Imaging For Breast Cancer Detection Research Articles

Simulation and design of an UWB imaging system for breast cancer detection

In Ultra-Wideband (UWB) imaging for breast cancer detection, UWB pulses illuminate the breast and the echoes are processed to create images of reflected energy. Experiments with RF instrumentation proved this method to be capable of detecting small tumors, but adoption in screening campaigns requires the replacement of RF tools with ad hoc circuits and systems. We report on our experience with the design of an UWB imaging system and assess its feasibility in various steps. We develop a simulation environment that includes breast electromagnetic model, antennas, transmitters, receivers, and digital processing. Simulations produce energy maps, which help identify qualitatively the presence of cancerous tissue, and more quantitative metrics such as Signal-to-Clutter and Signal-to-Mean ratios. Initially the system components are described behaviorally as ideal elements. We then focus on the most critical component, the receiver, and evaluate the impact of quantization, noise, jitter, and non-linearity. We then design three receiver key elements: a slot antenna, the LNA, and the track-and-hold amplifier, the latter two implemented in CMOS 130nm. In our simulator we can replace their behavioral description with a circuit-level one without changing the rest of the system, which permits a system-level assessment of low-level issues.

High-performance near-infrared imaging for breast cancer detection

We present a method for the noninvasive determination of the size, position, and optical properties of tumors in the human breast. The tumor is first detected by photothermal imaging. It is then sized, located, and optically characterized using designed digital image processing and edge-detection pattern recognition. The method assumes that the tumor is spherical and inhomogeneous and embedded in an otherwise homogeneous tissue. Heat energy is deposited in the tissue by absorption of near-infrared (NIR) Nd:YAG laser radiation, and its subsequent conversion to heat via vibrational relaxation causes a rise in temperature of the tissue. The tumor absorbs and scatters NIR light more strongly than the surrounding healthy tissue. Heat will diffuse through the tissue, causing a rise in temperature of the surrounding tissue. Differentiation between normal and cancerous tissues is determined using IR thermal imaging. Results are presented on a 55-year-old patient with a papillary breast cancer. We found that these results provide the clinician with more detailed information about breast lesions detected by photothermal imaging and thereby enhance its potential for specificity.

Abstract ES08-2: Predicting tumor response by functional imaging, PET imaging as a functional predictive biomarker

Abstract The ability to measure biochemical and molecular processes to guide breast cancer treatment represents a significant advance in individualized breast cancer treatment. These assays have traditionally been performed by analysis of cell culture or tissue samples. More recently, functional and molecular imaging allows in vivo assay of biochemistry and molecular biology that is highly complementary to tissue-based assay. Molecular imaging can help inform drug trial of targeted breast cancer treatment and clinical decision making by (1) measuring regional expression of the therapeutic target, (2) testing the ability of drugs to interact with their intended targets, and (3) by measuring cancer response early in the course of treatment. This talk will review basic principals of molecular imaging in breast cancer, with an emphasis on those methods that have been tested in patients. The talk will review the current state of molecular imaging in breast cancer patients, including methods in routine clinical use, those undergoing advanced clinical trials, and those in early-phase testing. Current trials and future directions will be highlighted. The session is designed for a broad audience, ranging from breast cancer translational scientists to practicing physicians caring for breast cancer patients.

Mono Pulse Confocal Microwave Imaging in Breast Cancer Detection

Mono pulse algorithm for confocal microwave imaging (CMI) for breast cancer detection is presented in this paper. All the antennas are used as receiver but only one is also used as transmitter. The transmitted signal is emitted for only once, thus the gross electromagnetic wave energy to the breast is reduced and the diagnosis time can be saved. Two confocal microwave imaging algorithms are presented in this paper: delay-sum-max and delay-production-sum. Both algorithms use the same delayed backscattered signals as the convectional CMI. The difference is how to use the delayed signals to form the image of the scattering intensity. Delay-sum-max method adds the signal together to generate the different value in confocal point via coherent and incoherent addition. Delay-production-sum algorithm products the delayed signal so as to make the assigned value in the confocal point outside the tumor is nearly zero. The image results can be compliment for more confirm diagnosis. Finite-difference time-domain (FDTD) method is used for simulation on 3 models of different tumor arrangements. The results show both methods are effective in detecting single-tumor, while there are some limitations in dealing with multi-tumor.

