The Near Future in Cardiac CT Image Reconstruction

Transcription

1 SCCT 2010 The Near Future in Cardiac CT Image Reconstruction Marc Kachelrieß Institute of Medical Physics (IMP) Friedrich-Alexander Alexander-University Erlangen-Nürnberg rnberg

2 Disclosures I have the following financial relationships to disclose Consultant to CT Imaging GmbH Managing director of RayConStruct GmbH Grant supports from AiF, DFG, Intel, Siemens, Varian, Ziehm I will discuss the following off-label use in my presentation Partial scan artifact reduction Dynamic iterative beam hardening correction Blooming artifact reduction Temporal resolution improvement Low-dose phase-correlated image reconstruction

3 Early Cardiac Spiral CT Single Slice CT (RSNA 1997) Standard 4-Slice CT (RSNA 1998) Univ. Erlangen Achenbach, Kalender, Kachelrieß ECG-correlated 1998: First 4D images of the heart! M. Kachelrieß, and W.A. Kalender. Electrocardiogram-correlated image reconstruction from subsecond spiral computed tomography scans of the heart. Med. Phys., 25(12): , December 1998.

4 Outline Cardiac beam hardening correction Iterative reconstruction and restoration Blooming artifact reduction Temporal resolution improvement Low-dose phase-correlated CT Motion compensation techniques Improved DECT reconstruction

5 Perfusion Analysis in CT Time-attenuation curves (TAC) C(t) Healthy Peak enhancement Ischemic Time to peak t Beam hardening artifacts cause an underestimation of the CT-values leading to incorrect perfusion parameters! 130/130

6 DIBHC: Beam Hardening Correction of Three Materials using Temporal Dependence Where is soft tissue? Where is bone? Where is Iodine? soft tissue bone+iodine σ-image bone iodine Stenner et al., Dynamic iterative beam hardening correction (DIBHC) in myocardial perfusion imaging using contrast-enhanced computed tomography. Investigative Radiology 45(6): , June 2010.

7 Original Corrected Difference 4 Application of DIBHC /200 1 Beam hardening Perfusion defect 80/200 0/50 ROI Original CT-values / HU Corrected CT-values / HU / HU (end-diastolic trigger) Rawdata courtesy of Prof. Stephan Achenbach, Department of Cardiology, University of Erlangen-Nürnberg, Erlangen, Germany

8 Iterative Reconstruction Iterative Restoration Iterative image reconstruction comparison in rawdata domain reduces noise reduces cone-beam artifacts enhances spatial resolution reduces beam hardening artifacts time consuming Iterative image restoration comparison in raw data domain not needed for noise reduction operating on an initial FBP image computationally highly efficient FBP (Standard) FBP + Image Restoration Images provided by Siemens Healthcare, Forchheim, Germany

9 Blooming Artifact Reduction High density objects calcifications high iodine concentrations in small vessels Limited spatial resolution blurrs high density regions

10 Blooming Artifact Reduction (BAR) Low resolution image f L (r) High resolution image f H (r) Weight function Bilateral filtered w (r) image f BH (r) Mixing ( 1 w( r) ) f ( r) w( r) f ( ) f ( r) = + r BAR L BH BAR image f BAR (r)

11 Is this a stenosis? B26f B26f Patient-data provided by Prof. Dr. Stephan Achenbach, Universitätsklinikum Erlangen C 150 W 1000 C 150 W 1000

12 Is this a stenosis? B26f B26f+B50f BAR C 150 W 1000 C 150 W 1000 Patient-data provided by Prof. Dr. Stephan Achenbach, Universitätsklinikum Erlangen

13 Stent visibility B26f B26f C 150 W 1000 C 150 W 1000 Patient-data provided by Prof. Dr. Stephan Achenbach, Universitätsklinikum Erlangen

14 Stent visibility B26f B26f+B75f BAR C 150 W 1000 C 150 W 1000 Patient-data provided by Prof. Dr. Stephan Achenbach, Universitätsklinikum Erlangen

