Attenuation-emission alignment in cardiac PET/CT based on consistency conditions

Department of Radiology, University of Washington Medical Center, 4000 15th Avenue NE, Box 357987, Seattle, Washington 98195-7987, USA.
Medical Physics (Impact Factor: 3.01). 03/2010; 37(3):1191-200. DOI: 10.1118/1.3315368
Source: PubMed

ABSTRACT In cardiac PET and PET/CT imaging, misaligned transmission and emission images are a common problem due to respiratory and cardiac motion. This misalignment leads to erroneous attenuation correction and can cause errors in perfusion mapping and quantification. This study develops and tests a method for automated alignment of attenuation and emission data.
The CT-based attenuation map is iteratively transformed until the attenuation corrected emission data minimize an objective function based on the Radon consistency conditions. The alignment process is derived from previous work by Welch et al. ["Attenuation correction in PET using consistency information," IEEE Trans. Nucl. Sci. 45, 3134-3141 (1998)] for stand-alone PET imaging. The process was evaluated with the simulated data and measured patient data from multiple cardiac ammonia PET/CT exams. The alignment procedure was applied to simulations of five different noise levels with three different initial attenuation maps. For the measured patient data, the alignment procedure was applied to eight attenuation-emission combinations with initially acceptable alignment and eight combinations with unacceptable alignment. The initially acceptable alignment studies were forced out of alignment a known amount and quantitatively evaluated for alignment and perfusion accuracy. The initially unacceptable studies were compared to the proposed aligned images in a blinded side-by-side review.
The proposed automatic alignment procedure reduced errors in the simulated data and iteratively approaches global minimum solutions with the patient data. In simulations, the alignment procedure reduced the root mean square error to less than 5 mm and reduces the axial translation error to less than 1 mm. In patient studies, the procedure reduced the translation error by > 50% and resolved perfusion artifacts after a known misalignment for the eight initially acceptable patient combinations. The side-by-side review of the proposed aligned attenuation-emission maps and initially misaligned attenuation-emission maps revealed that reviewers preferred the proposed aligned maps in all cases, except one inconclusive case.
The proposed alignment procedure offers an automatic method to reduce attenuation correction artifacts in cardiac PET/CT and provides a viable supplement to subjective manual realignment tools.

