Dual-energy mammography: simulation studies

Adenoid Cystic Carcinoma of the Breast

BACKGROUND

Contrast-enhanced spectral mammogram (CESM) is a modern technique providing additional information to detect or diagnose breast cancers.

INTRODUCTION

We present a rare ACC of the breast on CESM.

METHODS

A 49-year-old woman with surgicopathological proved ACC was reported with tumor features on CESM, sonography and contrast-enhanced magnetic resonance imaging (CE-MRI).

RESULTS

Sonography revealed a 1.4 cm × 1.2 cm × 1 cm circumscribe round mass in the upper outer quadrant of the left breast that was diagnosed with fibroadenoma. The mammogram did not show any discernible mass, however, the recombined subtracted images displayed a circumscribe mass with thin rim enhancement and enhanced internal patches that were resembling CE-MRI. Finally, the mass was proved to ACC.

CONCLUSION

CESM facilitates the detection of isodense cancer and provides the enhanced features for differential diagnosis. Resembling CE-MRI, CESM displayed rim enhancement and internal enhanced patches as diagnostic clues for this case of ACC.

Virtual clinical trials in medical imaging: a review

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities.

Susceptibility of iodine concentration map of dual-energy contrast-enhanced digital mammography for quantitative and tumor enhancement assessment

Background Dual-energy (DE) contrast-enhanced digital mammography (DE-CEDM) provides additional information on tumor angiogenesis. Purpose To investigate the susceptibility of reconstructing color-coded iodine concentration maps on the basis of quantitative calibrations of the iodine concentration and contrast-to-noise ratio (CNR) in DE-CEDM applications. Material and Methods A custom-made phantom filled with iodine concentrations in the range of 0.1-10 mg/cm² was used in calibrations. All DE images were acquired using the GE Senographe Essential system. From DE subtraction images, the image contrast and CNR were obtained, and the quantitative relationship between these two metrics and the iodine concentration at each phantom thickness was investigated. The quantitative CNR calibration curves were applied to reconstruct color-coded iodine maps on a pixel-by-pixel basis. Results Both the mean contrast and mean CNR increased linearly with the iodine concentration. The iodine concentration estimated from the iodine map reconstructed from quantitative CNR calibrations was highly consistent with the desired iodine concentration (R²= 0.989), and smaller relative errors (in the range of 3.0-19.5%) were observed with iodine concentrations not less than 1 mg/cm². Conclusion An iodine concentration map could be reconstructed based on the linear relationship between the CNR and iodine concentration. From the color-coded iodine concentration map, the contrast medium enhancement phenomenon could be further estimated quantitatively, and tumor enhancement patterns could be easily observed.

Technical Note: spektr 3.0-A computational tool for x-ray spectrum modeling and analysis

PURPOSE

A computational toolkit (spektr 3.0) has been developed to calculate x-ray spectra based on the tungsten anode spectral model using interpolating cubic splines (TASMICS) algorithm, updating previous work based on the tungsten anode spectral model using interpolating polynomials (TASMIP) spectral model. The toolkit includes a matlab (The Mathworks, Natick, MA) function library and improved user interface (UI) along with an optimization algorithm to match calculated beam quality with measurements.

METHODS

The spektr code generates x-ray spectra (photons/mm(2)/mAs at 100 cm from the source) using TASMICS as default (with TASMIP as an option) in 1 keV energy bins over beam energies 20-150 kV, extensible to 640 kV using the TASMICS spectra. An optimization tool was implemented to compute the added filtration (Al and W) that provides a best match between calculated and measured x-ray tube output (mGy/mAs or mR/mAs) for individual x-ray tubes that may differ from that assumed in TASMICS or TASMIP and to account for factors such as anode angle.

RESULTS

The median percent difference in photon counts for a TASMICS and TASMIP spectrum was 4.15% for tube potentials in the range 30-140 kV with the largest percentage difference arising in the low and high energy bins due to measurement errors in the empirically based TASMIP model and inaccurate polynomial fitting. The optimization tool reported a close agreement between measured and calculated spectra with a Pearson coefficient of 0.98.

