Cone Beam CT Breast Imaging Research Articles

Nomogram for preoperative differentiation of benign and malignant breast tumors using contrast-enhanced cone-beam breast CT (CE CB-BCT) quantitative imaging and assessment features.

Breast cancer's impact necessitates refined diagnostic approaches. This study develops a nomogram using radiology quantitative features from contrast-enhanced cone-beam breast CT for accurate preoperative classification of benign and malignant breast tumors. A retrospective study enrolled 234 females with breast tumors, split into training and test sets. Contrast-enhanced cone-beam breast CT-images were acquired using Koning Breast CT-1000. Quantitative assessment features were extracted via 3D-slicer software, identifying independent predictors. The nomogram was constructed to preoperative differentiation benign and malignant breast tumors. Calibration curve was used to assess whether the model showed favorable correspondence with pathological confirmation. Decision curve analysis confirmed the model's superiority. The study enrolled 234 female patients with a mean age of 50.2years (SD ± 9.2). The training set had 164 patients (89 benign, 75 malignant), and the test set had 70 patients (29 benign, 41 malignant). The nomogram achieved excellent predictive performance in distinguishing benign and malignant breast lesions with an AUC of 0.940 (95% CI 0.900-0.940) in the training set and 0.970 (95% CI 0.940-0.970) in the test set. This study illustrates the effectiveness of quantitative radiology features derived from contrast-enhanced cone-beam breast CT in distinguishing between benign and malignant breast tumors. Incorporating these features into a nomogram-based diagnostic model allows for breast tumor diagnoses that are objective and possess good accuracy. The application of these insights could substantially increase reliability and efficacy in the management of breast tumors, offering enhanced diagnostic capability.

Improving breast tumor segmentation via shape-wise prior-guided information on cone-beam breast CT images

Objective. Due to the blurry edges and uneven shape of breast tumors, breast tumor segmentation can be a challenging task. Recently, deep convolution networks based approaches achieve satisfying segmentation results. However, the learned shape information of breast tumors might be lost owing to the successive convolution and down-sampling operations, resulting in limited performance. Approach. To this end, we propose a novel shape-guided segmentation (SGS) framework that guides the segmentation networks to be shape-sensitive to breast tumors by prior shape information. Different from usual segmentation networks, we guide the networks to model shape-shared representation with the assumption that shape information of breast tumors can be shared among samples. Specifically, on the one hand, we propose a shape guiding block (SGB) to provide shape guidance through a superpixel pooling-unpooling operation and attention mechanism. On the other hand, we further introduce a shared classification layer (SCL) to avoid feature inconsistency and additional computational costs. As a result, the proposed SGB and SCL can be effortlessly incorporated into mainstream segmentation networks (e.g. UNet) to compose the SGS, facilitating compact shape-friendly representation learning. Main results. Experiments conducted on a private dataset and a public dataset demonstrate the effectiveness of the SGS compared to other advanced methods. Significance. We propose a united framework to encourage existing segmentation networks to improve breast tumor segmentation by prior shape information. The source code will be made available at https://github.com/TxLin7/Shape-Seg.

Cone-beam breast CT-guided surface location facilitates breast-conserving surgery in breast cancer patients with extensive calcifications: A pilot study.

