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Fracture, Bone

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Most cited protocols related to «Fracture, Bone»

Measuring Body Composition with DEXA and BIA

Total body fat mass and total bone-free lean mass (kg) were acquired from total body scans using fan-beamed dual-energy x-ray absorptiometry (Hologic, Waltham, MA or Lunar, Madison, WI) using standardized protocols (35 (link),36 (link)). Appendicular lean mass (ALM) was the sum of lean mass from both arms and legs. Participants missing lean mass measurements for an arm or leg were excluded. The validity and reproducibility of dual-energy x-ray absorptiometry have been reported previously. In Invecchiare in Chianti, body composition was measured using peripheral quantitative computed tomography of the calf. For Invecchiare in Chianti, estimated ALM was available only in men and was derived from equations from Osteoporotic Fractures in Men Study that included height, weight, waist circumference, fat area, muscle area, and muscle density. In Age, Gene/Environment Susceptibility-Reykjavik Study, body composition was measured with bioelectrical impedance (Xitron Hydra ECF/ICF Bio-Impedance Spectrum Analyzer).

Studenski S.A., Peters K.W., Alley D.E., Cawthon P.M., McLean R.R., Harris T.B., Ferrucci L., Guralnik J.M., Fragala M.S., Kenny A.M., Kiel D.P., Kritchevsky S.B., Shardell M.D., Dam T.T, & Vassileva M.T. (2014). The FNIH Sarcopenia Project: Rationale, Study Description, Conference Recommendations, and Final Estimates. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 69(5), 547-558.

Publication 2014

Bioelectrical Impedance Body Composition Body Fat Bone Density Dual-Energy X-Ray Absorptiometry Fracture, Bone Genetic Predisposition to Disease Hydra Muscle Tissue Silver Waist Circumference Whole Body Imaging X-Ray Computed Tomography

Comparing CRPS-I and Non-CRPS Neuropathic Pain

Protocol full text hidden due to copyright restrictions

Open the protocol to access the free full text link

Publication 2010

A 113 Allodynia Complex Regional Pain Syndromes Diabetes Mellitus Diabetic Neuropathies Fracture, Bone Hyperalgesia Injuries Injuries, Crush Intervertebral Disk Displacement Lower Extremity Nervousness Neuralgia Operative Surgical Procedures Pain Disorder Patients Peripheral Nerve Injuries Peripheral Nerves Peripheral Nervous System Diseases Physical Examination Plant Roots Radiculopathy Rehabilitation Tarsal Tunnel Syndrome Wrist Joint

Genetic Determinants of Fracture Risk

Fractures were defined as those occurring at any site, except fingers, toes and skull, after age 18. Both incident and prevalent fractures were included and were verified by either radiographic, casting, physician, or subject reporting. Fractures resulting from any type of trauma were considered. Covariates included in the additive model were age, age^{2 (link)}, sex, height, weight, estogen/menopause status (when available), ancestral genetic background and cohort-specific covariates (such as clinical centre). Association testing was done in two phases. The first involved all 1,482 genome-wide significant SNVs for BMD. In the second phase of fracture association testing, variants at EN1 were assessed in 18 cohorts, comprising 98,467 cases and 409,736 controls. Meta-analysis of cohort-level summary statistics was performed using GWAMA^{32 (link)}.