CONCLUSIONS

The computational toolkit, spektr, has been updated to version 3.0, validated against measurements and existing models, and made available as open source code. Video tutorials for the spektr function library, UI, and optimization tool are available.

Exploring silver as a contrast agent for contrast-enhanced dual-energy X-ray breast imaging

OBJECTIVE

Through prior monoenergetic modelling, we have identified silver as a potential alternative to iodine in dual-energy (DE) X-ray breast imaging. The purpose of this study was to compare the performance of silver and iodine contrast agents in a commercially available DE imaging system through a quantitative analysis of signal difference-to-noise ratio (SDNR).

METHODS

A polyenergetic simulation algorithm was developed to model the signal intensity and noise. The model identified the influence of various technique parameters on SDNR. The model was also used to identify the optimal imaging techniques for silver and iodine, so that the two contrast materials could be objectively compared.

RESULTS

The major influences on the SDNR were the low-energy dose fraction and breast thickness. An increase in the value of either of these parameters resulted in a decrease in SDNR. The SDNR for silver was on average 43% higher than that for iodine when imaged at their respective optimal conditions, and 40% higher when both were imaged at the optimal conditions for iodine.

CONCLUSION

A silver contrast agent should provide benefit over iodine, even when translated to the clinic without modification of imaging system or protocol. If the system were slightly modified to reflect the lower k-edge of silver, the difference in SDNR between the two materials would be increased.

ADVANCES IN KNOWLEDGE

These data are the first to demonstrate the suitability of silver as a contrast material in a clinical contrast-enhanced DE image acquisition system.

Objective models of compressed breast shapes undergoing mammography

PURPOSE

To develop models of compressed breasts undergoing mammography based on objective analysis, that are capable of accurately representing breast shapes in acquired clinical images and generating new, clinically realistic shapes.

METHODS

An automated edge detection algorithm was used to catalogue the breast shapes of clinically acquired cranio-caudal (CC) and medio-lateral oblique (MLO) view mammograms from a large database of digital mammography images. Principal component analysis (PCA) was performed on these shapes to reduce the information contained within the shapes to a small number of linearly independent variables. The breast shape models, one of each view, were developed from the identified principal components, and their ability to reproduce the shape of breasts from an independent set of mammograms not used in the PCA, was assessed both visually and quantitatively by calculating the average distance error (ADE).

RESULTS

The PCA breast shape models of the CC and MLO mammographic views based on six principal components, in which 99.2% and 98.0%, respectively, of the total variance of the dataset is contained, were found to be able to reproduce breast shapes with strong fidelity (CC view mean ADE = 0.90 mm, MLO view mean ADE = 1.43 mm) and to generate new clinically realistic shapes. The PCA models based on fewer principal components were also successful, but to a lesser degree, as the two-component model exhibited a mean ADE = 2.99 mm for the CC view, and a mean ADE = 4.63 mm for the MLO view. The four-component models exhibited a mean ADE = 1.47 mm for the CC view and a mean ADE = 2.14 mm for the MLO view. Paired t-tests of the ADE values of each image between models showed that these differences were statistically significant (max p-value = 0.0247). Visual examination of modeled breast shapes confirmed these results. Histograms of the PCA parameters associated with the six principal components were fitted with Gaussian distributions. The six-component model was also used to generate CC and MLO view mammogram breast shapes, using the mean PCA parameter values of these distributions and randomly generated values based on the fitted Gaussian distributions, which resemble clinically encountered breasts. A spreadsheet with the data necessary to apply this model is provided as the supplementary material.

CONCLUSIONS

Our PCA models of breast shapes in both mammographic views successfully reproduce analyzed breast shapes and generate new clinically relevant shapes. This work can aid in research applications which incorporate breast shape modeling, such as x-ray scatter correction, dosimetry, and image registration.

Improved microcalcification visualization using dual-energy digital mammography

BACKGROUND

Dual-energy digital mammography (DEDM), involving a combination of high-energy (HE) and low-energy (LE) images, has been investigated as offering a potential improvement in microcalcification detection obscured by overlapping tissue structures.