Interreader Scoring Variability in an Observer Study Using Dual-Modality Imaging for Breast Cancer Detection in Women with Dense Breasts

To evaluate variability in the clinical assessment of breast images, we evaluated scoring behavior of radiologists in a retrospective reader study combining x-ray mammography (XRM) and three-dimensional automated breast ultrasound (ABUS) for breast cancer detection in women with dense breasts. The study involved 17 breast radiologists in a sequential study design with readers first interpreting XRM-alone followed by an interpretation of combined XRM + ABUS. Each interpretation included a forced Breast Imaging Reporting and Data System scale and a likelihood that the woman had breast cancer. The analysis included 164 asymptomatic patients, including 31 breast cancer patients, with dense breasts and a negative screening XRM. Of interest were interreader scoring variability for XRM-alone, XRM + ABUS, and the sequential effect. In addition, a simulated double reading by pairs of readers of XRM + ABUS was investigated. Performance analysis included receiver operating characteristic analysis, percentile analysis, and κ statistics. Bootstrapping was used to determine statistical significance. The median change in area under the receiver operating characteristic curve after ABUS interpretation was 0.12 (range 0.04-0.19). Reader agreement was fair with the median interreader κ being 0.26 (0.05-0.48) for XRM-alone and 0.34 (0.11-0.55) forXRM + ABUS (95% confidence interval for the difference in κ, 0.06-0.11). Simulated double reading of XRM + ABUS demonstrated tradeoffs in sensitivity and specificity, but conservative simulated double reading resulted in a significant improvement in both sensitivity (16.7%) and specificity (7.6%) with respect to XRM-alone. A modest, but statistically significant, increase in interreader agreement was observed after interpretation of ABUS.

Abstract BS3-2: Molecular Imaging of Breast Cancer: Visualizing In Vivo Breast Cancer Biology

Abstract The ability to measure biochemical and molecular processes underlies progress in breast cancer biology and treatment. These assays have traditionally been performed by analysis of cell culture or tissue samples. More recently, functional and molecular imaging allows in vivo assay of biochemistry and molecular biology that is highly complementary to tissue-based assay. Molecular imaging can serve and number of roles, from characterization of pre-clinical models, to testing the ability of novel drugs to interact with their intended targets, to characterizing entire burden of disease for patients with breast cancer, to helping direct therapeutic choices and assign their efficacy. This talk will review basic principals of molecular imaging, with an emphasis on those methods of greatest translational potential. The session will discuss the use of pre-clinical models of breast disease to help test and validate new molecular imaging methods, and in turn, the use of molecular imaging to characterize the disease process in the animal models. The session will then review the current state of molecular imaging in breast cancer patients, including methods in routine clinical use, those undergoing advanced clinical trials, and those in early-phase testing. The session is designed for a broad audience, ranging from breast cancer translational scientists to practicing physicians caring for breast cancer patients.

