Breast Imaging System Research Articles

Characterization of a Molecular Breast Imaging system in Limited Angle Tomography using a dedicated breast phantom

This work reports on the Limited Angle Tomography (LAT) studies of a novel Molecular Breast Imaging (MBI) system with radionuclides, made by two asymmetric SPECT-like detector heads with two different optics. MBI has a central role to play in detecting the small breast tumours, especially for dense breasts, due to its specificity in detecting tumours even in dense breasts. For this purpose, an innovative device has been developed at ISS in Rome, composed of a dual detector setup which combines images from two complementary detectors at the opposite sides of the compressed breast, and that allows spot compression and LAT for a tumour 3-D reconstruction. Our study tries to demonstrate the feasibility of using this novel system in LAT , where a small detector head with pinhole collimator is able to rotate around the breast phantom, to diagnose the small tumours and to improve the sensitivity and efficiency. Detector heads and phantom, LAT setup and first preliminary results, are presented.

Metamaterial Loaded Nine High Gain Vivaldi Antennas Array for Microwave Breast Imaging Application

In this article, a metamaterial loaded high gain nine antennas based microwave breast imaging system has presented to detect an unwanted tumour in the breast phantom. The proposed antenna is designed on a modified version of a basic Vivaldi antenna. Single negative metamaterial structure has been loaded to the modified version Vivaldi to enhance far-field antenna properties like gain and radiation pattern, which is essential for the breast imaging system. The proposed antennas have achieved −10dB impedance bandwidth of 8.45 GHz (2.0- 10.45 GHz) and 7.9 dBi maximum gain in the operating band. To verify the time-domain performance, the fidelity factor is also calculated for the face-to-face orientation, which is near about 92.89%. After optimisation in high load phantom, near field directivity (NFD) is also analysed with the workload to ensure that the near field radiation properties. Finally, the nine metamaterial (MTM) antennas arrays are placed around the breast phantom in a hemispherical order to take the data of scattering parameters for tumour object analysis in a CST simulation environment. The extracted data has been processed through an imaging algorithm to reconstruct the image for identifying the unwanted tumour object inside the breast phantom.

Microglandular adenosis of the breast: A case report and a highlight on main diagnosis and management aspects

Microglandular adenosis (MA) is a basically benign–recently borderline-breast disease which mimics well differentiated breast carcinoma clinically and pathologically. The incidence of carcinoma associated with MA reaches up to 27%. In this manuscript, we present a 64-year-old female patient presented with a right breast swelling. Sonomammogram revealed a breast imaging, radiology, and data system IVa right breast architectural distortion. Breast magnetic resonance imaging showed a heterogeneous segmental non mass enhancement in the upper outer quadrant with less extension to lower outer quadrant. Core needle biopsy revealed small uniform glandular structures lined by single layer cuboidal cells with luminal eosinophilic secretions. The cells showed positivity for cytokeratin (CK) and S-100 while P63, smooth muscle actin and CK5/6 were negative. Wide local excision of the mass was done. Microscopic examination revealed proliferation of small glands surrounded by collagenous stroma, some of them infiltrated into the adipose tissue, these glands were lined by a single layer of epithelial cells that lacks a myoepithelial cell layer. They showed positive reaction for S100 and were negative for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. This led to the diagnosis of breast MA. MA should be considered as a precursor for malignancy rather than an innocent lesion. Adequate surgical excision is recommended.

Metamaterial-Inspired Antenna Array for Application in Microwave Breast Imaging Systems for Tumor Detection