15 Visibility of stent lumen B26f B26f Patient-data provided by Prof. Dr. Stephan Achenbach, Universitätsklinikum Erlangen C W C 400 W 1500

16 Visibility of stent lumen B26f B26f+B50f BAR C 400 W 1500 C 400 W 1500 Patient-data provided by Prof. Dr. Stephan Achenbach, Universitätsklinikum Erlangen

17 Temporal Resolution Improvement Temporal resolution can be improved by increasing the gantry rotation speed increasing the number of source detector units using reduced angular coverage for reconstruction Recent improvements in compressed sensing1, 2, 3 appear to enable reconstruction from less data are said to have the potential to improve temporal resolution may allow to reconstruct from only 90 or 2 45 of data 1 Sidky et al., Accurate image reconstruction from few-views and limited-angle data in divergent-beam CT, J. X-ray Sci. Tech., 14: , Chen et al., Temporal resolution improvement using PICCS in MDCT cardiac imaging, Med. Phys. 36: , Ritschl et al., Improved Sparsity-Constrained Image Reconstruction Applied to Clinical CT Data, submitted to IEEE Transactions on Medical Imaging, 2010

18 Approach for itri-piccs and itri-cs Cost function: Constraint α ( f f prior ) + (1 α) f 2 Rf p < ε General proceeding 1. Short scan to initialize ART 2. ART iteration 3. Minimize cost function 4. Continue with step 2 until result is satisfying Improved update strategy itri-piccs α = 0.4 / itri-cs α = 0

19 Example Short Scan itri-piccs itri-cs Dual Source Single Source C/W 200/1000

20 Low-Dose Phase-Correlated (LDPC) Double-Gated Reconstruction 1,2 Small animal cardiac CT imaging requires flat panel detector technology implies rather slow rotation times forces us to do respiratory (R) and cardiac (C) gating suffers from very high respiratory rates (around 150 rpm) and from very high heart rates (around 300 bpm) RC-gating (double gating) results in a very small amount of usable data e.g. 2% for a 10% respiratory and a 20% cardiac window High image quality requires either to scan at very high dose values (> 1 Gy) or to use sophisticated image reconstruction techniques 1 Sawall et al., Boosting image quality in low-dose RC-gated 5D cone-beam micro-ct, 5th European Molecular Imaging Meeting, May Sawall et al., Low Dose Phase Correlated Cone Beam Micro CT of Small Animals, IEEE Medical Imaging Conference, November 2010.

21 Mouse Double-Gating: Prior Art 2800 mgy 1840 mgy 500 mgy M. Drangova, N. L. Ford, S. A. Detombe, A. R. Wheatley, and D. W. Holdsworth, Fast retrospectively gated quantitative four dimensional (4D) cardiac micro computed tomography imaging of free breathing mice, Investigative Radiology, vol. 42, no. 2, pp , Feb C. Badea, B. Fubara, L. Hedlund, and G. Johnson, 4D micro CT of the mouse heart, Molecular Imaging, vol. 4, no. 2, pp , Apr./Jun Conventional, but at low dose

22 LDPC Algorithm edge-preserving smoothing f std =X -1 p p diff =p-xf std f LDPC =f std +X -1 PC p diff use image that is based on all projections as prior (standard image) calculate rawdata difference for desired motion phases perform correction include edge preserving anisotropic filtering Standard image f std reconstructed from all projections. LDPC reconstruction f LDPC.

23 Example, R=0%, Cardiac-Loop Axial Sagittal Coronal σ=125 HU LDPC PC σ=26 HU R=0%, R=10%, C=20% (400 HU / 700 HU)

24 Dose Reduction Study Phase-Correlated Low Dose Phase-Correlated Axial Sagittal Coronal Axial Sagittal Coronal σ=354 HU σ=89 HU 60 mgy σ=198 HU σ=57 HU 250 mgy σ=125 HU σ=26 HU 500 mgy R=0%, C=0%, R=10%, C=20% (400 HU / 800 HU)

25 What to expect is: lower dose less image noise reduced blooming artifacts improved temporal resolution lower beam hardening artifacts more quantitative images (including DE)

26 Thank You!