Determination of abdominal fat thickness using dual electrode separation in the focused impedance method (FIM)

Computed Tomography Image Analysis of Body Fat Based on Multi-Image Information

Body fat assessment is required as part of an objective health assessment, both for nonobese and obese people. Image-based body fat assessment will enable faster diagnosis. Body fat analysis that accounts for age and sex will help in both diagnosis and correlating diseases and fat distribution. After evaluating computed tomography imaging algorithms to identify and segment human abdominal and subcutaneous fat, we present an improved region growing scale-invariant feature transform algorithm. It applies Naive Bayes image thresholding for key point selection and image matching. This method enables rapid and accurate comparison and matching of images from multiple databases and improves the efficiency of image processing.

A Multi-Frequency Focused Impedance Measurement System Based on Analogue Synchronous Peak Detection

Monitoring of anatomical structures and physiological processes by electrical impedance has attracted scientists as it is noninvasive, nonionizing and the instrumentation is relatively simple. Focused Impedance Method (FIM) is attractive in this context, as it has enhanced sensitivity at the central region directly beneath the electrode configuration minimizing contribution from neighboring regions. FIM essentially adds or averages two concentric and orthogonal combinations of conventional Tetrapolar Impedance Measurements (TPIM) and has three versions with 4, 6, and 8 electrodes. This paper describes the design and testing of a multi-frequency FIM (MFFIM) system capable of measuring all three versions of FIM at 8 frequencies in the range 10 kHz—1 MHz. A microcontroller based multi-frequency signal generator and a balanced Howland current source with high output impedance (476 kΩ at 10 kHz and 58.3 kΩ at 1 MHz) were implemented for driving currents into biological tissues with an error <1%. The measurements were carried out at each frequency sequentially. The peak values of the amplified voltage signals were measured using a novel analogue synchronous peak detection technique from which the transfer impedances were obtained. The developed system was tested using TPIM measurements on a passive RC Cole network placed between two RC networks, the latter representing skin-electrode contact impedances. Overall accuracy of the measurement was very good (error <4% at all frequencies except 1 MHz, with error 6%) and the resolution was 0.1 Ω. The designed MFFIM system had a sampling rate of >45 frames per second which was deemed adequate for noninvasive real-time impedance measurements on biological tissues.

Regression models for near-infrared measurement of subcutaneous adipose tissue thickness

Obesity is often associated with the risks of diabetes and cardiovascular disease, and there is a need to measure subcutaneous adipose tissue (SAT) thickness for acquiring the distribution of body fat. The present study aimed to develop and evaluate different model-based methods for SAT thickness measurement using an SATmeter developed in our laboratory. Near-infrared signals backscattered from the body surfaces from 40 subjects at 20 body sites each were recorded. Linear regression (LR) and support vector regression (SVR) models were established to predict SAT thickness on different body sites. The measurement accuracy was evaluated by ultrasound, and compared with results from a mechanical skinfold caliper (MSC) and a body composition balance monitor (BCBM). The results showed that both LR- and SVR-based measurement produced better accuracy than MSC and BCBM. It was also concluded that by using regression models specifically designed for certain parts of human body, higher measurement accuracy could be achieved than using a general model for the whole body. Our results demonstrated that the SATmeter is a feasible method, which can be applied at home and in the community due to its portability and convenience.

Modeling the thermo-acoustic effects of thermal-dependent speed of sound and acoustic absorption of biological tissues during focused ultrasound hyperthermia

PURPOSE

To evaluate the effects of thermal dependence of speed of sound (SOS) and acoustic absorption of biological tissues during noninvasive focused ultrasound (US) hyperthermia therapy.

METHODS

A finite element (FE) model was used to simulate hyperthermia therapy in the liver by noninvasive focused US. The model consisted of an ultrasonic focused transducer radiating a four-layer biological medium composed of skin, fat, muscle, and liver. The acoustic field and temperature distribution along the layers were obtained after 15 s of hyperthermia therapy using the bio-heat equation. The model solution was found with and without the thermal dependence of SOS and acoustic absorption of biological tissues.

RESULTS

The inclusion of the thermal dependence of the SOS generated an increment of 0.4 mm in the longitudinal focus axis of the acoustic field. Moreover, results indicate an increment of the hyperthermia area (zone with temperature above 43 °C), and a maximum temperature difference of almost 3.5 °C when the thermal dependence of absorption was taken into account.

CONCLUSION

The increment of the achieved temperatures at the treatment zone indicated that the effects produced by the thermal dependence of SOS and absorption must be accounted for when planning hyperthermia treatment in order to avoid overheating undesired regions.

FOCUSED IMPEDANCE METHOD TO DETECT LOCALIZED LUNG VENTILATION DISORDERS IN COMBINATION WITH CONVENTIONAL SPIROMETRY

Conventional spirometry gives information on the overall ventilation of a person's lung; it cannot detect localized disorders in ventilation as occurring in pulmonary edema, pneumonia, tumor, TB, etc. Here we propose a new technique involving the recently developed focused impedance method (FIM) in combination with conventional spirometry to detect localized lung ventilation disorders. Electrical impedance of lung tissue changes as a function of air content and FIM provides a measurement of localized electrical impedance with sensitivity down to reasonable depths inside the body using a few surface electrodes; here we used a six-electrode version. At least four quadrants of the lungs in the frontal plane can be separately measured using a hand-held probe with spring backed skin surface electrodes. Firstly, spatial sensitivity distribution of the six-electrode FIM was obtained using finite element simulation which verified the focusing effect and its depth sensitivity. Percent change in impedance between maximum inspiration and expiration were measured at four quadrants of the chest of a healthy male subject giving four different values; that at the lower right quadrant was found to be the maximum, as also expected based on anatomy. Changes in impedance at this quadrant of the same subject were found to vary proportionately with exhaled air volumes, measured using a bellows-type spirometer. Similar FIM measurements at lower right lung of seven healthy subjects were found to be almost proportional (R2 = 0.7) to the total exhaled air volumes (vital capacity). This was the basis of the new technique. For a healthy individual, the ratio of the local impedance change to vital capacity (VC) will fall within a certain range for each of the four lung quadrants. A lower value at any quadrant would indicate disorder within that quadrant, while a larger value would indicate disorder in a region outside the particular quadrant. The FIM electrode probe can then be moved to take measurements at the other quadrants to locate the region of disorder. This preliminary study indicates that FIM in combination with conventional spirometry could be used to detect localized ventilation defects.

Measurement of subcutaneous adipose tissue thickness by near-infrared

Obesity is strongly associated with the risks of diabetes and cardiovascular disease, and there is a need to measure the subcutaneous adipose tissue (SAT) layer thickness and to understand the distribution of body fat. A device was designed to illuminate the body parts by near-infrared (NIR), measure the backscattered light, and predict the SAT layer thickness. The device was controlled by a single-chip microcontroller (SCM), and the thickness value was presented on a liquid crystal display (LCD). There were 30 subjects in this study, and the measurements were performed on 14 body parts for each subject. The paper investigated the impacts of pressure and skin colour on the measurement. Combining with principal component analysis (PCA) and support vector regression (SVR), the measurement accuracy of SAT layer thickness was 89.1 % with a mechanical caliper as reference. The measuring range was 5-11 mm. The study provides a non-invasive and low-cost technique to detect subcutaneous fat thickness, which is more accessible and affordable compared to other conventional techniques. The designed device can be used at home and in community.