This paper presents a study of a planar antenna-array inspired by the metamaterial concept where the resonant elements have sub-wavelength dimensions for application in microwave medical imaging systems for detecting tumors in biological tissues. The proposed antenna consists of square-shaped concentric-rings which are connected to a central patch through a common feedline. The array structure comprises several antennas that are arranged to surround the sample breast model. One antenna at a time in the array is used in transmission-mode while others are in receive-mode. The antenna array operates over 2–12 GHz amply covering the frequency range of existing microwave imaging systems. Measured results show that compared to a standard patch antenna array the proposed array with identical dimensions exhibits an average radiation gain and efficiency improvement of 4.8 dBi and 18%, respectively. The average reflection-coefficient of the array over its operating range is better than S11 ≤ −20 dB making it highly receptive to weak signals and minimizing the distortion encountered with the transmission of short duration pulse-trains. Moreover, the proposed antenna-array exhibits high-isolation on average of 30dB between radiators. This means that antennas in the array (i) can be closely spaced to accommodate more radiators to achieve higher-resolution imaging scans, and (ii) the imagining scans can be done over a wider frequency range to ascertain better contrast in electrical parameters between malignant tumor-tissue and the surrounding normal breast-tissue to facilitate the detection of breast-tumor. It is found that short wavelength gives better resolution. In this experimental study a standard biomedical breast model that mimics a real-human breast in terms of dielectric and optical properties was used to demonstrate the viability of the proposed antenna over a standard patch antenna in the detection and the localization of tumor. These results are encouraging for clinical trials and further refinement of the antenna-array.

Breast tumor classification through learning from noisy labeled ultrasound images.

To train deep learning models to differentiate benign and malignant breast tumors in ultrasound images, we need to collect many training samples with clear labels. In general, biopsy results can be used as benign/malignant labels. However, most clinical samples generally do not have biopsy results. Previous works have proposed generating benign/malignant labels according to Breast Imaging, Reporting and Data System (BI-RADS) ratings. However, this approach will cause noisy labels, which means that the benign/malignant labels produced from BI-RADS diagnoses may be inconsistent with the ground truths. Consequently, deep models will overfit the noisy labels and hence obtain poor generalization performance. In this work, we mainly focus on how to reduce the negative effect of noisy labels when they are used to train breast tumor classification models. We propose an effective approach called noise filter network (NF-Net) to address the problem of noisy labels when training breast tumor classification models. Specifically, to prevent deep models from overfitting the noisy labels, we propose incorporating two softmax layers for classification. Additionally, to strengthen the effect of clean labels, we design a teacher-student module for distilling the knowledge of clean labels. We conduct extensive comparisons with the existing works on addressing noisy labels. Our method achieves a classification accuracy of 73%, with a precision of 69%, recall of 80%, and F1-score of 0.74. This result is significantly better than those of the existing state-of-the-art works on addressing noisy labels. This work provides a means to overcome the label shortage problem in training breast tumor classification models. Specifically, we can generate benign/malignant labels according to the BI-RADS ratings. Although this approach will cause noisy labels, the design of NF-Net can effectively reduce the negative effect of such labels.

Opto-acoustic imaging of relative blood oxygen saturation and total hemoglobin for breast cancer diagnosis.

.Opto-acoustic imaging involves using light to produce sound waves for visualizing blood in biological tissue. By using multiple optical wavelengths, diagnostic images of blood oxygen saturation and total hemoglobin are generated using endogenous optical contrast, without injection of any external contrast agent and without using any ionizing radiation. The technology has been used in recent clinical studies for diagnosis of breast cancer to help distinguish benign from malignant lesions, potentially reducing the need for biopsy through improved diagnostic imaging accuracy. To enable this application, techniques for mapping oxygen saturation differences within tissue are necessary. Using biologically relevant opto-acoustic phantoms, we analyze the ability of an opto-acoustic imaging system to display colorized parametric maps that are generated using a statistical mapping approach. To mimic breast tissue, a material with closely matching properties for optical absorption, optical scattering, acoustic attenuation, and speed of sound is used. The phantoms include two vessels filled with whole blood at oxygen saturation levels determined using a sensor-based approach. A flow system with gas-mixer and membrane oxygenator adjusts the oxygen saturation of each vessel independently. Datasets are collected with an investigational Imagio® breast imaging system. We examine the ability to distinguish vessels as the oxygen saturation level and imaging depth are varied. At depth of 15 mm and hematocrit of 42%, a sufficient level of contrast to distinguish between two 1.6-mm diameter vessels was measured for an oxygen saturation difference of . In addition, an oxygenated vessel was visible at a depth of 48 mm using an optical wavelength of 1064 nm, and a deoxygenated vessel was visible to a depth of 42 mm with 757 nm. The results provide insight toward using color mapped opto-acoustic images for diagnosing breast cancer.

