Andrzej Krol, PhD
750 East Adams Street
Syracuse, NY 13210
Clinical Section Affiliations
- Radiology: Clinical Radiological Physics Section, Diagnostic Division, Image Science and Informatics, Nuclear Medicine
Research Programs and Affiliations
- Biomedical Sciences Program
- Center for Psychiatric Neuroimaging
- Research Pillars
Education & Fellowships
- Fellowship: SUNY Upstate Medical University, 1994, Medical Physics
- Postdoctoral Fellow: SUNY Stony Brook, 1989
- PhD: Warsaw University, Poland, 1980
- MS: Warsaw University, Poland, 1974
Tomographic reconstruction in Single Photon Emission Tomography (SPECT) and Positron Emission Tomography (PET), especially for brain and cardiac imaging. Breast cancer detection and imaging using Positron Emission Mammography (PEM), PET, Magnetic Resonance Imaging (MRI) including Contrast – Enhanced (CE) MRI, MR Diffusion Tensor Imaging (DTI) and MR Spectroscopy (MRS). Multimodality (PEM, PET/CT, CE-MRI, x-ray mammography) nonrigid medical image registration and fusion. Quantification of regional blood flow and perfusion defects in brain using SPECT and PET. Dosimetry in Nuclear Medicine.
Physics of Nuclear Medicine and Nuclear Cardiology, emission tomography
Advanced tomographic reconstruction in PET and SPECT. Breast cancer detection and imaging using molecular, MR and x-ray imaging. Nonrigid multimodality breast image registration and fusion. Advanced breast cancer lumpectomy. Ultrafast laser-based x-ray source for biomedical imaging. Advanced tomographic reconstruction in cone-beam micro-CT.
Specialties & Certification
- Medical Nuclear Physics
Diseases & Conditions Treated
- Thyroid Cancer
- Thyroid Disease
- Adults and Children
- Heart Nuclear Imaging
- Heart Nuclear Stress Testing
- Nuclear Imaging
- Radionuclide Scanning
- American Roentgen Ray Society (ARRS)
- New York Academy of Sciences
- American College of Radiology (ACR)
- Society of Nuclear Medicine (SNM)
- American Association of Physicists in Medicine
Current Hospital Privileges
- Upstate University Hospital
Languages Spoken (Other Than English)
Link to PubMed (Opens new window. Close the PubMed window to return to this page.)
Ultrafast laser-based x-ray in-vivo phase-contrast micro-CT
Emerging photonic technologies, such as ultrafast lasers, provide a new paradigm for overcoming the limitations of traditional biomedical imaging modalities. We are developing in-line x-ray phase-contrast micro-CT system that will utilize an ultrafast laser-based x-ray (ULX) source. This new source produces x rays through irradiation of a solid target by the laser beam. Any solid (metal or non-metal) can be used as a target. ULX delivers more power in x rays than a conventional microfocal tube is able to provide, thus allowing for much faster scans. Further, ULX generates narrow x ray spectra that consist mainly of characteristic lines. These can be easily tailored (by changing laser beam target) to the imaging task. The phase-contrast micro-CT will allow high-resolution measurements of the spatial distribution of the real (x-ray phase-shift) and the imaginary (x-ray absorption) components of the x-ray refractive index in a living animal. This is in contrast to conventional micro-CT, using a microfocal x-ray tube, which can only map 3D distribution of the x-ray absorption coefficient. Therefore, we expect that opening of the new channel of information provided by the x-ray phase-shift 3D mapping, in addition to conventional absorption map measurement, will significantly increase soft tissue low-contrast resolution of micro-CT without any dose increase, thus allowing improved imaging of cancer in small animal models. In due course, this method could be expanded to clinical CT scanners, providing that the high average power ultrafast lasers become available.
Nonrigid PET and MRI Breast Image Registration
We implemented nonrigid registration method for PET and MRI nonrigid breast-image registration that utilizes fiducial skin markers (FSMs) and finite element method (FEM). It is being tested in the ongoing IRB-approved research protocol. It requires careful patient prone positioning to assure that the stress conditions in the imaged breast tissue are not significantly changed between the scans. We demonstrate that under such conditions the observed FSM displacement vectors between MRI and PET distributed piecewise linearly over the breast volume produce deformed FEM mesh that reasonably approximates nonrigid deformation of the breast tissue. This method is robust, does not require difficult-to-obtain patient-specific biomechanical tissue data and could be fully automated. The estimated registration accuracy is better than 3 mm.