PURPOSE

To explore the possibility to improve detection of microcalcifications using the DEDM technique.

MATERIAL AND METHODS

Three DEDM protocols were performed by adjusting the effective tube current time product (mAs) of LE image at the same (100%), one half (50%), and one-quarter (25%) of that used in HE image acquisition, named DEDM100%, DEDM50%, and DEDM25%, respectively. A single-energy digital mammography (SEDM) method was also used as a control. A total of 525 regions of interest (ROIs) were used to compare the performance of the DEDM to that of SEDM using free-response receiver-operating characteristic (FROC) and areas under the FROC curve (Az).

RESULTS

All DEDM protocols ranked significantly higher than the SEDM method (P < 0.001). The true-positive fraction was 0.90 for an average of 0.017-0.042 false-positive per image using the DEDM100%, 0.017-0.114 using the DEDM50%, 0.021-0.148 using the DEDM25%, and 0.134-0.422 using the SEDM. The estimated Az values were 0.915-0.940, 0.867-0.935, 0.824-0.930, and 0.567-0.673, respectively.

CONCLUSION

The DEDM50% protocol provided a trade-off benefit between accurate microcalcification detectability and radiation dose for any tissue density. Therefore, the DEDM50% has the potential to minimize excess radiation dose without a negative impact on image quality which could improve earlier diagnosis of breast cancer.

The simulation of 3D microcalcification clusters in 2D digital mammography and breast tomosynthesis

PURPOSE

This work proposes a new method of building 3D models of microcalcification clusters and describes the validation of their realistic appearance when simulated into 2D digital mammograms and into breast tomosynthesis images.

METHODS

A micro-CT unit was used to scan 23 breast biopsy specimens of microcalcification clusters with malignant and benign characteristics and their 3D reconstructed datasets were segmented to obtain 3D models of microcalcification clusters. These models were then adjusted for the x-ray spectrum used and for the system resolution and simulated into 2D projection images to obtain mammograms after image processing and into tomographic sequences of projection images, which were then reconstructed to form 3D tomosynthesis datasets. Six radiologists were asked to distinguish between 40 real and 40 simulated clusters of microcalcifications in two separate studies on 2D mammography and tomosynthesis datasets. Receiver operating characteristic (ROC) analysis was used to test the ability of each observer to distinguish between simulated and real microcalcification clusters. The kappa statistic was applied to assess how often the individual simulated and real microcalcification clusters had received similar scores ("agreement") on their realistic appearance in both modalities. This analysis was performed for all readers and for the real and the simulated group of microcalcification clusters separately. "Poor" agreement would reflect radiologists' confusion between simulated and real clusters, i.e., lesions not systematically evaluated in both modalities as either simulated or real, and would therefore be interpreted as a success of the present models.

RESULTS

The area under the ROC curve, averaged over the observers, was 0.55 (95% confidence interval [0.44, 0.66]) for the 2D study, and 0.46 (95% confidence interval [0.29, 0.64]) for the tomosynthesis study, indicating no statistically significant difference between real and simulated lesions (p > 0.05). Agreement between allocated lesion scores for 2D mammography and those for the tomosynthesis series was poor.

CONCLUSIONS

The realistic appearance of the 3D models of microcalcification clusters, whether malignant or benign clusters, was confirmed for 2D digital mammography images and the breast tomosynthesis datasets; this database of clusters is suitable for use in future observer performance studies related to the detectability of microcalcification clusters. Such studies include comparing 2D digital mammography to breast tomosynthesis and comparing different reconstruction algorithms.

Effectiveness of the single-shot dual-energy subtraction technique for portal images

