A Multidimensional Approach to Abdominal Imaging

CHAPTER 5 A Multidimensional Approach to Abdominal Imaging



Through development of computed tomography (CT), Geoffrey Hounsfield and Allen Cormack left a truly remarkable legacy. Part of their legacy, however, is that after CT scanners became available for clinical use in the early 1970s, many physicians began to think about human anatomy in axial sections. Previously, understanding of anatomy was learned through cadaveric and then surgical dissection, as well as physical examination. Atlases of cross-sectional anatomy were designed to act as a “translation” of sectional anatomy to the three dimensions of human anatomy and disease. Ultrasound, of course, permits sections to be obtained in virtually any plane as long as there is access or a “window” to peer through. However, the presence of intestinal gas and bone, as well as variable operator dependence, secured a significant role for CT for imaging the abdomen and pelvis despite being restricted to axial sections.


The development of magnetic resonance imaging (MRI) introduced physicians to the benefits of obtaining large data-rich sections of anatomic detail that were not limited to the axial imaging plane. Clearly, spinal imaging with MRI illustrated the advantages for some organ systems of obtaining images along the long plane or z-axis of the patient. Even with MRI, however, nonaxial imaging remained arbitrary, depending on acquisition within a prescribed imaging plane that could not be altered once the examination was complete. Although useful for predictable anatomic structures such as the spine, bones, joints, and some blood vessels, even the dimensional versatility of MRI might not image the relation between diseased and anatomic structures that are not identified during scan acquisition.


Dramatic technical improvements in CT and magnetic resonance (MR) technology now permit the acquisition of data that provide the substrate for subsequent postprocessing. Availability of this “volumetric” data allows a sort of virtual dissection at the discretion of the interpreting physician. Although conventional planes of imaging are still provided, robust data sets allow the radiologist to manipulate the imaging plane, and even the data processing algorithm, long after the patient has left the department. Thus, an initially unsuspected mass can be interrogated in multiple planes, defining relations that can help guide therapeutic decisions. Although integration of three-dimensional (3D) processing software into picture archiving and communication systems (PACSs) is improving radiologist access to these programs during image interpretation, most image postprocessing is still performed by CT and MR technologists under the supervision of a radiologist. However, just as the captain of a ship must first learn to sail, effective use of 3D imaging techniques requires the radiologist to have an understanding of the basic principles underlying data processing techniques.



PIXELS AND VOXELS


Just as a masterpiece by Seurat is composed of hundreds of small independent points of color, each CT, MR, or ultrasound image is composed of hundreds of small squares that vary from black to white along a spectrum of gray. Together, these squares or pixels combine to comprise images that represent anatomic structures. The number of pixels used to compose each image is defined as the matrix size. For most CT examinations today, each image consists of 512 pixels in both the x– and y-planes, described as a matrix of 512 × 512 and yielding 262,144 pixels per image. (Remember this the next time you complain that your PACS is too slow!) The size of each pixel can be calculated easily by dividing the scan field of view (FOV) by 512. For example, for an acquisition using a 36-cm FOV, each square pixel measures 360 mm divided by 512, or 0.7 mm.


If the depth of each data component used to construct an image is considered, the square pixel is transformed into a 3D cuboid called a voxel. The depth or z-axis dimension of the voxel is defined by the value of the reconstructed section thickness. Until recently, virtually all CT and MR acquisitions yielded reconstructed voxels that were much thicker than the pixel size, usually by several fold. With the introduction of multidetector CT scanners (MDCT), particularly with 16 or more data channels, voxels can now be achieved routinely that are cubic in shape. Voxels with similar length in all three planes are called isotropic. Voxels that are not cube shaped are anisotropic (Fig. 5-1).



Voxel geometry has limited significance if axial sections alone comprise the total utilization of CT data. Because the voxel length in the z-axis is determined by reconstructed section thickness, voxel geometry does determine the degree of volume averaging that occurs (affecting image noise) but has minimal other impact on axial imaging. Such geometry, however, is one of the most crucial elements to successful application of nonaxial image processing. In general, these imaging applications may be divided into three main types: multiplanar reformations (MPRs), slab projections, and volume rendering.



