Original PaperIterative reconstruction methods in two different MDCT scanners: Physical metrics and 4-alternative forced-choice detectability experiments – A phantom approach
Introduction
Today, ionizing radiation from computed tomography (CT) scanners represents the greatest per capita medical exposure for the population of industrialized countries [1], [2], [3], [4], [5], [6]. Although this growth is mainly attributed to the increasing number of CT examinations, CT dose per examination is still high and remains an important concern.
Recently, new reconstruction algorithms based on iterative approaches were launched to complete existing strategies already widespread as a way to reduce CT dose during patient examination (tube current modulation, automatic exposure control, high pitch values on dual-source CT, automated kV modulation, etc.) [7], [8], [9], [10]. In 2008, General Electric (Milwaukee, WI, USA) introduced the first CT iterative reconstruction method commercially available for clinical applications, under the name of adaptive statistical iterative reconstruction (ASIR™). ASIR uses a blend of filtered back-projection (FBP) images with iteratively reconstructed images in the raw data domain to reduce the image noise [11], [12], [13], [14]. Two years later, Siemens (Erlangen, Germany) released an iterative reconstruction in image space (IRIS™). Contrary to ASIR, IRIS is based on an iterative reconstruction loop in the image domain to speed up the reconstruction process [15], [16], [17]. In 2011, Philips commercialized the fourth version of its iterative method, which was called iDose4 (™). This method attempts to reduce image noise without modifying the noise power spectrum (NPS) in order to keep close to the noise texture of classical FBP images [18], [19]. After noise removal in the raw data domain, an optimal anatomical model is used in the image domain to iteratively eliminate the quantum image noise and to maintain the appearance of full dose image. Toshiba (Tochigi, Japan) has also developed an iterative method, adaptive iterative dose reduction (AIDR™), which is adaptive and automatically calculates the optimized number of iterations [20]. Recently, GE introduced a full iterative reconstruction or model-based iterative reconstruction (MBIR), under the commercial name of VEO™. Unlike its first iterative reconstruction ASIR, VEO is a fully iterative method working in the raw data domain, which takes not only the data statistics into account but also the geometry of the machine itself by considering the voxel volumes of the scanned object, the focal spot size, the active area size of the detector, etc. Moreover, to enhance model precision of the CT scanner, complex mathematical formulations were determined to account for physical effects such as beam hardening, scatter and metal attenuation artifacts [20], [21]. Due to its complexity and specific properties, VEO is currently only designed for acquisitions performed with the Discovery CT750 HD scanner (GE Healthcare, Waukesha, WI, USA) and important reconstruction time is still required to reconstruct CT images.
The number and variety of new reconstruction methods introduces the need of investigating their dose and image quality relationships. Therefore, the purpose of this work was to characterize three commercial iterative reconstructions, ASIR, VEO and iDose4, through standard physical metrics (CT number accuracy, standard deviation (SD), modulation transfer function (MTF) and noise power spectrum) measured on Catphan phantom images. To go a step beyond physical measurements, five human observers performed four-alternative forced-choice (4AFC) experiments under the signal-known-exactly (SKE) paradigm to assess the detectability of low- and high-contrast objects embedded in two pediatric phantoms. Simple contrast and signal-difference-to-noise ratio (SDNR) metrics were also calculated and compared to low-contrast 4AFC results.
Section snippets
Data acquisition and image reconstruction
Images were acquired on two multi-detector CT (MDCT) scanners: (A) a 128-slice Discovery CT750 HD scanner and (B) a 128-slice Ingenuity CT (Philips Healthcare, Cleveland, OH, USA). Both systems were equipped with 64-row detector arrays able to supply up to 40 mm collimation with a standard configuration of 64 × 0.625 mm. Standard physical metrics were measured from Catphan 600 phantom (Phantom Laboratory, Salem, NY, USA) images scanned at 80 and 120 kVp. Because dose reduction is a main concern
Results
The normalized weighted CTDI (nCTDIw) measured at 80 kVp and 120 kVp in the 32 cm CTDI test phantom and at 80 kVp in the 16 cm phantom are presented in Table 2, Table 3. A good agreement (<14%) between console displays and measured values was obtained for both CT units.
Discussion
The purpose of this work was to characterize and compare three iterative reconstruction methods available on two commercial CT units using physical metrics and 4AFC detectability experiments. Because protocol parameters were slightly different (due to CT unit specificities), results were analyzed only when compared to the conventional FBP reconstruction method within the same unit.
For unit A, the second-generation iterative reconstruction VEO showed a large reduction of image noise combined
Conclusion
Based on phantom approaches, our results show that first-generation iterative reconstruction methods ASIR and iDose4 provide similar benefits and mainly act on noise reduction. Clinical studies have confirmed that these methods are able to strongly reduce image noise and allow a significant dose reduction (30–65%) with reconstruction time almost as fast as standard FBP methods [11], [12], [13], [14], [19]. Second-generation iterative reconstruction VEO shows extra noise reduction when compared
Acknowledgments
We would like to thank Professor Olivier Hélénon, chairman of the adult radiology department in the Necker Children’s Hospital of Paris, for his assistance and for providing the machine time required to perform this study as well as Stéphanie Bermon, Ivan Diaz, Eleni Samara and Dimitra Touli, for their participation in this study. This research was supported by the Swiss National Science Foundation grant [# 320030-120382].
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