Multimodal Ultrasonic Imaging for Breast Cancer Detection

Abstract Ultrasound is used for breast cancer detection as a technique complementary to mammography, the standard screening method. Current practice is based on reflectivity images obtained with conventional instruments by an operator who positions the ultrasonic transducer by hand over the patient’s body. It is a non-ionizing radiation, pain-free and not expensive technique that provides a higher contrast than mammography to discriminate among fluid-filled cysts and solid masses, especially for dense breast tissue. However, results are quite dependent on the operator’s skills, images are difficult to reproduce, and state-of-the-art instruments have a limited resolution and contrast to show micro-calcifications and to discriminate between lesions and the surrounding tissue. In spite of their advantages, these factors have precluded the use of ultrasound for screening. This work approaches the ultrasound-based early detection of breast cancer with a different concept. A ring array with many elements to cover 360◦ around a hanging breast allows obtaining repeatable and operator-independent coronal slice images. Such an arrangement is well suited for multi-modal imaging that includes reflectivity, compounded, tomography, and phase coherence images for increased specificity in breast cancer detection. Preliminary work carried out with a mechanical emulation of the ring array and a standard breast phantom shows a high resolution and contrast, with an artifact-free capability provided by phase coherence processing.

Fast 3-D Tomographic Microwave Imaging for Breast Cancer Detection

Microwave breast imaging (using electromagnetic waves of frequencies around 1 GHz) has mostly remained at the research level for the past decade, gaining little clinical acceptance. The major hurdles limiting patient use are both at the hardware level (challenges in collecting accurate and noncorrupted data) and software level (often plagued by unrealistic reconstruction times in the tens of hours). In this paper we report improvements that address both issues. First, the hardware is able to measure signals down to levels compatible with sub-centimeter image resolution while keeping an exam time under 2 min. Second, the software overcomes the enormous time burden and produces similarly accurate images in less than 20 min. The combination of the new hardware and software allows us to produce and report here the first clinical 3-D microwave tomographic images of the breast. Two clinical examples are selected out of 400+ exams conducted at the Dartmouth Hitchcock Medical Center (Lebanon, NH). The first example demonstrates the potential usefulness of our system for breast cancer screening while the second example focuses on therapy monitoring.

Advances in molecular imaging for breast cancer detection and characterization

Advances in our ability to assay molecular processes, including gene expression, protein expression, and molecular and cellular biochemistry, have fueled advances in our understanding of breast cancer biology and have led to the identification of new treatments for patients with breast cancer. The ability to measure biologic processes without perturbing them in vivo allows the opportunity to better characterize tumor biology and to assess how biologic and cytotoxic therapies alter critical pathways of tumor response and resistance. By accurately characterizing tumor properties and biologic processes, molecular imaging plays an increasing role in breast cancer science, clinical care in diagnosis and staging, assessment of therapeutic targets, and evaluation of responses to therapies. This review describes the current role and potential of molecular imaging modalities for detection and characterization of breast cancer and focuses primarily on radionuclide-based methods.

On the forward scattering of microwave breast imaging.

Microwave imaging for breast cancer detection has been of significant interest for the last two decades. Recent studies focus on solving the imaging problem using an inverse scattering approach. Efforts have mainly been focused on the development of the inverse scattering algorithms, experimental setup, antenna design and clinical trials. However, the success of microwave breast imaging also heavily relies on the quality of the forward data such that the tumor inside the breast volume is well illuminated. In this work, a numerical study of the forward scattering data is conducted. The scattering behavior of simple breast models under different polarization states and aspect angles of illumination are considered. Numerical results have demonstrated that better data contrast could be obtained when the breast volume is illuminated using cross-polarized components in linear polarization basis or the copolarized components in the circular polarization basis.

Recent Design Development in Molecular Imaging for Breast Cancer Detection Using Nanometer CMOS Based Sensors

As one of the key clinical imaging methods, the computed X-ray tomography can be further improved using new nanometer CMOS sensors. This will enhance the current technique's ability in terms of cancer detection size, position, and detection accuracy on the anatomical structures. The current paper reviewed designs of SOI-based CMOS sensors and their architectural design in mammography systems. Based on the existing experimental results, using the SOI technology can provide a low-noise (SNR around 87.8 db) and high-gain (30 v/v) CMOS imager. It is also expected that, together with the fast data acquisition designs, the new type of imagers may play important roles in the near-future high-dimensional images in additional to today's 2D imagers.

Acousto-optic imaging using a powerful long pulse laser and digital holography.

