JoVE Visualize What is visualize?
Stop Reading. Start Watching.
Advanced Search
Stop Reading. Start Watching.
Regular Search
Find video protocols related to scientific articles indexed in Pubmed.
Clinical assessment of the 1/3 radius using a new desktop ultrasonic bone densitometer.
Ultrasound Med Biol
PUBLISHED: 01-11-2013
Show Abstract
Hide Abstract
The objectives of this study were to evaluate the capability of a novel ultrasound device to clinically estimate bone mineral density (BMD) at the 1/3 radius. The device rests on a desktop and is portable, and permits real-time evaluation of the radial BMD. The device measures two net time delay (NTD) parameters, NTD(DW) and NTD(CW). NTD(DW) is defined as the difference between the transit time of an ultrasound pulse to travel through soft-tissue, cortex and medullary cavity, and the transit time through soft tissue only of equal overall distance. NTD(CW) is defined as the difference between the transit time of an ultrasound pulse to travel through soft-tissue and cortex only, and the transit time through soft tissue only again of equal overall distance. The square root of the product of these two parameters is a measure of the radial BMD at the 1/3 location as measured by dual-energy X-ray absorptiometry (DXA). A clinical IRB-approved study measured ultrasonically 60 adults at the 1/3 radius. BMD was also measured at the same anatomic site and time using DXA. A linear regression using NTD produced a linear correlation coefficient of 0.93 (p < 0.001). These results are consistent with previously reported simulation and in vitro studies. In conclusion, although X-ray methods are effective in bone mass assessment, osteoporosis remains one of the largest undiagnosed and under-diagnosed diseases in the world today. The research described here should enable significant expansion of diagnosis and monitoring of osteoporosis through a desktop device that ultrasonically assesses bone mass at the 1/3 radius.
Related JoVE Video
Finite element analysis of heel pad with insoles.
J Biomech
PUBLISHED: 02-24-2011
Show Abstract
Hide Abstract
To design optimal insoles for reduction of pedal tissue trauma, experimental measurements and computational analyses were performed. To characterize the mechanical properties of the tissues, indentation tests were performed. Pedal tissue geometry and morphology were obtained from magnetic resonance scan of the subjects foot. Axisymmetrical finite element models of the heel of the foot were created with 1/4 of body weight load applied. The stress, strain and strain energy density (SED) fields produced in the pedal tissues were computed. The effects of various insole designs and materials on the resulting stress, strain, and SED in the soft pedal tissues were analyzed. The results showed: (a) Flat insoles made of soft material provide some reductions in the maximum stress, strain and SED produced in the pedal tissues. These maximum values were computed near the calcaneus. (b) Flat insoles, with conical/cylindrical reliefs, provided more reductions in these maximum values than without reliefs. (c) Custom insoles, contoured to match the pedal geometry provide most reductions in the maximum stress, strain and SED. Also note, the maximum stress, strain and SED computed near the calcaneus were found to be about 10 times the corresponding peak values computed on the skin surface. Based on the FEA analysis, it can be concluded that changing insole design and using different material can significantly redistribute the stress/strain inside the heel pad as well as on the skin surface.
Related JoVE Video
A poisson process model for hip fracture risk.
Med Biol Eng Comput
PUBLISHED: 05-16-2010
Show Abstract
Hide Abstract
The primary method for assessing fracture risk in osteoporosis relies primarily on measurement of bone mass. Estimation of fracture risk is most often evaluated using logistic or proportional hazards models. Notwithstanding the success of these models, there is still much uncertainty as to who will or will not suffer a fracture. This has led to a search for other components besides mass that affect bone strength. The purpose of this paper is to introduce a new mechanistic stochastic model that characterizes the risk of hip fracture in an individual. A Poisson process is used to model the occurrence of falls, which are assumed to occur at a rate, lambda. The load induced by a fall is assumed to be a random variable that has a Weibull probability distribution. The combination of falls together with loads leads to a compound Poisson process. By retaining only those occurrences of the compound Poisson process that result in a hip fracture, a thinned Poisson process is defined that itself is a Poisson process. The fall rate is modeled as an affine function of age, and hip strength is modeled as a power law function of bone mineral density (BMD). The risk of hip fracture can then be computed as a function of age and BMD. By extending the analysis to a Bayesian framework, the conditional densities of BMD given a prior fracture and no prior fracture can be computed and shown to be consistent with clinical observations. In addition, the conditional probabilities of fracture given a prior fracture and no prior fracture can also be computed, and also demonstrate results similar to clinical data. The model elucidates the fact that the hip fracture process is inherently random and improvements in hip strength estimation over and above that provided by BMD operate in a highly "noisy" environment and may therefore have little ability to impact clinical practice.
Related JoVE Video
Comparison of male and female foot shape.
J Am Podiatr Med Assoc
PUBLISHED: 09-22-2009
Show Abstract
Hide Abstract
Morphological and geometric differences between male and female feet can be the decisive factor of whether well-fitting, functional, and comfortable footwear is available for both men and women.
Related JoVE Video

What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.