Technical note: Characterization, validation, and spectral optimization of a dedicated breast CT system for contrast-enhanced imaging.

BACKGROUND: The development of a new imaging modality, such as 4D dynamic contrast-enhanced dedicated breast CT (4D DCE-bCT), requires optimization of the acquisition technique, particularly within the 2D contrast-enhanced imaging modality. Given the extensive parameter space, cascade-systems analysis is commonly used for such optimization. PURPOSE: To implement and validate a parallel-cascaded model for bCT, focusing on optimizing and characterizing system performance in the projection domain to enhance the quality of input data for image reconstruction. METHODS: A parallel-cascaded system model of a state-of-the-art bCT system was developed and model predictions of the presampled modulation transfer function (MTF) and the normalized noise power spectrum (NNPS) were compared with empirical data collected in the projection domain. Validation was performed using the default settings of 49 kV with 1.5 mm aluminum filter and at 65 kV and 0.257 mm copper filter. A 10 mm aluminum plate was added to replicate the breast attenuation. Air kerma at the isocenter was measured at different tube current levels. Discrepancies between the measured projection domain metrics and model-predicted values were quantified using percentage error and coefficient of variation (CoV) for MTF and NNPS, respectively. The optimal filtration was for a 5 mm iodine disk detection task at 49, 55, 60, and 65 kV. The detectability index was calculated for the default aluminum filtration and for copper thicknesses ranging from 0.05 to 0.4 mm. RESULTS: At 49 kV, MTF errors were +5.1% and -5.1% at 1 and 2 cycles/mm, respectively; NNPS CoV was 5.3% (min = 3.7%; max = 8.5%). At 65 kV, MTF errors were -0.8% and -3.2%; NNPS CoV was 13.1% (min = 11.4%; max = 16.9%). Air kerma output was linear, with 11.67 µGy/mA (R2 = 0.993) and 19.14 µGy/mA (R2 = 0.996) at 49 and 65 kV, respectively. For iodine detection, a 0.25 mm-thick copper filter at 65 kV was found optimal, outperforming the default technique by 90%. CONCLUSION: The model accurately predicts bCT system performance, specifically in the projection domain, under varied imaging conditions, potentially contributing to the enhancement of 2D contrast-enhanced imaging in 4D DCE-bCT.

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

Background: 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. Methods: 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. Results: 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. Conclusion: 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.

Accuracy of Preoperative Contrast-enhanced Cone Beam Breast CT in Assessment of Residual Tumor after Neoadjuvant Chemotherapy: A Comparative Study with Breast MRI.

RATIONALE AND OBJECTIVES: To compare the accuracy of preoperative contrast-enhanced cone beam breast CT (CE-CBBCT) and MRI in assessment of residual tumor after neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: Residual tumor assessments in 91 female patients were performed on preoperative CE-CBBCT and MRI images after NAC. The agreements of tumor size between imaging and pathology were tested by Intraclass Correlation Coefficient (ICC). Subgroup analyses were set according to ductal carcinoma in situ (DCIS), calcifications and molecular subtypes. Correlated-samples Wilcoxon Signed-rank test was used to analyze the difference between imaging and pathology in total and subgroups. AUC, sensitivity, specificity, PPV, and NPV were calculated to compare the performance of CE-CBBCT and MRI in predicting pathological complete response (pCR). RESULTS: Comparing with pathology, the agreement on CE-CBBCT was good (ICC = 0.64, 95% CI, 0.35-0.78), whereas on MRI was moderate (ICC = 0.59, 95% CI, 0.36-0.77), and overestimation on CE-CBBCT was less than that on MRI (median (interquartile range, IQR): 0.24 [0.00, 1.31] cm vs. 0.67 [0.00, 1.81] cm; p = 0.000). In subgroup analysis, CE-CBBCT showed superior accuracy than MRI when residual DCIS (p = 0.000) and calcifications (p = 0.000) contained, as well as luminal A (p = 0.043) and luminal B (p = 0.009) breast cancer. CE-CBBCT and MRI performed comparable in predicting pCR, AUCs were 0.749 and 0.733 respectively (p > 0.05). CONCLUSION: CE-CBBCT showed superior accuracy in assessment of residual tumor compared with MRI, especially when residual DCIS or calcifications contained and luminal subtype. The performance of preoperative CE-CBBCT in predicting pCR was comparable to MRI. CE-CBBCT could be an alternative method used for preoperative assessment after NAC.

