The diagnostic capability of x-ray scattering parameters for the characterization of breast cancer

Target-filter combination effects on breast tissue characterization using mammographic X-rays: A Monte Carlo simulation study

BACKGROUND

Characterization of normal and malignant breast tissues using X-ray scattering techniques has shown promising results and applications.

OBJECTIVE

To examine possibility of characterizing normal and malignant breast tissues using the scattered photon distribution of polyenergetic beams of 30 kV X-rays.

METHODS

A Monte Carlo simulation is upgraded so that it is capable of simulating input mammographic X-ray spectra from different target-filter combinations, tracing photon transport, and producing the distribution of scattered photons. The target-filter combinations include Mo-Mo, Mo-Al, Mo-Rh, Rh-Rh, Rh-Al, W-Rh, and W-Al. Analysis of obtained scattered photon distribution is carried out by comparing the ratio of count under the peak in the momentum transfer region from 0 to 1.55 nm-1, to that in the region from 1.6 to 9.1 nm-1 (covering the regions of scattering from fat and soft tissue, respectively) for breast samples with different percentages of normal tissue (0-100%).

RESULTS

Mo-Mo target-filter combination shows a high linear dependence of the count under peak ratio on the percentage of normal tissue in breast samples (R2 = 0.9513). Despite slightly less linear than Mo-Mo, target-filter combinations other than Rh-Rh, W-Rh, and W-Al produce high linear responses (R2 > 0.9)CONCLUSION:Mo-Mo target-filter combination would probably be the most relevant in characterizing normal and malignant breast tissues from their scattered photon distribution.

Plasma membrane proteins: A new probe for the characterization of breast cancer

This work aimed to characterize normal, benign and malignant excised breast tissues through the analysis of the FTIR spectra of their plasma membrane proteins. Tissue characterization parameters such as peak position, peak intensity, area under the peak, relative peak intensity and relative area under peak were evaluated mainly for protein spectral peaks; 1150 cm^-1, Amide I, Amide II, Amide III, and Amide A. The sensitivity, specificity and diagnostic accuracy for each parameter were obtained and Receiver Operating Characteristic (ROC) Curves were plotted. Results showed significant spectral differences between normal and benign tissues compared to malignant tissues at 1536 and 1645 cm^-1. The three tissues could be distinguished at 2900 cm^-1, where the malignant peak uniquely split into two separate peaks. ROC curves showed that the Amide A peak position yielded a higher accuracy compared to all other investigated characterization parameters. The deconvolution of Amide I revealed the conformational changes in plasma proteins characterizing the transformation to malignancy (a decrease in the percentage of alpha helix accompanied by an increase in the percentage of beta sheets). The use of the present structure-based analysis in conjunction with histopathological examination of excised breast tissues would offer an enhanced characterization that might reduce possible personal diagnostic mistakes.

Coherent scatter imaging Monte Carlo simulation

Conventional mammography can suffer from poor contrast between healthy and cancerous tissues due to the small difference in attenuation properties. Coherent scatter slot scan imaging is an imaging technique which provides additional information and is compatible with conventional mammography. A Monte Carlo simulation of coherent scatter slot scan imaging was performed to assess its performance and provide system optimization. Coherent scatter could be exploited using a system similar to conventional slot scan mammography system with antiscatter grids tilted at the characteristic angle of cancerous tissues. System optimization was performed across several parameters, including source voltage, tilt angle, grid distances, grid ratio, and shielding geometry. The simulated carcinomas were detectable for tumors as small as 5 mm in diameter, so coherent scatter analysis using a wide-slot setup could be promising as an enhancement for screening mammography. Employing coherent scatter information simultaneously with conventional mammography could yield a conventional high spatial resolution image with additional coherent scatter information.

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples

A scatter imaging technique for the differentiation of cancerous and healthy breast tissue in a heterogeneous sample is introduced in this work. Such a technique has potential utility in intraoperative margin assessment during lumpectomy procedures. In this work, we investigate the feasibility of the imaging method for tumor classification using Monte Carlo simulations and physical experiments. The coded aperture coherent scatter spectral imaging technique was used to reconstruct three-dimensional (3-D) images of breast tissue samples acquired through a single-position snapshot acquisition, without rotation as is required in coherent scatter computed tomography. We perform a quantitative assessment of the accuracy of the cancerous voxel classification using Monte Carlo simulations of the imaging system; describe our experimental implementation of coded aperture scatter imaging; show the reconstructed images of the breast tissue samples; and present segmentations of the 3-D images in order to identify the cancerous and healthy tissue in the samples. From the Monte Carlo simulations, we find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside them with a cancerous voxel identification sensitivity, specificity, and accuracy of 92.4%, 91.9%, and 92.0%, respectively. From the experimental results, we find that the technique is able to identify cancerous and healthy tissue samples and reconstruct differential coherent scatter cross sections that are highly correlated with those measured by other groups using x-ray diffraction. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside samples within a time on the order of a minute per slice.