The aim of the present study was to evaluate the clinical efficacy of the single‐shot dual‐energy subtraction technique for obtaining portal images. We prepared two storage phosphor plates for this study. A 1 mm thick tungsten sheet was placed between the two storage phosphor plates. A single use of the double‐exposure technique provides two portal images simultaneously (i.e., a standard image and a low‐contrast image), using the same patient position and with no additional radiation delivered to the patient. A bone‐enhanced image is created by image subtraction between these two images. For evaluation of clinical efficacy, three treatment sites — the brain, lung, and pelvis — were imaged. Ten sets of images were obtained for each site, and five landmarks were selected for each treatment site. The visibility of each landmark and the ease of overall verification for the selected treatment sites were assessed separately for the standard and bone‐enhanced images. Four observers consisting of one radiation oncologist and three radiation therapists participated in the present study. For most of the landmarks studied, the bone‐enhanced images were significantly superior to the standard images. Regarding the ease of overall verification, the bone‐enhanced images were significantly superior to the standard images at all sites. The p‐values of mean rating for the brain, lung, and pelvis were 0.002, 0.012, and 0.003, respectively. The bone‐enhanced images obtained using our technique increased the image quality in terms of bone visibility, and are considered useful for routine clinical practice.

PACS number: 87.56.Da

Radiation doses in cone-beam breast computed tomography: a Monte Carlo simulation study

PURPOSE

In this article, we describe a method to estimate the spatial dose variation, average dose and mean glandular dose (MGD) for a real breast using Monte Carlo simulation based on cone beam breast computed tomography (CBBCT) images. We present and discuss the dose estimation results for 19 mastectomy breast specimens, 4 homogeneous breast models, 6 ellipsoidal phantoms, and 6 cylindrical phantoms.

METHODS

To validate the Monte Carlo method for dose estimation in CBBCT, we compared the Monte Carlo dose estimates with the thermoluminescent dosimeter measurements at various radial positions in two polycarbonate cylinders (11- and 15-cm in diameter). Cone-beam computed tomography (CBCT) images of 19 mastectomy breast specimens, obtained with a bench-top experimental scanner, were segmented and used to construct 19 structured breast models. Monte Carlo simulation of CBBCT with these models was performed and used to estimate the point doses, average doses, and mean glandular doses for unit open air exposure at the iso-center. Mass based glandularity values were computed and used to investigate their effects on the average doses as well as the mean glandular doses. Average doses for 4 homogeneous breast models were estimated and compared to those of the corresponding structured breast models to investigate the effect of tissue structures. Average doses for ellipsoidal and cylindrical digital phantoms of identical diameter and height were also estimated for various glandularity values and compared with those for the structured breast models.

RESULTS

The absorbed dose maps for structured breast models show that doses in the glandular tissue were higher than those in the nearby adipose tissue. Estimated average doses for the homogeneous breast models were almost identical to those for the structured breast models (p=1). Normalized average doses estimated for the ellipsoidal phantoms were similar to those for the structured breast models (root mean square (rms) percentage difference = 1.7%; p = 0.01), whereas those for the cylindrical phantoms were significantly lower (rms percentage difference = 7.7%; p < 0.01). Normalized MGDs were found to decrease with increasing glandularity.

CONCLUSIONS

Our results indicate that it is sufficient to use homogeneous breast models derived from CBCT generated structured breast models to estimate the average dose. This investigation also shows that ellipsoidal digital phantoms of similar dimensions (diameter and height) and glandularity to actual breasts may be used to represent a real breast to estimate the average breast dose with Monte Carlo simulation. We have also successfully demonstrated the use of structured breast models to estimate the true MGDs and shown that the normalized MGDs decreased with the glandularity as previously reported by other researchers for CBBCT or mammography.

Evaluation of an improved algorithm for producing realistic 3D breast software phantoms: application for mammography

PURPOSE

This work presents an improved algorithm for the generation of 3D breast software phantoms and its evaluation for mammography.

METHODS

The improved methodology has evolved from a previously presented 3D noncompressed breast modeling method used for the creation of breast models of different size, shape, and composition. The breast phantom is composed of breast surface, duct system and terminal ductal lobular units, Cooper's ligaments, lymphatic and blood vessel systems, pectoral muscle, skin, 3D mammographic background texture, and breast abnormalities. The key improvement is the development of a new algorithm for 3D mammographic texture generation. Simulated images of the enhanced 3D breast model without lesions were produced by simulating mammographic image acquisition and were evaluated subjectively and quantitatively. For evaluation purposes, a database with regions of interest taken from simulated and real mammograms was created. Four experienced radiologists participated in a visual subjective evaluation trial, as they judged the quality of the simulated mammograms, using the new algorithm compared to mammograms, obtained with the old modeling approach. In addition, extensive quantitative evaluation included power spectral analysis and calculation of fractal dimension, skewness, and kurtosis of simulated and real mammograms from the database.

