Stephen J. Glick, PhD - Faculty in Nuclear Medicine

Current Research Interests

Positron Emission Tomographic (PET) Imaging Systems

Monte Carlo modeling of PET systems

Optimization of PET systems

3D tomographic reconstruction methods for PET

Time-of-flight PET

Evaluation of image quality

Volumetric X-ray Imaging of the Breast

Flat-panel, cone-beam CT breast imaging

Breast tomosynthesis

Optimization of breast imaging systems

Current Grant Funding

Title: "Feasibility of CT Mammography Using Flat-Panel Detectors" – NIH/NIBIB – EB02133 ,

Detection of lesions in planar mammograms is a difficult task, predominantly due to the masking effect of superimposed parenchymal breast patterns. Tomographic imaging can provide the radiologist with image slices through the three-dimensional (3D) breast, possibly reducing this masking effect. The goal of the proposed research is to investigate the feasibility of using an amorphous silicon, flat-panel imager for volumetric computed tomography (CT) of the breast. Our hypothesis is that dedicated CT mammography using state-of-the-art digital detectors can provide high quality images and three-dimensional visualization of breast tissue, with a radiation dose approximately equivalent to that given in screening mammography. We propose to investigate the characteristics of such a system by integrating a commercial prototype, flat-panel imager, with an optical bench plate containing precision rotational and translational stages. This would allow the acquisition of projection images by rotating phantoms in angular steps over 360^o. We also propose to theoretically investigate optimal CT mammography system configurations using mathematical models of signal and noise propagation through the flat-panel detector, and realistic models of the lesion detection task in breast imaging. Design and acquisition parameters such as tomographic sampling requirements, imaging geometry, x-ray converter characteristics, and x-ray energy spectrum incident on the breast will be investigated. Previous reports have suggested great potential for tomographic breast imaging. To evaluate improvements in tomographic mammography, if any, we plan to compare lesion detection accuracy using human observer studies and simulated images generated with planar mammography, tomosynthesis, and CT mammography. An important component of these observer studies will be the use of realistic models for lesions and breast tissue. These models will be determined based on the statistical characterization of surgically removed lesion and breast tissue

Title: "Iterative Reconstruction for Breast Tomosynthesis" NIH/NCI - CA102758

The detection of lesions in conventional mammography is a difficult task, predominantly due to the masking effect of superimposed parenchymal breast patterns. Limited angle, tomographic mammography, also referred to as breast tomosynthesis, is a technique that has been proposed to reduce this masking effect, by providing the radiologist with tomographic image slices through the breast. The goal of the proposed research is to investigate the use of statistically based iterative reconstruction (IR) methods for breast tomosynthesis. Statistical IR methods have a number of potential advantages over some previously proposed tomosynthesis methods including; 1) a more accurate modeling of the noise in the data, 2) the capability for modeling the physics of x-ray transport, thus providing an integrated approach for compensation of scatter and detector blur, and 3) the capability of incorporating a priori information on the object to be reconstructed. Our hypothesis is that breast tomosynthesis using statistical IR methods can provide improved detection of malignant lesions as compared to backprojection tomosynthesis, as well as to conventional two-view digital mammography. To test this hypothesis, human observer psychophysical studies will be performed comparing conventional two-view digital mammography and tomosynthesis. We also propose to investigate a number of issues related to the acquisition process of breast tomosynthesis including; 1) alternative acquisition geometries, 2) the impact of varying levels of breast compression, 3) the impact of scatter, and 4) the optimal anti-scatter grid. Evaluation and optimization of different imaging system designs and acquisition processes will be conducted by evaluating lesion detection accuracy using realistically simulated tomosynthesis breast images.

Office: S7-322H
Phone: 508-856-6553
E-mail: Stephen.Glick@umassmed.edu

Postdoctoral Position Available

Posted: 04/11/06

A postdoctoral fellowship is available within the Medical Physics group at the University of Massachusetts Medical School, Department of Radiology. The Medical Physics group consists of physicists, engineers, and mathematicians,working on medical imaging problems. The successful candidate will work on projects related to x-ray tomosynthesis and CT, primarily focused on breast imaging.

Candidates must have a doctoral degree in medical physics, physics, engineering or computer science. Proven expertise in computer programming (C and C++) is essential as is familiarity with Unix and using a large computer cluster. Experience with digital radiographic imaging systems, x-ray imaging experiments, mathematics through linear algebra,digital signal processing, and tomographic image reconstruction is also essential.

This position requires excellent communication skills with a focus on scientific writing and presenting research at conferences. The position carries a minimum two-year commitment, and promotion to junior faculty is possible.

To apply, send a letter of application, a curriculum vitae, a list of graduate courses, and names of three references to: Stephen Glick, Ph.D., University of Massachusetts Medical School, Division of Nuclear Medicine, 55 Lake Avenue North,Worcester , MA, 01655 , or Stephen.Glick@umassmed.edu.