The potential role of dedicated 3D breast CT as a diagnostic tool: review and early clinical examples

Maximizing microcalcification detectability in low-dose dedicated cone-beam breast CT: parallel cascades-based theoretical analysis

Purpose

We aim to determine the combination of X-ray spectrum and detector scintillator thickness that maximizes the detectability of microcalcification clusters in dedicated cone-beam breast CT.

Approach

A cascaded linear system analysis was implemented in the spatial frequency domain and was used to determine the detectability index using numerical observers for the imaging task of detecting a microcalcification cluster with 0.17 mm diameter calcium carbonate spheres. The analysis considered a thallium-doped cesium iodide scintillator coupled to a complementary metal-oxide semiconductor detector and an analytical filtered-back-projection reconstruction algorithm. Independent system parameters considered were the scintillator thickness, applied X-ray tube voltage, and X-ray beam filtration. The combination of these parameters that maximized the detectability index was considered optimal.

Results

Prewhitening, nonprewhitening, and nonprewhitening with eye filter numerical observers indicate that the combination of 0.525 to 0.6 mm thick scintillator, 70 kV, and 0.25 to 0.4 mm added copper filtration maximized the detectability index at a mean glandular dose (MGD) of 4.5 mGy.

Conclusion

Using parallel cascade systems' analysis, the combination of parameters that could maximize the detection of microcalcifications was identified. The analysis indicates that a harder beam than that used in current practice may be beneficial for the task of detecting microcalcifications at an MGD suitable for breast cancer screening.

An attenuation field network for dedicated cone beam breast CT with short scan and offset detector geometry

The feasibility of full-scan, offset-detector geometry cone-beam CT has been demonstrated for several clinical applications. For full-scan acquisition with offset-detector geometry, data redundancy from complementary views can be exploited during image reconstruction. Envisioning an upright breast CT system, we propose to acquire short-scan data in conjunction with offset-detector geometry. To tackle the resulting incomplete data, we have developed a self-supervised attenuation field network (AFN). AFN leverages the inherent redundancy of cone-beam CT data through coordinate-based representation and known imaging physics. A trained AFN can query attenuation coefficients using their respective coordinates or synthesize projection data including the missing projections. The AFN was evaluated using clinical cone-beam breast CT datasets (n = 50). While conventional analytical and iterative reconstruction methods failed to reconstruct the incomplete data, AFN reconstruction was not statistically different from the reference reconstruction obtained using full-scan, full-detector data in terms of image noise, image contrast, and the full width at half maximum of calcifications. This study indicates the feasibility of a simultaneous short-scan and offset-detector geometry for dedicated breast CT imaging. The proposed AFN technique can potentially be expanded to other cone-beam CT applications.

Dedicated Cone-Beam Breast CT: Reproducibility of Volumetric Glandular Fraction with Advanced Image Reconstruction Methods

Dedicated cone-beam breast computed tomography (CBBCT) is an emerging modality and provides fully three-dimensional (3D) images of the uncompressed breast at an isotropic voxel resolution. In an effort to translate this modality to breast cancer screening, advanced image reconstruction methods are being pursued. Since radiographic breast density is an established risk factor for breast cancer and CBBCT provides volumetric data, this study investigates the reproducibility of the volumetric glandular fraction (VGF), defined as the proportion of fibroglandular tissue volume relative to the total breast volume excluding the skin. Four image reconstruction methods were investigated: the analytical Feldkamp-Davis-Kress (FDK), a compressed sensing-based fast, regularized, iterative statistical technique (FRIST), a fully supervised deep learning approach using a multi-scale residual dense network (MS-RDN), and a self-supervised approach based on Noise-to-Noise (N2N) learning. Projection datasets from 106 women who participated in a prior clinical trial were reconstructed using each of these algorithms at a fixed isotropic voxel size of (0.273 mm3). Each reconstructed breast volume was segmented into skin, adipose, and fibroglandular tissues, and the VGF was computed. The VGF did not differ among the four reconstruction methods (p = 0.167), and none of the three advanced image reconstruction algorithms differed from the standard FDK reconstruction (p > 0.862). Advanced reconstruction algorithms developed for low-dose CBBCT reproduce the VGF to provide quantitative breast density, which can be used for risk estimation.

New Approaches and Recommendations for Risk-Adapted Breast Cancer Screening

Population-based breast cancer screening using mammography as the gold standard imaging modality has been in clinical practice for over 40 years. However, the limitations of mammography in terms of sensitivity and high false-positive rates, particularly in high-risk women, challenge the indiscriminate nature of population-based screening. Additionally, in light of expanding research on new breast cancer risk factors, there is a growing consensus that breast cancer screening should move toward a risk-adapted approach. Recent advancements in breast imaging technology, including contrast material-enhanced mammography (CEM), ultrasound (US) (automated-breast US, Doppler, elastography US), and especially magnetic resonance imaging (MRI) (abbreviated, ultrafast, and contrast-agent free), may provide new opportunities for risk-adapted personalized screening strategies. Moreover, the integration of artificial intelligence and radiomics techniques has the potential to enhance the performance of risk-adapted screening. This review article summarizes the current evidence and challenges in breast cancer screening and highlights potential future perspectives for various imaging techniques in a risk-adapted breast cancer screening approach. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 5.

Propagation-based phase-contrast imaging of the breast: image quality and the effect of X-ray energy and radiation dose

OBJECTIVES

Propagation-based phase-contrast computed tomography (PB-CT) is a new imaging technique that exploits refractive and absorption properties of X-rays to enhance soft tissue contrast and improve image quality. This study compares image quality of PB-CT and absorption-based CT (AB-CT) for breast imaging while exploring X-ray energy and radiation dose.

METHODS

Thirty-nine mastectomy samples were scanned at energy levels of 28-34keV using a flat panel detector at radiation dose levels of 4mGy and 2mGy. Image quality was assessed using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), spatial resolution (res) and visibility (vis). Statistical analysis was performed to compare PB-CT images against their corresponding AB-CT images scanned at 32keV and 4mGy.

RESULTS

The PB-CT images at 4mGy, across nearly all energy levels, demonstrated superior image quality than AB-CT images at the same dose. At some energy levels, the 2mGy PB-CT images also showed better image quality in terms of CNR/Res and vis compared to the 4mGy AB-CT images. At both investigated doses, SNR and SNR/res were found to have a statistically significant difference across all energy levels. The difference in vis was statistically significant at some energy levels.

CONCLUSION

This study demonstrates superior image quality of PB-CT over AB-CT, with X-ray energy playing a crucial role in determining image quality parameters.

ADVANCES IN KNOWLEDGE

Our findings reveal that standard dose PB-CT outperforms standard dose AB-CT across all image quality metrics. Additionally, we demonstrate that low dose PB-CT can produce superior images compared to standard dose AB-CT in terms of CNR/Res and vis.

Equipment downtime in the radiology departments of three teaching hospitals in Ghana

INTRODUCTION

Radiology equipment requires routine maintenance to prevent equipment breakdown. Equipment breakdown can lead to adverse patient outcomes and lost revenue to hospitals. In Ghana, there is a mismatch between the available radiology equipment and requests which may result in frequent breakdown. Several studies have been conducted to investigate equipment downtime across radiology departments. However, there is none for Ghana. This study therefore investigated the downtimes of radiology equipment across three hospitals in Ghana.

METHOD

The study covered the period January-December 2020. An inventory sheet was used to collect data on equipment specifications, frequency of breakdown, downtimes, average daily patient throughput, the average cost of common examinations, the availability of post-installation training and maintenance contracts/agreements.