Monte Carlo simulations of an innovative molecular breast imaging system for the small breast cancer diagnosis using GATE

ABSTRACTThis paper draws attention to the study of performance of a new Molecular Breast Imaging (MBI) device, whose purpose is the early diagnosis of breast cancer, using Monte Carlo simulations. MBI provides functional and specific information that are more appropriated to dense breasts. Two asymmetric heads with different types of collimators, facing each other in anti-parallel viewing direction, characterize the system. Detectors and phantoms, together with the data taking procedure, are shortly reported. Monte Carlo simulations using the GATE (GEANT4 Application for Tomographic Emission) simulation toolkit have been implemented to evaluate the optimal detector configuration, in terms of sensitivity and spatial resolution, and also to reproduce the real experimental data. The device can be used both in spot compression and in Limited Angle Tomography (LAT); in the latter configuration one detector head with pinhole collimator is able to rotate around the breast in order to diagnose and localized the small tumors.

Photoacoustic imaging of breast cancer: a mini review of system design and image features.

.Breast cancer is one of the leading causes for cancer related deaths in women, and early detection is extremely important to improve survival rates. Currently, x-ray mammogram is the only modality for mass screening of asymptomatic women. However, it has decreased sensitivity in radiographically dense breasts, which is also associated with a higher risk for breast cancer. Photoacoustic (PA) imaging is an emerging modality that enables deep tissue imaging of optical contrast at ultrasonically defined spatial resolution, which is much higher than that can be achieved in purely optical imaging modalities. Because of high optical absorption from hemoglobin molecules, PA imaging can map out hemo distribution and dynamics in breast tissue and identify malignant lesions based on tumor associated angiogenesis and hypoxia. We review various PA breast imaging systems proposed over the past few years and summarize the PA features of breast cancer identified in these systems.

Semi-anthropomorphic photoacoustic breast phantom.

Imaging parameters of photoacoustic breast imaging systems such as the spatial resolution and imaging depth are often characterized with phantoms. These objects usually contain simple structures in homogeneous media such as absorbing wires or spherical objects in scattering gels. While these kinds of basic phantoms are uncluttered and useful, they do not challenge the system as much as a breast does, and can thereby overestimate the system's performance. The female breast is a complex collection of tissue types, and the acoustic and optical attenuation of these tissues limit the imaging depth, the resolution and the ability to extract quantitative information. For testing and challenging photoacoustic breast imaging systems to the full extent before moving to in vivo studies, a complex breast phantom which simulates the breast's most prevalent tissues is required. In this work we present the first three dimensional multi-layered semi-anthropomorphic photoacoustic breast phantom. The phantom aims to simulate skin, fat, fibroglandular tissue and blood vessels. The latter three are made from custom polyvinyl chloride plastisol (PVCP) formulations and are appropriately doped with additives to obtain tissue realistic acoustic and optical properties. Two tumors are embedded, which are modeled as clusters of small blood vessels. The PVCP materials are surrounded by a silicon layer mimicking the skin. The tissue mimicking materials were cast into the shapes and sizes expected in the breast using 3D-printed moulds developed from a magnetic resonance imaging segmented numerical breast model. The various structures and layers were assembled to obtain a realistic breast morphology. We demonstrate the phantom's appearance in both ultrasound imaging as photoacoustic tomography and make a comparison with a photoacoustic image of a real breast. A good correspondence is observed, which confirms the phantom's usefulness.

Twente Photoacoustic Mammoscope 2: system overview and three-dimensional vascular network images in healthy breasts.

.We present the Twente Photoacoustic Mammoscope 2, a photoacoustic breast imaging system employing a tomographic configuration. It images one breast pendant inside an imaging tank filled with water while a woman lies prone on a bed. A dual-head laser (755 and 1064 nm) illuminates the breast with one beam directed at the nipple and nine beams directed at the sides. Ultrasound signals are detected using 12 arc-shaped arrays, each curving along the pendant breast. Each array comprises 32 piezocomposite elements each with a center frequency of 1 MHz. The imaging tank and the ultrasound arrays rotate around the breast in steps to obtain additional multiple projections. Three-dimensional images are reconstructed using a filtered backprojection algorithm. The system is described in detail, and measurements on a test object are presented. As part of a preliminary study to assess the system’s in vivo performance, the breasts of two healthy volunteers were imaged. These images show the breast contour, the nipple, and the vascular anatomy within the breast. In the nipple of one case, multiple high-intensity “hot spots” are observed, which we suspect are associated with the lactiferous ducts terminating in the nipple.