Zheng H.F., Forgetta V., Hsu Y.H., Estrada K., Rosello-Diez A., Leo P.J., Dahia C.L., Park-Min K.H., Tobias J.H., Kooperberg C., Kleinman A., Styrkarsdottir U., Liu C.T., Uggla C., Evans D.S., Nielson C.M., Walter K., Pettersson-Kymmer U., McCarthy S., Eriksson J., Kwan T., Jhamai M., Trajanoska K., Memari Y., Min J., Huang J., Danecek P., Wilmot B., Li R., Chou W.C., Mokry L.E., Moayyeri A., Claussnitzer M., Cheng C.H., Cheung W., Medina-Gómez C., Ge B., Chen S.H., Choi K., Oei L., Fraser J., Kraaij R., Hibbs M.A., Gregson C.L., Paquette D., Hofman A., Wibom C., Tranah G.J., Marshall M., Gardiner B.B., Cremin K., Auer P., Hsu L., Ring S., Tung J.Y., Thorleifsson G., Enneman A.W., van Schoor N.M., de Groot L.C., van der Velde N., Melin B., Kemp J.P., Christiansen C., Sayers A., Zhou Y., Calderari S., van Rooij J., Carlson C., Peters U., Berlivet S., Dostie J., Uitterlinden A.G., Williams S.R., Farber C., Grinberg D., LaCroix A.Z., Haessler J., Chasman D.I., Giulianini F., Rose L.M., Ridker P.M., Eisman J.A., Nguyen T.V., Center J.R., Nogues X., Garcia-Giralt N., Launer L.L., Gudnason V., Mellström D., Vandenput L., Karlsson M.K., Ljunggren Ö., Svensson O., Hallmans G., Rousseau F., Giroux S., Bussière J., Arp P.P., Koromani F., Prince R.L., Lewis J.R., Langdahl B.L., Hermann A.P., Jensen J.E., Kaptoge S., Khaw K.T., Reeve J., Formosa M.M., Xuereb-Anastasi A., Åkesson K., McGuigan F.E., Garg G., Olmos J.M., Zarrabeitia M.T., Riancho J.A., Ralston S.H., Alonso N., Jiang X., Goltzman D., Pastinen T., Grundberg E., Gauguier D., Orwoll E.S., Karasik D., Davey-Smith G., Smith A.V., Siggeirsdottir K., Harris T.B., Zillikens M.C., van Meurs J.B., Thorsteinsdottir U., Maurano M.T., Timpson N.J., Soranzo N., Durbin R., Wilson S.G., Ntzani E.E., Brown M.A., Stefansson K., Hinds D.A., Spector T., Cupples L.A., Ohlsson C., Greenwood C.M., Jackson R.D., Rowe D.W., Loomis C.A., Evans D.M., Ackert-Bicknell C.L., Joyner A.L., Duncan E.L., Kiel D.P., Rivadeneira F, & Richards J.B. (2015). Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture. Nature, 526(7571), 112-117.

Publication 2015

Cranium Fingers Fracture, Bone Genetic Background Genome Menopause MLL protein, human Physicians Toes Wounds and Injuries X-Rays, Diagnostic

Quantifying Vertebral Bone Density from CT

Abdominal CT was done using multidetector CT scanners (LightSpeed Series, GE Healthcare) calibrated daily to ensure accurate vertebral CT-attenuation numbers, which reflect underlying BMD (Figure 1). We retrospectively accessed the CT images and evaluated vertebral BMD on a standard radiology picture archiving and communication system workstation, with images viewed in soft tissue and bone windows (windows define gray-scale assignment of the image display to emphasize particular tissues and do not influence attenuation or BMD values [Figure 1]) (14 (link)). We assessed vertebral BMD by placing a single oval click-and-drag region of interest (ROI) over an area of vertebral body trabecular bone and then measuring CT attenuation in Hounsfield units (HU), with lower HU (lower attenuation) representing less-dense bone, at each of the T12 through L5 levels (Figures 1 and 2); this process is identical to that used for measuring CT attenuation for other clinical conditions (for example, adrenal adenomas, renal lesion enhancement, and fatty liver assessment). We avoided placing the ROI near areas that would distort the BMD measurement (posterior venous plexus; focal heterogeneity or lesion, including compression fracture; and imaging-related artifacts).
We assessed the presence of vertebral compression fractures by using sagittal CT views of the lumbar spine (Figure 2, B) by employing the Genant visual semiquantitative method (15 (link)), a widely accepted way of assessing vertebral fractures on conventional radiography that can be easily applied to sagittal CT images. We counted only obvious moderate (grade 2, 25% to 40% loss of height) or severe (grade 3, >40% loss of height) compression deformities to avoid ambiguity related to more subjective borderline or mild compression deformities. All potential moderate-to-severe compression fractures identified on the initial review were verified in a separate reading session for final confirmation, further excluding any questionable mild fractures.