Extensive malignant-appearing calcifications have traditionally been considered a contraindication for breast-conserving surgery. The evaluation of calcifications largely depends on mammography, which is limited by tissue superimposition and is unable to reveal spatial information about extensive calcifications. Three-dimensional imaging modality is needed to reveal the architecture of extensive calcifications. In the present study, a novel cone-beam breast CT-guided surface location technique was investigated to facilitate breast-conserving surgery in breast cancer patients with extensive malignant breast calcifications. Biopsy-proved early breast cancer patients with extensive malignant-appearing breast calcifications were included. A patient will be considered suitable for breast-conserving surgery if the spatial segmental distribution of calcifications is found by 3D images of cone-beam breast CT. Then, the margins of the calcifications were located in contrast-enhanced cone-beam breast CT images. Next, skin markers were located using radiopaque materials, and cone-beam breast CT was reperformed to confirm the accuracy of surface location. During breast-conserving surgery, lumpectomy was performed according to the previous surface location, and an intraoperative specimen x-ray was applied to double-check that the entire lesion was removed. Margin assessment was made for both intraoperative frozen section and postoperative pathology examination. From May 2019 to Jun 2022, 11 eligible breast cancer patients in our institution were included. Breast-conserving surgery was performed successfully in all patients using the surface location approach mentioned before. All patients achieved negative margins and satisfied cosmetic results. This study proved the feasibility of cone-beam breast CT-guided surface location for facilitating breast-conserving surgery in breast cancer patients with extensive malignant breast calcifications.

X-ray scatter correction for dedicated cone beam breast CT using a forward-projection model.

The quality of dedicated cone-beam breast CT (CBBCT) imaging is fundamentally limited by x-ray scatter contamination due to the large irradiation volume. In this paper, we propose a scatter correction method for CBBCT using a novel forward-projection model with high correction efficacy and reliability. We first coarsely segment the uncorrected, first-pass, reconstructed CBBCT images into binary-object maps and assign the segmented fibroglandular and adipose tissue with the correct attenuation coefficients based on the mean x-ray energy. The modified CBBCT are treated as the prior images toward scatter correction. Primary signals are first estimated via forward projection on the modified CBBCT. To avoid errors caused by inaccurate segmentation, only sparse samples of estimated primary are selected for scatter estimation. A Fourier-Transform based algorithm, herein referred to as local filtration hereafter, is developed to efficiently estimate the global scatter distribution on the detector. The scatter-corrected images are obtained by removing the estimated scatter distribution from measured projection data. We evaluate the method performance on six patients with different breast sizes and shapes representing the general population. The results show that the proposed method effectively reduces the image spatial non-uniformity from 8.27 to 1.91% for coronal views and from 6.50 to 3.00% for sagittal views. The contrast-to-deviation ratio is improved by an average factor of 1.41. Comparisons on the image details reveal that the proposed scatter correction successfully preserves fine structures of fibroglandular tissues that are lost in the segmentation process. We propose a highly practical and efficient scatter correction algorithm for CBBCT via a forward-projection model. The method is attractive in clinical CBBCT imaging as it is readily implementable on a clinical system without modifications in current imaging protocols or system hardware.

Areas of breast tissue covered in cone beam breast CT imaging.

The value of cone beam breast computed tomography (CBBCT) imaging on covered areas of breast tissue, which is the relation between imaging quality and CT dose were studied. Multi-energy spectrum was used to radiate same-size built-in calcifications and lump breast motifs under the condition of the same number of particles by utilizing the Monte Carlo-based GATE simulation software; breast motif images were restructured by using FBP restructuration algorithm to gain the distribution of radiation dose in the breast motif; radiation dose was calculated and signal-to-noise ratio (SNR) to define how quality factor M and dose efficiency η reflect the relations between radiation dose and imaging quality. Based on the comparison of the calcification number, diameter, and the diameter of tumor among head side, foot side, inner side, outer side and rear side, the difference was meaningless in terms of statistics. Based on the comparison between SNR and contrast-to-noise ratio and between dose efficiency η and quality factor M in different areas, the difference was not statistically significant. In conclusion, the imaging quality of CBBCT was good in the head, foot, inner, outer and rear sides of breast, with acceptable CT dose.

TU-E-217BCD-08: Extraction and Insertion of Tumor Masses in Cone Beam Breast CT Images.

