarity-Inspired Sensitive Merit from CT Images

Differentiating COVID-19 Cases from Others by an Anatomy Sim...

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2020 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2020

作者： Gao, Yongfeng Pomeroy, Marc Cao, Weiguo Lu, Siming Han, Fangfang Wang, Luhao Chen, Mu Sun, Junqi Xie, Hong Liang, Zhengrong The Department of Radiology Stony Brook University Stony Brook NY11794 United States The School of Biomedical Engineering Southern Medical University Guangdong Guangzhou510515 China The School of Electrical Engineering and Computer Science Pennsylvania State University University ParkPA16802 United States Innovision Imaging Laboratory INC DurhamNC27709 United States Duke Kunshan University Kunshan Jiangsu215316 China The Department of Radiology Yuebei People's Hospital Guangdong Shaoguan710049 China The Department of Radiology Biomedical Engineering Computer Science and Electrical Engineering Stony Brook University Stony Brook NY11794 United States The Department of Radiology The Affiliated Hospital of Guizhou Medical University Guiyang550004 China

ISBN: (纸本)9781728176932

Computed tomography (CT) of COVID-19 manifests a relatively global effect through the whole lungs, like peripheral ground glass, consolidation, reticular pattern, nodules etc. This characteristic effect renders the difficulties in differentiating COVID-19 from the normal body or other lung diseases by CT. This work presents a novel method to relieve the difficulties by reducing the global effect through the 3D whole lung volume into 2D-like domain. The hypothesis is that the lung tissue shares the similar anatomic structure within a small lung sub-volume for normal subjects. Therefore, the anatomic land-markers along the z-axis, denoted as Lung Marks are used to eliminate axial variable. Our experiments indicated that 30 Lung Marks are sufficient to eliminate the axial variable. The method computes texture measures from each 2D-like volumetric data and maps the measures on to the corresponding Lung Mark, resulting in a profile along the z-axis. The difference of the profiles between two different abnormalities is the proposed sensitive merit to differentiate COVID-19 cases from others in CT images. 48 COVID-19 cases and 48 normal screening cases were used to test the effectiveness of the proposed sensitive merit. Intensity and gradient based texture descriptors were computed from each axial cross image at the corresponding Lung Mark along the z-axis. Euclidean, Jaccard and Dice distances are calculated to generate the profiles of the proposed sensitive merit. Consistent results are observed across texture descriptor types and distance types in the texture measure between the normal and COVID-19 subjects. Uneven Profiles demonstrate the variation along the z-axis. With Lung Mark, the variation of texture descriptor has been reduced prominently. The Gradient based descriptor is more sensitive. Individual Haralick features analysis shows the 2nd and 10th dimensions are most distinguishable. © 2020 IEEE

关键词： COVID-19

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Variational and phase response analysis for limit cycles with hard boundaries, with applications to neuromechanical control problems

arXiv

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arXiv 2022年

作者： Wang, Yangyang Gill, Jeffrey P. Chiel, Hillel J. Thomas, Peter J. Department of Mathematics The University of Iowa Iowa CityIA52242 United States Department of Biology Case Western Reserve University ClevelandOH44106 United States Departments of Biology Neurosciencesand Biomedical Engineering Case Western Reserve University ClevelandOH44106 United States Departments of Mathematics Applied Mathematics and StatisticsBiologyCognitive ScienceData and Computer Scienceand Electrical Control and Systems Engineering Case Western Reserve University ClevelandOH44106 United States

Motor systems show an overall robustness, but because they are highly nonlinear, understanding how they achieve robustness is difficult. In many rhythmic systems, robustness against perturbations involves response of both the shape and the timing of the trajectory. This makes the study of robustness even more challenging. To understand how a motor system produces robust behaviors in a variable environment, we consider a neuromechanical model of motor patterns in the feeding apparatus of the marine mollusk Aplysia californica (Shaw et al., 2015;Lyttle et al., 2017). We established in (Wang et al., 2021) the tools for studying combined shape and timing responses of limit cycle systems under sustained perturbations and here apply them to study robustness of the neuromechanical model against increased mechanical load during swallowing. Interestingly, we discover that nonlinear biomechanical properties confer resilience by immediately increasing resistance to applied loads. In contrast, the effect of changed sensory feedback signal is significantly delayed by the firing rates’ hard boundary properties. Our analysis suggests that sensory feedback contributes to robustness in swallowing primarily by shifting the timing of neural activation involved in the power stroke of the motor cycle (retraction). This effect enables the system to generate stronger retractor muscle forces to compensate for the increased load, and hence achieve strong robustness. The approaches that we are applying to understanding a neuromechanical model in Aplysia, and the results that we have obtained, are likely to provide insights into the function of other motor systems that encounter changing mechanical loads and hard boundaries, both due to mechanical and neuronal firing *** Codes 34C07, 34C15, 58E25, 49J52, 92B20, 93C73 Copyright © 2022, The Authors. All rights reserved.

关键词： Activation analysis

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