With the advancement of Computed Tomography technology, improving image quality while reducing patient dose has
been a big technical challenge. The recent CT750 HD system from GE Healthcare provides significantly improved
spatial resolution and the capability to reduce dose during routine clinical imaging. This paper evaluates the image
quality of this system. Spatial resolution, dose reduction, noise, and low contrast detectability have been quantitatively
characterized. Results show a quantifiable and visually discernable higher spatial resolution for both body and cardiac
scanning modes without compromise of image noise. Further, equivalent image quality performance with up to 50%
lower dose has been achieved.
Future generations of CT systems would need a mean to cover an entire organ in a single rotation. A way to accomplish
this is to physically increase detector size to provide, e.g., 120~160mm z (head-foot) coverage at iso. The x-ray cone
angle of such a system is usually 3~4 times of that of a 64-slice (40mm) system, which leads to more severe cone beam
artifacts in cardiac scans. In addition, the extreme x-ray take-off angles for such a system cause severe heel effect,
which would require an increase in anode target angle to compensate for it. One shortcoming of larger target angle is
that tube output likely decreases because of shorter thermal length. This would result in an increase of image noise. Our
goal is to understand from a physics and math point of view, what is the clinical acceptable level of artifacts, resolution,
and noise impact. The image artifacts are assessed through computer simulation of a helical body phantom and visual
comparison of reconstructed images between a 140mm system and a 64-slice system. The IQ impact from target angle
increase is studied analytically and experimentally by first finding the proper range of target angles that give the
acceptable heel effect, then estimating the impact on peak power (flux) and z resolution using an empirical model of
heel effect for given target angle and analytical models of z resolution and tube current loading factor for given target
thermal length. The results show that, for a 140mm system, 24.5% of imaging volume exhibits more severe cone beam
artifacts than a 64-slice system, which also brings up a patient dose concern. In addition, this system may suffer from a
36% peak power (flux) loss, which is equivalent to about 20% image noise increase. Therefore, a wide coverage CT
system using a single x-ray source is likely to face some severe challenges in IQ and clinical accuracy.
The expanding set of CT clinical applications demands increased attention to obtaining the maximum image quality at the lowest possible dose. Pre-patient beam shaping filters provide an effective means to improve dose utilization. In this paper we develop and apply characterization methods that lead to a set of filters appropriately matched to the patient. We developed computer models to estimate image noise and a patient size adjusted CTDI dose. The noise model is based on polychromatic X-ray calculations. The dose model is empirically derived by fitting CTDI style dose measurements for a demographically representative set of phantom sizes and shapes with various beam shaping filters. The models were validated and used to determine the optimum IQ vs dose for a range of patient sizes. The models clearly show that an optimum beam shaping filter exists as a function of object diameter. Based on noise and dose alone, overall dose efficiency advantages of 50% were obtained by matching the filter shape to the size of the object. A set of patient matching filters are used in the GE LightSpeed VCT and Pro32 to provide a practical solution for optimum image quality at the lowest possible dose over the range of patient sizes and clinical applications. Moreover, these filters mark the beginning of personalized medicine where CT scanner image quality and radiation dose utilization is truly individualized and optimized to the patient being scanned.
Dose is becoming increasingly important for computed tomography clinical practice. It is of general interest to understand the impact that system design can have on dose and image quality. This study addresses the effect of bowtie shape on the dose and contrast-to-noise across the field of view. Simulation of the CT acquisition is used to calculate the energy deposition throughout a numerical phantom for a set of relevant system operating parameters and bowtie shapes. Mean absorbed dose is calculated by summing over the phantom volume and is compared with other typical dose specifications. A more aggressive attenuation profile of the bowtie which offers higher attenuation in the periphery of the field of view can offer the benefit of lower dose but at the expense of reduced contrast-to-noise at the edge of the cross-sectional image.
Since the recent introduction of multi-slice helical computed tomography (MHCT), new clinical applications have experienced tremendous growth in recent years. MHCT offers improved volume coverage, faster scan speed, more isotropic spatial resolution, and reduced x-ray tube loading. Similar to the single slice helical CT, the projection data collected in MHCT is inherently inconsistent due to the constant table motion. In addition, cone beam effects in MHCT produce additional complexity and image artifacts. Although the cone angle is quite smaller even for the 16-slice configuration, the impact on image artifacts cannot be ignored. Many reconstruction algorithms have been proposed and investigated recently to combat image artifacts associated with the MHCT data acquisition. In this paper, we propose a cone-angle dependent generalized weighting scheme for 16-slice helical CT that allows the production of MHCT images with only 2D backprojection. The cone-angle dependency of the algorithm suppresses image artifacts due to the cone beam effect and the generalized weighting portion enables interpolation be performed with conjugate samples for the 16-slice helical dataset. With the proposed algorithm, image artifacts are significantly reduced.