X-ray phase sensitive imaging has been employed in the preclinical settings for more than two decades. The advancement in the technology has allowed to potentially translate this innovative imaging technique to the clinical environment. In-line phase sensitive imaging technique has shown promising potential to be used for breast cancer imaging. A high energy phase sensitive breast tomosynthesis (PBT) prototype system based on the inline phase sensitive imaging technique has been developed for the potential imaging in clinical environment. The prototype system incorporates a microfocus x-ray tube and a flat panel detector having a pixel pitch of 70μm. The microfocus x-ray tube has a tungsten (W) anode, Beryllium (Be) output window and a focal spot size that ranges from 18-50μm, depending on the output power. The x-ray tube/detector configuration produces a geometric magnification (M) of 2.2 and acquires 9 projection views within 15 degrees or 30 projection views within 30 degrees in stop-andshoot scanning mode. A single distance phase retrieval scheme method based on the Phase-Attenuation Duality (PAD) principle is applied on the angular projection views. A filtered back-projection operation reconstructs a set of tomogram slices at 1mm incremental depth within the breast along the z-direction. American College of Radiology phantom images demonstrate that both 2D and tomosynthesis images acquired on the prototype system meet the minimum criteria set by the Mammography Quality Standard Act. We have also imaged mastectomy specimens with the PBT prototype system at the University of Utah Huntsman Cancer Hospital. PBT 2D images and tomosynthesis images slices demonstrate image quality comparable to a conventional digital breast tomosynthesis clinical system.
To reduce cumulative radiation exposure and lifetime risks for radiation-induced cancer from breast cancer screening, we developed neural network convolution (NNC) deep learning for radiation dose reduction in digital breast tomosynthesis (DBT). Our NNC deep learning employed patched-based neural network regression in a convolutional manner to convert lower-dose (LD) to higher-dose (HD) tomosynthesis images. We trained our NNC with quarter-dose (25% of the standard dose: 12 mAs at 32 kVp) raw-projection images and corresponding “teaching” higher-dose (HD) images (200% of the standard dose: 99 mAs at 32 kVp) of a breast cadaver phantom acquired with a DBT system (Selenia Dimensions, Hologic, Inc, Bedford, MA). Once trained, NNC no longer requires HD images. It converts new LD images to images that look like HD images; thus the term “virtual” HD (VHD) images. We reconstructed tomosynthesis slices on a research DBT system. To determine a dose reduction rate, we acquired 4 studies of another test phantom at 4 different radiation doses (1.35, 2.7, 4.04, and 5.39 mGy entrance dose). Structural SIMilarity (SSIM) index was used to evaluate the image quality. Our cadaver phantom experiment demonstrated up to 79% dose reduction. For further testing, we collected half-dose (50% of the standard dose: 32±14 mAs at 33±5 kVp) and full-dose (100% of the standard dose: 68±23 mAs at 33±5 kvp) images of 10 clinical cases with the DBT system at University of Iowa Hospitals and Clinics. Our NNC converted half-dose DBT images of the 10 clinical cases to VHD DBT images that were equivalent to full-dose DBT images, according our observer rating study of 10 breast radiologists. Thus, we achieved 50% dose reduction without sacrificing the image quality.
The objective of this study was to compare the detectability of simulated objects within a dense breast phantom using high energy x-rays for phase sensitive breast imaging in comparison with a conventional imaging system. A 5 cm thick phantom was used which represented a compressed breast consisting of 70% glandular and 30% adipose tissue ratio in non-uniform background. The phantom had a 6 × 6 matrix of holes with milled depths ranging from 1 to 0.1 mm and diameters ranging from 4.25 to 0.25 mm representing simulated tumors. The in-line phase sensitive prototype was equipped with a micro-focus x-ray source and a flat panel detector with a 50 μm pixel pitch, both mounted on an optical rail. Phase contrast image of the phantom was acquired at 120 kVp, 4.5 mAs at source to object distance (SOD) of 68 cm and source to image detector distance (SIDD) of 170 cm with a geometric magnification (M) of 2.5. A 2.5 mm aluminum (Al) filter was used for beam hardening. The conventional image was acquired using the same porotype with the phantom in contact with the detector at 40 kVp, 12.5 mAs under SID = 68 cm. The mean glandular dose (Dg) for both the acquisitions was 1.3 mGy. The observer study and CNR analyses indicated that the phase contrast image had higher disk detectability as compared to the conventional image. The edge enhancement provided by the phase sensitive images warrants in identifying boundaries of malignant tissues and in providing optimal results in phase retrieval process. The potential demonstrated by this study for imaging a dense breast with a high energy phase sensitive x-ray imaging to improve tumor detection in warrants further investigation of this technique.
