Home » news »

Diagnosing Obesity by Mathematically Estimating Abdominal Fat


Medicine, Health Care Diagnosing Obesity by Mathematically Estimating…

Published: Jun 20, 2017.
Released by Society for Industrial and Applied Mathematics  

Abdominal obesity, or fat that accumulates around one’s stomach and abdomen, has prolonged been deliberate to poise a high health risk in individuals. Hence, dimensions of “central obesity”–as it’s mostly called–helps envision inclination to disorders caused by additional weight in a abdominal area.

In a paper edition successive week in a SIAM Journal on Imaging Sciences, researchers from ETH Zurich and Yonsei University in Seoul introduce a new technique to weigh abdominal plumpness by estimating a density of subcutaneous fat.

“Recent studies have shown that abdominal plumpness is related with diseases such as congestive heart disaster and metabolic syndrome,” pronounced author Jin Keun Seo. “Static electrical impedance tomography, or EIT, could be employed as a non-invasive broker of illness course in these conditions.”

In further to being noninvasive, EIT, an imaging technique, provides real-time information but regulating ionizing radiation, that creates it preferable to computed tomography (CT) given it’s reduction damaging to patients. Another imaging technique ordinarily used for this purpose, captivating inflection imaging (MRI) has poorer spatial fortitude than EIT.

“Compared to CT, EIT is some-more fitting given it is non-ionizing and can hence be used for continual studious self-monitoring to lane physique fat standing in daily routines,” Seo explained. “Unlike CT and MRI, EIT is a low cost, portable, and easy-to-use bedside technique to picture electrical conductivity distribution.”

Since electrical conductivity of biological hankie depends on a dungeon structure, it can assistance picture opposite tissues in a physique and heed them from any other. The dungeon structure of fat and flesh are utterly different; hence, a electrical conductivity values of fat and flesh differ over opposite frequencies.

Multi-frequency EIT (MFEIT) reconstructs a picture of conductivity inside a tellurian physique formed on this coherence of hankie conductivity on frequency. And given bone, muscle, and fat control electricity differently over several frequencies, MFEIT can use information of a range current-voltage attribute during different frequencies to guess a volume of fat. Again, given physique fat is reduction conductive than H2O and tissues such as muscle, this disproportion can be used to guess a density of abdominal and subcutaneous gross tissue.

The specific routine involves a specifically selected stream pattern, that generates a depth-dependent information set that is used to outline a borders between fat and muscle. Current is injected by one span of electrodes, and a successive voltage dump totalled during another span of electrodes. The propinquity between a injected stream and a voltage dump gives a transadmittance — or a ratio of stream to voltage, that depends on a positions of a dual pairs of electrodes, physique geometry, and admittivity distribution, that combines both conductivity and permittivity. Assuming that a distance of a electrodes is really tiny in comparison to a distance of a limit between a several hankie regions, a authors use a indicate electrode model, that provides a good estimation of a solution, while also simplifying a indication considerably.

One emanate with EIT is that a technique is disposed to forward-modeling errors; these errors mostly embody range geometry and electrode position uncertainties. In this paper, authors introduce a new reformation process that compensates for this ambuscade of EIT, regulating before anatomical information during a responsibility of spatial resolution, and improving reproducibility. Numerical simulations denote that a outcome of reformation is acceptable in identifying subcutaneous fat.

“Existing approaches for immobile conductivity imaging are formed on minimizing a disproportion between a voltage totalled and that performed from numerical simulations,” Hyeuknam explained. “Therefore, receiving arguable conductivity distributions requires both accurate displaying of a domain and a electrode configuration. This new process can obtain accurate imaging placement by canceling out displaying errors.”

Further investigate is indispensable to take advantage of a magnitude contingent function of tellurian hankie to guess a placement of abdominal fat. “Current initial work has shown earnest formula in detecting subcutaneous fat density as reliable with ultrasound imaging,” pronounced Hyeuknam. “Future work is indispensable to establish a volume of abdominal fat in patients with metabolic and cardiovascular disorders.”

Abnormally high deposition of fat hankie in a abdominal area has been compared with disorders such as metabolic syndrome, cardiovascular disease, and malignancies. Quantitative comment of abdominal fat in a abdominal segment regulating techniques such as a one described above can so assist in evaluating a intensity risk of building such conditions.

Chinese French German Italian Japanese Korean Portuguese Russian Spanish