Quantitative study of cardiac motion estimation and abnormality classification in emission computed tomography

Tang, Jing; Segars, W. Paul; Lee, Taek Soo; He, Xin; Rahmim, Arman; Tsui, B.M.W.

doi:10.1016/j.medengphy.2010.12.006

Cited by 9 publications

(10 citation statements)

References 34 publications

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“…In [9], we extensively studied the performance of this motion estimation technique in terms of detecting regional motion defects. We optimized parameter α for a better separability of normally beating hearts and hearts with regional motion defects.…”

Section: Methodsmentioning

confidence: 99%

“…We optimized parameter α for a better separability of normally beating hearts and hearts with regional motion defects. The signal-to-noise ratio, which reflected the statistical separability of the estimated normal and abnormal radial motion, was maximized [9]. …”

Section: Methodsmentioning

confidence: 99%

“…These techniques were visually evaluated and mainly applied for cardiac motion compensation in the reconstruction process. In [9], with the realistic 4D NCAT beating heart phantom, the performance of a 3D cardiac motion estimation method was studied quantitatively and optimized in terms of detecting regional motion abnormalities. The purpose of this study is to use the optimized cardiac motion estimation technique as a heart motion observer to compare the performance of a 4D MAP-RBI-EM reconstruction algorithm [10] with that of a standard 3D OS-EM algorithm with post Butterworth filtering.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of 3D OS-EM and 4D MAP-RBI-EM Reconstruction Algorithms for Cardiac Motion Abnormality Classification Using a Motion Observer

Tang

Lee

et al. 2010

IEEE Trans. Nucl. Sci.

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Using a heart motion observer, we compared the performance of two image reconstruction techniques, a 3D OS-EM algorithm with post Butterworth spatial filtering and a 4D MAP-RBI-EM algorithm. The task was to classify gated myocardial perfusion (GMP) SPECT images of beating hearts with or without regional motion abnormalities. Noise-free simulated GMP SPECT projection data was generated from two 4D NCAT beating heart phantom models, one with normal motion and the other with a 50% motion defect in a pie-shaped wedge region-of-interest (ROI) in the anterior-lateral left ventricular wall. The projection data were scaled to clinical GMP SPECT count level before Poisson noise was simulated to generate 40 noise realizations. The noise-free and noisy projection data were reconstructed using the two reconstruction algorithms, parameters chosen to optimize the tradeoff between image bias and noise. As a motion observer, a 3D motion estimation method previously developed was applied to estimate the radial motion on the ROI from two adjacent gates. The receiver operating characteristic (ROC) curves were computed for radial motion magnitudes corresponding to each reconstruction technique. The area under the ROC curve (AUC) was calculated as an index for classification of regional motion. The reconstructed images with better bias and noise tradeoff were found to offer better classification for hearts with or without regional motion defects. The 3D cardiac motion estimation algorithm, serving as a heart motion observer, was better able to distinguish the abnormal from the normal regional motion in GMP SPECT images obtained from the 4D MAP-RBI-EM algorithm than from the 3D OS-EM algorithm with post Butterworth spatial filtering.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparison of 3D OS-EM and 4D MAP-RBI-EM Reconstruction Algorithms for Cardiac Motion Abnormality Classification Using a Motion Observer

Tang

Lee

et al. 2010

IEEE Trans. Nucl. Sci.

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“…Despite extensive research in other imaging modalities over the last two decades, MP ECT, especially gated SPECT and more recently PET, has continued to be the major biomedical imaging technique for the assessment of MP in clinical practice. The potential of extracting additional quantitative information, such as abnormalities from existing data without additional clinical studies, radiation dose or discomfort to the patients, has great significance in biomedical imaging [9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Advances in 4D Gated Cardiac PET Imaging for Image Quality Improvement and Cardiac Motion and Contractility Estimation

Tsui¹,

Feng²,

Wang³

et al. 2016

Perspectives on Nuclear Medicine for Molecular Diagnosis and Integrated Therapy

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Quantitative four-dimensional (4D) image reconstruction methods with respiratory and cardiac motion compensation are an active area of research in ECT imaging, including SPECT and PET. They are the extensions of three-dimensional (3D) statistical image reconstruction methods with iterative algorithms that incorporate accurate models of the imaging process and provide significant improvement in the quality and quantitative accuracy of the reconstructed images as compared to that obtained from conventional analytical image reconstruction methods. The new 4D image reconstruction methods incorporate additional models of the respiratory and cardiac motion of the patient to reduce image blurring due to respiratory motion and image noise of the cardiac-gated frames of the 4D cardiac-gated images. We describe respiratory motion estimation and gating method based on patient PET listmode data. The estimated respiratory motion is applied to the respiratory gated data to reduce respiratory motion blur. The gated cardiac images derived from the listmodel data are used to estimate cardiac motion. They are then used in the cardiacgated images summing the motion-transformed cardiac-gated images for significant reduction in the gated images noise. Dual respiratory and cardiac motion compensation is achieved by combining the respiratory and cardiac motion compensation steps. The results are further significant improvements of the 4D gated cardiac PET images. The much improved gated cardiac PET image quality increases the visibility of anatomical details of the heart, which can be explored to provide more accurate estimation of the cardiac motion vector field and cardiac contractility.

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“…Many groups have developed different approaches based on the changes of blood flow or the cardiac cavity to quantitate cardiac function using various imaging modalities [12][13][14]. Cardiac nuclear medical imaging, including positron emission tomography (PET) and single-photon emission computed tomography (SPECT), uses radioactive material as tracers to obtain functional images for diagnosing and evaluating the severity of cardiomyopathy [14].…”

Section: Introductionmentioning

confidence: 99%

Ventricular hemodynamics using cardiac computed tomography and optical flow method

Lin

Huang

Lin

et al. 2014

Journal of X-Ray Science and Technology

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Ventricular hemodynamics plays an important role in assessing cardiac function in clinical practice. The aim of this study was to determine the ventricular hemodynamics based on contrast movement in the left ventricle (LV) between the phases in a cardiac cycle recorded using an electrocardiography (ECG) with cardiac computed tomography (CT) and optical flow method. Cardiac CT data were acquired at 120 kV and 280 mA with a 350 ms gantry rotation, which covered one cardiac cycle, on the 640-slice CT scanner with ECG for a selected patient without heart disease. Ventricular hemodynamics (mm/phase) were calculated using the optical flow method based on contrast changes with ECG phases in anterior-posterior, lateral and superior-inferior directions. Local hemodynamic information of the LV with color coating was presented. The visualization of the functional information made the hemodynamic observation easy.

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Quantitative study of cardiac motion estimation and abnormality classification in emission computed tomography

Cited by 9 publications

References 34 publications

Comparison of 3D OS-EM and 4D MAP-RBI-EM Reconstruction Algorithms for Cardiac Motion Abnormality Classification Using a Motion Observer

Comparison of 3D OS-EM and 4D MAP-RBI-EM Reconstruction Algorithms for Cardiac Motion Abnormality Classification Using a Motion Observer

Advances in 4D Gated Cardiac PET Imaging for Image Quality Improvement and Cardiac Motion and Contractility Estimation

Ventricular hemodynamics using cardiac computed tomography and optical flow method

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