RESULTS

The study reviewed 32 items of radiology equipment. Radiology equipment across the hospitals broke down frequently and downtimes were very high. Radiographers/radiologists across the hospitals were provided with poor/inadequate post-installation training, and maintenance contracts/agreements were unavailable. The radiology equipment downtimes resulted in significant lost revenue of GH₵ 16,279,803 (US$ 1,968,537).

CONCLUSION

Radiology equipment across the hospitals broke down frequently and downtimes were lengthy leading to significant lost revenue for the hospitals. Post-installation trainings were poor/inadequate, spanning a few hours. Also, maintenance contracts/agreements were non-existent across the three hospitals. A nationwide study is needed to determine equipment downtimes and lost revenue across all radiology departments in Ghanaian hospitals, to better inform policy-making.

IMPLICATIONS FOR PRACTICE

This study may help hospital managers and other stakeholders involved in policy formulation and strategic planning, put measures in place to minimise radiology equipment breakdown in Ghana. The study may also help optimise radiology services and enable radiology departments to render uninterrupted clinical services to patients in Ghana.

Detection of microcalcifications in photon-counting dedicated breast-CT using a deep convolutional neural network: Proof of principle

OBJECTIVE

In this study, we investigate the feasibility of a deep Convolutional Neural Network (dCNN), trained with mammographic images, to detect and classify microcalcifications (MC) in breast-CT (BCT) images.

METHODS

This retrospective single-center study was approved by the local ethics committee. 3518 icons generated from 319 mammograms were classified into three classes: "no MC" (1121), "probably benign MC" (1332), and "suspicious MC" (1065). A dCNN was trained (70% of data), validated (20%), and tested on a "real-world" dataset (10%). The diagnostic performance of the dCNN was tested on a subset of 60 icons, generated from 30 mammograms and 30 breast-CT images, and compared to human reading. ROC analysis was used to calculate diagnostic performance. Moreover, colored probability maps for representative BCT images were calculated using a sliding-window approach.

RESULTS

The dCNN reached an accuracy of 98.8% on the "real-world" dataset. The accuracy on the subset of 60 icons was 100% for mammographic images, 60% for "no MC", 80% for "probably benign MC" and 100% for "suspicious MC". Intra-class correlation between the dCNN and the readers was almost perfect (0.85). Kappa values between the two readers (0.93) and the dCNN were almost perfect (reader 1: 0.85 and reader 2: 0.82). The sliding-window approach successfully detected suspicious MC with high image quality. The diagnostic performance of the dCNN to classify benign and suspicious MC was excellent with an AUC of 93.8% (95% CI 87, 4%-100%).

CONCLUSION

Deep convolutional networks can be used to detect and classify benign and suspicious MC in breast-CT images.

The Role of Calcium in Non-Invasively Imaging Breast Cancer: An Overview of Current and Modern Imaging Techniques

The landscape of breast cancer diagnostics has significantly evolved over the past decade. With these changes, it is possible to provide a comprehensive assessment of both benign and malignant breast calcifications. The biochemistry of breast cancer and calcifications are thoroughly examined to describe the potential to characterize better different calcium salts composed of calcium carbonate, calcium oxalate, or calcium hydroxyapatite and their associated prognostic implications. Conventional mammographic imaging techniques are compared to available ones, including breast tomosynthesis and contrast-enhanced mammography. Additional methods in computed tomography and magnetic resonance imaging are discussed. The concept of using magnetic resonance imaging particularly magnetic susceptibility to characterize the biochemical characteristics of calcifications is described. As we know magnetic resonance imaging is safe and there is no ionization radiation. Experimental findings through magnetic resonance susceptibility imaging techniques are discussed to illustrate the potential for integrating this technique to provide a quantitative assessment of magnetic susceptibility. Under the right magnetic resonance imaging conditions, a distinct phase variability was isolated amongst different types of calcium salts.

Breast dosimetry in alternative X-ray-based imaging modalities used in current clinical practices

In X-ray breast imaging, Digital Mammography (DM) and Digital Breast Tomosynthesis (DBT), are the standard and largely used techniques, both for diagnostic and screening purposes. Other techniques, such as dedicated Breast Computed Tomography (BCT) and Contrast Enhanced Mammography (CEM) have been developed as an alternative or a complementary technique to the established ones. The performance of these imaging techniques is being continuously assessed to improve the image quality and to reduce the radiation dose. These imaging modalities are predominantly used in the diagnostic setting to resolve incomplete or indeterminate findings detected with conventional screening examinations and could potentially be used either as an adjunct or as a primary screening tool in select populations, such as for women with dense breasts. The aim of this review is to describe the radiation dosimetry for these imaging techniques, and to compare the mean glandular dose with standard breast imaging modalities, such as DM and DBT.

Cone-beam breast CT using an offset detector: effect of detector offset and image reconstruction algorithm

Objective.A dedicated cone-beam breast computed tomography (BCT) using a high-resolution, low-noise detector operating in offset-detector geometry has been developed. This study investigates the effects of varying detector offsets and image reconstruction algorithms to determine the appropriate combination of detector offset and reconstruction algorithm.Approach.Projection datasets (300 projections in 360°) of 30 breasts containing calcified lesions that were acquired using a prototype cone-beam BCT system comprising a 40 × 30 cm flat-panel detector with 1024 × 768 detector pixels were reconstructed using Feldkamp-Davis-Kress (FDK) algorithm and served as the reference. The projection datasets were retrospectively truncated to emulate cone-beam datasets with sinograms of 768×768 and 640×768 detector pixels, corresponding to 5 cm and 7.5 cm lateral offsets, respectively. These datasets were reconstructed using the FDK algorithm with appropriate weights and an ASD-POCS-based Fast, total variation-Regularized, Iterative, Statistical reconstruction Technique (FRIST), resulting in a total of 4 offset-detector reconstructions (2 detector offsets × 2 reconstruction methods). Signal difference-to-noise ratio (SDNR), variance, and full-width at half-maximum (FWHM) of calcifications in two orthogonal directions were determined from all reconstructions. All quantitative measurements were performed on images in units of linear attenuation coefficient (1/cm).Results.The FWHM of calcifications did not differ (P > 0.262) among reconstruction algorithms and detector formats, implying comparable spatial resolution. For a chosen detector offset, the FRIST algorithm outperformed FDK in terms of variance and SDNR (P < 0.0001). For a given reconstruction method, the 5 cm offset provided better results.Significance.This study indicates the feasibility of using the compressed sensing-based, FRIST algorithm to reconstruct sinograms from offset-detectors. Among the reconstruction methods and detector offsets studied, FRIST reconstructions corresponding to a 30 cm × 30 cm with 5 cm lateral offset, achieved the best performance. A clinical prototype using such an offset geometry has been developed and installed for clinical trials.

Comparison of background parenchymal enhancement (BPE) on contrast-enhanced cone-beam breast CT (CE-CBBCT) and breast MRI

OBJECTIVES

To compare the background parenchymal enhancement (BPE) levels on contrast-enhanced cone-beam breast CT (CE-CBBCT) and MRI, evaluate inter-reader reliability, and analyze the relationship between clinical factors and BPE level on CE-CBBCT.