To develop and validate algorithms for extraction and insertion of three-dimensional (3D) profiles of tumor masses in cone beam breast CT (CBBCT) images to create simulated abnormality for evaluation with observer performance study. A bench-top experimental CBBCT scanner was constructed and used to image mastectomy breast specimens with IRB approval. 5 sets of CBBCT images with confirmed tumor masses and 2 sets of normal CBBCT images were selected and used for this study. All CBBCT images were first corrected for cupping artifacts. The corrected images were then processed to reduce their noise levels and form the denoised images. The corrected and denoised CBBCT images for normal breasts were then segmented into adipose and glandular voxels. The images for abnormal breasts were reviewed by mammographers with the help of clinical images and reports to delineate the tumor masses and form 3D tumor maps. Using these maps, the 3D tumor profiles were rescaled to average glandular signals around the insertion locations in normal images. The boundaries of the 3D rescaled tumor profiles were smoothed to avoid sharp edge. The resultant 3D tumor profiles were inserted onto cupping artifact corrected normal CBBCT images by replacing the signals in adipose voxels near the insertion locations. The cupping artifacts were then added back to generate the simulated abnormal CBBCT images. These images were then visually compared with actual abnormal images for their degree of realism. Based on visual comparison, the simulated abnormal CBBCT images showed no significant difference in realism from actual abnormal CBBCT images. We have successfully demonstrated the technique to extract 3D tumor profiles from abnormal CBBCT images and insert them onto normal CBBCT images to form simulated abnormal images for use in observer performance study. This work was supported in part by grants CA104759, CA13852 and CA124585 from the NIH-NCI, a research grant EB00117 from the NIH-NIBIB, and a subcontract from NIST-ATP.

Enhancement of breast calcification visualization and detection using a modified PG method in Cone Beam Breast CT

Cone Beam Breast CT is a promising diagnostic modality in breast imaging. Its isotropic 3D spatial resolution enhances the characterization of micro-calcifications in breasts that might not be easily distinguishable in mammography. However, due to dose level considerations, it is beneficial to further enhance the visualization of calcifications in Cone Beam Breast CT images that might be masked by noise. In this work, the Papoulis-Gerchberg method was modified and implemented in Cone Beam Breast CT images to improve the visualization and detectability of calcifications. First, the PG method was modified and applied to the projections acquired during the scanning process; its effects on the reconstructed images were analyzed by measuring the Modulation Transfer Function and the Noise Power Spectrum. Second, Cone Beam Breast CT images acquired at different dose levels were pre-processed using this technique to enhance the visualization of calcification. Finally, a computer-aided diagnostic algorithm was utilized to evaluate the efficacy of this method to improve calcification detectability. The results demonstrated that this technique can effectively improve image quality by improving the Modulation Transfer Function with a minor increase in noise level. Consequently, the visualization and detectability of calcifications were improved in Cone Beam Breast CT images. This technique was also proved to be useful in reducing the x-ray dose without degrading visualization and detectability of calcifications.

TU-A-301-06: Image Quality, Dose Saving and Scatter Reduction in Dual-Resolution Cone Beam CT Breast Imaging Using Two Different VOI Scanning Techniques

Purpose: To estimate the image quality, dose saving and scatter reduction in the dual‐resolution cone beam CT(CBCT) breast imaging using two different VOI scanning techniques. Methods: There are two different VOI scanning techniques in dual‐resolution CBCT breast imaging: (1) breast‐ centered with a moving VOI mask technique and (2) the VOI‐centered with a stationary VOI mask technique. In either case, the breast is first scanned with a low resolution detector at a lower exposure level. The VOI in the breast is then scanned with a high resolution detector at a higher exposure level through the VOI mask. The two image sets are combined together to reconstruct high resolution CTimages. A bench‐top experimental CBCTsystem with a flat panel detector and a high resolution CMOSdetector was built. A paraffin cylinder with a diameter of 130 mm was used to simulate breast. A wire phantom, a 15 mm diameter paraffin cylinder with 8 vertically oriented aluminum wires of various diameters, was used to test the image quality. The wire phantom was inserted into the breast phantom 45 mm away from the center and designated as the VOI. The spatial resolution in the reconstructed images, phantom dose and scatter‐to‐primary ratio were measured for both scanning techniques. Results: For both techniques, a visual review of the reconstructed images showed that the diameter of thinnest resolvable wire is 254 μm for regular CBCT and 152 μm for dual resolution CBCT. The doses for dual‐resolution CBCT can be reduced by a factor of 2 inside of the VOI and up to a factor of 6 outside the VOI. The scatter components can be reduced by a factor of 6 inside the VOI. Conclusions: Both scanning techniques were found to result in improved image quality, substantially reduced dose and scatter in dual‐resolution CBCT. This work was supported in part by grants CA104759, CA13852 and CA124585 from NIH‐NCI, a grant EB00117 from NIH‐NIBIB, and a subcontract from NIST‐ATP.