Acousto-optic tomography is a technique that couples ultrasounds and light in order to measure local optical properties through thick and highly scattering media, e.g. human breast tissues. Thanks to the acousto-optic effect, we can get the optical contrast information given by light and get the spatial localization from the ultrasound longitudinal waves. The use of a powerful long pulse laser (1 ms, 200 mJ) helps to improve the sensitivity of the technique by raising the optical peak power and collect more ultrasound tagged photons. Moreover, its tunable wavelength around 780 nm is appropriate for biological imaging since it is where light has its maximum penetrating depth in tissues. Detection of acousto-optic signals is done by off-axis heterodyne digital holography on a high speed CMOS camera. This enables us to make a tunable spatio-temporal filter with a high signal to noise ratio. Experimentally, this technique enables to image optical absorbers embedded within a thick scattering media (a few centimetres). It is also theoretically possible to use a conventional pulsed ultrasound scanner to generate acousto-optic signals that can at the same time record ultrasound images, which will be a step toward multimodal imaging for breast cancer detection.

Photoacoustic Imaging: An Emerging Optical Modality in Diagnostic and Theranostic Medicine

Photoacoustic imaging, also referred to optoacoustic imaging, is an emerging optical imaging technique that is capable of providing both structural and functional optical information of tissues up to several centimeters deep with scalable ultrasound resolution. The combination of ultrasound spatial resolution and intrinsic rich optical contrast in cancer / inflammatory tissues allow photoacoustic imaging a promising early detection tool in diagnostic medicine. At the same time, the availability of various optical absorbing nanostructures extensively studied in targeted drug delivery extends the capability of photoacoustic imaging to theranostic medicine, where functionalized nanostructures provide photoacoustic imaging contrast and targeting moieties / drug carrier for targeted drug delivery. In this paper, we provide a review of the photoacoustic imaging technique for studies in diagnostic and theranostic medicine. The technical consideration for photoacoustic imaging systems and reconstruction algorithms of structural / quantitative photoacoustic imaging have been introduced. A review of the photoacoustic imaging in breast cancer detection and osteoarthritis evaluation is included in the section of photoacoustic applications in diagnostic medicine, where patient subjects have been already recruited and photoacoustically evaluated. At the end of this paper, a brief review of optical controlled drug release and photoacoustic evaluation is presented as a view to the effort of combining laser induced photoacoustic imaging with laser controlled drug delivery / release in theranostic medicine.

O-83 Digital infrared imaging for breast cancer detection in younger women undergoing breast biopsy

O-83 Digital infrared imaging for breast cancer detection in younger women undergoing breast biopsy

The accuracy of digital infrared imaging for breast cancer detection in women undergoing breast biopsy

Background Mammography has a lower sensitivity for breast cancer detection in younger women and those with dense breasts. Recent improvements in digital infrared breast imaging suggest there may be a role for this technology and we have studied its performance in 100 women prior to breast needle core biopsy (CB). Methods All patients were imaged using a digital infrared breast (DIB) scan (Sentinel BreastScan™) prior to breast biopsy. Analysis of the infrared scans was performed, blinded to biopsy results, in four different ways: Sentinel screening report, Sentinel artificial intelligence (neural network), expert manual review and NoTouch BreastScan a novel artificial intelligence programme. Results Of 106 biopsies performed in 100 women, 65 were malignant and 41 were benign. Sensitivity of Sentinel screening (53%) and Sentinel neural network (48%) was low but analysis with NoTouch software (70%) was much closer to expert manual review (78%). Sensitivity (78%) and specificity (75%) using NoTouch BreastScan were higher in women under 50 and the combination of mammography and DIB, with NoTouch interpretation, in this age group resulted in a sensitivity of 89%. Conclusion DIB using NoTouch is an effective adjunctive test for breast cancer detection in women under 70 and appears to be particularly effective in women under 50 where maximal sensitivity (78%) and specificity (75%) were observed. The combined sensitivity of NoTouch BreastScan and mammography in women under 50 was encouraging at 89%, suggesting a potential way forward for a dual imaging approach in this younger age group.