Deep learning for x-ray scatter correction in dedicated breast CT.

BACKGROUND: Accurate correction of x-ray scatter in dedicated breast computed tomography (bCT) imaging may result in improved visual interpretation and is crucial to achieve quantitative accuracy during image reconstruction and analysis. PURPOSE: To develop a deep learning (DL) model to correct for x-ray scatter in bCT projection images. METHODS: A total of 115 patient scans acquired with a bCT clinical system were segmented into the major breast tissue types (skin, adipose, and fibroglandular tissue). The resulting breast phantoms were divided into training (n = 110) and internal validation cohort (n = 5). Training phantoms were augmented by a factor of four by random translation of the breast in the image field of view. Using a previously validated Monte Carlo (MC) simulation algorithm, 12 primary and scatter bCT projection images with a 30-degree step were generated from each phantom. For each projection, the thickness map and breast location in the field of view were also calculated. A U-Net based DL model was developed to estimate the scatter signal based on the total input simulated image and trained single-projection-wise, with the thickness map and breast location provided as additional inputs. The model was internally validated using MC-simulated projections and tested using an external data set of 10 phantoms derived from images acquired with a different bCT system. For this purpose, the mean relative difference (MRD) and mean absolute error (MAE) were calculated. To test for accuracy in reconstructed images, a full bCT acquisition was mimicked with MC-simulations and then assessed by calculating the MAE and the structural similarity (SSIM). Subsequently, scatter was estimated and subtracted from the bCT scans of three patients to obtain the scatter-corrected image. The scatter-corrected projections were reconstructed and compared with the uncorrected reconstructions by evaluating the correction of the cupping artifact, increase in image contrast, and contrast-to-noise ratio (CNR). RESULTS: The mean MRD and MAE across all cases (min, max) for the internal validation set were 0.04% (-1.1%, 1.3%) and 2.94% (2.7%, 3.2%), while for the external test set they were -0.64% (-1.6%, 0.2%) and 2.84% (2.3%, 3.5%), respectively. For MC-simulated reconstruction slices, the computed SSIM was 0.99 and the MAE was 0.11% (range: 0%, 0.35%) with a single outlier slice of 2.06%. For the three patient bCT reconstructed images, the correction increased the contrast by a mean of 25% (range: 20%, 30%), and reduced the cupping artifact. The mean CNR increased by 0.32 after scatter correction, which was not found to be significant (95% confidence interval: [-0.01, 0.65], p = 0.059). The time required to correct the scatter in a single bCT projection was 0.2 s on an NVIDIA GeForce GTX 1080 GPU. CONCLUSION: The developed DL model could accurately estimate scatter in bCT projection images and could enhance contrast and correct for cupping artifact in reconstructed patient images without significantly affecting the CNR. The time required for correction would allow its use in daily clinical practice, and the reported accuracy will potentially allow quantitative reconstructions.

Dedicated cone-beam breast CT: Data acquisition strategies based on projection angle-dependent normalized glandular dose coefficients.