We report our continued study of phase-contrast diffuse optical tomography (PCCDOT) for evaluating its
fidelity in distinguishing malignant breast lesions form benign ones. 144 breast masses were examined
from 134 patients, aging from 22~82 with the mean age of 56. Tissue optical parameters including
refractive index, and absorption and scattering coefficients, were obtained and compared with their
corresponding biopsy/pathology reports. In consistent with our previous study, malignant masses tended to
have a decreased refractive index relative to their surrounding normal tissue, which acts as the key
character to differentiate them from benign masses. The results show that the specificity is improved
significantly over the previous smaller scale study (85% vs. 70%) due to the addition of significantly more
benign cases, while the sensitivity stays about the same (81% vs. 82%) due to the similar number of
malignant cases used compared to the smaller scale study.
An automated procedure for detecting breast cancer using near-infrared (NIR) tomographic images is presented. This classification procedure automatically extracts attributes from three imaging parameters obtained by an NIR imaging system. These parameters include tissue absorption and reduced scattering coefficients, as well as a tissue refractive index obtained by a phase-contrast-based reconstruction approach. A support vector machine (SVM) classifier is utilized to distinguish the malignant from the benign lesions using the automatically extracted attributes. The classification results of in vivo tomographic images from 35 breast masses using absorption, scattering, and refractive index attributes demonstrate high sensitivity, specificity, and overall accuracy of 81.8%, 91.7%, and 88.6% respectively, while the classification sensitivity, specificity, and overall accuracy are 63.6%, 83.3%, and 77.1%, respectively, when only the absorption and scattering attributes are used. Furthermore, the automated classification procedure provides significantly improved specificity and overall accuracy for breast cancer detection compared to those by an experienced technician through visual examination.
A high spatial resolution computed radiography (CR) detector was used to develop a phase contrast x-ray imaging prototype with a microfocus x-ray source. The phase contrast imaging was realized with appropriate magnifications. Meanwhile, the basic system parameters, such as the modulation transfer function (MTF) and detective quantum efficiency (DQE) were measured with and without phase contrast effect. The experimental results indicated that the phase contrast can enhance the detectability of the imaging system.
In this report, a phase-contrast diffuse optical tomography system, which can measure the refractive indices
of human breast masses in vivo, is described. To investigate the utility of phase-contrast diffuse optical
tomography (PCDOT) for differentiation of malignant and benign breast masses in humans, and to compare
PCDOT with conventional diffuse optical tomography (DOT) for analysis of breast masses in humans. 35
breast masses were imaged in 33 patients (mean age = 51 years; range 22-80 years) using PCDOT. Images
characterizing the tissue refractive index, absorption and scattering of breast masses were obtained with a
finite element-based reconstruction algorithm. The accuracies of absorption and scattering images were
compared with images of refractive index in light of the pathology results. Absorption and scattering images
were unable to accurately discriminate benign from malignant lesions. Malignant lesions tended to have
decreased refractive index allowing them to discriminate from benign lesions in most cases. The sensitivity,
specificity, false positive value, and overall accuracy for refractive index were 81.8%, 70.8%, 29.2%, and
74.3%, respectively. Overall we show that benign and malignant breast masses in humans demonstrate
different refractive index and differences in refractive index properties can be used to discriminate benign
from malignant masses in patients with high accuracy. This opens up a new avenue for improved breast
cancer detection using NIR diffusing light.
Breast cancer is the second leading cause of cancer death in women in the United States. Currently, X-ray
mammography is the method of choice for screening and diagnosing breast cancer. However, this 2D projective
modality is far from perfect; with up to 17% breast cancer going unidentified. Over past several years, there has been an
increasing interest in cone-beam CT for breast imaging. However, previous methods utilizing cone-beam CT only
produce approximate reconstructions. Following Katsevich's recent work, we propose a new scanning mode and
associated exact cone-beam CT method for breast imaging. In our design, cone-beam scans are performed along two
tilting arcs for collection of a sufficient amount of data for exact reconstruction. In our Katsevich-type algorithm, conebeam
data is filtered in a shift-invariant fashion and then backprojected in 3D for the final reconstruction. This approach
has several desirable features. First, it allows data truncation unavoidable in practice. Second, it optimizes image quality
for quantitative analysis. Third, it is efficient for sequential/parallel computation. Furthermore, we analyze the
reconstruction region and the detection window in detail, which are important for numerical implementation.