METHODS

In this retrospective study, patients who underwent both CE-CBBCT and MRI were analyzed. BPE levels on CE-CBBCT and MRI were assessed by five specialists independently in random fashion, with a wash-out period of 4 weeks. Weighted kappa was used to analyze the agreement between CE-CBBCT and MRI, and intraclass correlation coefficient (ICC) was used to evaluate the inter-reader reliability for each modality. The association between BPE level on CE-CBBCT and clinical factors was evaluated by univariate and multivariate logistic regression.

RESULTS

A total of 221 patients from January 2017 to April 2021 were enrolled. CE-CBBCT showed substantial agreement (weighted kappa = 0.690) with MRI for BPE evaluation, with good degree of inter-reader reliability on both CE-CBBCT (ICC = 0.712) and MRI (ICC = 0.757). Based on majority reports, BPE levels on CE-CBBCT were lower than MRI (p < 0.001). BPE level on CE-CBBCT was significantly associated with menstrual status (odds ratio, OR = 0.125), breast density (OR = 2.308), and previously treated breast cancer (OR = 0.052) (all p < 0.05). BPE level for premenopausal patients was associated with menstrual cycle, with lower BPE level for the 2^nd week of menstrual cycle (OR = 0.246).

CONCLUSIONS

CE-CBBCT showed substantial agreement and comparable inter-reader reliability with MRI for BPE evaluation, indicating that the corresponding BI-RADS lexicons could be used to describe BPE level on CE-CBBCT. The 2^nd week of menstrual cycle timing is suggested as the optimal examination period for CE-CBBCT.

KEY POINTS

• CE-CBBCT showed substantial agreement and comparable inter-reader reliability with MRI for BPE evaluation. • Menstrual status, breast density, and previously treated breast cancer were associated with the BPE level on CE-CBBCT images. • The 2^ndweek of the menstrual cycle is suggested as the optimal examination period for CE-CBBCT.

The cone-beam breast computed tomography characteristics of breast non-mass enhancement lesions

BACKGROUND

Cone-beam computed tomography (CBBCT) of the breast is emerging as a way of improving breast cancer diagnostic yield.

PURPOSE

To find characteristics of non-mass enhancement (NME) lesions on breast CBBCT and to identify the characteristics that distinguish malignant and benign lesions.

MATERIAL AND METHODS

Breast CBBCT images of 84 NME lesions were analyzed. Internal enhancement distribution and patterns, calcification distribution and suspicious morphology, and ΔHU enhancement values were compared between post-contrast and pre-contrast malignant and benign lesions. Univariate analyses were applied to find the strongest indicators of malignancy, and logistic regression analysis was used to develop a fitting equation for the combined diagnostic model.

RESULTS

In the 84 NME lesions, the indicators of malignancy were as follows: segmental enhancement distribution (P = 0.011, 53.62% sensitivity, 86.67% specificity, 94.87% positive predictive value [PPV], and 28.89% negative predictive value [NPV]), clumped internal enhancement patterns (P = 0.017, 50.72% sensitivity, 86.67% specificity, 94.59% PPV, and 27.66% NPV), ΔHU ≥ 93.57 Hounsfield units (HU) (P = 0.004, 66.67% sensitivity, 73.33% specificity, 92.00% PPV, and 32.35% NPV), and NME lesions with calcification (P = 0.002, 36.23% sensitivity, 20.00% specificity, 82.14% PPV, and 67.57% NPV). The fitting equation for the combined diagnostic model was as follows: Logit (P) = -0.579 +1.318 × enhancement distribution + 1.000 × internal enhancement patterns + 1.539 × ΔHU value + 1.641 ×NME type.

CONCLUSION

Individual diagnostic criteria based on breast CBBCT characteristics (segmental enhancement distribution, clumped internal enhancement patterns, ΔHU values > 93.57 HU, and NME lesions with calcification) had high specificity and PPV; when combined, they had high sensitivity in predicting malignant NME lesions.

Dedicated breast CT: state of the art-Part II. Clinical application and future outlook

Dedicated breast CT is being increasingly used for breast imaging. This technique provides images with no compression, removal of tissue overlap, rapid acquisition, and available simultaneous assessment of microcalcifications and contrast enhancement. In this second installment in a 2-part review, the current status of clinical applications and ongoing efforts to develop new imaging systems are discussed, with particular emphasis on how to achieve optimized practice including lesion detection and characterization, response to therapy monitoring, density assessment, intervention, and implant evaluation. The potential for future screening with breast CT is also addressed. KEY POINTS: • Dedicated breast CT is an emerging modality with enormous potential in the future of breast imaging by addressing numerous clinical needs from diagnosis to treatment. • Breast CT shows either noninferiority or superiority with mammography and numerical comparability to MRI after contrast administration in diagnostic statistics, demonstrates excellent performance in lesion characterization, density assessment, and intervention, and exhibits promise in implant evaluation, while potential application to breast cancer screening is still controversial. • New imaging modalities such as phase-contrast breast CT, spectral breast CT, and hybrid imaging are in the progress of R & D.

High-resolution μ CT imaging for characterizing microcalcification detection performance in breast CT

Purpose: To demonstrate the utility of high-resolution micro-computed tomography ( μ CT ) for determining ground-truth size and shape properties of calcium grains for evaluation of detection performance in breast CT (bCT). Approach: Calcium carbonate grains ( ∼ 200    μ m ) were suspended in 1% agar solution to emulate microcalcifications ( μ Calcs ) within a fibroglandular tissue background. Ground-truth imaging was performed on a commercial μ CT scanner and was used for assessing calcium-grain size and shape, and for generating μ Calc signal profiles. Calcium grains were placed within a realistic breast-shaped phantom and imaged on a prototype bCT system at 3- and 6-mGy mean glandular dose (MGD) levels, and the non-prewhitening detectability was assessed. Additionally, the μ CT -derived signal profiles were used in conjunction with the bCT system characterization (MTF and NPS) to obtain predictions of bCT detectability. Results: Estimated detectability of the calcium grains on the bCT system ranged from 2.5 to 10.6 for 3 mGy and from 3.8 to 15.3 for 6 mGy with large fractions of the grains meeting the Rose criterion for visibility. Segmentation of μ CT images based on morphological operations produced accurate results in terms of segmentation boundaries and segmented region size. A regression model linking bCT detectability to μ Calc parameters indicated significant effects of μ Calc size and vertical position within the breast phantom. Detectability using μ CT -derived detection templates and bCT statistical properties (MTF and NPS) were in good correspondence with those measured directly from bCT ( R 2 > 0.88 ). Conclusions: Parameters derived from μ CT ground-truth data were shown to produce useful characterizations of detectability when compared to estimates derived directly from bCT. Signal profiles derived from μ CT imaging can be used in conjunction with measured or hypothesized statistical properties to evaluate the performance of a system, or system component, that may not currently be available.

Distinguishing benign and malignant lesions on contrast-enhanced breast cone-beam CT with deep learning neural architecture search

PURPOSE

To utilize a neural architecture search (NAS) approach to develop a convolutional neural network (CNN) method for distinguishing benign and malignant lesions on breast cone-beam CT (BCBCT).

METHOD

165 patients with 114 malignant and 86 benign lesions were collected by two institutions from May 2012 to August 2014. The NAS method autonomously generated a CNN model using one institution's dataset for training (patients/lesions: 71/91) and validation (patients/lesions: 20/23). The model was externally tested on another institution's dataset (patients/lesions: 74/87), and its performance was compared with fine-tuned ResNet-50 models and two breast radiologists who independently read the lesions in the testing dataset without knowing lesion diagnosis.

