Image quality of microcalcifications in digital breast tomosynthesis: Effects of projection-view distributions

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98731/1/MPH005703.pd

Virtual clinical trials in medical imaging: a review

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities

Modeling the Anisotropic Resolution and Noise Properties of Digital Breast Tomosynthesis

Digital breast tomosynthesis (DBT) is a 3D imaging modality in which a reconstruction of the breast is generated from various x-ray projections. Due to the newness of this technology, the development of an analytical model of image quality has been on-going. In this thesis, a more complete model is developed by addressing the limitations found in the previous linear systems (LS) model [Zhao, Med. Phys. 2008, 35(12): 5219-32]. A central assumption of the LS model is that the angle of x-ray incidence is approximately normal to the detector in each projection. To model the effect of oblique x-ray incidence, this thesis generalizes Swank\u27s calculations of the transfer functions of x-ray fluorescent screens to arbitrary incident angles. In the LS model, it is also assumed that the pixelation in the reconstruction grid is the same as the detector; hence, the highest frequency that can be resolved is the detector alias frequency. This thesis considers reconstruction grids with smaller pixelation to investigate super-resolution, or visibility of higher frequencies. A sine plate is introduced as a conceptual test object to analyze super-resolution. By orienting the long axis of the sine plate at various angles, the feasibility of oblique reconstruction planes is also investigated. This formulation differs from the LS model in which reconstruction planes are parallel to the breast support. It is shown that the transfer functions for arbitrary angles of x-ray incidence can be modeled in closed form. The high frequency modulation transfer function (MTF) and detective quantum efficiency (DQE) are degraded due to oblique x-ray incidence. In addition, using the sine plate, it is demonstrated that a reconstruction can resolve frequencies exceeding the detector alias frequency. Experimental images of bar patterns verified the existence of super-resolution. Anecdotal clinical examples showed that super-resolution improves the visibility of microcalcifications. The feasibility of oblique reconstructions was established theoretically with the sine plate and was validated experimentally with bar patterns. This thesis develops a more complete model of image quality in DBT by addressing the limitations of the LS model. In future studies, this model can be used as a tool for optimizing DBT

Enhancing the image quality of digital breast tomosynthesis

A novel imaging technology, digital breast tomosynthesis (DBT), is a technique that overcomes the tissue superposition limitation of conventional mammography by acquiring a limited number of X-ray projections from a narrow angular range, and combining these projections to reconstruct a pseudo-3D image. The emergence of DBT as a potential replacement or adjunct to mammographic screening mandates that solutions be found to two of its major limitations, namely X-ray scatter and mono-energetic reconstruction methods. A multi-faceted software-based approach to enhance the image quality of DBT imaging has the potential to increase the sensitivity and specificity of breast cancer detection and diagnosis. A scatter correction (SC) algorithm and a spectral reconstruction (SR) algorithm are both ready for implementation and clinical evaluation in a DBT system and exhibit the potential to improve image quality. A principal component analysis (PCA) based model of breast shape and a PCA model of X-ray scatter optimize the SC algorithm for the clinical realm. In addition, a comprehensive dosimetric characterization of a FDA approved DBT system has also been performed, and the feasibility of a new dual-spectrum, single-acquisition DBT imaging technique has also been evaluated.Ph.D

Improving Image Reconstruction for Digital Breast Tomosynthesis

Digital breast tomosynthesis (DBT) has been developed to reduce the issue of overlapping tissue in conventional 2-D mammography for breast cancer screening and diagnosis. In the DBT procedure, the patient’s breast is compressed with a paddle and a sequence of x-ray projections is taken within a small angular range. Tomographic reconstruction algorithms are then applied to these projections, generating tomosynthesized image slices of the breast, such that radiologists can read the breast slice by slice. Studies have shown that DBT can reduce both false-negative diagnoses of breast cancer and false-positive recalls compared to mammography alone. This dissertation focuses on improving image quality for DBT reconstruction. Chapter I briefly introduces the concept of DBT and the inspiration of my study. Chapter II covers the background of my research including the concept of image reconstruction, the geometry of our experimental DBT system and figures of merit for image quality. Chapter III introduces our study of the segmented separable footprint (SG) projector. By taking into account the finite size of detector element, the SG projector improves the accuracy of forward projections in iterative image reconstruction. Due to the more efficient access to memory, the SG projector is also faster than the traditional ray-tracing (RT) projector. We applied the SG projector to regular and subpixel reconstructions and demonstrated its effectiveness. Chapter IV introduces a new DBT reconstruction method with detector blur and correlated noise modeling, called the SQS-DBCN algorithm. The SQS-DBCN algorithm is able to significantly enhance microcalcifications (MC) in DBT while preserving the appearance of the soft tissue and mass margin. Comparisons between the SQS-DBCN algorithm and several modified versions of the SQS-DBCN algorithm indicate the importance of modeling different components of the system physics at the same time. Chapter V investigates truncated projection artifact (TPA) removal algorithms. Among the three algorithms we proposed, the pre-reconstruction-based projection view (PV) extrapolation method provides the best performance. Possible improvements of the other two TPA removal algorithms have been discussed. Chapter VI of this dissertation examines the effect of source blur on DBT reconstruction. Our analytical calculation demonstrates that the point spread function (PSF) of source blur is highly shift-variant. We used CatSim to simulate digital phantoms. Analysis on the reconstructed images demonstrates that a typical finite-sized focal spot (~ 0.3 mm) will not affect the image quality if the x-ray tube is stationary during the data acquisition. For DBT systems with continuous-motion data acquisition, the motion of the x-ray tube is the main cause of the effective source blur and will cause loss in the contrast of objects. Therefore modeling the source blur for these DBT systems could potentially improve the reconstructed image quality. The final chapter of this dissertation discusses a few future studies that are inspired by my PhD research.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144059/1/jiabei_1.pd

Image reconstruction and imaging configuration optimization with a novel nanotechnology enabled breast tomosynthesis multi-beam X-ray system

Digital breast tomosynthesis is a new technology that provides three-dimensional information of the breast and makes it possible to distinguish the cancer from overlying breast tissues. We are dedicated to optimizing image reconstruction and imaging configuration for a new multi-beam parallel digital breast tomosynthesis prototype system. Several commonly used algorithms from the typical image reconstruction models which were used for iso-centric tomosynthesis systems were investigated for our multi-beam parallel tomosynthesis imaging system. The representative algorithms, including back-projection (BP), filtered back-projection (FBP), matrix inversion tomosynthesis reconstruction (MITS), maximum likelihood expectation maximization (MLEM), ordered-subset maximum likelihood expectation maximization (OS-MLEM), simultaneous algebraic reconstruction technique (SART), were implemented to fit our system design. An accelerated MLEM algorithm was proposed, which significantly reduced the running time but had the same image quality. Furthermore, two statistical variants of BP reconstruction were validated for our tomosynthesis prototype system. Experiments based on phantoms and computer simulations show that the prototype system combined with our algorithms is capable of providing three-dimensional information of the objects with good image quality and has great potentials to improve digital breast tomosynthesis technology. Four methodologies were employed to optimize the reconstruction algorithms and different imaging configurations for the prototype system. A linear tomosynthesis imaging analysis tool was used to investigate blurring-out reconstruction algorithms. Computer simulations of sphere and wire objects aimed at the performance of out-of-plane artifact removal. A frequency-domain-based methodology, relative NEQ(f) analysis, was investigated to evaluate the overall system performance based on the propagation of signal and noise. Conclusions were made to determine the optimal image reconstruction algorithm and imaging configuration of this new multi-beam parallel digital breast tomosynthesis prototype system for better image quality and system performance