Tomography

Vol. 3 No. 4 - Dec 2017

Tomography is a scientific journal for publication of articles in imaging research

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Ultra-Low-Dose Sparse-View Quantitative CT Liver Perfusion Imaging Esmaeil Enjilela 1 , Ting-Yim Lee 1,2 , Jiang Hsieh 4 , Amol Murjoomdar 3 , Errol Stewart 1 , Mark Dekaban 1 , Feng Su 1 , and Aaron So 2 1 Imaging Research Laboratories, Robarts Research Institute, London, ON, Canada; 2 Imaging Program, Lawson Health Research Institute, London, ON, Canada; 3 Department of Medical Imaging, Western University, London, ON, Canada; and 4 CT Engineering, GE Healthcare, Waukesha, WI Corresponding Author: Aaron So, PhD, FSCCT Imaging Program, Lawson Health Research Institute, 268 Grosvenor Street, London, ON, Canada, N6A 4V2; E-mail: aso@robarts.ca Key Words: sparse-view image reconstruction, compressed sensing, radiation dose reduction, quantitative liver perfusion imaging, hepatic arterial blood flow Abbreviations: Hepatic arterial blood flow (H A BF), hepatocellular carcinoma (HCC), dynamic contrast-enhanced (DCE), filtered backprojection (FBP), compressed sensing (CS), computed tomography perfusion (CTP) Radiation dose of computed tomography liver perfusion imaging can be reduced by collecting fewer x-ray projections in each gantry rotation, but the resulting aliasing artifacts could affect the hepatic perfusion mea- surement. We investigated the effect of projection undersampling on the assessment of hepatic arterial blood flow (H A BF) in hepatocellular carcinoma (HCC) when dynamic contrast-enhanced (DCE) liver images were reconstructed with filtered backprojection (FBP) and compressed sensing (CS). DCE liver images of a patient with HCC acquired with a 64-row CT scanner were reconstructed from all the measured projections (984- view) with the standard FBP and from one-third (328-view) and one-fourth (246-view) of all available projec- tions with FBP and CS. Each of the 5 sets of DCE liver images was analyzed with a model-based deconvolu- tion algorithm from which H A BF maps were generated and compared. Mean H A BF in the tumor and normal tissue measured by the 328-view CS and FBP protocols was within 5% differences from that assessed by the reference full-view FBP protocol. In addition, the tumor size measured by using the 328-view CS and FBP average images was identical to that determined by using the full-view FBP average image. By contrast, both the 246-view CS and FBP protocols exhibited larger differences (.20%) in anatomical and functional assess- ments compared with the full-view FBP protocol. The preliminary results suggested that computed tomography perfusion imaging in HCC could be performed with 3 times less projection measurement than the current full-view protocol (67% reduction in radiation dose) when either FBP or CS was used for image reconstruction. INTRODUCTION There has been considerable improvement in the therapeutic treat- ments for hepatocellular carcinoma (HCC) and other metastatic diseases in recent years. These advanced therapies require diagnos- tic and surveillance tools beyond morphology to prevail (1). Quan- titative computed tomography perfusion (CTP) can go beyond morphological classification and provide a more accurate tissue characterization via quantitative assessment of hepatic arterial blood flow (H A BF), which is a useful marker of primary and met- astatic hepatic malignancies (1). However, one limitation of the CTP assessment of H A BF is the higher radiation dose arising from re- peatedly scanning the liver after contrast administration (1-3). Radiation dose reduction for a hepatic CTP study can be achieved by scanning the liver with low x-ray tube current (measured in milliampere) (4, 5). Although the x-ray photon noise in projections can be modeled and corrected for using statistical iterative reconstruction algorithms (6), the dominant electronic noise in very low milliampere conditions cannot be properly modeled with Poisson statistics alone (7), which may lead to poor tumor visualization and inaccurate assessment of hepatic perfusion. Alternatively, dose reduction can be achieved by reducing the number of projections collected in each gantry rotation. However, the aliasing artifact arising from projection undersampling could substantially affect the dynamic contrast- enhanced (DCE) liver images, which could lead to inaccurate hepatic perfusion measurement. Compressed sensing (CS) was first introduced for signal recovery from underdetermined linear measurements (8) and later exploited for magnetic resonance imaging and computed tomography (CT) reconstruction in sparse sampling conditions (9-12). In this study, we investigated the effectiveness of CS and the conventional filtered backprojection (FBP) for reconstruct- ing DCE-CT images of the liver from a subset of measured projections in an HCC perfusion study, to determine if sparse- view dynamic acquisition and image reconstruction are feasible for ultra-low-dose CT liver perfusion imaging. ADVANCES IN BRIEF ABSTRACT © 2017 The Authors. Published by Grapho Publications, LLC This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). ISSN 2379-1381 http://dx.doi.org/10.18383/j.tom.2017.00018 TOMOGRAPHY.ORG | VOLUME 3 NUMBER 4 | DECEMBER 2017 175

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