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Spiral computed tomography

Spiral computed tomography
MeSH D036542

Spiral computed tomography is a computed tomography[1] technology involving movement in a helical pattern for the purpose of increasing resolution. Most modern hospitals currently use spiral CT scanners.

CT beam types have included parallel beams, fan-beams, and cone-beams.[2]


Willi Kalender, who is credited with the invention prefers the term Spiral scan CT,[3] arguing that spiral is synonymous with helical: for example as used in 'spiral staircase'.[4]

Since its invention by Kalender in the 1980s, helical scan CT machines have steadily increased the number of rows of detectors (slices) they deploy. The prototype 16 multi-slice scanner was introduced in 2001 and in 2004, 64 multislice scanners are on the market. These can produce an image in less than a second and thus can obtain images of the heart and its blood vessels (coronary vessels) as if frozen in time.

The earliest devices, developed in 1989, were called "SSCT", for "single-slice spiral computed tomography". In 1998, "MSCT" or "multi-slice spiral computed tomography" was introduced.[5]

Helical (or spiral) cone beam computed tomography

Further information: Cone beam computed tomography

In cone-beam computed tomography (commonly abbreviated CBCT), the x-ray beam is conical.[6]

Helical (or spiral) cone beam computed tomography is a type of three-dimensional computed tomography (CT) in which the source (usually of x-rays) describes a helical trajectory relative to the object while a two-dimensional array of detectors measures the transmitted radiation on part of a cone of rays emanating from the source.

In practical helical cone beam x-ray CT machines, the source and array of detectors are mounted on a rotating gantry while the patient is moved axially at a uniform rate. Earlier x-ray CT scanners imaged one slice at a time by rotating source and one-dimensional array of detectors while the patient remained static. The helical scan method reduces the x-ray dose to the patient required for a given resolution while scanning more quickly. This is however at the cost of greater mathematical complexity in the reconstruction of the image from the measurements.


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