HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Slomka, P. J. Search for Related Content PubMed PubMed Citation Articles by Slomka, P. J.

Software Approach to Merging Molecular with Anatomic Information

Departments of Imaging and Medicine, Cedars-Sinai Medical Center and UCLA School of Medicine, Los Angeles, California; and Department of Diagnostic Radiology and Nuclear Medicine, University of Western Ontario, London, Ontario, Canada

View larger version (32K): [in a new window]   FIGURE 1. Concept of image registration based on mutual information (MI) is explained using example of PET and CT. Separate PET and CT image intensity histograms are derived from PET and CT, which contain frequencies (f) of occurrence for specific voxel values in 3D volumes (p = PET, c = CT). Additional 2D image histogram is created from combination of PET and CT data, in which frequencies of occurrence for particular PET/CT voxel intensity pairs (p, c), both at same location, are calculated. Subsequently, PET and CT image entropies are calculated from PET and CT histograms, and 2D PET/CT histogram is used to calculate joint entropy. Joint entropy is smallest and, consequently, MI is largest when images are closely aligned and 2D histogram is least dispersed. Search is performed, which continuously modifies 3D shifts (X,Y,Z) and rotations (XY, XZ, YZ), each time transforming PET data. Although it is possible to perform image registration using joint entropy only, inclusion of separate PET and CT entropies is needed when portions of PET volume could move outside of overlapping field of view.

View larger version (60K): [in a new window]   FIGURE 2. Example of image warping. (A) Fusion of diagnostic CT acquired in inspiration with stand-alone PET using linear registration. Note gross misalignment of tumor and diaphragm. (B) Same CT images fused with emission PET images after automatic warping correction (11). Patient data acquired at Department of Nuclear Medicine/PET Center, Zentralklinik Bad Berka, Germany.

View larger version (38K): [in a new window]   FIGURE 3. Fusion of 123I-ß-carbomethoxyiodophenyl tropane SPECT neuroreceptor images with MRI. MR images can be used to provide anatomic region of interest for basal ganglia, thus avoiding quantification errors resulting from blurred SPECT boundaries. Such anatomic information also potentially can be used for partial volume correction. Images courtesy of Henryk Barthel, MD, Leipzig University, Germany.

View larger version (79K): [in a new window]   FIGURE 4. Two patients imaged with SPECT 111In-capromab pendetide images registered by software with MRI. Patient without involvement of neurovascular bundles (yellow arrows) imaged with MRI (A) and with MRI/SPECT fusion (B). Second patient with uptake in left neurovascular bundle imaged with MRI (C) and with MRI/SPECT fusion (D). Fused images aided planning of brachytherapy in these patients. Images courtesy of Dr. Samuel Kipper, MD, Medical Director, Pacific Coast Imaging, Irvine, CA.

View larger version (68K): [in a new window]   FIGURE 5. Staging and evaluation of chemotherapy response in non-Hodgkin’s lymphoma with software registration. 18F-FDG PET examinations defined 2 lesions: hypermetabolic substernal, indicating continuing active disease, in what had been decrease in size noted on CT, and an additional small focal area in right paratracheal location. Lesions are shown on maximum intensity projection view (A, left) and corresponding transaxial slices (A, right). With image coregistration, extent of patent’s disease is defined as involving an osseous lesion not appreciated on CT alone. (B) Subsequent MR evaluation and MRI/PET fusion confirmed PET osseous lesion (arrow). PET with MRI coregistration confirmed osseous involvement and location that dramatically changed therapeutic approach. Images courtesy of John Vansant, MD, Providence Medical Center, Portland, OR.

View larger version (65K): [in a new window]   FIGURE 6. Application of software registration in radiotherapy. (A) Stand-alone whole-body 18F-FDG PET and thoracic CT images are registered using mutual information method. Both emission (top left) and transmission maps (bottom left) were used by computer algorithm. Note flat shape of bed used for simulation CT. Similar flat-bed configuration was simulated on PET scanner using styrofoam insert. Patient was positioned with arms up during both scans. Simulation CT scan was acquired during normal breathing. 3D orthogonal slices are shown (right) demonstrating volume of tumor in right lung as smaller on PET than on CT, probably because of necrosis. (B) Subsequently, radiotherapy planning was performed with coregistered PET and CT. Coregistered images were transferred via DICOM protocol to treatment planning workstation, and tumor volume was delineated using both scans. PET data allowed reduction of treatment volume. Patient data acquired at London Regional Cancer Center and Hamilton Health Sciences Center, Ontario, Canada.

View larger version (70K): [in a new window]   FIGURE 7. Future applications for molecular-anatomic cardiac image fusion. Volume-rendered phantom study of biplane 3D vessel reconstruction of x-ray angiography is fused with 18F-FDG PET phantom scan containing simulated defect. Such displays also could be used with 3D CT angiography and SPECT or PET data to compare perfusion and viability defects with extent of stenosis. Phantom data acquired at Ottawa Heart Institute, Ontario, Canada.

View larger version (25K): [in a new window]   FIGURE 8. Coregistration of delayed contrast enhancement cardiac MR viability images with 18F-FDG viability images. (A) MRI, (B) (PET/MRI image fusion), and (C) PET demonstrate concordance, with reduced metabolic activity in regions of near-transmural myocardial scarring in septum and lateral wall (arrows), as seen in left ventricular short-axis imaging plane. Patient data acquired at Cedars-Sinai Medical Center, Los Angeles, CA.