Model predictions for the wide-angle x-ray scatter signals of healthy and malignant breast duct biopsies

Wide-angle x-ray scatter (WAXS) could potentially be used to diagnose ductal carcinoma in situ (DCIS) in breast biopsies. The regions of interest were assumed to consist of fibroglandular tissue and epithelial cells and the model assumed that biopsies with DCIS would have a higher concentration of the latter. The scattered number of photons from a 2-mm diameter column of tissue was simulated using a 110-kV beam and selectively added in terms of momentum transfer. For a 1-min exposure, specificities and sensitivities of unity were obtained for biopsies 2- to 20-mm thick. The impact of sample and tumor cell layer thicknesses was studied. For example, a biopsy erroneously estimated to be 8 mm would be correctly diagnosed if its actual thickness was between 7.3 and 8.7 mm. An 8-mm thick malignant biopsy can be correctly diagnosed provided the malignant cell layer thickness is [Formula: see text]. WAXS methods could become a diagnostic tool for DCIS within breast biopsies.

A method to estimate the fractional fat volume within a ROI of a breast biopsy for WAXS applications: animal tissue evaluation

PURPOSE

To develop a method to estimate the mean fractional volume of fat (ν¯fat) within a region of interest (ROI) of a tissue sample for wide-angle x-ray scatter (WAXS) applications. A scatter signal from the ROI was obtained and use of ν¯fat in a WAXS fat subtraction model provided a way to estimate the differential linear scattering coefficient μs of the remaining fatless tissue.

METHODS

The efficacy of the method was tested using animal tissue from a local butcher shop. Formalin fixed samples, 5 mm in diameter 4 mm thick, were prepared. The two main tissue types were fat and meat (fibrous). Pure as well as composite samples consisting of a mixture of the two tissue types were analyzed. For the latter samples, νfat for the tissue columns of interest were extracted from corresponding pixels in CCD digital x-ray images using a calibration curve. The means ν¯fat were then calculated for use in a WAXS fat subtraction model. For the WAXS measurements, the samples were interrogated with a 2.7 mm diameter 50 kV beam and the 6° scattered photons were detected with a CdTe detector subtending a solid angle of 7.75 × 10(-5) sr. Using the scatter spectrum, an estimate of the incident spectrum, and a scatter model, μs was determined for the tissue in the ROI. For the composite samples, a WAXS fat subtraction model was used to estimate the μs of the fibrous tissue in the ROI. This signal was compared to μs of fibrous tissue obtained using a pure fibrous sample.

RESULTS

For chicken and beef composites, ν¯fat=0.33±0.05 and 0.32 ± 0.05, respectively. The subtractions of these fat components from the WAXS composite signals provided estimates of μs for chicken and beef fibrous tissue. The differences between the estimates and μs of fibrous obtained with a pure sample were calculated as a function of the momentum transfer x. A t-test showed that the mean of the differences did not vary from zero in a statistically significant way thereby validating the methods.

CONCLUSIONS

The methodology to estimate ν¯fat in a ROI of a tissue sample via CCD x-ray imaging was quantitatively accurate. The WAXS fat subtraction model allowed μs of fibrous tissue to be obtained from a ROI which had some fat. The fat estimation method coupled with the WAXS models can be used to compare μs coefficients of fibroglandular and cancerous breast tissue.

WAXS fat subtraction model to estimate differential linear scattering coefficients of fatless breast tissue: phantom materials evaluation

PURPOSE

Develop a method to subtract fat tissue contributions to wide-angle x-ray scatter (WAXS) signals of breast biopsies in order to estimate the differential linear scattering coefficients μ(s) of fatless tissue. Cancerous and fibroglandular tissue can then be compared independent of fat content. In this work phantom materials with known compositions were used to test the efficacy of the WAXS subtraction model.

METHODS

Each sample 5 mm in diameter and 5 mm thick was interrogated by a 50 kV 2.7 mm diameter beam for 3 min. A 25 mm(2) by 1 mm thick CdTe detector allowed measurements of a portion of the θ = 6° scattered field. A scatter technique provided means to estimate the incident spectrum N(0)(E) needed in the calculations of μ(s)[x(E, θ)] where x is the momentum transfer argument. Values of [Formula: see text] for composite phantoms consisting of three plastic layers were estimated and compared to the values obtained via the sum [Formula: see text], where ν(i) is the fractional volume of the ith plastic component. Water, polystyrene, and a volume mixture of 0.6 water + 0.4 polystyrene labelled as fibphan were chosen to mimic cancer, fat, and fibroglandular tissue, respectively. A WAXS subtraction model was used to remove the polystyrene signal from tissue composite phantoms so that the μ(s) of water and fibphan could be estimated. Although the composite samples were layered, simulations were performed to test the models under nonlayered conditions.

RESULTS

The well known μ(s) signal of water was reproduced effectively between 0.5 < x < 1.6 nm(-1). The [Formula: see text] obtained for the heterogeneous samples agreed with [Formula: see text]. Polystyrene signals were subtracted successfully from composite phantoms. The simulations validated the usefulness of the WAXS models for nonlayered biopsies.

CONCLUSIONS

The methodology to measure μ(s) of homogeneous samples was quantitatively accurate. Simple WAXS models predicted the probabilities for specific x-ray scattering to occur from heterogeneous biopsies. The fat subtraction model can allow μ(s) signals of breast cancer and fibroglandular tissue to be compared without the effects of fat provided there is an independent measurement of the fat volume fraction ν(f). Future work will consist of devising a quantitative x-ray digital imaging method to estimate ν(f) in ex vivo breast samples.