Many studies have examined the diagnostic efficacy of low-dose CT in the setting of renal colic, and a variety of protocols have described that result in effective radiation dose reductions of up to 95% from greater than 10
mSv to as low as 0.5–3.5
]. Low-dose CT is uniformly associated with an increase in image noise, but successes in dose reduction in the setting of renal colic have been aided by the inherent high contrast of renal calculi against the relatively low-density soft tissues surrounding the urinary tract.
In the past, fixed CT settings (e.g., kVp and mAs) resulted in lower attenuating areas such as the midabdomen receiving the same radiation exposure as higher attenuating regions such as the pelvis. This was an inefficient method of image acquisition and of imparting radiation exposure to patients as some regions were overirradiated, without any benefit in terms of image quality, while other regions were potentially underexposed, increasing image noise and reducing image quality. Automatic tube current modulation (ATCM) was a major development in CT technology in the last decade. One of the first major papers which evaluated ATCM as a means of optimizing radiation dose at CT reported dose reductions of 32% in 87% of CT examinations using ATCM [25
]. Reductions in CT dose inherently create an increase in image noise, and the current focus of research and development in the area of CT radiation dose optimization is on the development of noise reduction algorithms to help preserve image quality in CT images acquired at a significantly reduced radiation dose; iterative reconstruction algorithms currently represent the most exciting dose optimizing developments in CT [26
] (see ). Various modifications of iterative reconstruction are being developed and refined by different CT manufacturers including: adaptive statistical iterative reconstruction (ASIR) (General Electric Healthcare, Milwaukee, Wisconsin), sinogram affirmed iterative reconstruction (SAFIRE) (Siemens Healthcare, Erlangen, Germany), iterative reconstruction in image space (IRIS) (Siemens Healthcare, Erlangen, Germany), adaptive iterative dose reduction (AIDR) (Toshiba Medical Systems, Tustin, California), and iDose (Phillips Healthcare, Best, The Netherlands).
Figure 1 A 25-year-old male presenting with left flank pain. (a) Plain radiograph of the abdomen showing a possible renal calculus in the upper pole of the left kidney (estimated institutional dose ~0.7mSv). The coned pelvic radiograph (b) does not demonstrate (more ...)
Emerging iterative reconstruction algorithms are typically noise efficient and computationally fast, and studies to date have mostly found images with good low-contrast detail, preserved image quality, and have facilitated dose reductions of between 20 and 60% in a variety of phantom [27
] and in vivo
] studies [36
]. Iterative reconstruction will be particularly useful in low-dose CT of the urinary tract where image noise is typically high.
The next step in optimizing image quality in studies acquired at significantly reduced radiation dose is the ongoing development of advanced generations of iterative reconstruction such as model-based iterative reconstruction (MBIR), which is being developed by GE Healthcare. MBIR is a fully iterative reconstruction algorithm, which incorporates a physical model of the CT system into the reconstruction process to characterize the data acquisition process, including noise, beam hardening, and scatter. However, due to limitations in computing power and reconstruction technology, model-based iterative approaches have not been practical for commercial CT scanners until recently as reconstruction times had been exceedingly long.