Cascaded systems analysis of anatomic noise in digital mammography and dual-energy digital mammography

In x-ray based imaging of the breast, contrast between fibroglandular (Fg) tissue and adipose (Ad) tissue is a source of anatomic noise. The goal of this work was to validate by simulation and experiment a mathematical framework for modelling the Fg component of anatomic noise in digital mammograpy (DM) and dual-energy (DE) DM. Our mathematical framework unifies and generalizes existing approaches. We compared mathematical predictions directly with empirical measurements of the anatomic noise power spectrum of the CIRS BR3D structured breast phantom using two clinical mammography systems and four beam qualities. Our simulation and experimental results showed agreement with mathematical predictions. As a demonstration of utility, we used our mathematical framework in a theoretical spectral optimization of DM for the task of detecting breast masses. Our theoretical optimization showed that the optimal tube voltage for DM may be higher than that based on predictions that do not account for anatomic noise, in agreement with recent theoretical findings. Additionally, our theoretical optimization predicts that filtering tungsten-anode x-ray spectra with rhodium has little influence on lesion detectability, in contrast with previous findings. The mathematical methods validated in this work can be incorporated easily into cascaded systems analysis of breast imaging systems and will be useful when optimizating novel techniques for x-ray-based imaging of the breast.

An Experimental Phantom Study for Air-Based Quasi-Resonant Microwave Breast Imaging

The tumor detection performance of two air-based metallic microwave breast imaging systems is evaluated experimentally using breast phantoms having realistic tissue permittivities. The first system has a circular-cylindrical shape, whereas the second has a faceted hemispherical shape. No immersion medium is utilized making these systems low-loss quasi-resonant structures. The breast phantoms are composed of three distinct volumes representing structurally simplified adipose, fibroglandular, and tumor regions filled with tissue-mimicking fluids. Scattered-field data are collected, at multiple frequencies, on the inside surface of the chambers: the normal component of the electric field at 18 locations in the cylindrical chamber and 24 tangential magnetic field components in the faceted chamber. Quantitative 3-D imaging of these high-contrast phantoms is performed utilizing the finite-element contrast-source-inversion algorithm wherein an inhomogeneous numerical background, constituting prior information, is introduced. Experiments are conducted with various accuracies of this prior information, both in terms of the permittivity that is used as well as the accuracy of the geometry compared with the true regions within the phantom. Image segmentation techniques based on thresholding the 3-D reconstructed images are evaluated for tumor detection. Utilizing receiver operating characteristic (ROC) curves, it is shown that taking the intersection of multifrequency thresholded 3-D images performs the best for detecting tumors.

Pediatric and Adolescent Surgical Breast Clinic: Preliminary Experience.

The diagnostic and treatment tools used in breast centers are largely geared to adults, and there is little consideration of the unique characteristics of breast diseases in younger age groups. Herein we report on the preliminary experience of a specialized breast clinic for children and adolescents. Retrospective, observational. Pediatric Surgical Breast Clinic of Schneider Children's Medical Center of Israel. Patients referred to the clinic during the first 18months of its establishment. Rate of breast masses, rate of malignancy, and types of evaluation and treatment. Forty-seven patients aged 0-19years were referred. Breast masses were suspected in 23/47 (48.9%) and confirmed using ultrasound in 14/47 (29.7%; mean age, 16.4years), followed by needle core biopsy in 7. Seven patients had multiple masses. Breast Imaging and Reporting Data System scores ranged from 3 to 4b. All cases were treated as fibroadenomas. Four patients underwent surgery because of a large mass (>5cm; n=3) or patient's preference to remove the lump rather than follow-up (n=1). There were no malignancies. The median time from patient identification of the mass until seeking medical help was 5months. Several findings distinct to this age group were highlighted: high rate of multiple masses, lack of malignancy, and high risk of delayed diagnosis. Care should be taken when using Breast Imaging and Reporting Data System categorization because it was formulated for adults and might be very limited in the adolescent population. Longer-term studies of larger cohorts are planned.

