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Four-Dimensional Imaging of the Heart Based on Near-Isotropic MDCT Data Sets

¹ Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, 601 N. Caroline Street, Rm. 3254, Baltimore, MD 21287-0801.
² Hip Graphics, Baltimore, MD.

Received February 6, 2004; accepted after revision July 8, 2004.

 
Address correspondence to L. P. Lawler.

Introduction

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Four-dimensional cardiac CT is a concept in evolution [1, 2]. In this paper, we define 4D cardiac CT as a processed study that assimilates a series of sequential, static, phase-specific, 3D volume helical data sets into a cine image that reflects the in vivo model of the 3D spatial information mapped to the sequential time and motion relationship of the cardiac cycle. It can be applied to derive morphologic and functional information, but it is distinct from existing tools, which deduce such information from static planar slices of end systole and end diastole alone. This technique will form an important facet of the comprehensive cardiac CT study.

The initial relatively high-speed acquisition of electron beam CT (EBCT) [3] provided some of the earliest quantitative CT information on ventricular size and shape and on systolic function. However, this complex technology was never widely available, was limited to prospective gating, and is fast being replaced by the the more versatile mechanical CT where its acquisition parameters in terms of temporal resolution are rapidly approaching those of EBCT. Earlier work with single-detector helical scanning was able to produce animated 2D images of the heart with ventricular values that closely correlated with conventional ventriculography [4].

Materials and Methods

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Data Acquisition and Processing
To generate a 4D data set, one must first acquire a density profile and positional information that characterize each voxel of the heart structure for a series of time points throughout the cardiac systolic and diastolic phases. The patient is scanned in a single breath-hold with simultaneous recording of the ECG signal. Current helical MDCT systems provide near-isotropic voxels from 0.75-mm detector systems (Sensation, Siemens Medical Solutions) giving 0.75- to 1-mm slice collimation reconstructed at 50% overlap. Large detector arrays, fast gantry rotation, and segmental reconstruction contribute to a TR of 120–130 msec. Vascular lumen, endocardial surface, and chamber contrast resolution is achieved through a peripheral-venous upper-extremity power injection of 120 mL of nonionic iodinated contrast (Visipaque 320, Amersham Health) delivered at a rate of 3 mL/sec followed by a saline flush from a dual-head injector. Scanning acquisition begins 17 sec after the contrast administration. Unlike coronary CT angiography, which uses only diastolic data, 4D CT utilizes all data derived from irradiating the patient. Effective dose depends on heart rate but is approximately 7.0 mSv for a man and 10.2 mSv for a woman, with a CT dose index of 42.0 mGy.

Axial planar data for 3D and 4D postprocessing are reconstructed from the raw data using retrospective gating, which defines a portion of the cardiac cycle as a percentage of the R-R interval. For 4D imaging, a contiguous sequence of nine or more separate "whole-heart" volumes, of equal duration intervals, is generated. These volumes represent the distinct phases (i.e., "time windows") of cardiac motion (e.g., 10%, 20%, 30%, and so forth up to 90% of the R-R interval). This is a semiautomatic standard process of all cardiac software and is performed at the scanner. The user simply defines the percentage reconstruction desired, and the result is a series of separate stacks of axial images with each stack representing a particular period of the cardiac cycle. Within each time window, all voxels of the heart are represented. The total number of images may be more than 2,000 images, depending on the slice reconstruction used (0.75–1 mm). The data are sent to a 3D workstation that incorporates commercially available volume-rendering software and supports a work-in-progress version of 4D software.

4D Reconstruction, Visualization, and Measurement
Four-dimensional CT of the heart is not yet universally defined. We define it as a moving 3D representation of the cardiac cycle. The 4D data display is based on an existing 3D platform (InSpace, Siemens Medical Solutions) that permits the user to view the data with a variety of techniques—maximum intensity projection, multiplanar reconstruction, and volume rendering. Unlike 3D imaging, which requires only a single time window of helical data, 4D imaging requires the entire set of sequential time windows (representing the full R-R cycle) to be loaded into the 4D program; this loading takes approximately 60–90 sec. The nine volumes of data are then sorted on the basis of their sequential temporal interrelationship within the cardiac cycle, which is deduced from the ECG map of cardiac motion over time. The computer performs this task automatically. Thus, a coherent cine loop is generated, and the user defines its cycle rate.

Existing interactive, real-time 3D tools are preserved for the user, and the beating heart may be also displayed in 2D axial and multiplanar formats. The user maintains control over variables such as opacity, brightness, and window width and level. Regions of interest are applied to remove unwanted data from the image. Infinite, real-time interactive planes and projections using clip-editing plane slab segmentation of data allow display of standard ventricle short and long axes and four-chamber views. Planes orthogonal to specified wall segments of interest show the presence or absence of cyclical thickness changes to best effect. Patient- or abnormality-specific planes may also be drawn; for example, planes may be drawn through the valve to depict the moving leaflets (Figs. 1A, 1B, 1C, 1D, and 1E).