TU-A-301-01: Microcalcifications Visibility in Cone Beam Breast CT with Various Flat Panel Detectors

Purpose: To investigate the visibility of microcalcifications (MCs) in cone beam breast CT using various flat panel detectors. Methods: We investigated the visibility of MCs in cone beam CT(CBCT) breast imaging using various flat panel detectors, including PaxScan 4030CB (aSi/CsI) by Varian MedicalSystems, FPD14 (aSi/aSe) by Anrad, C4742 (CCD/GdO2S:Tb) and C7921 (CMOS/CsI) detectors by Hamamatsu. A paraffin cylinder with a diameter of 135 mm and a thickness of 40 mm was used to simulate a 100% adipose breast. Calcium carbonate grains, from 125 – 140 μm to 224 – 250 μm in various size groups, were used to simulate the MCs. Groups of 25 same size MCs were arranged into 5 × 5 clusters. Each cluster was embedded at the center of a 15 mm diameter cylindrical paraffin phantom, which as inserted into a hole at the center of the breast phantom. The breast phantom with the simulated MCs was scanned on a bench top CBCTsystem at various exposure levels for each detector. The reconstructed images were reviewed by 6 readers independently. The MCvisibility was quantified as the fraction of visible MCs and averaged over all readers for analysis. The visibility was plotted as a function of the estimated dose level and image signal‐to‐noise ratio (SNR) for various scans and detectors. The relative detector DQEs were compared among the four detectors. Results: It was found the relationship between the visibility and size can be fitted with a Boltzmann function for all the detectors. The Varian detector has the best MCvisibility among all the detectors at the same dose level. Conclusions: The visibility of MCs increased with the isocenter dose and image SNR for all detectors.Detector with better DQE could achieve the same MCvisibility with lower radiation dose. This work was supported in part by grants CA104759, CA13852 and CA1245 85 from NIH‐NCI, a grant EB00117 from NIH‐NIBIB, and a subcontract from NIST‐ATP.

TH-E-110-10: Doses in Volume-Of-Interest Cone-Beam Computed Tomography (CBCT)- a Monte Carlo Simulation Study

Purpose: Volume‐of‐interest (VOI) cone‐beam CT(CBCT) is a technique to image a pre‐selected VOI with enhanced image quality while maintaining an acceptable average breast dose. This technique requires a high exposure VOI scan with a low exposure full‐field scan. In this study, Monte Carlo(MC) simulation was used to estimate the doses of the full‐field scan, VOI scan and various combinations of the two for breast imaging. Methods: For MC simulation, BEAMnrc and DOSXYZnrc were used to simulate CBCT breast imaging and estimate the average doses. For validation, air kermas at the VOI and iso‐center were measured and simulated for comparison. For simulation study, a 13‐cm‐diam, 9‐cm‐high Lucite cylinder was scanned by an x‐ray source located at 88 cm away. The VOI was defined to be a 2.5‐ cm‐diam, 2.5‐cm‐high cylindrical volume located at various radial positions in the middle plane of the phantom. Two scanning techniques were simulated: (1) the breast centered scan, (2) the VOI centered scan. The former requires a moving collimator to be used during the VOI scan while the latter requires only a stationary collimator to be used. 400 million incident photons were used to simulate 300 projections over 360 degrees to achieve 3D dose maps. Results: It was found that the average VOI doses decreased by 37% in the VOI scans as compared to those in the full‐field scans. The additional dose incurred by a VOI scan (VOI centered) was 6% of the dose from a full‐field scan for the same x‐ray techniques used. Conclusions: Our results indicated that it is feasible to employ a high exposure VOI scan in conjunction with a low exposure full‐field scan to enhance the image quality within the VOI while maintaining the overall average dose to be equal to or even lower than that of a regular full‐field scan. This work was supported in part by grants CA104759, CA124585 and CA13852 from NIH‐NCI, a grant EB00117 from NIH‐NIBIB, and a subcontract from NIST‐ATP.

