Using in Vivo Subject-Specific Musculotendon Parameters to Investigate Voluntary Movement Changes after Stroke

2014 ◽  
pp. 161-180
Author(s):  
Hujing Hu ◽  
Le Li
Keyword(s):  
Voluntary Movement ◽  
Imaging Techniques ◽  
Movement Trajectory ◽  
Fitting Procedure ◽  
Emg Signal ◽  
Subject Specific ◽  
Elbow Movement ◽  
The Individual ◽  
Neuromusculoskeletal Modeling

Neuromusculoskeletal modeling provides insights into the muscular system which are not always obtained through experiment or observation alone. One of the major challenges in neuromusculoskeletal modeling is to accurately estimate the musculotendon parameters on a subject-specific basis. The latest medical imaging techniques such as ultrasound for the estimation of musculotendon parameters would provide an alternative method to obtain the muscle architecture parameters noninvasively. In this chapter, the feasibility of using ultrasonography to measure the musculotendon parameters of elbow muscles is validated. These parameters help to build a subject-specific EMG-driven model, which could predict the individual muscle force and elbow voluntary movement trajectory using the input of EMG signal without any trajectory fitting procedure involved. The results demonstrate the feasibility of using EMG-driven neuromusculoskeletal modeling with ultrasound-measured data for prediction of voluntary elbow movement for both unimpaired subjects and persons after stroke.

Combinatorial Responses Controlled by Synaptic Inhibition in the Cerebellum Granular Layer

2010 ◽  
Vol 103 (1) ◽  
pp. 250-261 ◽  
Author(s):  
Jonathan Mapelli ◽  
Daniela Gandolfi ◽  
Egidio D'Angelo
Keyword(s):  
Granular Layer ◽  
Mossy Fiber ◽  
Imaging Techniques ◽  
Coincidence Detection ◽  
Acid Type ◽  
Receptor Blockers ◽  
Simultaneous Activation ◽  
Spatial Pattern Separation ◽  
The Individual

The granular layer of cerebellum has been long hypothesized to perform combinatorial operations on incoming signals. Although this assumption is at the basis of main computational theories of cerebellum, it has never been assessed experimentally. Here, by applying high-resolution voltage-sensitive dye imaging techniques, we show that simultaneous activation of two partially overlapping mossy fiber bundles (either with single pulses or high-frequency bursts) can cause combined excitation and combined inhibition, which are compatible with the concepts of coincidence detection and spatial pattern separation predicted by theory. Combined excitation appeared as an area in which the combination of two inputs is greater than the arithmetic sum of the individual inputs and was enhanced by γ-aminobutyric acid type A (GABAA) receptor blockers. Combined inhibition was manifest as an area where two inputs combined resulted in a reduction to less than half of the activity evoked from either one of the two inputs alone and was prevented by GABAA receptor blockers. The combinatorial responses occupied small granular layer regions (∼30 μm diameter), with combined inhibition being interspersed among extended areas of combined excitation. Moreover, the combinatorial effects lasted for tens of milliseconds and combined inhibition occurred only after termination of the stimuli. These combinatorial operations, if engaged by natural input patterns in vivo, may be important to influence incoming impulses organizing spatiotemporal spike sequences to be relayed to Purkinje cells.

Determining Subject-Specific Lower-Limb Muscle Architecture Data for Musculoskeletal Models Using Diffusion Tensor Imaging

2019 ◽  
Vol 141 (6) ◽  
Author(s):  
James P. Charles ◽  
Chan-Hong Moon ◽  
William J. Anderst
Keyword(s):  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Imaging Techniques ◽  
Muscle Architecture ◽  
Lower Limbs ◽  
Cross Sectional ◽  
Musculoskeletal Models ◽  
Subject Specific

