Basics of iterative reconstruction methods in computed tomography: A vendor-independent overview. Issue 109 (December 2018)

• Record Type: Journal Article
• Authors: Stiller, Wolfram
• Is Part Of: European journal of radiology. Issue 109(2018)
• Page Start: 147
• Page End: 154
• Publication Date: 2018-12
• Subjects: CNR contrast-to-noise ratio -- CT computed tomography -- CTDIvol volumetric computed tomography dose index -- FBP filtered back projection -- IQ image quality -- IR iterative image reconstruction -- kVp kilovolt peak (unit of tube potential) -- mAs milliampere second (unit of tube current-time product) -- MBIR model-based iterative reconstruction -- MTF modulation transfer function -- NPS noise power spectrum -- ROI region-of-interest -- SD standard deviation (image noise) -- SNR signal-to-noise ratio; Tomography, X-ray computed -- Image reconstruction -- Filtered back projection -- Iterative reconstruction -- Image quality -- Radiation dose reduction; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2018.10.025
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: Compared to filtered back projection, iterative reconstruction enhances image quality through noise and artifact reduction. Enhanced image quality of iterative reconstruction can be exploited for radiation dose reduction in CT. Iterative reconstruction preserves diagnostic image quality, e.g. for reduced-dose CT and in obese patients. Iteratively reconstructed image data may seem artificial due to lack of noise and altered, unfamiliar texture. Iterative reconstruction may need suited image quality metrics and adapted reference standards for quantitative CT. Abstract: Over the past two decades, technical innovations in computed tomography (CT) have constantly extended its spectrum of clinical applications and made new radiodiagnostic applications accessible. At the same time, concerns have arisen with respect to the radiation exposure to the patients caused by CT examinations. In order to address this issue, different strategies for radiation dose reduction in CT have been introduced, spanning technical approaches as well as specific examination techniques applied in clinical practice, such as reduced-dose CT. Developed technical approaches for reducing radiation dose in CT by improvements of CT scanner hardware and acquisition mechanisms, however, have not been sufficient to address the degradation of image quality caused by increasing noise and susceptibility to artifacts inherent to reduced-dose CT acquisitions. Recent advances in computing power have enabled the development of software-based methods for iterative image reconstruction (IR) in CT enabling simultaneous reduction of image noise and improvement of overall image quality. Thereby, IR allows for dose reduction by reconstruction of low-noise image data from intrinsically noisy reduced-dose CT acquisitions, thereby preserving diagnostic image quality equivalent to current clinical standards. This review provides an overview of the underlying basic principles of iterative image reconstruction methods currently available for and applied in CT imaging, independent of vendor-specific details regarding algorithms and implementations. It discusses potential strengths and weaknesses of these CT image reconstruction techniques in view of their application in clinical routine, especially in view of the potential of IR for noise and artifact reduction as well as for radiation dose reduction. Furthermore, the effect of statistical (hybrid) and model-based IR methods on image quality are exemplarily illustrated in comparison to filtered back projection (FBP) traditionally used for image reconstruction in CT.