MULTIPLANAR REFORMATIONS


As mentioned earlier, each axial section that comprises a CT or MR examination is created by calculating attenuation or signal values for each of its component voxels. An MPR is created by using a computer to create a new nonaxial imaging plane through the voxels of a “stacked” set of reconstructed sections. With CT, the reconstructed sections are always axial, so axial sections are stacked and a nonaxial imaging plane one voxel in thickness is defined within that volume (Fig. 5-2). With MR, the original scan data can be in any acquisition-defined imaging plane.




Choosing an Imaging Plane for Multiplanar Reformation


The additional perspective available with MPRs may be beneficial in two distinct ways: (1) improved lesion detection, and (2) lesion characterization. Lesion detection is improved when the structure does not lend itself to thorough evaluation in the axial plane. For example, because compressive deformity of vertebral bodies may be difficult to detect on axial sections, sagittal reformations can improve detection of spine fractures on routine abdominal CT scans (Fig. 5-3). Coronal and sagittal MPRs are helpful for the diaphragm and the hips. In most cases, the imaging plane is flat, similar to a pane of glass inserted into the volume of data.



MPRs may facilitate lesion characterization by helping to identify the origin of a lesion or its shape. In some cases, MPRs are useful to characterize a specific lesion such as a suprarenal mass of uncertain origin. In other cases, the change in perspective may provide insight into the shape of a lesion, either providing a diagnosis or directing more specific investigation (Fig. 5-4). MPRs are also useful in lesion detection, such as locating an appendix not readily apparent on axial sections. Because the potential benefit of MPRs rests on an improved alignment between the orientation of the organ in question and the selected imaging plane, arbitrary imaging planes may not be the optimal choice. Oblique planes are those that are off-axis from standard axial, coronal, and sagittal planes. One of the most commonly prescribed oblique planes is a coronal oblique view of the abdominal aorta (Fig. 5-5). In certain cases, it is helpful to manipulate the imaging plane in real time to clarify issues raised during the interpretive session.




For focused evaluation of a curvilinear structure such as a blood vessel, an imaging plane may be defined that follows that one particular structure. This is a curved planar reformation (CPR), and the resulting image transforms a curved length of vessel, ureter, or intestine into a straight segment (Fig. 5-6). Because all other structures in the image are distorted by the curved imaging plane, CPR is useful only to investigate the structure used to define its imaging plane. Similar to MPRs, CPRs are a single voxel in depth.




PROJECTION TECHNIQUES


Although MPRs can provide perspective tailored to the anatomic structure or clinical question at hand, thickening the MPR into a slab of data that is two or more voxels in thickness opens the door to additional possibilities that further enhance the diagnostic value of the data (Fig. 5-7). The imaging algorithms become more complex using slabs, because utilizing the “depth” of a slab requires extrapolating a line of sight from the viewer’s eye through the slab, intersecting all voxels within the slab along that specific path. If the image is rotated, the line of sight intersects different combinations of voxels as the incident angle changes. Because the line of projection determines the appearance of the resulting image, these are called projection techniques.



The main benefit of thickening an MPR into a slab projection is that it incorporates multiple voxels along the line of sight to determine the displayed value. This allows the user to select from among different mathematical algorithms to determine how the collection of voxel values will be processed (Fig. 5-8). Each of these types of projection processing techniques is discussed briefly in the following sections.




Maximum Intensity Projection


Maximum intensity projection (MIP) is perhaps the most well-known type of projection technique and one of the most commonly used. When MIP is used, of all the voxels intersected by a particular line of sight, only the one with the greatest value is represented in the image. This technique is effective at demonstrating continuous segments of high-attenuation or high-signal structures such as arteries opacified with intravascular contrast media or ureters filled with excreted contrast media (Fig. 5-9). Note that because high-intensity voxels are emphasized and low-attenuation voxels are ignored or deemphasized, evaluation of soft-tissue structures may be limited (Fig. 5-10), and small filling defects within a high-intensity lumen may be obscured (Fig. 5-11).





MIP first gained popularity using data from magnetic resonance angiography (MRA) but has become increasingly popular for CT applications as well. The number of images required to visualize the full length of a structure depends on the orientation and thickness of the slab, as well as how straight or tortuous the structure in question is. As with all projection techniques, the thickness and orientation of the slab are selected by the operator, and thus are likely to be of greater utility with a knowledgeable user.



Mar 6, 2016 | Posted by in GENERAL RADIOLOGY | Comments Off on A Multidimensional Approach to Abdominal Imaging
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