RESULTS

The lesion diameters (mean ± SD) were 18.8 ± 12.9 mm, 22.7 ± 10.5 mm, and 20.0 ± 11.8 mm in the training, validation, and external testing set, respectively. Compared to the best ResNet-50 model, the NAS-generated CNN model performed three times faster and, in the external testing set, achieved a higher (though not statistically different) AUC, with sensitivity (95% CI) and specificity (95% CI) of 0.727, 80% (66-90%), and 60% (42-75%), respectively. Meanwhile, the performances of the NAS-generated CNN and the two radiologists' visual ratings were not statistically different.

CONCLUSIONS

Our preliminary results demonstrated that a CNN autonomously generated by NAS performed comparably to pre-trained ResNet models and radiologists in predicting malignant breast lesions on contrast-enhanced BCBCT. In comparison to ResNet, which must be designed by an expert, the NAS approach may be used to automatically generate a deep learning architecture for medical image analysis.

Prediction of chemotherapy response in breast cancer patients at pre-treatment using second derivative texture of CT images and machine learning

•

Textural and second derivative textural features of CT images can be used in conjunction with machine learning models to predict breast cancer response to chemotherapy prior to the start of treatment.

•

The proposed predictive model separates the patients at pre-treatment into two cohorts (responders/non-responders) with significantly different survival.

•

The proposed methodology is a step forward towards the precision oncology paradigm for breast cancer patients.

Although neoadjuvant chemotherapy (NAC) is a crucial component of treatment for locally advanced breast cancer (LABC), only about 70% of patients respond to it. Effective adjustment of NAC for individual patients can significantly improve survival rates of those resistant to standard regimens. Thus, the early prediction of NAC outcome is of great importance in facilitating a personalized paradigm for breast cancer therapeutics. In this study, quantitative computed tomography (qCT) parametric imaging in conjunction with machine learning techniques were investigated to predict LABC tumor response to NAC. Textural and second derivative textural (SDT) features of CT images of 72 patients diagnosed with LABC were analysed before the initiation of NAC to quantify intra-tumor heterogeneity. These quantitative features were processed through a correlation-based feature reduction followed by a sequential feature selection with a bootstrap 0.632+ area under the receiver operating characteristic (ROC) curve (AUC0.632+) criterion. The best feature subset consisted of a combination of one textural and three SDT features. Using these features, an AdaBoost decision tree could predict the patient response with a cross-validated AUC0.632+ accuracy, sensitivity and specificity of 0.88, 85%, 88% and 75%, respectively. This study demonstrates, for the first time, that a combination of textural and SDT features of CT images can be used to predict breast cancer response NAC prior to the start of treatment which can potentially facilitate early therapy adjustments.

Quantitative breast density measurement based on three-dimensional images: a study on cone-beam breast computed tomography

BACKGROUND

Breast density is an independent predictor of breast cancer risk. Quantitative volumetric breast density (QVBD) is expected to provide more information on the prediction of breast cancer risk.

PURPOSE

To evaluate the reliability of QVBD measurements based on cone-beam breast computed tomography (CBBCT) images.

MATERIAL AND METHODS

A total of 216 breasts were used to evaluate the stability of QVBD measurements based on CBBCT images and the correlations between this volumetric measurement and visual and area-based measurement methods. The intra- and inter-observer consistency of QVBD measurements were compared. Visual breast density (VBD) was evaluated with Breast Imaging Reporting and Data System (BI-RADS) standard on CBBCT images. The correlation between QVBD and VBD was evaluated by Spearman correlation coefficient. Receiver operating characteristic (ROC) curve was used to assess the sensitivity and specificity of the volumetric method in distinguishing dense and non-dense breasts. The correlation between QVBD and quantitative area-based breast density (QABD) was determined with Pearson correlation coefficient. Then, the breast volume measured with CBBCT images was compared with the breast specimen obtained during nipple-sparing mastectomy (NSM) by Pearson correlation coefficient and linear regression.

RESULTS

Excellent intra- and inter-observer consistency was found from QVBD measurements. The volumetric method distinguished dense and non-dense breasts at a cutoff value of 9.5%, with 94.5% sensitivity and 77.1% specificity. Positive correlations were found between QVBD and QABD (r=0.890; P<0.001) and between the volume measured with CBBCT images and Archimedes method (r=0.969; P<0.001).

CONCLUSION

CBBCT images can evaluate breast density reliably on a continuous scale.

Motion artifacts assessment and correction using optical tracking in synchrotron radiation breast CT

Purpose

The SYRMA‐3D collaboration is setting up a breast computed tomography (bCT) clinical program at the Elettra synchrotron radiation facility in Trieste, Italy. Unlike the few dedicated scanners available at hospitals, synchrotron radiation bCT requires the patient's rotation, which in turn implies a long scan duration (from tens of seconds to few minutes). At the same time, it allows the achievement of high spatial resolution. These features make synchrotron radiation bCT prone to motion artifacts. This article aims at assessing and compensating for motion artifacts through an optical tracking approach.

Methods

In this study, patients’ movements due to breathing have been first assessed on seven volunteers and then simulated during the CT scans of a breast phantom and a surgical specimen, by adding a periodic oscillatory motion (constant speed, 1 mm amplitude, 12 cycles/minute). CT scans were carried out at 28 keV with a mean glandular dose of 5 mGy. Motion artifacts were evaluated and a correction algorithm based on the optical tracking of fiducial marks was introduced. A quantitative analysis based on the structural similarity (SSIM) index and the normalized mean square error (nMSE) was performed on the reconstructed CT images.

Results

CT images reconstructed through the optical tracking procedure were found to be as good as the motionless reference image. Moreover, the analysis of SSIM and nMSE demonstrated that an uncorrected motion of the order of the system's point spread function (around 0.1 mm in the present case) can be tolerated.

Conclusions

Results suggest that a motion correction procedure based on an optical tracking system would be beneficial in synchrotron radiation bCT.

Radiation dosimetry of a clinical prototype dedicated cone-beam breast CT system with offset detector

PURPOSE

A clinical-prototype, dedicated, cone-beam breast computed tomography (CBBCT) system with offset detector is undergoing clinical evaluation at our institution. This study is to estimate the normalized glandular dose coefficients ( DgN CT ) that provide air kerma-to-mean glandular dose conversion factors using Monte Carlo simulations.

MATERIALS AND METHODS

The clinical prototype CBBCT system uses 49 kV x-ray spectrum with 1.39 mm 1st half-value layer thickness. Monte Carlo simulations (GATE, version 8) were performed with semi-ellipsoidal, homogeneous breasts of various fibroglandular weight fractions ( f g = 0.01 , 0.15 , 0.5 , 1 ) , chest wall diameters ( d = 8 , 10 , 14 , 18 , 20  cm), and chest wall to nipple length ( l = 0.75 d ), aligned with the axis of rotation (AOR) located at 65 cm from the focal spot to determine the DgN CT . Three geometries were considered - 40 × 30 -cm detector with no offset that served as reference and corresponds to a clinical CBBCT system, 30 × 30 -cm detector with 5 cm offset, and a 30 × 30 -cm detector with 10 cm offset.

RESULTS

For 5 cm lateral offset, the DgN CT ranged 0.177 - 0.574  mGy/mGy and reduction in DgN CT with respect to reference geometry was observed only for 18 cm ( 6.4 % ± 0.23 % ) and 20 cm ( 9.6 % ± 0.22 % ) diameter breasts. For the 10 cm lateral offset, the DgN CT ranged 0.221 - 0.581  mGy/mGy and reduction in DgN CT was observed for all breast diameters. The reduction in DgN CT was 1.4 % ± 0.48 % , 7.1 % ± 0.13 % , 17.5 % ± 0.19 % , 25.1 % ± 0.15 % , and 27.7 % ± 0.08 % for 8, 10, 14, 18, and 20 cm diameter breasts, respectively. For a given breast diameter, the reduction in DgN CT with offset-detector geometries was not dependent on f g . Numerical fits of DgN CT d , l , f g were generated for each geometry.

