Paul Licato

Adjunct Associate Professor Milwaukee School of Engineering

  • Milwaukee WI

Paul Licato is an expert in the physics and clinical applications of medical imaging.

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Milwaukee School of Engineering

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Education, Licensure and Certification

B.S.

Mathematics and Physics

University of Wisconsin-Milwaukee

1982

M.S.

Physics

University of Wisconsin-Milwaukee

1984

Biography

Paul Licato is an adjunct assistant professor in the Electrical, Computer and Biomedical Engineering Department at MSOE. He has been a technical innovator in the medical imaging field for more than 30 years. He spent 26 years at GE Healthcare where he contributed to the development of ultra-fast MRI imaging, dual energy computed tomography (CT), CT brain perfusion and image reconstruction improvements for positron emission tomography (PET). He managed several clinical research patient studies in support of the development and regulatory approval of PET/MRI hybrid scanning, interventional x-ray and digital breast tomosynthesis mammography. He has 22 U.S. Patents. Mr. Licato has a BS and MS in physics from the University of Wisconsin - Milwaukee.

Areas of Expertise

Medical Device Clinical Research
X-Ray Imaging
Computed Tomography
Medical Imaging
Magnetic Resonance Imaging
Positron Emission Tomography
Medical Device Regulation

Patents

System architecture for medical imaging systems

U.S. Patent # 6,348,793

2002

Method and apparatus for managing peripheral devices in a medical imaging system

U.S. Patent # 6,356,780

2002

Method and apparatus for defining a three-dimensional imaging

U.S. Patent # 6,757,417

2004

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Selected Publications

Multi-material decomposition of spectral CT images

Medical Imaging 2010: Physics of Medical Imaging

Mendonça, P.R., Bhotika, R., Maddah, M., Thomsen, B., Dutta, S., Licato, P.E., Joshi, M.C.

2010

Spectral Computed Tomography (Spectral CT), and in particular fast kVp switching dual-energy computed tomography, is an imaging modality that extends the capabilities of conventional computed tomography (CT). Spectral CT enables the estimation of the full linear attenuation curve of the imaged subject at each voxel in the CT volume, instead of a scalar image in Hounsfield units. Because the space of linear attenuation curves in the energy ranges of medical applications can be accurately described through a two-dimensional manifold, this decomposition procedure would be, in principle, limited to two materials. This paper describes an algorithm that overcomes this limitation, allowing for the estimation of N-tuples of material-decomposed images. The algorithm works by assuming that the mixing of substances and tissue types in the human body has the physicochemical properties of an ideal solution, which yields a model for the density of the imaged material mix. Under this model the mass attenuation curve of each voxel in the image can be estimated, immediately resulting in a material-decomposed image triplet. Decomposition into an arbitrary number of pre-selected materials can be achieved by automatically selecting adequate triplets from an application-specific material library. The decomposition is expressed in terms of the volume fractions of each constituent material in the mix; this provides for a straightforward, physically meaningful interpretation of the data. One important application of this technique is in the digital removal of contrast agent from a dual-energy exam, producing a virtual nonenhanced image, as well as in the quantification of the concentration of contrast observed in a targeted region, thus providing an accurate measure of tissue perfusion.

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Initial use of fast switched dual energy CT for coronary artery disease

Medical Imaging 2010: Physics of Medical Imaging

Pavlicek, W., Panse, P., Hara, A., Boltz, T., Paden, R., Yamak, D., Licato, P., Chandra, N., Okerlund, D., Dutta, S., Bhotika, R.

2010

Coronary CT Angiography (CTA) is limited in patients with calcified plaque and stents. CTA is unable to confidently differentiate fibrous from lipid plaque. Fast switched dual energy CTA offers certain advantages. Dual energy CTA removes calcium thereby improving visualization of the lumen and potentially providing a more accurate measure of stenosis. Dual energy CTA directly measures calcium burden (calcium hydroxyapatite) thereby eliminating a separate non-contrast series for Agatston Scoring. Using material basis pairs, the differentiation of fibrous and lipid plaques is also possible. Patency of a previously stented coronary artery is difficult to visualize with CTA due to resolution constraints and localized beam hardening artifacts. Monochromatic 70 keV or Iodine images coupled with Virtual Non-stent images lessen beam hardening artifact and blooming. Virtual removal of stainless steel stents improves assessment of in-stent re-stenosis. A beating heart phantom with 'cholesterol' and 'fibrous' phantom coronary plaques were imaged with dual energy CTA. Statistical classification methods (SVM, kNN, and LDA) distinguished 'cholesterol' from 'fibrous' phantom plaque tissue. Applying this classification method to 16 human soft plaques, a lipid 'burden' may be useful for characterizing risk of coronary disease. We also found that dual energy CTA is more sensitive to iodine contrast than conventional CTA which could improve the differentiation of myocardial infarct and ischemia on delayed acquisitions. These phantom and patient acquisitions show advantages with using fast switched dual energy CTA for coronary imaging and potentially extends the use of CT for addressing problem areas of non-invasive evaluation of coronary artery disease.

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Comparison of Iterative and Filtered Nack Projection Techniques for Abdominal CT: A Prospective Double-Blinded Clinical Study

American Journal of Roentgenology

Singh, S., Kalra, M., Hsieh, J., Doyle, M., Licato, P., Blake, M.

2010

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