Abstract
The purpose of this study was to compare the ability of multidetector computed tomography (MDCT) and magnetic resonance imaging (MRI) to evaluate treatment results after transarterial chemoembolization (TACE), with a special focus on the influence of Lipiodol on calculation of tumor necrosis according to EASL criteria. A total of 115 nodules in 20 patients (17 males, 3 females; 69.5 ± 9.35 years) with biopsy-proven hepatocellular carcinoma were treated with TACE. Embolization was performed using a doxorubicin-Lipiodol emulsion (group I) or DC Beads loaded with doxorubicin (group II). Follow-up included triphasic contrast-enhanced 64-row MDCT (collimation, 0.625 mm; slice, 3 mm; contrast bolus, 120 ml iomeprol; delay by bolus trigger) and contrast-enhanced MRI (T1 native, T2 native; five dynamic contrast-enhanced phases; 0.1 mmol/kg body weight gadolinium-DTPA; slice thickness, 4 mm). Residual tumor and the extentoftumor necrosis were evaluated according to EASL. Contrast enhancement within tumor lesions was suspected to represent vital tumor. In the Lipiodol-based TACE protocol, MDCT underestimated residual viable tumor compared to MRI, due to Lipiodol artifacts (23.2% vs 47.7% after first, 11.9% vs 31.2% after second, and 11.4% vs 23.7% after third TACE; p = 0.0014, p < 0.001, and p <0.001, respectively). In contrast to MDCT, MRI was completely free of any artifacts caused by Lipiodol. In the DC Bead-based Lipiodol-free TACE protocol, MRI and CT showed similar residual tumor and rating of treatment results (46.4% vs 41.2%, 31.9 vs 26.8%, and 26.0% vs 25.6%; n.s.). In conclusion, MRI is superior to MDCT for detection of viable tumor residuals after Lipiodol-based TACE. Since viable tumor tissue is superimposed by Lipiodol artifacts in MDCT, MRI is mandatory for reliable decision-making during follow-up after Lipiodol-based TACE protocols.
| Original language | English |
|---|---|
| Journal | CardioVascular and Interventional Radiology |
| Volume | 33 |
| Issue number | 3 |
| Pages (from-to) | 532-540 |
| Number of pages | 9 |
| ISSN | 0174-1551 |
| DOIs | |
| Publication status | Published - 06.2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 9 Industry, Innovation, and Infrastructure
Research Areas and Centers
- Academic Focus: Biomedical Engineering
DFG Research Classification Scheme
- 2.22-30 Radiology
- 2.22-32 Medical Physics, Biomedical Technology
- 2.22-14 Hematology, Oncology
- 2.22-15 Gastroenterology
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