BACKGROUND: Dedicated cone-beam breast computed tomography (CBBCT) using short-scan acquisition is being actively investigated to potentially reduce the radiation dose to the breast. This would require determining the optimal x-ray source trajectory for such short-scan acquisition. PURPOSE: To quantify the projection angle-dependent normalized glandular dose coefficient ( D g N C T $Dg{N^{CT}}$ ) in CBBCT, referred to as angular D g N C T $Dg{N^{CT}}$ , so that the x-ray ray source trajectory that minimizes the radiation dose to the breast for short-scan acquisition can be determined. MATERIALS AND METHODS: A cohort of 75 CBBCT clinical datasets was segmented and used to generate three breast models - (I) patient-specific breast with heterogeneous fibroglandular tissue distribution and real breast shape, (II) patient-specific breast shape with homogeneous tissue distribution and matched fibroglandular weight fraction, and (III) homogeneous semi-ellipsoidal breast with patient-specific breast dimensions and matched fibroglandular weight fraction, which corresponds to the breast model used in current radiation dosimetry protocols. For each clinical dataset, the angular D g N C T $Dg{N^{CT}}$ was obtained at 10 discrete angles, spaced 36° apart, for full-scan, circular, x-ray source trajectory from Monte Carlo simulations. Model III is used for validating the Monte Carlo simulation results. Models II and III are used to determine if breast shape contributes to the observed trends in angular D g N C T $Dg{N^{CT}}$ . A geometry-based theory in conjunction with center-of-mass ( C O M $COM$ ) based distribution analysis is used to explain the projection angle-dependent variation in angular D g N C T $Dg{N^{CT}}$ . RESULTS: The theoretical model predicted that the angular D g N C T $Dg{N^{CT}}$ will follow a sinusoidal pattern and the amplitude of the sinusoid increases when the center-of-mass of fibroglandular tissue ( C O M f $CO{M_f}$ ) is farther from the center-of-mass of the breast ( C O M b $CO{M_b}$ ). It also predicted that the angular D g N C T $Dg{N^{CT}}$ will be minimized at x-ray source positions complementary to the C O M f $CO{M_f}$ . The C O M f $CO{M_f}$ was superior to the C O M b $CO{M_b}$ in 80% (60/75) of the breasts. From Monte Carlo simulations and for homogeneous breasts (models II and III), the deviation in breast shape from a semi-ellipsoid had minimal effect on angular D g N C T $Dg{N^{CT}}$ and showed less than 4% variation. From Monte Carlo simulations and for model I, as predicted by our theory, the angular D g N C T $Dg{N^{CT}}$ followed a sinusoidal pattern with maxima and minima at x-ray source positions superior and inferior to the breast, respectively. For model I, the projection angle-dependent variation in angular D g N C T $Dg{N^{CT}}$ was 16.4%. CONCLUSION: The heterogeneous tissue distribution affected the angular D g N C T $Dg{N^{CT}}$ more than the breast shape. For model I, the angular D g N C T $Dg{N^{CT}}$ was lowest when the x-ray source was inferior to the breast. Hence, for short-scan CBBCT acquisition with C O M b $CO{M_b}$ aligned with axis-of-rotation, an x-ray source trajectory inferior to the breast is preferable and such an acquisition spanning 205° can potentially reduce the mean glandular dose by up to 52%.

[Sparse-view Cone-beam Breast CT Reconstruction via cGAN Constrained by Image Edges].

Clinical applications of cone-beam breast CT(CBBCT) are hindered by relatively higher radiation dose and longer scan time. This study proposes sparse-view CBBCT, i.e. with a small number of projections, to overcome the above bottlenecks. A deep learning method - conditional generative adversarial network constrained by image edges (ECGAN) - is proposed to suppress artifacts on sparse-view CBBCT images reconstructed by filtered backprojection (FBP). The discriminator of the ECGAN is the combination of patchGAN and LSGAN for preserving high frequency information, with a modified U-net as the generator. To further preserve subtle structures and micro calcifications which are particularly important for breast cancer screening and diagnosis, edge images of CBBCT are added to both the generator and the discriminator to guide the learning. The proposed algorithm has been evaluated on 20 clinical raw datasets of CBBCT. ECGAN substantially improves the image qualities of sparse-view CBBCT, with a performance superior to those of total variation (TV) based iterative reconstruction and FBPConvNet based post-processing. On one CBBCT case with the projection number reduced from 300 to 100, ECGAN enhances peak-signal-to-noise ratio (PSNR) and structural similarity (SSIM) on FBP reconstruction from 24.26 and 0.812 to 37.78 and 0.963, respectively. These results indicate that ECGAN successfully reduces radiation dose and scan time of CBBCT by 1/3 with only small image degradations.