Scatter correction for clinical cone beam CT breast imaging based on breast phantom studies

In flat-panel detector-based cone beam CT breast imaging (CBCTBI) systems, scattering is an important factor that degrades image quality. It is not practical to measure the scattering profiles of a breast for all view angles in a patient study, but it is possible to develop a method to estimate the scattering profiles based on information acquired from breast phantom studies. A new scattering correction method is proposed for clinical CBCTBI in this study. The scattering profiles of three anthropomorphic uncompressed breast phantoms of different sizes were thoroughly investigated, and the results indicated that though phantom size differed, the scattering profiles were mainly determined by local breast diameters, which are the approximate diameters of coronal slices that are perpendicular to the nipple-to-chestwall direction. Thus for scattering correction purposes it is possible to establish a relationship between location breast diameters and local scattering profiles, namely the fitted smooth curves of scatter-to-primary ratios (SPR) and normalized scattered radiations (NSR). In clinical CBCTBI studies, after the local breast diameters are sampled and measured on projection images, the scattering image for every projection image can be generated based on the established relationship, and the projection images can be corrected using either the SPR based method or the NSR based method. Phantom studies and clinical studies showed that both the SPR and NSR methods are able to correct cupping artifacts and reduce reconstruction error. The SPR method does not increase tissue contrast or noise while the NSR method increases both.

Cone-Beam CT for Breast Imaging: Radiation Dose, Breast Coverage, and Image Quality

The primary objectives of this pilot study were to evaluate the radiation dose, breast coverage, and image quality of cone-beam breast CT compared with a conventional mammographic examination. Image quality analysis was focused on the concordance of cone-beam breast CT with conventional mammography in terms of mammographic findings. This prospective study was performed from July 2006 through August 2008. Twenty-three women were enrolled who met the inclusion criteria, which were age 40 years or older with final BI-RADS assessment category 1 or 2 lesions on conventional mammograms within the previous 6 months. The breasts were imaged with a flat-panel detector-based cone-beam CT system, and the images were reviewed with a 3D visualization system. Cone-beam breast CT image data sets and the corresponding mammograms were reviewed by three qualified mammographers. The parameters assessed and compared in this pilot study were radiation dose, breast tissue coverage, and image quality, including detectability of masses and calcifications. The mammograms and cone-beam breast CT images were independently reviewed side by side, and the reviewers were not blinded to the other technique. The observed agreement and Cohen's kappa were used to evaluate agreement between the mammographic and cone-beam breast CT findings and interobserver agreement. Each subject responded to a questionnaire on multiple parameters, including comfort of the cone-beam breast CT examination compared with mammography. For a conventional mammographic examination, the average glandular radiation dose ranged from 2.2 to 15 mGy (mean, 6.5 [SD, 2.9] mGy). For cone-beam breast CT, the average glandular dose ranged from 4 to 12.8 mGy (mean, 8.2 [SD, 1.4] mGy). The average glandular dose from cone-beam breast CT was generally within the range of that from conventional mammography. For heterogeneously dense and extremely dense breasts, the difference between the mean dose of conventional mammography and that of cone-beam breast CT was not statistically significant (7.0 vs 8.1 mGy, p = 0.06). Breast tissue coverage was statistically significantly better with cone-beam breast CT than with mammography in the lateral (p < 0.0001), medial (p < 0.0001), and posterior (p = 0.0002) aspects. Mammography had statistically significantly better coverage than cone-beam breast CT in the axilla and axillary tail (p < 0.0001). Overall, most calcifications and all masses detected with mammography were also detected with cone-beam breast CT. The interobserver agreement on cone-beam breast CT was 83.7% in the detectability of imaging findings. The overall interobserver agreement on type of findings, size of findings (<1, 1-4.99, and > or = 5 mm), and location of findings was 77.2%, 84.8%, and 78.3%, respectively. The results of this study show that cone-beam breast CT can be used to image the entire breast from chest wall to nipple with sufficient spatial and contrast resolution for detection of masses and calcifications at a radiation dose within the range of that of conventional mammography.