Pickhardt P.J., Pooler B.D., Lauder T., del Rio A.M., Bruce R.J, & Binkley N. (2013). Opportunistic Screening for Osteoporosis Using Abdominal Computed Tomography Scans Obtained for Other Indications. Annals of internal medicine, 158(8), 588-595.

Publication 2013

Abdomen Adrenal Cortical Adenoma Bones Cancellous Bone CAT SCANNERS X RAY Congenital Abnormality Fatty Liver Fracture, Bone Fracture, Compression Genetic Heterogeneity Kidney Radiography Spinal Fractures Tissues Training Programs Veins Vertebra Vertebrae, Lumbar Vertebral Body

Fracture Risk Assessment Models

Four models were constructed from the risk factor analysis to compute fracture probabilities. These comprised the probability of hip fracture, with and without BMD, and the probability of other major osteoporotic fractures (clinical spine, forearm and proximal humerus), with and without BMD. For each model, fracture and death as continuous hazard functions were computed using a Poisson regression [26 , 27 (link)] and detailed in the Appendix. In brief, for each risk factor, all significant interactions terms that were identified by meta-analysis were entered (with age, time, sex and the risk factor) with and without BMD [17 (link)]. Interactions that were significant for hip fracture risk were also entered into the model for other osteoporotic fractures, and also included in the model for death. Where interactions noted in the “mega-analyses” were no longer significant for both hip fracture and other osteoporotic fractures, these were omitted in a step-wise manner by dropping the interaction with the largest p value. For the death hazard, all significant interactions for fracture risk were included and thereafter omitted if appropriate in a step-wise manner, as described for the fracture hazard.

Kanis J.A., Johnell O., Oden A., Johansson H, & McCloskey E. (2008). FRAX™ and the assessment of fracture probability in men and women from the UK. Osteoporosis International, 19(4), 385-397.

Publication 2008

Forearm Fracture, Bone Hip Fractures Humerus Osteoporotic Fractures Vertebral Column

Most recents protocols related to «Fracture, Bone»

Tailored Crush-Resistant Particles

Not available on PMC !

EXAMPLE 8

A protected particle was formed of a base particle having an average diameter of 20 μm. The base particle is a hollow sphere having a shell thickness of 1 μm. The interior pressure in the hollow cavity of the base particle is 14.7 psi. The density of the base particle is 0.38 g/cc and the crush strength of the base particle is 1,500 psi. The outer surface of the base particle was coated with a PLGA by suspension deposition. The coating thickness was 18 μm. The protected particle had a crush strength of about 8000 psi. The protected particles were subjected to well conditions of 30,000 ppm brine solution at a pH of 7.5, a temperature of 90° C., and under 6,000 psi hydrostatic pressure. After about 12 hours and over the period of 2 hours thereafter, the base particles were fractured or crushed. The acoustic sound or emission created by the fractured or crushed base particles had a traceable harmonic resonant frequency peak at 3,000 Hz. As is evident from Examples 7 and 8, the protected particle can be tailored by using different sized base particles to create a certain frequency or range of frequencies when the base particle fractures or crushes.

US11859489B2. Acoustic imaging agent (2024-01-02). Powdermet, Inc. [US]. Inventors: Brian S. Werry [US], Brian Doud [US], Andrew Sherman [US].

Full text: Click here

Patent 2024

Acoustics Dental Caries Fracture, Bone Hydrostatic Pressure Polylactic Acid-Polyglycolic Acid Copolymer Pressure Sound Training Programs

Pressure-Controlled Acoustic Particle Fracture

Not available on PMC !