Sparse-view Cone-beam Breast CT Reconstruction via cGAN Constrained by Image Edges / 中国医疗器械杂志

Clinical applications of cone-beam breast CT(CBBCT) are hindered by relatively higher radiation dose and longer scan time. This study proposes sparse-view CBBCT, i.e. with a small number of projections, to overcome the above bottlenecks. A deep learning method - conditional generative adversarial network constrained by image edges (ECGAN) - is proposed to suppress artifacts on sparse-view CBBCT images reconstructed by filtered backprojection (FBP). The discriminator of the ECGAN is the combination of patchGAN and LSGAN for preserving high frequency information, with a modified U-net as the generator. To further preserve subtle structures and micro calcifications which are particularly important for breast cancer screening and diagnosis, edge images of CBBCT are added to both the generator and the discriminator to guide the learning. The proposed algorithm has been evaluated on 20 clinical raw datasets of CBBCT. ECGAN substantially improves the image qualities of sparse-view CBBCT, with a performance superior to those of total variation (TV) based iterative reconstruction and FBPConvNet based post-processing. On one CBBCT case with the projection number reduced from 300 to 100, ECGAN enhances peak-signal-to-noise ratio (PSNR) and structural similarity (SSIM) on FBP reconstruction from 24.26 and 0.812 to 37.78 and 0.963, respectively. These results indicate that ECGAN successfully reduces radiation dose and scan time of CBBCT by 1/3 with only small image degradations.

[Comparison of the diagnostic efficiency in breast malignancy between cone beam breast CT and mammography in dense breast].

Objective: To compare the diagnostic efficiency of lesion in dense breast between cone beam breast computer tomography (CBBCT) and mammography. Methods: From May 2012 to August 2014, 160 patients with 165 breasts who underwent mammography and CBBCT examinations were included in this study. The diagnostic results of CBBCT and mammography were reviewed and compared with pathological results. Results: In the 165 breast, 24 were dense breasts and 141 were dense breasts. The diagnostic results were similar in 109 lesions, but different in 56 lesions. According to the analysis of the 165 breasts using receiver operation characteristics (ROC) curve, the area under the ROC curves (AUC) of CBBCT and mammography were 0.923 (95%CI: 0.878-0.967, P<0.05) and 0.959 (95%CI: 0.926-0.992, P<0.05), respectively. With Breast Imaging-Reporting and Data System (BI-RADS) 4b as the critical value, the sensitivity and specificity were 70.0% and 98.7% using mammography, and 83.3% and 97.3% using CBBCT, respectively. The AUC of CBBCT and mammography of the 141 dense breasts was 0.919(95%CI: 0.868-0.969, P<0.05) and 0.973(95%CI: 0.947-0.999, P<0.05), respectively. With BI-RADS 4b as the critical value, the sensitivity and specificity were 69.0% and 98.6% by mammography, and 83.1% and 98.6% by CBBCT, respectively. Conclusions: CBBCT showed higher sensitivity and specificity in the diagnosis of breast malignant tumors compared to mammography. It is expected to be applied to breast cancer detection in the future, especially in dense breast.

Contrast-enhanced cone-beam breast-CT: Analysis of optimal acquisition time for discrimination of breast lesion malignancy.