Nonrigid Registration of Dynamic Breast F-18-FDG PET/CT Images
We implemented this protocol to correct for motion artifacts in dynamic breast F-18-FDG PET/CT images, to improve differential-image quality, and to increase accuracy of time-activity curves. Dynamic PET studies, with patients prone, and breast suspended freely employed a protocol with 50 frames, each 1-minute long. A 10 s long CT scan was acquired immediately before the first PET frame. F-18-FDG was administered during the first PET time frame. Fiducial skin markers (FSMs) each containing ~0.5 ?Ci of Ge-68 were taped to each breast. In our PET/PET registration approach we utilized CT data and the finite element method (FEM). We observe that contrast and spatial definition of metabolically hyperactive regions are superior in registered images compared to unregistered images.
Advanced Brain SPECT reconstruction with 3D Total Variation Regularization and a fully 3D System Model
In order to improve tomographically reconstructed image quality, we have implemented a fully 3D reconstruction, using an ordered subsets expectation maximization (OSEM) algorithm for fan-beam collimator (FBC) SPECT, along with a volumetric system modelófan-volume system model (FVSM), a modified attenuation compensation, a 3D depth- and angle-dependent resolution and sensitivity correction, and a 3D total variation (TV) regularization. It is being tested in the ongoing IRB-approved research protocol. We are performing comparative studies between our algorithm (OSEM-FVSM) and standard-of-care clinical FBP algorithm. Initial results indicate overall improvement in the image quality has been observed, including better axial and transaxial resolution, better integral uniformity, higher contrast-to-noise ration between the gray matter and the white matter, and better accuracy and lower bias in OSEM-FVSM, compared to clinical FBP.
Fusion of SPECT and MRI images for improved localization of parathyroid adenomas in patients with persistent or recurrent hyperparathyroidism
We have implemented this method to improve accuracy and preoperative localization of parathyroid adenomas (PA). To facilitate minimally invasive surgical approach to PA, as opposed to open cervicotomy and bilateral neck exploration. It is being tested in the ongoing IRB-approved research protocol. MRI and SPECT images are acquired on the same patients with fiducial skin markers (FSMs) placed on patientís thorax and neck. MRI is performed at 3T magnet using a neck surface coil and T2-weigted spin-echo sequences optimized for the high-resolution neck/chest soft tissue imaging. SPECT images were acquired from the level of the submandibular glands through the mediastinum: (i) 1 mCi of Tc-99m pertechnetate; (ii) 15 min. and (iii) 120 min. after administration of 30 mCi of Tc-99m sestamibi. A deformable finite element model (FEM) has been implemented for accurate nonrigid registration and fusion of SPECT and MRI images. Application of our fusion and registration method allowed creation a detailed anatomic map of the neck/thorax from MRI accurately combined with functional map from SPECT for improved preoperative localization of the parathyroid adenomas.
Quantification of differences between normal and abnormal neuroanatomy in mouse model at the cellular level
This research aims at improvement over current methodologies for objectively, accurately and quantitatively assessing differences in neuroanatomy between samples from normal and abnormal brain tissue from mouse models. This project involves: (i) Volume synthesis (combination into one volume smaller volumes imaged at any given time by laser scanning microscopy); (ii) Segmentation of nuclei; (iii) Analysis of cytoarchitecture differences between mutant and normal brain.
Faculty Profile Shortcut: http://www.upstate.edu/faculty/krola
Sue Stearns, PhD
Associate Professor of Cell and Developmental Biology
Sue Stearns, PhD, is one of four faculty members who teach Gross Anatomy to first-year medical students at SUNY Upstate. Students routinely cite this course as a favorite.
Steven Youngentob, PhD
Associate Dean of Basic Research and Graduate Studies
Steven Youngentob, PhD, is at the forefront of research into alcohol addiction.