EXAMPLE 10

A protected particle was formed of a base particle having an average diameter of 40 μm. The base particle is a hollow sphere having a shell thickness of 1 μm. The interior pressure in the hollow cavity of the base particle is 1000 psi. The density of the base particle is 0.39 g/cc. The outer surface of the base particle was coated with a PVA by suspension deposition. The coating thickness was 68 μm. The protected particle had a crush strength of about 8000 psi. The protected particles were subjected to well conditions of 10,000 ppm brine solution at a pH of 8, a temperature of 80° C., and under 6,000 psi hydrostatic pressure. After about 36 hours and over the period of 72 hours thereafter, the base particles were fractured or crushed. The acoustic sound or emission created by the fractured or crushed base particles had a traceable harmonic resonant frequency peak at 600 Hz. As is evident from Examples 9 and 10, the protected particle can be tailored by using certain pressures in the hollow cavity of the base particle to create a certain frequency or range of frequencies when the base particle fractures or crushes.

US11859489B2. Acoustic imaging agent (2024-01-02). Powdermet, Inc. [US]. Inventors: Brian S. Werry [US], Brian Doud [US], Andrew Sherman [US].

Full text: Click here

Patent 2024

Acoustics Dental Caries Fracture, Bone Hydrostatic Pressure Sound Training Programs

High-Resolution Imaging of Hydraulic Fractures Using DAS

Not available on PMC !

Example 1

High-Resolution Imaging Using Microseismic Events on DAS Data.

Using the high-frequency data recorded in DAS array to form high-resolution seismic images, which are used to image hydraulic fractures. The embodiment of this example has several advantages or prior systems, including: (a) Sensors are closer to the sources thus can provide much higher frequency comparing to traditional surface seismic data; (b) microseismic data generally carries frequency around 200 Hz while the surface seismic data is usually below 30 Hz. High-frequency data will improve the spatial-resolution of seismic images; (c) microseismic data have much stronger S-wave amplitude comparing to the surface seismic data, which is dominated by P-wave. S-wave is sensitive to the highly compliant fluids. Thus, the seismic attributes derived from the S-wave seismic images can be used to identify the fluid-filled hydraulic fractures; (d) DAS array forms much larger aperture (generally much greater than 2000 feet) comparing to traditional geophones (usually less than 2000 feet), while having much smaller spatial interval between the sensors. Those properties are ideal for producing high-resolution seismic images.

A velocity model is built using known-sources, such as (perforation shots) and microseismic events. Next microseismic events using geophone or DAS arrays are located. From this a reflection traveltime table between sources/sensors to the image voxels is computed. Next events on the DAS data are identified, provided they are located by geophones. The DAS data is then migrated to form a seismic image. Computations are then performed on the seismic attributes for fracture identification.

It is noted that there is no requirement to provide or address the theory underlying the novel and groundbreaking production rates, performance or other beneficial features and properties that are the subject of, or associated with, embodiments of the present inventions. Nevertheless, various theories are provided in this specification to further advance the art in this important area, and in particular in the important area of hydrocarbon exploration and production. These theories put forth in this specification, and unless expressly stated otherwise, in no way limit, restrict or narrow the scope of protection to be afforded the claimed inventions. These theories many not be required or practiced to utilize the present inventions. It is further understood that the present inventions may lead to new, and heretofore unknown theories to explain the conductivities, fractures, drainages, resource production, and function-features of embodiments of the methods, articles, materials, devices and system of the present inventions; and such later developed theories shall not limit the scope of protection afforded the present inventions.

The various embodiments of restimulation operations set forth in this specification may be used for various oil field operations, other mineral and resource recovery fields, as well as other activities and in other fields. Additionally, these embodiments, for example, may be used with: oil field systems, operations or activities that may be developed in the future; and with existing oil field systems, operations or activities which may be modified, in-part, based on the teachings of this specification. Further, the various embodiments set forth in this specification may be used with each other in different and various combinations. Thus, for example, the configurations provided in the various embodiments of this specification may be used with each other; and the scope of protection afforded the present inventions should not be limited to a particular embodiment, configuration or arrangement that is set forth in a particular embodiment, example, or in an embodiment in a particular Figure.