CONCLUSION

The DgN CT and the numerical fit, D g N CT d , l , f g would be of benefit for current CBBCT systems using the reference geometry and for future generations using offset-detector geometry. There exists a potential for radiation dose reduction with offset-detector geometry, provided the same technique factors as the reference geometry are used, and the image quality is clinically acceptable.

Optical conductivity of triple point fermions

As a low-energy effective theory on non-symmorphic lattices, we consider a generic triple point fermion Hamiltonian, which is parameterized by an angular parameterλ. We find strongλdependence in both Drude and interband optical absorption of these systems. The deviation of theT2coefficient of the Drude weight from Dirac/Weyl fermions can be used as a quick way to optically distinguish the triple point degeneracies from the Dirac/Weyl degeneracies. At the particularλ=π/6 point, we find that the 'helicity' reversal optical transition matrix element is identically zero. Nevertheless, deviating from this point, the helicity reversal emerges as an absorption channel.

Adaptive Image Rescaling for Weakly Contrast-Enhanced Lesions in Dedicated Breast CT: A Phantom Study

Purpose

Dedicated breast CT is an emerging volumetric X-ray imaging modality for diagnosis that does not require any painful breast compression. To improve the detection rate of weakly enhanced lesions, an adaptive image rescaling (AIR) technique was proposed.

Materials and Methods

Two disks containing five identical holes and five holes of different diameters were scanned using 60/100 kVp to obtain single-energy CT (SECT), dual-energy CT (DECT), and AIR images. A piece of pork was also scanned as a subclinical trial. The image quality was evaluated using image contrast and contrast-to-noise ratio (CNR). The difference of imaging performances was confirmed using student's t test.

Results

Total mean image contrast of AIR (0.70) reached 74.5% of that of DECT (0.94) and was higher than that of SECT (0.22) by 318.2%. Total mean CNR of AIR (5.08) was 35.5% of that of SECT (14.30) and was higher than that of DECT (2.28) by 222.8%. A similar trend was observed in the subclinical study.

Conclusion

The results demonstrated superior image contrast of AIR over SECT, and its higher overall image quality compared to DECT with half the exposure. Therefore, AIR seems to have the potential to improve the detectability of lesions with dedicated breast CT.

Developing a Microbubble-Based Contrast Agent for Synchrotron In-Line Phase Contrast Imaging

OBJECTIVE

X-ray phase contrast imaging generates contrast from refraction of X-rays, enhancing soft tissue contrast compared to conventional absorption-based imaging. Our goal is to develop a contrast agent for X-ray in-line phase contrast imaging (PCI) based on ultrasound microbubbles (MBs), by assessing size, shell material, and concentration.

METHODS

Polydisperse perfluorobutane-core lipid-shelled MBs were synthesized and size separated into five groups between 1 and 10 μm. We generated two size populations of polyvinyl-alcohol (PVA)-MBs, 2-3 μm and 3-4 μm, whose shells were either coated or integrated with iron oxide nanoparticles (SPIONs). Microbubbles were then embedded in agar at three concentrations: 5 × 10⁷, 5 × 10⁶ and 5 × 10⁵ MBs/ml. In-line phase contrast imaging was performed at the Canadian Light Source with filtered white beam micro-computed tomography. Phase contrast intensity was measured by both counting detectable MBs, and comparing mean pixel values (MPV) in minimum and maximum intensity projections of the overall samples.

RESULTS

Individual lipid-MBs 6-10 μm, lipid-MBs 4-6 μm and PVA-MBs coated with SPIONs were detectable at each concentration. At the highest concentration, lipid-MBs 6-10 μm and 4-6 μm showed an overall increase in positive contrast, whereas at a moderate concentration, only lipid-MBs 6-10 μm displayed an increase. Negative contrast was also observed from two largest lipid-MBs at high concentration.

CONCLUSION

These data indicate that lipid-MBs larger than 4 μm are candidates for PCI, and 5 × 10⁶ MBs/ml may be the lowest concentration suitable for generating visible phase contrast in vivo.

SIGNIFICANCE

Identifying a suitable MB for PCI may facilitate future clinical translation.

Sparse-view, short-scan, dedicated cone-beam breast computed tomography: image quality assessment

The purpose of this study is to quantify the impact of sparse-view acquisition in short-scan trajectories, compared to 360-degrees full-scan acquisition, on image quality measures in dedicated cone-beam breast computed tomography (BCT). Projection data from 30 full-scan (360-degrees; 300 views) BCT exams with calcified lesions were selected from an existing clinical research database. Feldkamp-Davis-Kress (FDK) reconstruction of the full-scan data served as the reference. Projection data corresponding to two short-scan trajectories, 204 and 270-degrees, which correspond to the minimum and maximum angular range achievable in a cone-beam BCT system were selected. Projection data were retrospectively sampled to provide 225, 180, and 168 views for 270-degrees short-scan, and 170 views for 204-degrees short-scan. Short-scans with 180 and 168 views in 270-degrees used non-uniform angular sampling. A fast, iterative, total variation-regularized, statistical reconstruction technique (FIRST) was used for short-scan image reconstruction. Image quality was quantified by variance, signal-difference to noise ratio (SDNR) between adipose and fibroglandular tissues, full-width at half-maximum (FWHM) of calcifications in two orthogonal directions, as well as, bias and root-mean-squared-error (RMSE) computed with respect to the reference full-scan FDK reconstruction. The median values of bias (8.6 × 10-4-10.3 × 10-4cm-1) and RMSE (6.8 × 10-6-9.8 × 10-6cm-1) in the short-scan reconstructions, computed with the full-scan FDK as the reference were close to, but not zero (P < 0.0001, one-sample median test). The FWHM of the calcifications in the short-scan reconstructions did not differ significantly from the reference FDK reconstruction (P > 0.118), except along the superior-inferior direction for the short-scan reconstruction with 168 views in 270-degrees (P = 0.046). The variance and SDNR from short-scan reconstructions were significantly improved compared to the full-scan FDK reconstruction (P < 0.0001). This study demonstrates the feasibility of the short-scan, sparse-view, compressed sensing-based iterative reconstruction. This study indicates that shorter scan times and reduced radiation dose without sacrificing image quality are potentially feasible.

X-ray induced acoustic computed tomography

X-ray imaging has proved invaluable in medical diagnoses and non-destructive testing (NDT) in the past century. However, there remain two major limitations: radiation harm and inaccessibility to the sample. A recent imaging modality, X-ray induced acoustic computed tomography (XACT), allows a novel solution. In XACT, x-ray induced excitation causes localized heating (<mK) and thermoelastic expansion. This induces a detectable ultrasonic emission, thereby enabling imaging. XACT has the potential to enable low-dose, fast, 3D imaging requiring only single side access. We discuss the fundamentals of XACT and summarize milestones in its evolution over the past several years since its first demonstration using a Medical Linear Accelerator. We highlight XACT's potential applications in biomedical imaging and NDT, and discuss the latest advanced concepts and future directions.