SU‐FF‐I‐26: Automatic Detection of Calcifications in Cone Beam Breast CT Images

Purpose: Microcalcifications (MCs) play an important role in early detection of breast cancer. This study is to describe a technique to automatically identify and segment the calcifications from the breast anatomy in cone beam CT (CBCT) images. Method and Materials: Projection images of mastectomy breast specimens were acquired with a bench‐top experimental CBCT system and reconstructed using FDK algorithm with a regular ramp filter. The reconstructed images were first corrected for the non‐uniform cupping artifacts due to x‐ray scatter and beam hardening. The corrected CBCT images had more uniform background but were still too noisy for threshold segmentation. To reduce the noise level, the images were processed with a noise averaging filter in z direction followed by a total variation filter to reduce the noise level while keeping the edge sharpness and contrast of calcifications. To automatically detect the calcifications with proper threshold level, a Gaussian curve fitting was used to fit the histogram of the CBCT image. Since the CT numbers of calcifications are usually significantly above those for breast tissue, cutoff point of the Gaussian curve was used as the threshold value to segment the calcifications. Results: With this method, the calcifications in the entire breast were successfully segmented from the breast tissue background. The results agreed well with those identified by visualization. Conclusion: The calcifications in CBCT breast images can be automatically detected by threshold based segmentation method with the nonuniform cupping artifacts corrected for and the noise level properly reduced.

SU‐FF‐I‐21: Dose Variation with Breast Density in Cone Beam Breast CT‐ a Monte Carlo Simulation Study

Purpose: By using Monte Carlo (MC) dose calculation to investigate the variation of radiation dose with the breast density (tissue composition) in cone beam breast CT, both globally and on a voxel‐by‐voxel basis. Method and Materials: To simulate cone beam breast CT imaging, we first used Rep78 to build an x‐ray spectrum for an x‐ray tube with tungsten target and a HVL of 4.08mm Al. A collimator was defined in BEAMnrc and used to form a half‐cone beam for pendant geometry used in cone beam breast CT. For validation, we compared MC dose calculations with ionization chamber measurements at 4 different locations inside the 11 cm diameter, 12 cm high cylindrical phantom under the same imaging conditions. After normalizing for the iso‐center dose, the deviations were within 3.7%. 3 cone beam CT images were first corrected and filtered to minimize the cupping artifacts and then filtered to reduce the noise level. The processed images were then segmented using threshold method to separate the dense tissue from the adipose tissue. The segmented image sets were binned into a 100×100×80 image sets with a pixel size of 1mm for MC calculation. DOSXYZnrc was used to track 1×109 incident photons distributed over 300 projection images over 360°. The resulting radiation dose was tallied for each voxel and averaged over all voxels in the breast. Results: Results from MC calculations indicated that radiation dose was significantly higher in dense tissue structures and lower in the adipose tissue. The regions of higher dose were found to match the 3D dense tissue structures. The average breast dose was found to linearly vary with the breast density computed from the breast CT data. Conclusion: Our MC study has shown a close relationship between the radiation dose and the breast density both globally and on a voxel‐by‐voxel basis.