Accurate individualized muscle architecture data are crucial for generating subject-specific musculoskeletal models to investigate movement and dynamic muscle function. Diffusion tensor imaging (DTI) magnetic resonance (MR) imaging has emerged as a promising method of gathering muscle architecture data in vivo; however, its accuracy in estimating parameters such as muscle fiber lengths for creating subject-specific musculoskeletal models has not been tested. Here, we provide a validation of the method of using anatomical magnetic resonance imaging (MRI) and DTI to gather muscle architecture data in vivo by directly comparing those data obtained from MR scans of three human cadaveric lower limbs to those from dissections. DTI was used to measure fiber lengths and pennation angles, while the anatomical images were used to estimate muscle mass, which were used to calculate physiological cross-sectional area (PCSA). The same data were then obtained through dissections, where it was found that on average muscle masses and fiber lengths matched well between the two methods (4% and 1% differences, respectively), while PCSA values had slightly larger differences (6%). Overall, these results suggest that DTI is a promising technique to gather in vivo muscle architecture data, but further refinement and complementary imaging techniques may be needed to realize these goals.

scholarly journals A Combined Experimental and Computational Approach to Subject-Specific Analysis of Knee Joint Laxity

2016 ◽  
Vol 138 (8) ◽  
Author(s):  
Michael D. Harris ◽  
Adam J. Cyr ◽  
Azhar A. Ali ◽  
Clare K. Fitzpatrick ◽  
Paul J. Rullkoetter ◽  
...  
Keyword(s):  
Knee Joint ◽  
Knee Laxity ◽  
Experimental Tests ◽  
Population Based ◽  
Knee Mechanics ◽  
Ligament Strain ◽  
Subject Specific ◽  
Joint Biomechanics ◽  
The Individual

Modeling complex knee biomechanics is a continual challenge, which has resulted in many models of varying levels of quality, complexity, and validation. Beyond modeling healthy knees, accurately mimicking pathologic knee mechanics, such as after cruciate rupture or meniscectomy, is difficult. Experimental tests of knee laxity can provide important information about ligament engagement and overall contributions to knee stability for development of subject-specific models to accurately simulate knee motion and loading. Our objective was to provide combined experimental tests and finite-element (FE) models of natural knee laxity that are subject-specific, have one-to-one experiment to model calibration, simulate ligament engagement in agreement with literature, and are adaptable for a variety of biomechanical investigations (e.g., cartilage contact, ligament strain, in vivo kinematics). Calibration involved perturbing ligament stiffness, initial ligament strain, and attachment location until model-predicted kinematics and ligament engagement matched experimental reports. Errors between model-predicted and experimental kinematics averaged <2 deg during varus–valgus (VV) rotations, <6 deg during internal–external (IE) rotations, and <3 mm of translation during anterior–posterior (AP) displacements. Engagement of the individual ligaments agreed with literature descriptions. These results demonstrate the ability of our constraint models to be customized for multiple individuals and simultaneously call attention to the need to verify that ligament engagement is in good general agreement with literature. To facilitate further investigations of subject-specific or population based knee joint biomechanics, data collected during the experimental and modeling phases of this study are available for download by the research community.

Trends in Nanotechnology for in vivo Cancer Diagnosis: Products and Patents

2020 ◽  
Vol 26 (18) ◽  
pp. 2167-2181
Author(s):  
Tatielle do Nascimento ◽  
Melanie Tavares ◽  
Mariana S.S.B. Monteiro ◽  
Ralph Santos-Oliveira ◽  
Adriane R. Todeschini ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Quantum Dots ◽  
Magnetic Resonance ◽  
Metal Nanoparticles ◽  
Cancer Diagnosis ◽  
Imaging Techniques ◽  
Tumor Detection ◽  
Abnormal Growth ◽  
Pharmaceutical Nanotechnology