Diffuse optical tomography of the breast: a potential modifiable biomarker of breast cancer risk with neoadjuvant chemotherapy.

The purpose of this study is to evaluate whether a diffuse optical tomography breast imaging system (DOTBIS) can provide a comparable optical-based image index of mammographic breast density, an established biomarker of breast cancer risk. Oxyhemoglobin concentration (ctO2Hb) measured by DOTBIS was collected from 40 patients with stage II-III breast cancer. The tumor-free contralateral breast was used for this evaluation. We observed a moderate positive correlation between the patient's mammogram density classification and ctO2Hb, rs = 0.486 (p = 0.001). In addition, significant reduction in ctO2Hb levels were noted during neoadjuvant chemotherapy treatment (p = 0.017). This observation indicates that ctO2Hb levels measured by DOTBIS could be a novel modifiable imaging biomarker of breast cancer risk and warrants further investigation.

A Discrete Dipole Approximation Solver Based on the COCG-FFT Algorithm and Its Application to Microwave Breast Imaging.

We introduce the discrete dipole approximation (DDA) for efficiently calculating the two-dimensional electric field distribution for our microwave tomographic breast imaging system. For iterative inverse problems such as microwave tomography, the forward field computation is the time limiting step. In this paper, the two-dimensional algorithm is derived and formulated such that the iterative conjugate orthogonal conjugate gradient (COCG) method can be used for efficiently solving the forward problem. We have also optimized the matrix-vector multiplication step by formulating the problem such that the nondiagonal portion of the matrix used to compute the dipole moments is block-Toeplitz. The computation costs for multiplying the block matrices times a vector can be dramatically accelerated by expanding each Toeplitz matrix to a circulant matrix for which the convolution theorem is applied for fast computation utilizing the fast Fourier transform (FFT). The results demonstrate that this formulation is accurate and efficient. In this work, the computation times for the direct solvers, the iterative solver (COCG), and the iterative solver using the fast Fourier transform (COCG-FFT) are compared with the best performance achieved using the iterative solver (COCG-FFT) in C++. Utilizing this formulation provides a computationally efficient building block for developing a low cost and fast breast imaging system to serve under-resourced populations.

A four-alternative forced choice (4AFC) methodology for evaluating microcalcification detection in clinical full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) systems using an inkjet-printed anthropomorphic phantom.

The advent of three-dimensional breast imaging systems such as digital breast tomosynthesis (DBT) has great promise for improving the detection and diagnosis of breast cancer. With these new technologies comes an essential need for testing methods to assess the resultant image quality. Although randomized clinical trials are the gold standard for assessing image quality, phantom-based studies can provide a simpler and less burdensome approach. In this work, a complete framework is presented for task-based evaluation of microcalcification (MCs) detection performance for DBT imaging systems. The framework consists of three parts. The first part is a realistic anthropomorphic physical breast phantom created through inkjet printing, with parchment paper and iodine-doped ink. The second is a method for inserting realistic MCs fabricated from calcium hydroxyapatite. The reproducibility and stability of the phantom materials were investigated through multiple samples of parchment and ink over 6 months. The final part is an analysis using a four-alternative forced choice (4AFC) reader study. To demonstrate the framework, a task-based 4AFC study was conducted using a clinical system to compare performance from DBT, synthetic mammography (SM), and full-field digital mammography (FFDM). Nine human observers read images containing MC clusters imaged with all three modalities and tried to correctly locate the MCs. The proportion correct (PC) was measured as the number of correctly detected clusters out of all trials. Overall, readers scored the highest with FFDM, (PC=0.95±0.03) then DBT (0.85±0.04), and finally SM (0.44±0.06). For the parchment and ink samples, the linear attenuation properties were very stable over 6 months. In addition, little difference was found between the various parchment and ink samples, indicating good reproducibility. This framework presents a promising methodology for evaluating diagnostic task performance of clinical breast DBT systems.

Super-resolution radar imaging for breast cancer detection with microwaves: the integrated information selection criteria.