NPS characterization and evaluation of a cone beam CT breast imaging system

The Noise Power Spectrum (NPS) is a function that yields information about the spatial frequency composition of noise in images obtained by a system. It is evaluated by calculating the absolute value squared of the noise image and normalizing it with respect to the voxel and matrix sizes. Consequently, the NPS has been one of the physical characteristics that is commonly used to quantitatively measure the physical performance of a system. In this article, we evaluated the NPS of a Cone Beam CT Breast Imaging system by considering the following factors. First, we evaluated its symmetry around the x- and y-axis along with the influence of the cone angle and the matrix size on the NPS. Then, an analytical curve was suggested to best represent the NPS. Second, we analyzed the influence on the NPS of a set of seven parameters, namely the pixel size, exposure level, kVp value, number of projections acquired, voxel size, back projection filter, and the reconstruction algorithm employed. In addition, since the breast induced scattering in the image, we investigated the effect of the scattering-correction algorithm used in this system. Finally, we evaluated the uniformity of the NPS as a function of z with the matrix center located at {r = 0 mm}. The results demonstrate that the proposed curve is an ideal candidate that best represents the NPS. Hence, two parameters, the amplitude (A) and the width (sigma), can be used to characterize the curve. The results also demonstrate that the voxel size and the cone angle are the only two parameters investigated in this study that do not affect the NPS. On the other hand, the matrix and pixel sizes, the back-projection filter and the reconstruction algorithm, the exposure level and the scattering correction, all influence the NPS. Finally, the results of the last part of this investigation suggest that this imaging system does not have a 3D isotropic noise distribution along the z-axis; yielding less noisy images at around z = 0.00 m and z = 80 mm.

Cone Beam Breast CT noise reduction using 3D adaptive Gaussian filtering

In Cone Beam Breast CT (CBBCT) imaging, noise causes degradation of three dimensional breast images, impeding correct diagnosis of breast cancer. Within Feldkamp's cone beam reconstruction framework, applying weighted reconstruction filters to the projection images after pre-processing procedures has long been used to reduce noise and improve image quality. However, CBBCT noise is distributed across frequencies along with the useful signal. Various reconstruction filters working in the frequency domain suppress noise as well as the edge detail signal. Based on fuzzy c-means clustering and the two-dimensional histogram analysis of a large number of clinical CBBCT data, we managed to discriminate fatty stroma, glandular tissues and the transition areas between these tissues by the local mean and standard deviation values. We also proposed a three-dimensional Gaussian filtering scheme to reduce the noise in 3D reconstructed images adaptively without much blurring of detail signal.

Simplified method of scatter correction using a beam-stop-array algorithm for cone-beam computed tomography breast imaging

In flat-panel detector-based cone-beam computed-tomography breast imaging (CBCTBI) systems, scatter is an important factor that degrades image quality. It has been shown that despite the use of a large air gap, scatter still causes problems when imaging breast phantoms with our CBCTBI prototype. As a result, linear attenuation coefficient (LAC) distortion is obvious in the reconstruction; it appears as cupping artifacts and contrast loss. A simplified beam-stop array (BSA) algorithm is presented in this paper to solve this problem practically and efficiently. When the breast is positioned along the rotational axis, the scatter profiles from different views along a circular orbit are similar, and thus it is possible to use only one x-ray shot with the BSA in place for scatter pattern estimation, and this BSA image is used to generate a scatter pattern for all projections. The result of this scatter correction algorithm is compared with the reconstruction image over a small field of view, where scatter is assumed to be negligible, and the relative reconstruction error (RRE) is evaluated. The reconstruction is not sensitive to the estimation of scatter profile curvature, but is sensitive to the estimation of scatter intensity. It is shown as well that for any angular position where the BSA image is taken, the RRE is very small. The results show that the BSA algorithm works well for our CBCTBI prototype system with almost unchanged x-ray exposure.