Laser-induced photoacoustic imaging for breast cancer detection using multivariate image analysis.

Abstract:Time-resolved photoacoustic imaging has been used to characterize breast tissue for the purpose of discriminating between normal and maligned areas of the tissue. Ultrasonic thermoelastic waves were generated in breast tissue by the absorption of nanosecond laser pulses at 193 nm produced by Q-switched Excimer laser in conjunction with a Michelson interferometer used to detect the thermoelastic waves and plot the 2-D and the 3-D image through IR- CCD. The concepts behind the use of photo-acoustic techniques for off-line detection of breast cancer tumor features were presented in earlier research papers [1][2]. This paper illustrates the application of multivariate image analysis (MIA) techniques to detect the presence of tumor features of breast cancer. MIA is used to rapidly detect the presence and quantity of common tumor features as they scanned by an RGB camera. Multiway principal component analysis is used to decompose the acquired three-channel tumor images into a two dimensional principal components (PC) space. Masking score point clusters in the score space and highlighting corresponding pixels in the image space of the two dominant PCs enables isolation of tumor defect pixels based on contrast and color information. The technique provides a qualitative result that can be used for early tumor detection. The proposed technique can potentially be used on-line to prescreen the existence of tumors through vision based systems.

Role of Imaging in Breast Cancer Detection

This article reviews the role of imaging (i.e., mammography, ultrasound, magnetic resonance imaging) in breast cancer detection. Screening and diagnostic indications are outlined for each modality. New mammography screening guidelines are discussed, and risk factors for breast cancer are included.

Role of Imaging in Breast Cancer Detection

This article reviews the role of imaging (i.e., mammography, ultrasound, magnetic resonance imaging) in breast cancer detection. Screening and diagnostic indications are outlined for each modality. New mammography screening guidelines are discussed, and risk factors for breast cancer are included.

HOMOGENEOUS AND HETEROGENEOUS BREAST PHANTOMS FOR ULTRA-WIDEBAND MICROWAVE IMAGING APPLICATIONS

The paper discusses fabrication of homogenous and heterogeneous breast phantoms to simulate the dielectric properties of human breast over the microwave frequency range from 0.5GHz to 13.5GHz. The breast phantoms have stable mechanical conflguration and dielectric properties suitable for microwave imaging experiments particularly ultra-wideband microwave imaging for breast cancer detection.

A Sparsity Regularization Approach to the Electromagnetic Inverse Scattering Problem

We investigate solving the electromagnetic inverse scattering problem using the distorted Born iterative method (DBIM) in conjunction with a variable-selection approach known as the elastic net. The elastic net applies both ℓ1 and ℓ2 penalties to regularize the system of linear equations that result at each iteration of the DBIM. The elastic net thus incorporates both the stabilizing effect of the ℓ2 penalty with the sparsity encouraging effect of the ℓ1 penalty. The DBIM with the elastic net outperforms the commonly used ℓ2 regularizer when the unknown distribution of dielectric properties is sparse in a known set of basis functions. We consider two very different 3-D examples to demonstrate the efficacy and applicability of our approach. For both examples, we use a scalar approximation in the inverse solution. In the first example the actual distribution of dielectric properties is exactly sparse in a set of 3-D wavelets. The performances of the elastic net and ℓ2 approaches are compared to the ideal case where it is known a priori which wavelets are involved in the true solution. The second example comes from the area of microwave imaging for breast cancer detection. For a given set of 3-D Gaussian basis functions, we show that the elastic net approach can produce a more accurate estimate of the distribution of dielectric properties (in particular, the effective conductivity) within an anatomically realistic 3-D numerical breast phantom. In contrast, the DBIM with an ℓ2 penalty produces an estimate which suffers from multiple artifacts.