This paper focuses on the data preprocessing scheme, as well as on the frequency selection and spatial filtering modules integrated with a Time-Reversal Multiple Signal Classification (TR-MUSIC) algorithm, for microwave breast imaging. This algorithm is part of the data processing chain of the Wavelia Microwave Breast Imaging (MBI) system prototype, which has been recently installed at the University Hospital of Galway, Ireland, for a first-in-human clinical trial. Indicative results from application of the algorithm on an experimental phantom dataset, and on a first patient dataset, are presented in this paper. Good correspondence between the two datasets is demonstrated, confirming the validity of the experimental setup used so far for the on-site acceptance of the Wavelia system, after installation at the hospital for clinical testing.

Quantification of Tomographic Incompleteness in Cone-Beam Reconstruction.

For situations of cone-beam scanning where the measurements are incomplete, we propose a method to quantify the severity of the missing information at each voxel. This incompleteness metric is geometric; it uses only the relative locations of all cone-beam vertices with respect to the voxel in question, and does not apply global information such as the object extent or the pattern of incompleteness of other voxels. The values are non-negative, with zero indicating "least incompleteness," i.e. minimal danger of incompleteness artifacts. The incompleteness value can be related to the severity of the potential reconstruction artifact at the voxel location, independent of reconstruction algorithm. We performed a computer simulation of x-ray sources along a circular trajectory, and used small multi-disk test-objects to examine the local effects of data incompleteness. The observed behavior of the reconstructed test-objects quantitatively matched the precalculated incompleteness values. A second simulation of a hypothetical SPECT breast imaging system used only 12 pinholes. Reconstructions were performed using analytic and iterative methods, and five reconstructed test-objects matched the behavior predicted by the incompleteness model. The model is based on known sufficiency conditions for data incompleteness, and provides strong predictive guidance for what can go wrong with incomplete cone-beam data.

A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model.

BackgroundAccurate breast cancer risk assessment for women attending routine screening is needed to guide screening and preventive interventions. We evaluated the accuracy of risk predictions from both visual and volumetric mammographic density combined with the Tyrer-Cuzick breast cancer risk model.MethodsA case-control study (474 patient participants and 2243 healthy control participants) of women aged 40–79 years was performed using self-reported classical risk factors. Breast density was measured by using automated volumetric software and Breast Imaging and Reporting Data System (BI-RADS) density categories. Odds ratios (95% CI) were estimated by using logistic regression, adjusted for age, demographic factors, and 10-year risk from the Tyrer-Cuzick model, for a change from the 25th to 75th percentile of the adjusted percent density distribution in control participants (IQ-OR).ResultsAfter adjustment for classical risk factors in the Tyrer-Cuzick model, age, and body mass index (BMI), BI-RADS density had an IQ-OR of 1.55 (95% CI = 1.33 to 1.80) compared with 1.40 (95% CI = 1.21 to 1.60) for volumetric percent density. Fibroglandular volume (IQ-OR = 1.28, 95% CI = 1.12 to 1.47) was a weaker predictor than was BI-RADS density (Pdiff = 0.014) or volumetric percent density (Pdiff = 0.065). In this setting, 4.8% of women were at high risk (8% + 10-year risk), using the Tyrer-Cuzick model without density, and 7.1% (BI-RADS) compared with 6.8% (volumetric) when combined with density.ConclusionThe addition of volumetric and visual mammographic density measures to classical risk factors improves risk stratification. A combined risk could be used to guide precision medicine, through risk-adapted screening and prevention strategies.

PET/CT for Patients With Breast Cancer: Where Is the Clinical Impact?

OBJECTIVE. FDG PET/CT affects the management of patients with breast cancer in multiple settings, including initial staging, treatment response assessment, and evaluation of suspected recurrence. This article reviews the strengths and weaknesses of FDG PET/CT for the staging of the primary breast lesion, axillary and extraaxillary nodal metastases, and distant metastases. The utility of FDG PET/CT for measuring breast cancer treatment response is appraised and compared with other imaging modalities. The role that tumor histologic type may have on PET/CT interpretation is also discussed. CONCLUSION. Although FDG PET/CT is currently the PET modality with the greatest effect on clinical management of patients with breast cancer, novel radiotracers and imaging systems continue to broaden the application of PET for patients with breast cancer. National Comprehensive Cancer Network guidelines for FDG PET/CT for patients with breast cancer are reviewed. Emphasis is given where FDG PET/CT has shown clinical effect.