SU‐GG‐I‐16: A Segmentation Technique to Estimate Breast Density From Cone Beam Breast CT Images

Purpose: To describe and demonstrate the use of an improved segmentation technique to estimate breast density from cone beam breast CT (BCT) images. Method and Materials: To compute the breast density, the dense tissue must be separated from the adipose tissue in the BCT images. To accomplish this task, the BCT images were first processed with a previously reported post‐reconstruction method to correct for the beam hardening and scatter induced cupping artifacts. With this method, the adipose signals were extracted from the coronal view CT image and used to form a 3‐D background map which was then subtracted from the original images for correction. The corrected data were edge enhanced and smoothed to reduce the noise levels in the images. The results were processed by threshold segmentation to separate the dense tissue from the adipose tissue and form a 3‐D dense tissue map which was then used to compute the dense tissue volume and the breast density. Results: For demonstration, the proposed technique was applied to cone beam CT images of mastectomy breast specimens to estimate the breast density. The cupping artifacts were successively corrected for and the dense tissue was successfully separated from the adipose tissue with the segmented dense tissue structures matching well with those visualized in the images. Conclusion: We have successfully implemented a method to use cone beam breast CT images to estimate the breast density. The technique was successfully demonstrated with cone beam CT images of mastectomy breast specimens. This technique lends itself to more accurate and consistent measurement of breast density which may be used an indicator for breast cancer risk.This work was supported in part by grants CA104759 and CA124585 from NIH‐NCI, a grant EB00117 from NIH‐NIBIB, and a subcontract from NIST‐ATP.

Dedicated Cone-Beam Breast CT: Feasibility Study with Surgical Mastectomy Specimens

The purpose of this study was to investigate the feasibility of diagnostic breast imaging using a flat-panel detector-based cone-beam CT system. Imaging of 12 mastectomy specimens was performed at 50-80 kVp with a voxel size of 145 or 290 microm. Our study shows that cone-beam breast CT images have exceptional tissue contrast and can potentially reduce examination time with comparable radiation dose.

WE-E-L100J-03: Scatter Measurements and Simulations in X-Ray Cone Beam CT Breast Imaging

Purpose: To compare and validate Monte Carlo simulation using the GATE software with experimental measurements for scattered radiation in X‐ray cone beam CT breast imaging . In addition, to determine the scatter distribution for single‐order, and multiple‐order incoherent and coherent scatter using validated Monte Carlo simulation.Methods: This study used a bench‐top cone‐beam CT breast imagingsystem using a flat‐panel detector. A cylindrical phantom with equivalent composition of 50% fibro‐glandular and 50% adipose tissues was used. Scatter distributions were measured by beam stop and aperture methods. A lead strip was positioned between the X‐ray source and the breast phantom in the beam stop method. Its inverse version was used in the aperture method. We computed the scatter contribution in the breast phantom by subtracting background scatter. The background scatter fraction was measured without the phantom. The Geant4‐based simulation package GATE was used to model X‐ray photon interactions in the phantom and detector. Two implemented electromagnetic interactions packages, standard and low energy models, were compared for computing efficiency and physics ingredients. A structured breast phantom was used in GATE simulations to determine the characteristics of various scatter components which cannot be separated in measurements. Results: Measurements by the two methods are consistent within 5% after background subtraction, and agree with the low energy model simulations. A hybrid model in GATE, with photoelectric process from the standard model and Compton and Rayleigh scattering processes from the low energy model, is computationally efficient while maintaining physics accuracy. The GATE simulations in the Bakic phantom show that the multiple‐order scatter distribution, as well as single‐order Compton scatter, has predominantly low‐frequency characteristics. Single‐order Rayleigh scatter was observed to be the primary contribution to the spatially variant scatter component.