The role of advanced reconstruction algorithms in cardiac CT

Sandra S. Halliburton, Yuki Tanabe, Sasan Partovi, Prabhakar Rajiah
2017 Cardiovascular Diagnosis and Therapy  
Advanced non-linear iterative reconstruction (IR) algorithms have been introduced by all vendors as an alternative to traditional, linear filtered back projection (FBP) reconstruction ( Table 1) . FBP is a simple reconstruction technique that requires relatively little computational processing, but is associated with higher noise and poor contrast resolution. Noise can be reduced in FBP only by increasing the radiation dose. IR algorithms operate by initially generating an expected dataset
more » ... on modeling, which is then compared to the actual, acquired dataset. Noise is detected and removed by using the difference between the anticipated and actual datasets using a process of iterative steps. All commercial IR algorithms employ statistics-model based de-noising in the image domain, raw (projection) data domain, or both. Statistics model-based algorithms operate by assigning a lower value to data with higher statistical uncertainty (noise). Some IR algorithms, described as partial model-based, additionally employ models of scanner geometry to estimate the acquired data. Full model-based IR algorithms, employ complete system models that include simulation of X-ray interaction with the imaged object. Statistics-model based algorithms can be utilized to either improve image quality at the same radiation dose or maintain image quality at a lower radiation dose compared to FBP. However, combining dose management with image quality improvements simultaneously is limited. Model-based IR can provide image quality improvements at lower doses. Model-based algorithms are also more likely to reduce other artifacts in addition to noise as well as improve spatial resolution. Although IR algorithms have been utilized in nuclear medicine for several decades, widespread use in CT is recent and facilitated by advances in computational processing. Cardiovascular CT imagers were early adopters of IR algorithms because most cardiovascular clinical targets are robust to changes in noise. Rigorous validation has come from both retrospective and prospective studies demonstrating non-inferiority of coronary CT data acquired at lower doses and reconstructed with IR techniques compared to standard dose data reconstructed with FBP. Other clinical studies have validated the diagnostic utility of low-dose coronary CT angiograms (CTA) reconstructed with IR algorithms using invasive coronary angiography (ICA) as a standard of reference (1-3). Abstract: Non-linear iterative reconstruction (IR) algorithms have been increasingly incorporated into clinical cardiac CT protocols at institutions around the world. Multiple IR algorithms are available commercially from various vendors. IR algorithms decrease image noise and are primarily used to enable lower radiation dose protocols. IR can also be used to improve image quality for imaging of obese patients, coronary atherosclerotic plaques, coronary stents, and myocardial perfusion. In this article, we will review the various applications of IR algorithms in cardiac imaging and evaluate how they have changed practice.
doi:10.21037/cdt.2017.08.12 pmid:29255694 pmcid:PMC5716948 fatcat:wa36vchxd5ci7gzcoioeamnl2i