The invention may be embodied in other forms than those specifically disclosed herein without departing from its spirit or essential characteristics. The described embodiments are to be considered in all respects only as illustrative and not restrictive.

US11874418B2. High resolution composite seismic imaging, systems and methods (2024-01-16). Borehole Seismic, LLC. [US]. Inventors: Robinson Butler Howell [US], Zhao Li [US].

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Patent 2024

Drainage Electric Conductivity Foot Fracture, Bone Hydrocarbons Medical Devices Minerals Oil Fields Reflex Teaching

Invasive Knee Joint Tracking Protocol

Not available on PMC !

Example 1

Provided herein is an exemplary embodiment of workflow for tracking and registering a knee joint using markers that are drilled into the in tibia and femur of the knee joint in the patient and protrude out from their placement site. The placement of the marker in order to track and register the bones of the knee joint is an invasive procedure that damages the tissue at and around the knee joint. The marker is used in marker-based tracking to track and register the knee joint and in robot-assisted surgical systems. Such invasive fixation of markers to bones may lead to complications, infections, nerve injury, and bone fracture. The marker fixation may reduce the flexibility during the procedure as the protruding markers may get in the way during the procedure. The surgical procedure may take longer to fix the marker into place than a markerless approach.

US11857271B2. Markerless navigation using AI computer vision (2024-01-02). Future Health Works Ltd. [GB]. Inventors: Thomas Harte [GB], Huy Quoc Phan [GB].

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Patent 2024

Bones Femur Fracture, Bone Infection Injuries Knee Joint Nervousness Operative Surgical Procedures Patients Robotic Surgical Procedures Tibia Tissues

Degradable Hollow Particle Proppant

Not available on PMC !

EXAMPLE 13

A protected particle was formed of a base particle having an average diameter of 200 μm. The base particle is a hollow sphere having a shell thickness of 48 μm. The base particle was formed of degradable sodium silicate. The interior pressure in the hollow cavity of the base particle is 14.7 psi. The density of the base particle is 2.06 g/cc. The outer surface of the base particle was coated with a polylactic acid (PLA) by fluid bed spray coating. The coating thickness was 0.5 μm. The protected particle had a crush strength of over 12,000 psi. The protected particles were added to a proppant slurry and constituted about 0.5 wt. % of the proppant slurry. The proppant slurry with the protected particles was pumped into the fracturing zones of a well. The outer coating of PLA degraded by hydrolysis in the well and the rate of degradation only increased to an appreciable rate once the PLA encounters the higher temperatures within the deep well's fractures (around 60-100° C.), and thereafter degraded within 24 hours which exposed the readily degradable sodium silicate hollow spheres to the well pressure, thus being hydrostatically crushed.

US11859489B2. Acoustic imaging agent (2024-01-02). Powdermet, Inc. [US]. Inventors: Brian S. Werry [US], Brian Doud [US], Andrew Sherman [US].

Full text: Click here

Patent 2024

Acoustics Dental Caries Fever Fracture, Bone Hydrolysis poly(lactic acid) Pressure sodium silicate

Top products related to «Fracture, Bone»

Sas version 9 by SAS Institute

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SAS version 9.4 is a statistical software package. It provides tools for data management, analysis, and reporting. The software is designed to help users extract insights from data and make informed decisions.

Sas 9 by SAS Institute

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A universal testing machine is a device used to measure the force required to break, stretch, or compress a sample of material. It applies tensile, compressive, or shear stress to the sample and measures the resulting deformation. The core function of a universal testing machine is to perform standardized material tests to determine the mechanical properties of a wide range of materials.

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What are the different types of bone fractures?

Bone fractures can occur in a variety of forms, including simple fractures (where the bone is broken but the skin is not broken), compound fractures (where the bone protrudes through the skin), stress fractures (small cracks in the bone), and comminuted fractures (where the bone is broken into multiple pieces). Understanding the specific type of fracture is important for determining the appropriate treatment approach.