OBJECTIVE: To investigate the optimal acquisition time of contrast-enhanced cone-beam breast-CT (CBBCT) for best discrimination of breast lesion malignancy and whether contrast enhancement can aid in classification of tumor histology. MATERIAL AND METHODS: The study included patients with BI-RADS 4 or 5 lesions identified on mammography and/or ultrasound. All patients were examined by non-contrast (NC-CBBCT) and contrast-enhanced CBBCT (CE-CBBCT) at 2 and 3min after contrast media (CM) injection. Lesion enhancement of suspicious breast lesions was evaluated in corresponding CBBCT slices. RESULTS: A total of 31 patients with 57 breast lesions, 30 malignant and 27 benign, were included. Malignant breast lesions demonstrated higher contrast enhancement than benign breast lesions at both 2min and 3min CE-CBBCT (2min: 48.17 vs. 0.3 HU, p<0.001; 3min: 57.38 vs. 15.43 HU, p<0.001). Enhancement differences between malignant and benign breast lesions were largest at 2min CE-CBBCT. Ductal carcinoma in situ (DCIS) showed highest mean contrast enhancement among malignant breast lesions (100.93 HU at 3min CE-CBBCT, p=0.0314) compared to invasive carcinoma of no special type with DCIS component (55.82 HU at 3min CE-CBBCT) and invasive ductal carcinoma (52.31 HU at 3min CE-CBBCT). CONCLUSIONS: The contrast enhancement on CE-CBBCT best discriminates between malignant and benign breast lesions at 2min after CM injection. The enhancement has the potential to differentiate histopathological subtypes, with highest enhancement among malignant lesions seen for DCIS.

The role of off-focus radiation in scatter correction for dedicated cone beam breast CT.

PURPOSE: Dedicated cone beam breast CT (CBBCT) suffers from x-ray scatter contamination. We aim to identify the source of the significant difference between the scatter distributions estimated by two recent methods proposed by our group and to investigate its effect on CBBCT image quality. METHOD: We recently proposed two novel methods of scatter correction for CBBCT, using a library based (LB) technique and a forward projection (FP) model. Despite similar enhancement on CBBCT image qualities, these two methods obtain very different scatter distributions. We hypothesize that the off-focus radiation (OFR) is the contributor and results in nontrivial signals in x-ray projections, which is ignored in the scatter estimation via the LB method. Experiments using a thin wire test tool are designed to study the effect of OFR on CBBCT spatial resolution by measuring the point spread function (PSF) and the modulation transfer function (MTF). A narrow collimator setting is used to suppress the OFR-induced signals. In addition, "PSFs" and "MTFs" are measured on clinical CBBCT images obtained by the LB and FP methods using small calcifications as point sources. The improvement of spatial resolution achieved by suppressing OFR in the wire experiment as well as in the clinical study is quantified by the improvement ratios of PSFs and spatial frequencies at different MTF values. Our hypothesis that OFR causes the imaging difference between the FP and LB methods is verified if these ratios obtained from experimental and clinical data are consistent. RESULTS: In the wire experiment, the results show that suppression of OFR increases the maximum signal of the PSF by about 14% and reduces the full-width-at-half-maximum (FWHM) by about 12.0%. Similar improvement on spatial resolution is achieved by the FP method compared with the LB method in the patient study. The improvement ratios of spatial frequencies at different MTF values without OFR match very well in both studies at a level of around 16%, with an average root-mean-square difference of 0.47%. CONCLUSION: The results of the wire experiment and the clinical study indicate that the main difference between the LB and FP methods is whether the OFR-induced signals are included after scatter correction. Our study further shows that OFR significantly affects the image spatial resolution of CBBCT, indicating that the visualization of micro-calcifications is susceptible to OFR contamination. Our finding is therefore important in further improvement of diagnostic performance of CBBCT.

