Program Information

Spectral Photon-Counting Computed Tomography for Classification of Liver Lesions

P Noel

D Muenzel , H Daer , R Proksa , A Fingerle , F Kopp , P Douek , J Herzen , F Pfeiffer , E Rummeny , PB Noel*, Technical University Munich, Munich, Bavaria

Presentations

WE-DE-605-3 (Wednesday, August 2, 2017) 10:15 AM - 12:15 PM Room: 605

Purpose: To introduce dual-contrast agent spectral photon-counting computed tomography (SPCCT) in liver imaging for improved visual and automated detection and characterization of lesions.

Methods: We present simulations of SPCCT with two contrast agents (CA) that simultaneously map the complementary distribution of CA1 (gadolinium) and CA2 (iodine) in the liver. We employed liver lesions with a characteristic arterial and portal venous pattern (hemangioma, hepatocellular carcinoma, cyst, metastasis) and different diameters (5-20 mm). The image acquisition is simulated at the time point with portal venous contrast distribution of CA1 and arterial contrast phase for CA2. A material decomposition was performed to reconstruct quantitative iodine and gadolinium maps. Finally, we introduced a multi-dimensional classification algorithm for automatic detection of different liver lesions.

Results: With SPCCT and an adapted contrast injection protocol, it was possible to reconstruct contrast-enhanced images of the liver with arterial distribution of CA2 and portal venous phase of CA1 in a single CT scan. All four synthetically inserted liver lesions are clearly differentiable, and the characteristic patterns of contrast enhancement are visible in the arterial and portal venous maps. The approach allows for an automatic detection and classification procedure of liver lesions using a multi-dimensional analysis.

Conclusion: Dual-contrast SPCCT simultaneously visualizes the characteristic arterial and portal venous enhancement in a single scan. This provides an automatic detection and characterization of lesions on the basis of a pixel-by-pixel comparison of the image and the CA maps without patient motion. Additionally, the proposed application significantly reduces radiation dose.


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