Background: Cancer is a set of diseases formed by abnormal growth of cells leading to the formation of the tumor. The diagnosis can be made through symptoms’ evaluation or imaging tests, however, the techniques are limited and the tumor detection may be late. Thus, pharmaceutical nanotechnology has emerged to optimize the cancer diagnosis through nanostructured contrast agent’s development. Objective: This review aims to identify commercialized nanomedicines and patents for cancer diagnosis. Methods: The databases used for scientific articles research were Pubmed, Science Direct, Scielo and Lilacs. Research on companies’ websites and articles for the recognition of commercial nanomedicines was performed. The Derwent tool was applied for patent research. Results: This article aimed to research on nanosystems based on nanoparticles, dendrimers, liposomes, composites and quantum dots, associated to imaging techniques. Commercialized products based on metal and composite nanoparticles, associated with magnetic resonance and computed tomography, have been observed. The research conducted through Derwent tool displayed a small number of patents using nanotechnology for cancer diagnosis. Among these patents, the most significant number was related to the use of systems based on metal nanoparticles, composites and quantum dots. Conclusion: Although few systems are found in the market and patented, nanotechnology appears as a promising field for the development of new nanosystems in order to optimize and accelerate the cancer diagnosis.

scholarly journals Predicting chromosome damage in astronauts participating in international space station missions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alan Feiveson ◽  
Kerry George ◽  
Mark Shavers ◽  
Maria Moreno-Villanueva ◽  
Ye Zhang ◽  
...  
Keyword(s):  
International Space Station ◽  
Dose Response ◽  
Ex Vivo ◽  
Space Station ◽  
Space Radiation ◽  
Blood Samples ◽  
International Space ◽  
Significant Difference ◽  
Subject Specific

AbstractSpace radiation consists of energetic protons and other heavier ions. During the International Space Station program, chromosome aberrations in lymphocytes of astronauts have been analyzed to estimate received biological doses of space radiation. More specifically, pre-flight blood samples were exposed ex vivo to varying doses of gamma rays, while post-flight blood samples were collected shortly and several months after landing. Here, in a study of 43 crew-missions, we investigated whether individual radiosensitivity, as determined by the ex vivo dose–response of the pre-flight chromosome aberration rate (CAR), contributes to the prediction of the post-flight CAR incurred from the radiation exposure during missions. Random-effects Poisson regression was used to estimate subject-specific radiosensitivities from the preflight dose–response data, which were in turn used to predict post-flight CAR and subject-specific relative biological effectiveness (RBEs) between space radiation and gamma radiation. Covariates age, gender were also considered. Results indicate that there is predictive value in background CAR as well as radiosensitivity determined preflight for explaining individual differences in post-flight CAR over and above that which could be explained by BFO dose alone. The in vivo RBE for space radiation was estimated to be approximately 3 relative to the ex vivo dose response to gamma irradiation. In addition, pre-flight radiosensitivity tended to be higher for individuals having a higher background CAR, suggesting that individuals with greater radiosensitivity can be more sensitive to other environmental stressors encountered in daily life. We also noted that both background CAR and radiosensitivity tend to increase with age, although both are highly variable. Finally, we observed no significant difference between the observed CAR shortly after mission and at > 6 months post-mission.

scholarly journals Detecting apoptosis as a clinical endpoint for proof of a clinical principle

2020 ◽  
Author(s):  
Piero Zollet ◽  
Timothy E.Yap ◽  
M Francesca Cordeiro
Keyword(s):  
Drug Development ◽  
Therapeutic Response ◽  
Imaging Techniques ◽  
Brain Diseases ◽  
Promising Strategy ◽  
Sight Loss ◽  
Apoptosis Detection ◽  
Novel Therapeutic Strategies