View larger version (177K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1A. —Four-dimensional cardiac CT images obtained in 44-year-old man. In axial four-chamber 4D volume-rendered image, right ventricle (arrowhead) left ventricle (long arrow), mitral valve (short arrow).

View larger version (117K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1B. —Four-dimensional cardiac CT images obtained in 44-year-old man. In coronal short-axis 4D volume-rendered image, right ventricle (arrowhead) left ventricle (long arrow).

View larger version (123K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1C. —Four-dimensional cardiac CT images obtained in 44-year-old man. In long-axis 4D volume-rendered image, left atrium (arrowhead, mitral valve (short arrow), left ventricle (long arrow).

View larger version (94K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1D. —Four-dimensional cardiac CT images obtained in 44-year-old man. In right anterior 4D volume-rendered image, right coronary artery (short arrow), right ventricle (arrowhead), left ventricle (long arrow).

View larger version (146K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1E. —Four-dimensional cardiac CT images obtained in 44-year-old man. In left anterior oblique 4D volume-rendered image, right ventricle (arrowhead), left anterior descending artery (short arrow), left ventricle (long arrow).

The data obtained may be quantified. By viewing the 4D images, the user may first observe the most diastolic and most systolic phases of cardiac motion as defined by chamber size, wall thickness, and valve motion. Existing cardiac software platforms allow one to define the endocardial and epicardial surfaces by region of interest drawing or density threshold techniques. From this systolic and diastolic information on cardiac volume and regional wall thickness, changes may be assessed and ejection fraction and stroke volume may be measured. As in echocardiography and conventional ventriculography, experience allows one to learn the patterns of abnormal wall motion including akinesis and dyskinesis by observing normal and abnormal 4D sequences, which to date remains largely subjective [5].

Discussion

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With 4D cardiac CT, one can visualize dynamic information that complements existing tools of anatomic and functional assessment. Like echocardiography and MRI, 4D cardiac CT in its current form provides an overview of global and regional myocardial or valvular motion and volume changes during the cardiac cycle. It can be used to select optimal image phases for 3D and functional analysis (e.g., coronary artery assessment or ejection fraction) [6]. With experience, observers can identify myocardial segments of abnormal motion or thickening as on echocardiography or MRI. Our early experience suggests that 4D cardiac CT may have a role in assessing areas of ischemia, infarction, and arrhythmogenic right ventricle.

MDCT generates isotropic voxels that allow a perspective of interpretation independent of the plane of acquisition. This independent perspective permits us to view animated 3D images that simulate the cardiac motion. In the future, 4D CT will be indexed to the particular patient's heart rate and rhythm to reflect the individual cardiac cycle. Improved temporal resolution of MDCT will enhance the systolic image quality. The visualized motion will be reconciled to existing wall volume and thickness mapping derived from planar data. It is hoped that a method will be developed to quantifiably assess myocardial displacement, which is contained in the data. High contrast and spatial resolution information reflecting chamber performance is already contained within routine retrospectively gated data sets. Four-dimensional cardiac CT will make a major contribution to harnessing the full morphologic and functional potential of high-quality MDCT data acquired from a single cardiac CT study.

References

Top Introduction Materials and Methods Discussion References

 

1. Nieman K, van Ooijen P, Rensing B, Oudkerk M, de Feyter PJ. Four-dimensional cardiac imaging with multislice computed tomography. Circulation2001; 103:e62[Free Full Text]
2. Saito K, Saito M, Komatu S, Ohtomo K. Real-time four-dimensional imaging of the heart with multidetector row CT. RadioGraphics 2003;23:e8 [Erratum in: RadioGraphics2003; 23:686 ][Free Full Text]
3. Rumberger JA. Use of electron beam tomography to quantify cardiac diastolic function. Cardiol Clin2000; 18:547 -556[Medline]
4. Mochizuki T, Murase K, Higashino H, et al. Two- and three-dimensional CT ventriculography: a new application of helical CT. AJR 2000;174:203 -208[Abstract/Free Full Text]
5. Juergens KU, Grude M, Maintz D, et al. Multi-detector row CT of left ventricular function with dedicated analysis software versus MR imaging: initial experience. Radiology2004; 230:403 -410[Abstract/Free Full Text]
6. Kopp AF, Schroeder S, Kuettner A, et al. Coronary arteries: retrospectively ECG-gated multidetector row CT angiography with selective optimization of the image reconstruction window. Radiology2001; 221:683 -688[Abstract/Free Full Text]

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