A priori prediction of tumour response to neoadjuvant chemotherapy in breast cancer patients using quantitative CT and machine learning

Response to Neoadjuvant chemotherapy (NAC) has demonstrated a high correlation to survival in locally advanced breast cancer (LABC) patients. An early prediction of responsiveness to NAC could facilitate treatment adjustments on an individual patient basis that would be expected to improve treatment outcomes and patient survival. This study investigated, for the first time, the efficacy of quantitative computed tomography (qCT) parametric imaging to characterize intra-tumour heterogeneity and its application in predicting tumour response to NAC in LABC patients. Textural analyses were performed on CT images acquired from 72 patients before the start of chemotherapy to determine quantitative features of intra-tumour heterogeneity. The best feature subset for response prediction was selected through a sequential feature selection with bootstrap 0.632 + area under the receiver operating characteristic (ROC) curve (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{A}\mathrm{U}\mathrm{C}}_{0.632+}$$\end{document}AUC0.632+) as a performance criterion. Several classifiers were evaluated for response prediction using the selected feature subset. Amongst the applied classifiers an Adaboost decision tree provided the best results with cross-validated \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{A}\mathrm{U}\mathrm{C}}_{0.632+}$$\end{document}AUC0.632+, accuracy, sensitivity and specificity of 0.89, 84%, 80% and 88%, respectively. The promising results obtained in this study demonstrate the potential of the proposed biomarkers to be used as predictors of LABC tumour response to NAC prior to the start of treatment.

Radiochromic film dosimetry in synchrotron radiation breast computed tomography: a phantom study

This study relates to the INFN project SYRMA-3D for in vivo phase-contrast breast computed tomography using the SYRMEP synchrotron radiation beamline at the ELETTRA facility in Trieste, Italy. This peculiar imaging technique uses a novel dosimetric approach with respect to the standard clinical procedure. In this study, optimization of the acquisition procedure was evaluated in terms of dose delivered to the breast. An offline dose monitoring method was also investigated using radiochromic film dosimetry. Various irradiation geometries have been investigated for scanning the prone patient's pendant breast, simulated by a 14 cm-diameter polymethylmethacrylate cylindrical phantom containing pieces of calibrated radiochromic film type XR-QA2. Films were inserted mid-plane in the phantom, as well as wrapped around its external surface, and irradiated at 38 keV, with an air kerma value that would produce an estimated mean glandular dose of 5 mGy for a 14 cm-diameter 50% glandular breast. Axial scans were performed over a full rotation or over 180°. The results point out that a scheme adopting a stepped rotation irradiation represents the best geometry to optimize the dose distribution to the breast. The feasibility of using a piece of calibrated radiochromic film wrapped around a suitable holder around the breast to monitor the scan dose offline is demonstrated.

Deformable Mapping Method to Relate Lesions in Dedicated Breast CT Images to Those in Automated Breast Ultrasound and Digital Breast Tomosynthesis Images

This work demonstrates the potential for using a deformable mapping method to register lesions between dedicated breast computed tomography (bCT) and both automated breast ultrasound (ABUS) and digital breast tomosynthesis (DBT) images (craniocaudal [CC] and mediolateral oblique [MLO] views). Two multi-modality breast phantoms with external fiducial markers attached were imaged by the three modalities. The DBT MLO view was excluded for the second phantom. The automated deformable mapping algorithm uses biomechanical modeling to determine corresponding lesions based on distances between their centers of mass (d_COM) in the deformed bCT model and the reference model (DBT or ABUS). For bCT to ABUS, the mean d_COM was 5.2 ± 2.6 mm. For bCT to DBT (CC), the mean d_COM was 5.1 ± 2.4 mm. For bCT to DBT (MLO), the mean d_COM was 4.7 ± 2.5 mm. This application could help improve a radiologist's efficiency and accuracy in breast lesion characterization, using multiple imaging modalities.

Breast mass assessment on chest CT: Axial, sagittal, coronal or maximal intensity projection?

OBJECTIVES

The goal of this work is to determine the optimal projection to detect breast masses on Chest CT.

METHODS

Institutional Review Board (HIPPA compliant) approval was obtained with a waiver of consent. 10 image pairs of Chest CT images containing breast masses were selected for review by 10 chest radiologists: the pairs consisted of axial, sagittal, coronal and axial MIP images (MIP images) with each projection compared to a MIP and with one another. For each pair, the image where the mass was most conspicuous was recorded.

RESULTS

MIPs were preferred to any cross sectional projection 82% of the time; sagittal (63%) or coronal (63%) images were preferred to the axial projection. When sagittal and coronal images were compared there was no preference.

CONCLUSIONS

MIP images should be obtained and reviewed for breast pathology; sagittal or coronal projections may provide additional information.

Dedicated cone-beam breast CT using laterally-shifted detector geometry: Quantitative analysis of feasibility for clinical translation

BACKGROUND

High-resolution, low-noise detectors with minimal dead-space at chest-wall could improve posterior coverage and microcalcification visibility in the dedicated cone-beam breast CT (CBBCT). However, the smaller field-of-view necessitates laterally-shifted detector geometry to enable optimizing the air-gap for x-ray scatter rejection.

OBJECTIVE

To evaluate laterally-shifted detector geometry for CBBCT with clinical projection datasets that provide for anatomical structures and lesions.

METHODS

CBBCT projection datasets (n = 17 breasts) acquired with a 40×30 cm detector (1024×768-pixels, 0.388-mm pixels) were truncated along the fan-angle to emulate 20.3×30 cm, 22.2×30 cm and 24.1×30 cm detector formats and correspond to 20, 120, 220 pixels overlap in conjugate views, respectively. Feldkamp-Davis-Kress (FDK) algorithm with 3 different weighting schemes were used for reconstruction. Visual analysis for artifacts and quantitative analysis of root-mean-squared-error (RMSE), absolute difference between truncated and 40×30 cm reconstructions (Diff), and its power spectrum (PSDiff) were performed.

RESULTS

Artifacts were observed for 20.3×30 cm, but not for other formats. The 24.1×30 cm provided the best quantitative results with RMSE and Diff (both in units of μ, cm-1) of 4.39×10-3±1.98×10-3 and 4.95×10-4±1.34×10-4, respectively. The PSDiff (>0.3 cycles/mm) was in the order of 10-14μ2mm3 and was spatial-frequency independent.

CONCLUSIONS

Laterally-shifted detector CBBCT with at least 220 pixels overlap in conjugate views (24.1×30 cm detector format) provides quantitatively accurate and artifact-free image reconstruction.

Novel imaging approaches to screen for breast cancer: Recent advances and future prospects

AIM OF THE STUDY

Over the past 50 years, the application of mammography - an X-ray of the breast - to screen healthy women has been a successful strategy to reduce breast cancer mortality. The aim of this study was to review the literature on novel imaging approaches that have the potential to replace mammography.

METHODS

An online literature search was carried out using PubMed, Google Scholar, ScienceDirect and Google Patents. The search keywords included "breast cancer", "imaging" and "screening", with 51 journal articles and five United States patents being selected for review. Seventeen relevant online sources were also identified and referenced.

RESULTS

In addition to full-field digital mammography (FFDM), a further nine imaging modalities were identified for review. These included: digital breast tomosynthesis (DBT); breast computed tomography (BCT); automated breast ultrasound (ABUS); fusion of FFDM and ABUS; fusion of DBT and ABUS; magnetic resonance imaging (MRI); optical imaging; radio-wave imaging; and tactile sensor imaging. Important parameters were considered: diagnostic success (sensitivity and specificity), especially in dense breasts; time to acquire the images; and capital cost of the equipment.