The transparent eye media represent a window through which to observe changes occurring in the retina during pathological processes. In contrast to visualising the extent of neurodegenerative damage that has already occurred, imaging an active process such as apoptosis has the potential to report on disease progression and therefore the threat of irreversible functional loss in various eye and brain diseases. Early diagnosis in these conditions is an important unmet clinical need to avoid or delay irreversible sight loss. In this setting, apoptosis detection is a promising strategy with which to diagnose, provide prognosis, and monitor therapeutic response. Additionally, monitoring apoptosis in vitro and in vivo has been shown to be valuable for drug development in order to assess the efficacy of novel therapeutic strategies both in the pre-clinical and clinical setting. Detection of Apoptosing Retinal Cells (DARC) technology is to date the only tool of its kind to have been tested in clinical trials, with other new imaging techniques under investigation in the fields of neuroscience, ophthalmology and drug development. We summarize the transitioning of techniques detecting apoptosis from bench to bedside, along with the future possibilities they encase.

scholarly journals Hyperpolarized 13C-glucose magnetic resonance highlights reduced aerobic glycolysis in vivo in infiltrative glioblastoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mor Mishkovsky ◽  
Olga Gusyatiner ◽  
Bernard Lanz ◽  
Cristina Cudalbu ◽  
Irene Vassallo ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Tumor Recurrence ◽  
Aerobic Glycolysis ◽  
Imaging Techniques ◽  
Tumor Type ◽  
Hyperpolarized 13C ◽  
Metabolic Heterogeneity ◽  
Metabolic Information ◽  
Opposite Response

AbstractGlioblastoma (GBM) is the most aggressive brain tumor type in adults. GBM is heterogeneous, with a compact core lesion surrounded by an invasive tumor front. This front is highly relevant for tumor recurrence but is generally non-detectable using standard imaging techniques. Recent studies demonstrated distinct metabolic profiles of the invasive phenotype in GBM. Magnetic resonance (MR) of hyperpolarized 13C-labeled probes is a rapidly advancing field that provides real-time metabolic information. Here, we applied hyperpolarized 13C-glucose MR to mouse GBM models. Compared to controls, the amount of lactate produced from hyperpolarized glucose was higher in the compact GBM model, consistent with the accepted “Warburg effect”. However, the opposite response was observed in models reflecting the invasive zone, with less lactate produced than in controls, implying a reduction in aerobic glycolysis. These striking differences could be used to map the metabolic heterogeneity in GBM and to visualize the infiltrative front of GBM.

scholarly journals Optimization of X-ray Investigations in Dentistry Using Optical Coherence Tomography

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4554
Author(s):  
Ralph-Alexandru Erdelyi ◽  
Virgil-Florin Duma ◽  
Cosmin Sinescu ◽  
George Mihai Dobre ◽  
Adrian Bradu ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Radiation Dose ◽  
Imaging Techniques ◽  
Image Resolution ◽  
Optical Coherence ◽  
X Rays ◽  
High Quality ◽  
X Ray

The most common imaging technique for dental diagnoses and treatment monitoring is X-ray imaging, which evolved from the first intraoral radiographs to high-quality three-dimensional (3D) Cone Beam Computed Tomography (CBCT). Other imaging techniques have shown potential, such as Optical Coherence Tomography (OCT). We have recently reported on the boundaries of these two types of techniques, regarding. the dental fields where each one is more appropriate or where they should be both used. The aim of the present study is to explore the unique capabilities of the OCT technique to optimize X-ray units imaging (i.e., in terms of image resolution, radiation dose, or contrast). Two types of commercially available and widely used X-ray units are considered. To adjust their parameters, a protocol is developed to employ OCT images of dental conditions that are documented on high (i.e., less than 10 μm) resolution OCT images (both B-scans/cross sections and 3D reconstructions) but are hardly identified on the 200 to 75 μm resolution panoramic or CBCT radiographs. The optimized calibration of the X-ray unit includes choosing appropriate values for the anode voltage and current intensity of the X-ray tube, as well as the patient’s positioning, in order to reach the highest possible X-rays resolution at a radiation dose that is safe for the patient. The optimization protocol is developed in vitro on OCT images of extracted teeth and is further applied in vivo for each type of dental investigation. Optimized radiographic results are compared with un-optimized previously performed radiographs. Also, we show that OCT can permit a rigorous comparison between two (types of) X-ray units. In conclusion, high-quality dental images are possible using low radiation doses if an optimized protocol, developed using OCT, is applied for each type of dental investigation. Also, there are situations when the X-ray technology has drawbacks for dental diagnosis or treatment assessment. In such situations, OCT proves capable to provide qualitative images.

