Dynamic Iterative Beam Hardening Correction (DIBHC) in Myocardial Perfusion Imaging Using Contrast-Enhanced Computed Tomography

Stenner, Philip Dipl-Phys^*; Schmidt, Bernhard PhD^†; Allmendinger, Thomas PhD^†; Flohr, Thomas PhD^†; Kachelrie, Marc PhD^*ß

Author Information

From the *Institute of Medical Physics, University of Erlangen-Nürnberg, Erlangen, Germany; and †Siemens AG, Healthcare Sector, Forchheim, Germany.

Received December 2, 2009; accepted for publication (after revision) February 26, 2010.

Supported by Siemens Healthcare, Forchheim, Germany and funded in parts by the Deutsche Forschungsgemeinschaft (DFG) under grant KA1678/3–1.

Corresponding author: Philip Stenner, Dipl-Phys, Institute of Medical Physics, University of Erlangen-Nürnberg, Henkestraße 91, D-91052 Erlangen, Germany. E-mail:[email protected].

Investigative Radiology45(6):p 314-323, June 2010. |DOI:10.1097/RLI.0b013e3181e0300f

Abstract

Objectives:

In cardiac perfusion examinations with computed tomography (CT) large concentrations of iodine in the ventricle and in the descending aorta cause beam hardening artifacts that can lead to incorrect perfusion parameters. The aim of this study is to reduce these artifacts by performing an iterative correction and by accounting for the 3 materials soft tissue, bone, and iodine.

Materials and Methods:

Beam hardening corrections are either implemented as simple precorrections which cannot account for higher order beam hardening effects, or as iterative approaches that are based on segmenting the original image into material distribution images. Conventional segmentation algorithms fail to clearly distinguish between iodine and bone. Our new algorithm, DIBHC, calculates the time-dependent iodine distribution by analyzing the voxel changes of a cardiac perfusion examination (typicallyN ≈ 15 electrocardiogram-correlated scans distributed over a total scan time up toT ≈ 30 s). These voxel dynamics are due to changes in contrast agent. This prior information allows to precisely distinguish between bone and iodine and is key to DIBHC where each iteration consists of a multimaterial (soft tissue, bone, iodine) polychromatic forward projection, a raw data comparison and a filtered backprojection. Simulations with a semi-anthropomorphic dynamic phantom and clinical scans using a dual source CT scanner with 2 × 128 slices, a tube voltage of 100 kV, a tube current of 180 mAs, and a rotation time of 0.28 seconds have been carried out.

Results:

The uncorrected images suffer from beam hardening artifacts that appear as dark bands connecting large concentrations of iodine in the ventricle, aorta, and bony structures. The CT-values of the affected tissue are usually underestimated by roughly 20 HU although deviations of up to 61 HU have been observed. For a quantitative evaluation circular regions of interest have been analyzed. After application of DIBHC the mean values obtained deviate by only 1 HU for the simulations and the corrected values show an increase of up to 61 HU for the measurements.

Conclusions:

One iteration of DIBHC greatly reduces the beam hardening artifacts induced by the contrast agent dynamics (and those due to bone) now allowing for an improved assessment of contrast agent uptake in the myocardium which is essential for determining myocardial perfusion.