This paper reports the results of our investigation in a phantom imaging experiments with a prototype phase contrast x-ray imaging system. Two types of phantoms, including a standard mammography phantom, and a contrast-detail phantom, were imaged, and the impact of the x-ray focal spot sizes and the magnification ratios were investigated. The images acquired with phase contrast prototype system shows better detectability as compared with the images acquired under conventional attenuation base x-ray imaging conditions.
The current mammography uses analog screen film for acquisition, storage, and display, however, there still remain many improvements to be made such as increasing sensitivity, higher contrast resolution, and wider dynamic range. Also, the analog mammography shows inadequate results for young women under the age of 40 because of the radiodense breast tissue. Thus, it is essential to improve the current standard for greater chance of detection with a minimum amount of radiation exposed to the patient. The goal of this project was to investigate the contrast detail detectability of a prototype Full Field Digital Mammography system using simulated lesions from CDMAM phantom.
This paper presents the key techniques of a stereo- fluoroscopic image-guided robotic biopsy system: 3D position reconstruction, 3D path planning, path registration and robot trajectory control with safety considerations. This system automatically adjusts the needle inserting path according to a real-time 3D position error feedback. This system is particularly applicable to the soft tissue and organ biopsy, with advantages of increased accuracy, short completion time and minimum invasiveness to the patient. Simulation shows the safety and accuracy of this robotic biopsy system.
KEYWORDS: Imaging systems, 3D image processing, X-rays, X-ray imaging, 3D modeling, Digital imaging, Mathematical modeling, X-ray sources, Systems modeling, Digital x-ray imaging
A mathematical model for x-ray stereo-image guidance system is present in this paper. Based on this model, the relationship between 3D point and its 2D image projection is expressed as a 4 X 4 transformation matrix, which is composed by a series of coordinate transformations including translation, rotation and perspective projection. The principle method to recover 3D object position from stereo- image pairs is derived according to the system model we presented. The 3D object positional accuracy and system sensitivity of the x-ray stereo-image guidance system is discussed, and effectiveness of system incoherent parameter is revealed. The result shows that the absolute positioning error is proportion to the absolute position of the object under world coordinate system, and the system sensitivity is inversely proportional to the object position. Our result is very helpful to determine the system parameters in building a costly prototype. Such parameters include x-ray tubes separation, detector size, digital image resolution, SID and so on. The experiment was performed and the result was consistent with the expected value predicated by theoretic analysis. Our promising application of this method lies in digital mammography imaging guidance, but applications in other types of radiographic imagine are possible also.
This paper reports the results of our investigation into developing a theoretical model to predict the contrast-detail detectability in digital radiography. The equations presented in this paper are a continuation of our previous study on quasi-ideal observer signal-to-noise ratio and lesion detectability. In this project, numerical calculations were performed to determine contrast-detail curves of CCD and other x-ray imaging systems under clinical mammographic conditions. A contrast-detail phantom was imaged to validate the calculations predicted by our theoretical model. The experimental measurements were well predicted by the model's calculations. The theoretical model and the experimental techniques investigated in this research will help mammographers, scientists and engineers to optimize design trade-offs for emerging digital mammographic systems. It will also leverage efforts toward the development of practical techniques that can be performed at non-academic clinical sites, to quantitatively access the performance of new or existing digital radiography systems.
This paper presents results of experiments performed to find parameters affecting signal, noise and Detective Quantum Efficiency of x-ray imaging systems with potential for use in mammography.
This paper describes experiments performed to determine image quality of three x-ray imaging systems designed for stereotactic breast needle biopsy: A system developed in-house, a LoRad DSM and a Fischer MammoVision. All systems have been successfully used to perform stereotactic breast needle biopsies and preoperative needle localizations. They all successfully decrease the time for stereotactic needle biopsy procedures. The systems are being characterized with respect to image quality for a variety of mammographic x-ray screens. The sensitivity can be as high as 96 ADU/mR and as low as 28 ADU/mR, depending on the phosphor screen and the gain used. The response is linear with respect to x-ray exposure. The highest spatial resolution found was on the order of 10 lp/mm, which is the Nyquist frequency for systems with 1024 pixels at a linear field of 5 cm. The noise at zero spatial frequency was found to be mainly determined by x-ray photon noise.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.