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: 2.64). 03/2010; 37(3):1191-200. DOI: 10.1118/1.3315368
Source: PubMed


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.

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Available from: Paul E Kinahan, Sep 30, 2015
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    • "Finally, the pseudo-gated CT was derived in a simple manner by applying PET-derived motion fields to the HCT. McQuaid et al. 28 have produced a detailed method of generating cine CTs from static CT images, and Alessio et al. 46 have shown that consistency criteria can also be used to reduce respiratory motion artefacts in cardiac PET imaging. These approaches may improve the results for the pseudo-gated CT approach. "
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    ABSTRACT: Respiratory motion affects cardiac PET-computed tomography (CT) imaging by reducing attenuation correction (AC) accuracy and by introducing blur. The aim of this study was to compare three approaches for reducing motion-induced AC errors and evaluate the inclusion of respiratory motion correction. AC with a helical CT was compared with averaged cine and gated cine CT, as well as with a pseudo-gated CT, which was produced by applying PET-derived motion fields to the helical CT. Data-driven gating was used to produce respiratory-gated PET and CT images, and 60 NH3 PET scans were attenuation corrected with each of the CTs. Respiratory motion correction was applied to the gated and pseudo-gated attenuation-corrected PET images. Anterior and lateral wall intensity measured in attenuation-corrected PET images generally increased when PET-CT alignment improved and decreased when alignment degraded. On average, all methods improved PET-CT liver and cardiac alignment, and increased anterior wall intensity by more than 10% in 36, 33 and 25 cases for the averaged, gated and pseudo-gated CTAC PET images, respectively. However, cases were found where alignment worsened and severe artefacts resulted. This occurred in more cases and to a greater extent for the averaged and gated CT, where the anterior wall intensity reduced by more than 10% in 21 and 24 cases, respectively, compared with six cases for the pseudo-gated CT. Application of respiratory motion correction increased the average anterior and inferior wall intensity, but only 13% of cases increased by more than 10%. All methods improved average respiratory-induced AC errors; however, some severe artefacts were produced. The pseudo-gated CT was found to be the most robust method.
    Nuclear Medicine Communications 10/2013; 34(12). DOI:10.1097/MNM.0b013e328365bb27 · 1.67 Impact Factor
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    • "We assume that A m = D m A 0 , m = 1, · · · , M, (29) where D m denotes a diagonal matrix for patient-dependent attenuation and detector efficiency for the mth frame, and A 0 is a system geometry. We assume known and well-aligned attenuation map (i.e., D m is given), which can be the case for PET-CT [38] or PET-MR [39]. We still allow the warp T m,1 to differ for each m. "
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    ABSTRACT: Many motion-compensated image reconstruction (MCIR) methods have been proposed to correct for subject motion in medical imaging. MCIR methods incorporate motion models to improve image quality by reducing motion artifacts and noise. This paper analyzes the spatial resolution properties of MCIR methods and shows that nonrigid local motion can lead to nonuniform and anisotropic spatial resolution for conventional quadratic regularizers. This undesirable property is akin to the known effects of interactions between heteroscedastic log-likelihoods (e.g., Poisson likelihood) and quadratic regularizers. This effect may lead to quantification errors in small or narrow structures (such as small lesions or rings) of reconstructed images. This paper proposes novel spatial regularization design methods for three different MCIR methods that account for known nonrigid motion. We develop MCIR regularization designs that provide approximately uniform and isotropic spatial resolution and that match a user-specified target spatial resolution. Two-dimensional PET simulations demonstrate the performance and benefits of the proposed spatial regularization design methods.
    04/2012; 31(7):1413-25. DOI:10.1109/TMI.2012.2192133
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    ABSTRACT: The presence of metallic dental fillings is prevalent in head and neck PET/CT imaging and generates bright and dark streaking artifacts in reconstructed CT images. The resulting artifacts would propagate to the corresponding PET images following CT-based attenuation correction (CTAC). This would cause over- and/or underestimation of tracer uptake in corresponding regions thus leading to inaccurate quantification of tracer uptake. The purpose of this study is to improve our recently proposed metal artifact reduction (MAR) approach and to assess its performance in a clinical setting. The proposed MAR algorithm is performed in the virtual sinogram space to overcome the challenges associated with manipulating raw CT data. The corresponding bins of the virtual sinogram affected by metallic objects are obtained by forward projection of segmented metallic objects in the original CT image. These bins are then substituted by weighted values of three estimates: the affected bins in the original sinogram, the bins in the corrected sinogram using spline interpolation, and the sinogram bins in the neighboring column of the sinogram matrix. The optimized weighting factors (alpha, beta, and gamma) were estimated using a genetic algorithm (GA). The optimized combination of weighting coefficients was obtained using the GA applied to 24 clinical CT data sets. The proposed MAR method was then applied to 12 clinical head and neck PET/CT data sets containing dental artifacts. Analysis of the results was performed using Bland and Altman plots and a method allowing analysis in the absence of gold standard called regression without truth (RWT). The proposed method was also compared to an image-based MAR method. Optimization of the weighting coefficients using the GA resulted in an optimum combination of parameters of alpha=0.26, beta=0.67, and gamma=0.07. According to Bland and Altman plots generated for both CT and PET images of the clinical data, the proposed MAR algorithm is efficient for reduction of streak artifacts in CT images and such reduce the over- and/or underestimation o tracer uptake. The RWT method also confirmed the effectiveness of the proposed MAR method. The obtained figures of merit revealed that attenuation corrected PET data corrected using CTAC after applying the MAR algorithm are more similar to the assumed gold standard. Comparison with the knowledge-based method revealed that the proposed method mainly corrects the artifactual regions without modifying the unaffected regions. The knowledge-based method globally modifies the images including those that do not include metallic artifacts. The proposed MAR algorithm improves the quality and quantitative accuracy of clinical head and neck PET/CT images and could be easily integrated in clinical setting.
    Medical Physics 12/2010; 37(12):6166-77. DOI:10.1118/1.3511507 · 2.64 Impact Factor
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