  • [Show abstract] [Hide abstract]
    ABSTRACT: The accuracy of attenuation correction in positron emission tomography scanners depends mainly on deriving the reliable 511-keV linear attenuation coefficient distribution in the scanned objects. In the PET/CT system, the linear attenuation distribution is usually obtained from the intensities of the CT image. However, the intensities of the CT image relate to the attenuation of photons in an energy range of 40 keV─140 keV. Before implementing PET attenuation correction, the intensities of CT images must be transformed into the PET 511-keV linear attenuation coefficients. However, the CT scan parameters can affect the effective energy of CT X-ray photons and thus affect the intensities of the CT image. Therefore, for PET/CT attenuation correction, it is crucial to determine the conversion curve with a given set of CT scan parameters and convert the CT image into a PET linear attenuation coefficient distribution. A generalized method is proposed for converting a CT image into a PET linear attenuation coefficient distribution. Instead of some parameter-dependent phantom calibration experiments, the conversion curve is calculated directly by employing the consistency conditions to yield the most consistent attenuation map with the measured PET data. The method is evaluated with phantom experiments and small animal experiments. In phantom studies, the estimated conversion curve fits the true attenuation coefficients accurately, and accurate PET attenuation maps are obtained by the estimated conversion curves and provide nearly the same correction results as the true attenuation map. In small animal studies, a more complicated attenuation distribution of the mouse is obtained successfully to remove the attenuation artifact and improve the PET image contrast efficiently.
    Chinese Physics B 01/2014; 23(2). DOI:10.1088/1674-1056/23/2/027802 · 1.39 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The development of methods for correcting patient motion in emission tomography has been receiving increased attention. Often the performance of these methods is evaluated through simulations using digital anthropomorphic phantoms, such as the commonly used extended cardiac torso (XCAT) phantom, which models both respiratory and cardiac motion based on human studies. However, non-rigid body motion, which is frequently seen in clinical studies, is not present in the standard XCAT phantom. In addition, respiratory motion in the standard phantom is limited to a single generic trend. In this work, to obtain a more realistic representation of motion, we developed a series of individual-specific XCAT phantoms, modeling non-rigid respiratory and non-rigid body motions derived from the magnetic resonance imaging (MRI) acquisitions of volunteers. Acquisitions were performed in the sagittal orientation using the Navigator methodology. Baseline (no motion) acquisitions at end-expiration were obtained at the beginning of each imaging session for each volunteer. For the body motion studies, MRI was again acquired only at end-expiration for five body motion poses (shoulder stretch, shoulder twist, lateral bend, side roll, and axial slide). For the respiratory motion studies, an MRI was acquired during free/regular breathing. The magnetic resonance slices were then retrospectively sorted into 14 amplitude-binned respiratory states, end-expiration, end-inspiration, six intermediary states during inspiration, and six during expiration using the recorded Navigator signal. XCAT phantoms were then generated based on these MRI data by interactive alignment of the organ contours of the XCAT with the MRI slices using a graphical user interface. Thus far we have created five body motion and five respiratory motion XCAT phantoms from the MRI acquisitions of six healthy volunteers (three males and three females). Non-rigid motion exhibited by the volunteers was reflected in both respiratory and body motion phantoms with a varying extent and character for each individual. In addition to these phantoms, we recorded the position of markers placed on the chest of the volunteers for the body motion studies, which could be used as external motion measurement. Using these phantoms and external motion data, investigators will be able to test their motion correction approaches for realistic motion obtained from different individuals. The non-uniform rational B-spline data and the parameter files for these phantoms are freely available for downloading and can be used with the XCAT license.
    Physics in Medicine and Biology 06/2014; 59(14):3669–3682. DOI:10.1088/0031-9155/59/14/3669 · 2.92 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Purpose: Tracking the motion of biological tissues represents an important issue in the field of medical ultrasound imaging. However, the longitudinal component of the motion (i.e. perpendicular to the beam axis) remains more challenging to extract due to the rather coarse resolution cell of ultrasound scanners along this direction. The aim of this study is to introduce a real-time beamforming strategy dedicated to acquire tagged images featuring a distinct pattern in the objective to ease the tracking. Methods: Under the conditions of the Fraunhofer approximation, a specific apodization function was applied to the received raw channel data, in real-time during image acquisition, in order to introduce a periodic oscillations pattern along the longitudinal direction of the radio frequency signal. Analytic signals were then extracted from the tagged images, and sub-pixel motion tracking of the intima-media complex was subsequently performed offline, by means of a previously introduced bi-dimensional analytic phase-based estimator. Results: Our framework was applied in vivo on the common carotid artery from 20 young healthy volunteers and 6 elderly patients with high atherosclerosis risk. Cine-loops of tagged images were acquired during three cardiac cycles. Evaluated against reference trajectories manually generated by three experienced analysts, the mean absolute tracking error was 98±84 μm and 55±44 μm in the longitudinal and axial directions, respectively. These errors corresponded to 28±23 % and 13±9 % of the longitudinal and axial amplitude of the assessed motion, respectively. Conclusion: The proposed framework enables tagged ultrasound images of in vivo tissues to be acquired in real-time. Such unconventional beamforming strategy contributes to improve tracking accuracy and could potentially benefit to the interpretation and diagnosis of bio-medical images.
    Medical Physics 12/2014; 42(8):820-830. DOI:10.1118/1.4905376 · 3.01 Impact Factor

Full-text (2 Sources)

Available from
May 31, 2014