title: 3-D imaging with MDCT.
abstract: Without doubt, the greatest challenge of multidetector-row CT is dealing with 'data explosion'. For our carotid/intracranial CT angiograms, we routinely have 375 images to review (300 mm coverage reconstructed every 0.8 mm); for aortic studies we have 450-500 images ( approximately 600 mm coverage reconstructed every 1.3 mm); and for a study of the lower extremity inflow and run-off, we may generate 900-1000 transverse reconstructions. While we could reconstruct fewer images for these data, experience with single-detector row CT scanners indicates that longitudinal resolution and disease detection is improved when at least 50% overlap of cross-sections is generated [Radiology 200 (1996) 312]. If we are to optimize our clinical protocols and take full advantage of these CT scanners, we will need to change the way that we interpret, transfer, and store CT data. Film is no longer a viable option. Workstation based review of transverse reconstructions for interpretation is a necessity, but the workstations must improve to provide efficient access to these data, and we must have a way of providing our clinicians with images that can be transported to clinics and the operating room. Alternative visualization and analysis using volumetric tools, including 3-D visualization must evolve from luxury to necessity. We cannot rest on historical precedent to interpret these near isotropically sampled volumetric data using transverse reconstructions alone [Radiology 173 (1989) 527]. Although the tools for volumetric analysis on 3-D workstations have evolved over recent years, they have probably not yet evolved to a level that routine interpretation can be performed as efficiently and accurately as transverse section review. Both hardware and software developments must occur. While current computer workstations and visualization software are certainly adequate for assessing these MDCT data volumetrically, the process is very time consuming. What follows are a description of current workstation capabilities and a brief discussion of where development needs to go to facilitate the complete integration of volumetric analysis into the interpretive process of CT data.
authors.affiliation: Department of Radiology, Stanford University School of Medicine, Mail Code 5105 GRANT, S072B Stanford, CA 94305-5105, USA. grubin@stanford.edu
authors.forename: Geoffrey D
authors.initials: GD
authors.lastname: Rubin
mesh_terms: D006801:Humans; D021621:Imaging, Three-Dimensional; D011857:Radiographic Image Interpretation, Computer-Assisted; D014057:Tomography, X-Ray Computed