Comparison of the diagnostic efficiency in breast malignancy between cone beam breast CT and mammography in dense breast / 中华肿瘤杂志

Objective@#To compare the diagnostic efficiency of lesion in dense breast between cone beam breast computer tomography (CBBCT) and mammography.@*Methods@#From May 2012 to August 2014, 160 patients with 165 breasts who underwent mammography and CBBCT examinations were included in this study. The diagnostic results of CBBCT and mammography were reviewed and compared with pathological results.@*Results@#In the 165 breast, 24 were dense breasts and 141 were dense breasts. The diagnostic results were similar in 109 lesions, but different in 56 lesions. According to the analysis of the 165 breasts using receiver operation characteristics (ROC) curve, the area under the ROC curves (AUC) of CBBCT and mammography were 0.923 (95%CI: 0.878-0.967, P<0.05) and 0.959 (95%CI: 0.926-0.992, P<0.05), respectively. With Breast Imaging-Reporting and Data System (BI-RADS) 4b as the critical value, the sensitivity and specificity were 70.0% and 98.7% using mammography, and 83.3% and 97.3% using CBBCT, respectively. The AUC of CBBCT and mammography of the 141 dense breasts was 0.919(95%CI: 0.868-0.969, P<0.05) and 0.973(95%CI: 0.947-0.999, P<0.05), respectively. With BI-RADS 4b as the critical value, the sensitivity and specificity were 69.0% and 98.6% by mammography, and 83.1% and 98.6% by CBBCT, respectively.@*Conclusions@#CBBCT showed higher sensitivity and specificity in the diagnosis of breast malignant tumors compared to mammography. It is expected to be applied to breast cancer detection in the future, especially in dense breast.

Reliability of breast density estimation based on cone beam breast CT / 中国肿瘤临床

Objective:To investigate the accuracy of a threshold-based segmentation method based on cone beam breast CT(CBBCT) images in breast density measurement,and its value for breast-type classification and breast cancer screening.Methods:A retrospec-tive analysis of 195 patients who had undergone CBBCT examination at Tianjin Medical University Cancer Institute and Hospital be-tween May 2012 and August 2014 was performed.A total of 64 breasts were analyzed.On the basis of the classification criteria for breast density in BI-RADS,they were classified into four types and the majority report was reported.Breast density was measured by the threshold-based segmentation method based on CBBCT images and corrected manually to obtain the corrected breast density.A month later,the procedure was repeated.Intra-class correlation coefficients(ICCs)were used to compare the intra-observer and inter-observer consistencies of threshold-based segmentation and manually corrected breast density measurement results for non-dense and dense breasts.Results:For threshold-based segmentation measurements the intra-observer and inter-observer ICC values were 0.0.9624(95% CI:0.9388~0.9770)and 0.9666(95% CI:0.9500~0.9785).For manually corrected measurements,the intra-observer and inter-observer ICC values were 0.9750 (95% CI: 0.9592~0.9847) and 0.9775 (95% CI: 0.9661~0.9855). The ICC between the threshold-based segmentation method and manual correction was 0.9962 (95% CI: 0.9983~0.9977). The ICC values of threshold-based and manually corrected measurement in non-dense and dense breasts were 0.9497(95% CI:0.7072-0.9914)and 0.9983(95% CI:0.9971-0.9990),respectively.Conclusions:The threshold-based segmentation method based on CBBCT is a reliable and accurate com-puter-aided method of measuring breast density.It is expected to be applied in large-scale screening of breast cancer and to provide more information for predicting the risk of breast cancer.

The role of cone-beam breast-CT for breast cancer detection relative to breast density.

OBJECTIVES: To evaluate the impact of breast density on the diagnostic accuracy of non-contrast cone-beam breast computed tomography (CBBCT) in comparison to mammography for the detection of breast masses. METHODS: A retrospective study was conducted from August 2015 to July 2016. Fifty-nine patients (65 breasts, 112 lesions) with BI-RADS, 5th edition 4 or 5 assessment in mammography and/or ultrasound of the breast received an additional non-contrast CBBCT. Independent double blind reading by two radiologists was performed for mammography and CBBCT imaging. Sensitivity, specificity and AUC were compared between the modalities. RESULTS: Breast lesions were histologically examined in 85 of 112 lesions (76%). The overall sensitivity for CBBCT (reader 1: 91%, reader 2: 88%) was higher than in mammography (both: 68%, p<0.001), and also for the high-density group (p<0.05). The specificity and AUC was higher for mammography in comparison to CBBCT (p<0.05 and p<0.001). The interobserver agreement (ICC) between the readers was 90% (95% CI: 86-93%) for mammography and 87% (95% CI: 82-91%) for CBBCT. CONCLUSIONS: Compared with two-view mammography, non-contrast CBBCT has higher sensitivity, lower specificity, and lower AUC for breast mass detection in both high and low density breasts. KEY POINTS: • Overall sensitivity for non-contrast CBBCT ranged between 88%-91%. • Sensitivity was higher for CBBCT than mammography in both density types (p<0.001). • Specificity was higher for mammography than CBBCT in both density types (p<0.05). • AUC was larger for mammography than CBBCT in both density types (p<0.001).

