Monte Carlo modelling of an extended DXA technique

Combining 3D optical imaging and dual energy absorptiometry to measure three compositional components

We report on the design of the technique combining 3D optical imaging and dual-energy absorptiometry body scanning to estimate local body area compositions of three compartments. Dual-energy attenuation and body shape measures are used together to solve for the three compositional tissue thicknesses: water, lipid, and protein. We designed phantoms with tissue-like properties as our reference standards for calibration purposes. The calibration was created by fitting phantom values using non-linear regression of quadratic and truncated polynomials. Dual-energy measurements were performed on tissue-mimicking phantoms using a bone densitometer unit. The phantoms were made of materials shown to have similar x-ray attenuation properties of the biological compositional compartments. The components for the solid phantom were tested and their high energy/low energy attenuation ratios are in good correspondent to water, lipid, and protein for the densitometer x-ray region. The three-dimensional body shape was reconstructed from the depth maps generated by Microsoft Kinect for Windows. We used open-source Point Cloud Library and freeware software to produce dense point clouds. Accuracy and precision of compositional and thickness measures were calculated. The error contributions due to two modalities were estimated. The preliminary phantom composition and shape measurements are found to demonstrate the feasibility of the method proposed.

Compositional breast imaging using a dual-energy mammography protocol

PURPOSE

Mammography has a low sensitivity in dense breasts due to low contrast between malignant and normal tissue confounded by the predominant water density of the breast. Water is found in both adipose and fibroglandular tissue and constitutes most of the mass of a breast. However, significant protein mass is mainly found in the fibroglandular tissue where most cancers originate. If the protein compartment in a mammogram could be imaged without the influence of water, the sensitivity and specificity of the mammogram may be improved. This article describes a novel approach to dual-energy mammography, full-field digital compositional mammography (FFDCM), which can independently image the three compositional components of breast tissue: water, lipid, and protein.

METHODS

Dual-energy attenuation and breast shape measures are used together to solve for the three compositional thicknesses. Dual-energy measurements were performed on breast-mimicking phantoms using a full-field digital mammography unit. The phantoms were made of materials shown to have similar x-ray attenuation properties of the compositional compartments. They were made of two main stacks of thicknesses around 2 and 4 cm. Twenty-six thickness and composition combinations were used to derive the compositional calibration using a least-squares fitting approach.

RESULTS

Very high accuracy was achieved with a simple cubic fitting function with root mean square errors of 0.023, 0.011, and 0.012 cm for the water, lipid, and protein thicknesses, respectively. The repeatability (percent coefficient of variation) of these measures was tested using sequential images and was found to be 0.5%, 0.5%, and 3.3% for water, lipid, and protein, respectively. However, swapping the location of the two stacks of the phantom on the imaging plate introduced further errors showing the need for more complete system uniformity corrections. Finally, a preliminary breast image is presented of each of the compositional compartments separately.

CONCLUSIONS

FFDCM has been derived and exhibited good compositional thickness accuracy on phantoms. Preliminary breast images demonstrated the feasibility of creating individual compositional diagnostic images in a clinical environment.

Human body composition: in vivo methods

In vivo methods used to study human body composition continue to be developed, along with more advanced reference models that utilize the information obtained with these technologies. Some methods are well established, with a strong physiological basis for their measurement, whereas others are much more indirect. This review has been structured from the methodological point of view to help the reader understand what can be examined with each technique. The associations between the various in vivo methods (densitometry, dilution, bioelectrical impedance and conductance, whole body counting, neutron activation, X-ray absorptiometry, computer tomography, and magnetic resonance imaging) and the five-level multicompartment model of body composition are described, along with the limitations and advantages of each method. This review also provides an overview of the present status of this field of research in human biology, including examples of reference body composition data for infants, children, adolescents, and adults.