CONCLUSIONS

DBT is rapidly replacing FFDM although it still misses invasive cancers in dense tissue. The fusion of ABUS, either with FFDM or DBT, will lead to sensitivity and specificity approaching 100%. The fusion of opto-acoustic imaging with ultrasound holds considerable promise for the future.

Optimization of the energy for Breast monochromatic absorption X-ray Computed Tomography

The limits of mammography have led to an increasing interest on possible alternatives such as the breast Computed Tomography (bCT). The common goal of all X-ray imaging techniques is to achieve the optimal contrast resolution, measured through the Contrast to Noise Ratio (CNR), while minimizing the radiological risks, quantified by the dose. Both dose and CNR depend on the energy and the intensity of the X-rays employed for the specific imaging technique. Some attempts to determine an optimal energy for bCT have suggested the range 22 keV-34 keV, some others instead suggested the range 50 keV-60 keV depending on the parameters considered in the study. Recent experimental works, based on the use of monochromatic radiation and breast specimens, show that energies around 32 keV give better image quality respect to setups based on higher energies. In this paper we report a systematic study aiming at defining the range of energies that maximizes the CNR at fixed dose in bCT. The study evaluates several compositions and diameters of the breast and includes various reconstruction algorithms as well as different dose levels. The results show that a good compromise between CNR and dose is obtained using energies around 28 keV.

Advancements towards the implementation of clinical phase-contrast breast computed tomography at Elettra

Breast computed tomography (BCT) is an emerging application of X-ray tomography in radiological practice. A few clinical prototypes are under evaluation in hospitals and new systems are under development aiming at improving spatial and contrast resolution and reducing delivered dose. At the same time, synchrotron-radiation phase-contrast mammography has been demonstrated to offer substantial advantages when compared with conventional mammography. At Elettra, the Italian synchrotron radiation facility, a clinical program of phase-contrast BCT based on the free-space propagation approach is under development. In this paper, full-volume breast samples imaged with a beam energy of 32 keV delivering a mean glandular dose of 5 mGy are presented. The whole acquisition setup mimics a clinical study in order to evaluate its feasibility in terms of acquisition time and image quality. Acquisitions are performed using a high-resolution CdTe photon-counting detector and the projection data are processed via a phase-retrieval algorithm. Tomographic reconstructions are compared with conventional mammographic images acquired prior to surgery and with histologic examinations. Results indicate that BCT with monochromatic beam and free-space propagation phase-contrast imaging provide relevant three-dimensional insights of breast morphology at clinically acceptable doses and scan times.

A Reliability Comparison of Cone-Beam Breast Computed Tomography and Mammography: Breast Density Assessment Referring to the Fifth Edition of the BI-RADS Atlas

RATIONALE AND OBJECTIVES

To evaluate the reliability of cone-beam breast computed tomography (CBBCT) in visual assessment of breast density referring to the fifth edition of the Breast Imaging Reporting and Data System compared to digital mammography.

MATERIALS AND METHODS

Breast density assessments of 130 female patients were performed by five radiologists referring to the fifth edition of Breast Imaging Reporting and Data System atlas both on two-view mammograms and CBBCT images. Assessments were repeated by three radiologists with different experience more than 1 month after the initial evaluation. The inter- and intrareader agreements were compared by using the Cohen's weighted Kappa statistic and intraclass correlation coefficient. Weighted Kappa statistic was also used to analyze the agreement between CBBCT images and mammograms. The influence of radiologist experience for breast density assessment was analyzed using a chi-square test.

RESULTS

For CBBCT images, the inter-reader agreement was 0.781, whereas the agreement on mammograms was 0.744, both demonstrating moderate agreement. The level of intrareader reliability was higher on the CBBCT images than mammograms for breast density evaluation, 0.856 versus 0.786. Based on the majority report, the agreement between these two modalities was on substantial agreement degree. There was a statistically significant difference among radiologists with different levels of experience, and higher density categories were reported more often by experienced reader.

CONCLUSION

CBBCT showed equal aptitude and better agreement for the breast density evaluation compared to mammography. CBBCT could be an effective modality for breast density assessment and breast cancer risk evaluation in routine diagnosis and breast cancer screening.

Quantitative assessment of breast density using transmission ultrasound tomography

Purpose

Breast density is important in the evaluation of breast cancer risk. At present, breast density is evaluated using two‐dimensional projections from mammography with or without tomosynthesis using either (a) subjective assessment or (b) a computer‐aided approach. The purpose of this work is twofold: (a) to establish an algorithm for quantitative assessment of breast density using quantitative three‐dimensional transmission ultrasound imaging; and (b) to determine how these quantitative assessments compare with both subjective and objective mammographic assessments of breast density.

Methods

We described and verified a threshold‐based segmentation algorithm to give a quantitative breast density (QBD) on ultrasound tomography images of phantoms of known geometric forms. We also used the algorithm and transmission ultrasound tomography to quantitatively determine breast density by separating fibroglandular tissue from fat and skin, based on imaged, quantitative tissue characteristics, and compared the quantitative tomography segmentation results with subjective and objective mammographic assessments.

Results

Quantitative breast density (QBD) measured in phantoms demonstrates high quantitative accuracy with respect to geometric volumes with average difference of less than 0.1% of the total phantom volumes. There is a strong correlation between QBD and both subjective mammographic assessments of Breast Imaging ‐ Reporting and Data System (BI‐RADS) breast composition categories and Volpara density scores — the Spearman correlation coefficients for the two comparisons were calculated to be 0.90 (95% CI: 0.71–0.96) and 0.96 (95% CI: 0.92–0.98), respectively.

Conclusions

The calculation of breast density using ultrasound tomography and the described segmentation algorithm is quantitatively accurate in phantoms and highly correlated with both subjective and Food and Drug Administration (FDA)‐cleared objective assessments of breast density.

Three-dimensional visualization technique in endoscopic breast-conserving surgery and pedicled omentum for immediate breast reconstruction

PURPOSE

To evaluate the three-dimensional visualization technique (3DVT) in endoscopic breast-conserving surgery (EBCS) and pedicled omentum for immediate breast reconstruction.

METHODS

Clinical data of 256-slice multi-detector CT scanning from 52 patients (group A) were introduced into self-developed Medical Imaging 3D Visualization Systems (MI-3DVS) for individualized segmentation, 3D reconstruction and volume calculation. The surgical process was designed according to the 3D model. Next, the EBCS and pedicled omentum breast reconstruction were performed according to the preoperative design. Finally, the operating time, blood loss, length of postoperative hospital stay, complications and cosmetic outcomes in group A were compared to 44 patients in group B, who underwent the same operation without 3DVT.

RESULTS

The 3DVT can be used to analyze the location of the breast tumors and determine the excision extension of the breast precisely. Compared to group B, group A had the advantage of less bleeding, shortened operating time and earlier discharge (p < 0.05). The cosmetic results of group A were more satisfactory than those of group B (p < 0.05). After a postoperative follow-up of 6-30 months, none of the patients in either group showed any signs of recurrence.

CONCLUSIONS

3DVT can be used to design the surgical process preoperatively and results in positive therapeutic and cosmetic outcomes in EBCS and pedicled omentum for immediate breast reconstruction.