scholarly journals Preclinical Testing of Radiopharmaceuticals for the Detection and Characterization of Osteomyelitis: Experiences from a Porcine Model

Molecules ◽  
2021 ◽  
Vol 26 (14) ◽  
pp. 4221
Author(s):  
Aage Kristian Olsen Alstrup ◽  
Svend Borup Jensen ◽  
Ole Lerberg Nielsen ◽  
Lars Jødal ◽  
Pia Afzelius
Keyword(s):  
Animal Model ◽  
Animal Models ◽  
Porcine Model ◽  
Animal Experiments ◽  
Radioactive Tracers ◽  
The Individual ◽  
Selection Of

The development of new and better radioactive tracers capable of detecting and characterizing osteomyelitis is an ongoing process, mainly because available tracers lack selectivity towards osteomyelitis. An integrated part of developing new tracers is the performance of in vivo tests using appropriate animal models. The available animal models for osteomyelitis are also far from ideal. Therefore, developing improved animal osteomyelitis models is as important as developing new radioactive tracers. We recently published a review on radioactive tracers. In this review, we only present and discuss osteomyelitis models. Three ethical aspects (3R) are essential when exposing experimental animals to infections. Thus, we should perform experiments in vitro rather than in vivo (Replacement), use as few animals as possible (Reduction), and impose as little pain on the animal as possible (Refinement). The gain for humans should by far exceed the disadvantages for the individual experimental animal. To this end, the translational value of animal experiments is crucial. We therefore need a robust and well-characterized animal model to evaluate new osteomyelitis tracers to be sure that unpredicted variation in the animal model does not lead to a misinterpretation of the tracer behavior. In this review, we focus on how the development of radioactive tracers relies heavily on the selection of a reliable animal model, and we base the discussions on our own experience with a porcine model.

scholarly journals Supervised Machine Learning Methods and Hyperspectral Imaging Techniques Jointly Applied for Brain Cancer Classification

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3827
Author(s):  
Gemma Urbanos ◽  
Alberto Martín ◽  
Guillermo Vázquez ◽  
Marta Villanueva ◽  
Manuel Villa ◽  
...  
Keyword(s):  
Machine Learning ◽  
Blood Vessel ◽  
Hyperspectral Imaging ◽  
Imaging Techniques ◽  
Venous Blood ◽  
Healthy Tissue ◽  
Supervised Machine Learning ◽  
Support Vector ◽  
Arterial Blood

Hyperspectral imaging techniques (HSI) do not require contact with patients and are non-ionizing as well as non-invasive. As a consequence, they have been extensively applied in the medical field. HSI is being combined with machine learning (ML) processes to obtain models to assist in diagnosis. In particular, the combination of these techniques has proven to be a reliable aid in the differentiation of healthy and tumor tissue during brain tumor surgery. ML algorithms such as support vector machine (SVM), random forest (RF) and convolutional neural networks (CNN) are used to make predictions and provide in-vivo visualizations that may assist neurosurgeons in being more precise, hence reducing damages to healthy tissue. In this work, thirteen in-vivo hyperspectral images from twelve different patients with high-grade gliomas (grade III and IV) have been selected to train SVM, RF and CNN classifiers. Five different classes have been defined during the experiments: healthy tissue, tumor, venous blood vessel, arterial blood vessel and dura mater. Overall accuracy (OACC) results vary from 60% to 95% depending on the training conditions. Finally, as far as the contribution of each band to the OACC is concerned, the results obtained in this work are 3.81 times greater than those reported in the literature.

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