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

PURPOSE: 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. METHOD: 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. RESULTS: 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. CONCLUSION: 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.

Artifacts Caused by Breast Tissue Markers in a Dedicated Cone-beam Breast CT in Comparison to Full-field Digital Mammography.

RATIONALE AND OBJECTIVES: The purpose of this ex vivo study was to investigate artifacts in a cone-beam breast computed tomography (CBBCT) caused by breast tissue markers. MATERIALS AND METHODS: Breast phantoms with self-made tissue pork mincemeat were created. Twenty-nine different, commercially available markers with varying marker size, composition, and shape were evaluated. A dedicated CBBCT evaluation of all phantoms was performed with 49 kVp, 50 and 100 mA, and marker orientation parallel and orthogonal to the scan direction. The resultant images were evaluated in sagittal, axial, and coronal view with a slice thickness of 0.5 mm. Additionally, measurements of all markers in the same directions were done with full-field digital mammography. RESULTS: All markers were visible in full-field digital mammography without any artifacts. However, all markers caused artifacts on a CBBCT. Artifacts were measured as the length of the resulting streakings. Median length of artifacts was 7.2 mm with a wide range from 0 to 48.3 mm (interquartile range 4.3-11.4 mm) dependent on composition, size, shape, weight, and orientation of the markers. The largest artifacts occurred in axial view with a median size of 12.6 mm, with a range from 0 to 48.3 mm, resulting in a relative artifact length (quotient artifact in mm/real physical length of the marker itself) of 4.1 (interquartile range 2.3-6.1, range 0-8.7). CONCLUSIONS: Artifacts caused by markers can significantly influence image quality in a CBBCT, thus limiting primary diagnostics and follow-up in breast cancer. The size of the artifacts depends on the marker characteristics, orientation, and the image plane of reconstruction.

A general method for cupping artifact correction of cone-beam breast computed tomography images.

PURPOSE: Cone-beam breast computed tomography (CBBCT), a promising breast cancer diagnostic technique, has been under investigation for the past decade. However, owing to scattered radiation and beam hardening, CT numbers are not uniform on CBBCT images. This is known as cupping artifact, and it presents an obstacle for threshold-based volume segmentation. In this study, we proposed a general post-reconstruction method for cupping artifact correction. METHODS: There were four steps in the proposed method. First, three types of local region histogram peaks were calculated: adipose peaks with low CT numbers, glandular peaks with high CT numbers, and unidentified peaks. Second, a linear discriminant analysis classifier, which was trained by identified adipose and glandular peaks, was employed to identify the unidentified peaks as adipose or glandular peaks. Third, adipose background signal profile was fitted according to the adipose peaks using the least squares method. Finally, the adipose background signal profile was subtracted from original image to obtain cupping corrected image RESULTS: In experimental study, standard deviation of adipose tissue CT numbers was obviously reduced and the CT numbers were more uniform after cupping correction by proposed method; in simulation study, root-mean-square errors were significantly reduced for both symmetric and asymmetric cupping artifacts, indicating that the proposed method was effective to both artifacts. CONCLUSIONS: A general method without a circularly symmetric assumption was proposed to correct cupping artifacts in CBBCT images for breast. It may be properly applied to images of real patient breasts with natural pendent geometry.