RESULTS

The results from the subjective evaluation strongly suggest that the new methodology for mammographic breast texture creates improved breast models compared to the old approach. Calculated parameters on simulated images such as beta exponent deducted from the power law spectral analysis and fractal dimension are similar to those calculated on real mammograms. The results for the kurtosis and skewness are also in good coincidence with those calculated from clinical images. Comparison with similar calculations published in the literature showed good agreement in the majority of cases.

CONCLUSIONS

The improved methodology generated breast models with increased realism compared to the older model as shown in evaluations of simulated images by experienced radiologists. It is anticipated that the realism will be further improved using an advanced image simulator so that simulated images may be used in feasibility studies in mammography.

Radiation dose reduction using a CdZnTe-based computed tomography system: comparison to flat-panel detectors

PURPOSE

Although x-ray projection mammography has been very effective in early detection of breast cancer, its utility is reduced in the detection of small lesions that are occult or in dense breasts. One drawback is that the inherent superposition of parenchymal structures makes visualization of small lesions difficult. Breast computed tomography using flat-panel detectors has been developed to address this limitation by producing three-dimensional data while at the same time providing more comfort to the patients by eliminating breast compression. Flat panels are charge integrating detectors and therefore lack energy resolution capability. Recent advances in solid state semiconductor x-ray detector materials and associated electronics allow the investigation of x-ray imaging systems that use a photon counting and energy discriminating detector, which is the subject of this article.

METHODS

A small field-of-view computed tomography (CT) system that uses CdZnTe (CZT) photon counting detector was compared to one that uses a flat-panel detector for different imaging tasks in breast imaging. The benefits afforded by the CZT detector in the energy weighting modes were investigated. Two types of energy weighting methods were studied: Projection based and image based. Simulation and phantom studies were performed with a 2.5 cm polymethyl methacrylate (PMMA) cylinder filled with iodine and calcium contrast objects. Simulation was also performed on a 10 cm breast specimen.

RESULTS

The contrast-to-noise ratio improvements as compared to flat-panel detectors were 1.30 and 1.28 (projection based) and 1.35 and 1.25 (image based) for iodine over PMMA and hydroxylapatite over PMMA, respectively. Corresponding simulation values were 1.81 and 1.48 (projection based) and 1.85 and 1.48 (image based). Dose reductions using the CZT detector were 52.05% and 49.45% for iodine and hydroxyapatite imaging, respectively. Image-based weighting was also found to have the least beam hardening effect.

CONCLUSIONS

The results showed that a CT system using an energy resolving detector reduces the dose to the patient while maintaining image quality for various breast imaging tasks.

Quantification of breast density with dual energy mammography: an experimental feasibility study

PURPOSE

Breast density, the percentage of glandular breast tissue, has been shown to be a strong indicator of breast cancer risk. A quantitative method to measure breast density with dual energy mammography was investigated using physical phantoms.

METHODS

The dual energy mammography system used a tungsten anode x-ray tube with a 50 microm rhodium beam filter for low energy images and a 300 microm copper beam filter for high energy images. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Four different phantom studies were used to evaluate the technique. The first study consisted of phantoms with thicknesses of 2.5-8.5 cm in 0.5 cm steps with variable densities centered at a mean of 28%. The second study consisted of phantoms at a fixed thickness of 4.0 cm, which ranged in densities from 0% to 100% in increments of 12.5%. The third study consisted of 4.0 cm thick phantoms at densities of 25%, 50% and 75% each imaged at three areal sizes, approximately 62.5, 125, and 250 cm2, in order to assess the effect of breast size on density measurement. The fourth study consisted of step phantoms designed to more closely mimic the shape of a female breast with maximal thicknesses from 3.0 to 7.0 cm at a fixed density of 50%. All images were corrected for x-ray scatter.