Emerging Breast Imaging Technologies on the Horizon

Early detection of breast cancers by mammography in conjunction with adjuvant therapy has contributed to reduction in breast cancer mortality. Mammography remains the "gold-standard" for breast cancer screening but is limited by tissue superposition. Digital breast tomosynthesis and more recently, dedicated breast computed tomography have been developed to alleviate the tissue superposition problem. However, all of these modalities rely upon x-ray attenuation contrast to provide anatomical images, and there are ongoing efforts to develop and clinically translate alternative modalities. These emerging modalities could provide for new contrast mechanisms and may potentially improve lesion detection and diagnosis. In this article, several of these emerging modalities are discussed with a focus on technologies that have advanced to the stage of in vivo clinical evaluation.

Ultrasound Imaging Technologies for Breast Cancer Detection and Management: A Review

Ultrasound imaging is a commonly used modality for breast cancer detection and diagnosis. In this review, we summarize ultrasound imaging technologies and their clinical applications for the management of breast cancer patients. The technologies include ultrasound elastography, contrast-enhanced ultrasound, 3-D ultrasound, automatic breast ultrasound and computer-aided detection of breast ultrasound. We summarize the study results seen in the literature and discuss their future directions. We also provide a review of ultrasound-guided, breast biopsy and the fusion of ultrasound with other imaging modalities, especially magnetic resonance imaging (MRI). For comparison, we also discuss the diagnostic performance of mammography, MRI, positron emission tomography and computed tomography for breast cancer diagnosis at the end of this review. New ultrasound imaging techniques, ultrasound-guided biopsy and the fusion of ultrasound with other modalities provide important tools for the management of breast patients.

Review of quantitative multiscale imaging of breast cancer

Breast cancer is the most common cancer among women worldwide and ranks second in terms of overall cancer deaths. One of the difficulties associated with treating breast cancer is that it is a heterogeneous disease with variations in benign and pathologic tissue composition, which contributes to disease development, progression, and treatment response. Many of these phenotypes are uncharacterized and their presence is difficult to detect, in part due to the sparsity of methods to correlate information between the cellular microscale and the whole-breast macroscale. Quantitative multiscale imaging of the breast is an emerging field concerned with the development of imaging technology that can characterize anatomic, functional, and molecular information across different resolutions and fields of view. It involves a diverse collection of imaging modalities, which touch large sections of the breast imaging research community. Prospective studies have shown promising results, but there are several challenges, ranging from basic physics and engineering to data processing and quantification, that must be met to bring the field to maturity. This paper presents some of the challenges that investigators face, reviews currently used multiscale imaging methods for preclinical imaging, and discusses the potential of these methods for clinical breast imaging.

Potential Use of American College of Radiology BI-RADS Mammography Atlas for Reporting and Assessing Lesions Detected on Dedicated Breast CT Imaging: Preliminary Study

RATIONALE AND OBJECTIVES

Dedicated breast computed tomography (DBCT) is an emerging and promising modality for breast lesions. The objective of this study was to evaluate the potential use of applying the BI-RADS Mammography Atlas 5th Edition for reporting and assessing breast lesions on DBCT. Currently, no atlas exists for DBCT.

MATERIALS AND METHODS

Four radiologists trained in breast imaging were recruited in this institutional review board-approved, Health Insurance Portability and Accountability Act-compliant study. The enrolled radiologists, who were blinded to mammographic and histopathologic findings, individually reviewed 30 randomized DBCT cases that contained marked lesions. Thirty-four lesions were included in this study: 24 (70.6%) masses, 7 (20.6%) calcifications, and 3 (8.8%) architectural distortions. Eight (23.5%) lesions were malignant and 26 (76.5%) were benign. The reader was asked to specify according to the BI-RADS Mammography Atlas for each marked DBCT lesion: primary findings, features, breast density, and final assessment. We calculated readers' diagnostic performances for differentiating between benign and malignant lesions and interobserver variability for reporting and assessing lesions using a generalized estimating equation and the Fleiss kappa (κ) statistic.

RESULTS

The estimated overall sensitivity of the readers was 0.969, and the specificity was 0.529. There were no significant differences in the sensitivity and the specificity between lesion types. For reporting the presence of a primary finding, the overall substantial agreement (κ = 0.70) was seen. In assigning the breast density and the final assessment, the overall agreement was moderate (κ = 0.53) and fair (κ = 0.30).

CONCLUSION

The use of the BI-RADS Mammography Atlas 5th Edition for DBCT showed high performance and good agreement among readers.

[Diagnostic imaging of breast cancer : An update]

Advances in imaging of the female breast have substantially influenced the diagnosis and probably also the therapy and prognosis of breast cancer in the past few years. This article gives an overview of the most important imaging modalities in the diagnosis of breast cancer. Digital mammography is considered to be the gold standard for the early detection of breast cancer. Digital breast tomosynthesis can increase the diagnostic accuracy of mammography and is used for the assessment of equivocal or suspicious mammography findings. Other modalities, such as ultrasound and contrast-enhanced magnetic resonance imaging (MRI) play an important role in the diagnostics, staging and follow-up of breast cancer. Percutaneous needle biopsy is a rapid and minimally invasive method for the histological verification of breast cancer. New breast imaging modalities, such as contrast-enhanced spectral mammography, diffusion-weighted MRI and MR spectroscopy can possibly further improve breast cancer diagnostics; however, further studies are necessary to prove the advantages of these methods so that they cannot yet be recommended for routine clinical use.

Newer Technologies in Breast Cancer Imaging: Dedicated Cone-Beam Breast Computed Tomography

Dedicated breast computed tomography (CT) is the latest in a long history of breast imaging techniques dating back to the 1960s. Breast imaging is performed both for cancer screening as well as for diagnostic evaluation of symptomatic patients. Dedicated breast CT received US Food and Drug Administration approval for diagnostic use in 2015 and is slowly gaining recognition for its value in diagnostic 3-dimensional imaging of the breast, and also for injected contrast-enhanced imaging applications. Conventional mammography has known limitations in sensitivity and specificity, especially in dense breasts. Breast tomosynthesis was US Food and Drug Administration approved in 2011 and is now widely used. Dedicated breast CT is the next technological advance, combining real 3-dimensional imaging with the ease of contrast administration. The lack of painful compression and manipulation of the breasts also makes dedicated breast CT much more acceptable for the patients.

Cone-beam Breast Computed Tomography: CT Density Does Not Reflect Proliferation Potential and Receptor Expression of Breast Carcinoma

PURPOSE: Recently, cone-beam breast computed tomography (CBCT) is established for the breast investigation. The purpose of the present study was to investigate possible associations between CBCT findings and histopathological features in breast cancer. METHODS: Overall, 59 female patients, mean age of 64.6 years with histological proven breast cancer were included into the study. In all cases, non-contrast CBCT examination was done. The diagnosis of the identified lesions was confirmed histologically by biopsy. Immunohistochemical staining against estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and Ki-67 was performed for every lesion. Collected data were evaluated by means of descriptive statistics. Spearman's correlation coefficient was used to analyze the association between CT density and Ki-67 values. P values <0.05 were taken to indicate statistical significance in all instances. RESULTS: The size of the lesion varied from 2.7 to 90.0, mean size, 15.88 ± 13.0 mm. The mean value of CT density of the lesions was 63.95 ± 38.18 HU. The density tended to be higher in tubular carcinoma. Correlation analysis identified no significant correlations between CT density and Ki-67 level (r = −0.031, P = .784). There were no statistically significant differences of CT density between tumors with different receptor status. CONCLUSIONS: No significant associations between CT density and receptor status in breast cancer. Tubular carcinoma tended to have higher CT density in comparison to other subtypes of breast carcinomas.

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.