How can PubCompare.ai help with Fracture, Bone research?

PubCompare.ai allows researchers to screen protocol literature more efficiently and leverage AI to pinpoint critical insights. The platform can help identify the most effective protocols related to Fracture, Bone for your specific research goals. PubCompare.ai's AI-driven analysis can highlight key differences in protocol effectiveness, enabling you to choose the best option for reproducibility and accuracy in your Fracture, Bone studies.

What are some common challenges in Fracture, Bone research?

Some common challenges in Fracture, Bone research include ensuring accurate diagnosis, selecting the most appropriate treatment approach, monitoring healht progress, and achieving optimal outcomes. Researchers must also consider factors like patient age, bone density, and the severity of the fracture when designing their studies. PubCompare.ai can help address these challenges by providing a comprehensive overview of the latest protocols and techniques in the field.

How does PubCompare.ai assist in comparing Fracture, Bone protocols?

PubCompare.ai's AI-driven platform allows researchers to quickly compare the latest techniques and products related to Fracture, Bone. The tool can analyze protocol literature, preprints, and patents to identify key differences in effectiveness, safety, and reproducibility. This enables researchers to make more informed decisions about the best protocol to use for their specific study objectives, helping to unleash the full potential of their Fracture, Bone research.

What are some specific applications of PubCompare.ai for Fracture, Bone research?

PubCompare.ai can be leveraged for a variety of applications in Fracture, Bone research, such as: 1) Screening protocol literature more efficently to identify the most promising techniques. 2) Utilizing AI to pinpoint critical insights that may have been overlooked. 3) Comparing the latst protocols to determine the optimal approach for ensuring reproducibility and accuracy. 4) Discovering new and innovative methods for treating bone fractures. By empowering researchers with these capabiliteis, PubCompare.ai helps unlock new possibiliteis in the field of Fracture, Bone.

How does PubCompare.ai ensure accuracy and reproducibiltiy in Fracture, Bone research?

One of the key benefits of using PubCompare.ai for Fracture, Bone research is the platform's ability to help ensure accuracy and reproducibility. The AI-driven analysis provided by PubCompare.ai can highlight critical differences between protocols, alloweing researchers to identify the most effective and reliable approaches. This helps mitigate the risk of flawed or irreproducible results, which is a common chalenge in this field of study. By leveraging PubCompare.ai, researchers can have confidence that their Fracture, Bone findings are both accurate and replicable.

More about "Fracture, Bone"

Fracture, Bone is a term used to describe a break or crack in the hard, dense tissue that makes up the majority of the skeletal structure.
These injuries can range in severity from a small hairline fracture to a complete break in the bone.
Bone fractures are commonly caused by trauma, such as a fall, car accident, or sports injury, but can also occur due to underlying conditions like osteoporosis.
Researchers in the field of bone fracture often utilize various equipment and software to study and analyze these injuries.
Some commonly used tools include: - Universal testing machines (e.g., Instron, MTS) - Used to measure the mechanical properties of bone, such as strength and stiffness. - Scanning electron microscopes (e.g., S-4800) - Provide high-resolution images of the bone structure for detailed analysis. - Texture analyzers (e.g., TA-XT Plus) - Assess the texture and mechanical properties of bone. - Micro-CT scanners (e.g., VivaCT 40) - Generate 3D images of bone structure and enable the study of bone microarchitecture. - Statistical analysis software (e.g., SPSS Statistics, versions 22.0 and 25) - Allows researchers to analyze data and draw insights from their studies.
Researchers in the field of bone fracture can leverage the power of PubCompare.ai, an AI-driven platform that helps locate optimal protocols from literature, preprints, and patents.
This tool ensures reproducibility and accuracy, allowing researchers to compare the latest techniques and products to find the best fit for their studies.
By utilizing PubCompare.ai, researchers can unleash the full potential of their bone fracture research and drive advancements in this important field of study.