RESULTS

The RMS errors in breast density measurements were 0.44% for the variable thickness phantoms, 0.64% for the variable density phantoms, 2.87% for the phantoms of different areal sizes, and 4.63% for step phantoms designed to closely resemble the shape of a breast.

CONCLUSIONS

The results of the phantom studies indicate that dual energy mammography can be used to measure breast density with an RMS error of approximately 5%.

Introducing DeBRa: a detailed breast model for radiological studies

Currently, x-ray mammography is the method of choice in breast cancer screening programmes. As the mammography technology moves from 2D imaging modalities to 3D, conventional computational phantoms do not have sufficient detail to support the studies of these advanced imaging systems. Studies of these 3D imaging systems call for a realistic and sophisticated computational model of the breast. DeBRa (Detailed Breast model for Radiological studies) is the most advanced, detailed, 3D computational model of the breast developed recently for breast imaging studies. A DeBRa phantom can be constructed to model a compressed breast, as in film/screen, digital mammography and digital breast tomosynthesis studies, or a non-compressed breast as in positron emission mammography and breast CT studies. Both the cranial-caudal and mediolateral oblique views can be modelled. The anatomical details inside the phantom include the lactiferous duct system, the Cooper ligaments and the pectoral muscle. The fibroglandular tissues are also modelled realistically. In addition, abnormalities such as microcalcifications, irregular tumours and spiculated tumours are inserted into the phantom. Existing sophisticated breast models require specialized simulation codes. Unlike its predecessors, DeBRa has elemental compositions and densities incorporated into its voxels including those of the explicitly modelled anatomical structures and the noise-like fibroglandular tissues. The voxel dimensions are specified as needed by any study and the microcalcifications are embedded into the voxels so that the microcalcification sizes are not limited by the voxel dimensions. Therefore, DeBRa works with general-purpose Monte Carlo codes. Furthermore, general-purpose Monte Carlo codes allow different types of imaging modalities and detector characteristics to be simulated with ease. DeBRa is a versatile and multipurpose model specifically designed for both x-ray and gamma-ray imaging studies.

Quantification of breast density with dual energy mammography: a simulation study

Breast density, the percentage of glandular breast tissue, has been identified as an important yet underutilized risk factor in the development of breast cancer. A quantitative method to measure breast density with dual energy imaging was investigated using a computer simulation model. Two configurations to measure breast density were evaluated: the usage of monoenergetic beams and an ideal detector, and the usage of polyenergetic beams with spectra from a tungsten anode x-ray tube with a detector modeled after a digital mammography system. The simulation model calculated the mean glandular dose necessary to quantify the variability of breast density to within 1/3%. The breast was modeled as a semicircle 10 cm in radius with equal homogenous thicknesses of adipose and glandular tissues. Breast thicknesses were considered in the range of 2-10 cm and energies in the range of 10-150 keV for the two monoenergetic beams, and 20-150 kVp for spectra with a tungsten anode x-ray tube. For a 4.2 cm breast thickness, the required mean glandular doses were 0.183 microGy for two monoenergetic beams at 19 and 71 keV, and 9.85 microGy for two polyenergetic spectra from a tungsten anode at 32 and 96 kVp with beam filtrations of 50 microm Rh and 300 microm Cu for the low and high energy beams, respectively. The results suggest that for either configuration, breast density can be precisely measured with dual energy imaging requiring only a small amount of additional dose to the breast. The possibility of using a standard screening mammogram as the low energy image is also discussed.

The impact of calibration phantom errors on dual-energy digital mammography

Microcalcification is one of the earliest and main indicators of breast cancer. Because dual-energy digital mammography could suppress the contrast between the adipose and glandular tissues of the breast, it is considered a promising technique that will improve the detection of microcalcification. In dual-energy digital mammography, the imaged object is a human breast, while in calibration measurements only the phantoms of breast tissue equivalent materials are available. Consequently, the differences between phantoms and breast tissues will lead to calibration phantom errors. Based on the dual-energy imaging model, formulae of calibration phantom errors are derived in this paper. Then, this type of error is quantitatively analyzed using publicly available data and compared with other types of error. The results demonstrate that the calibration phantom error is large and dominant in dual-energy mammography, seriously decreasing calculation precision. Further investigations on the physical meaning of calibration phantom error reveal that the imaged objects with the same glandular ratio have identical calibration phantom error. Finally, an error correction method is proposed based on our findings.

Empirical electro-optical and x-ray performance evaluation of CMOS active pixels sensor for low dose, high resolution x-ray medical imaging

Monolithic complementary metal oxide semiconductor (CMOS) active pixel sensors with high performance have gained attention in the last few years in many scientific and space applications. In order to evaluate the increasing capabilities of this technology, in particular where low dose high resolution x-ray medical imaging is required, critical electro-optical and physical x-ray performance evaluation was determined. The electro-optical performance includes read noise, full well capacity, interacting quantum efficiency, and pixels cross talk. The x-ray performance, including x-ray sensitivity, modulation transfer function, noise power spectrum, and detection quantum efficiency, has been evaluated in the mammographic energy range. The sensor is a 525 x 525 standard three transistor CMOS active pixel sensor array with more than 75% fill factor and 25 x 25 microm pixel pitch. Reading at 10 f/s, it is found that the sensor has 114 electrons total additive noise, 10(5) electrons full well capacity with shot noise limited operation, and 34% interacting quantum efficiency at 530 nm. Two different structured CsI:Tl phosphors with thickness 95 and 115 microm, respectively, have been optically coupled via a fiber optic plate to the array resulting in two different system configurations. The sensitivity of the two different system configurations was 43 and 47 electrons per x-ray incident on the sensor. The MTF at 10% of the two different system configurations was 9.5 and 9 cycles/mm with detective quantum efficiency of 0.45 and 0.48, respectively, close to zero frequency at approximately 0.44 microC/kg (1.72 mR) detector entrance exposure. The detector was quantum limited at low spatial frequencies and its performance was comparable with high resolution a: Si and charge coupled device based x-ray imagers. The detector also demonstrates almost an order of magnitude lower noise than active matrix flat panel imagers. The results suggest that CMOS active pixel sensors when coupled to structured CsI:Tl can be used for conventional and advanced digital mammography due to their low noise, high resolution performance.

Digital mouse phantom for optical imaging

We present a method for design and use of a digital mouse phantom for small animal optical imaging. We map the boundary of a mouse model from magnetic resonance imaging (MRI) data through image processing algorithms and discretize the geometry by a finite element (FE) descriptor. We use a validated FE implementation of the three-dimensional (3-D) diffusion equation to model transport of near infrared (NIR) light in the phantom with a mesh resolution optimized for representative tissue optical properties on a computing system with 8-GB RAM. Our simulations demonstrate that a section of the mouse near the light source is adequate for optical system design and that the variation of intensity of light on the boundary is well within typical noise levels for up to 20% variation in optical properties and nodes used to model the boundary of the phantom. We illustrate the use of the phantom in setting goals for specific binding of targeted exogenous fluorescent contrasts based on anatomical location by simulating a nearly tenfold change in the detectability of a 2-mm-deep target depending on its placement. The methodology described is sufficiently general and may be extended to generate digital phantoms for designing clinical optical imaging systems.

A novel simulation algorithm for soft tissue compression

This paper presents a novel general approach to simulation of soft tissue compression. A theoretical framework of the compression algorithm has been developed and implemented, based on the concept of a simple spring. The volume subjected to compression is divided into a number of "model elements", each one consisting of 27 nodes. The nodes are connected with springs. The mechanical properties of the tissues are assumed to be linear and isotropic. The compressed volume remains constant due to the introduced concept of spring variable equilibrium lengths. Initial settings for compression simulation are introduced in order that the algorithm converges faster. The developed compression algorithm was used to model breast compression during a standard mammography examination. Specifically, the method was applied to a high-resolution three-dimensional software breast phantom, composed to have a medium glandularity and calcification abnormalities. The compression was set to 50%. Results showed that the abnormalities maintain their shape and dimensions during the compression, while the surrounding breast tissues undergo considerable deformation and displacement. A "decompression" algorithm was also applied to test the reversibility of the model.