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Related Concept Videos

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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization
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Ultrafast cone-beam computed tomography imaging and postprocessing data during image-guided therapeutic practice.

Jijo Paul1, Emmanuel C Mbalisike, Thomas J Vogl

  • 1Diagnostic and Interventional Radiology, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt/Main, Germany, jijopaul1980@gmail.com.

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Ultrafast cone-beam CT (u-CBCT) with perfusion blood volume (PBV) and MRI fusion improves tumor detection and guidance during chemoembolization. This technique enhances tumor delineation, differentiation, and identification of feeding vessels and catheter tips.

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Area of Science:

  • Radiology
  • Medical Imaging
  • Oncology

Background:

  • Transarterial chemoembolization (TCE) is a standard cancer treatment.
  • Accurate tumor detection and guidance are crucial for effective TCE.
  • Limitations exist in current imaging techniques for precise tumor delineation and vessel identification.

Purpose of the Study:

  • To evaluate ultrafast cone-beam computed tomography (u-CBCT) imaging data.
  • To assess the utility of cross-sectional images, perfusion blood volume (PBV), and image fusion for tumor detection during TCE.
  • To compare the efficacy of different u-CBCT data sets for tumor delineation and catheter guidance.

Main Methods:

  • One hundred fifty patients undergoing TCE were examined using u-CBCT.
  • Tumor delineation and conspicuity were assessed using u-CBCT cross-sectional PBV and u-CBCT-MRI fused datasets.
  • Catheter localization and feeding vessel identification were evaluated using all available data sets.

Main Results:

  • Significant differences in tumor delineation were observed across different tumor categories (P < 0.05).
  • Mean tumor-liver contrast was significantly higher in hyperenhanced (HYET) tumors compared to heterogeneously enhanced (HEET) and unenhanced (UET) tumors (P < 0.0001).
  • Image fusion demonstrated statistically significant higher values for catheter localization and feeding vessel identification compared to other datasets (P < 0.05).

Conclusions:

  • u-CBCT cross-sectional images with contrast material enable clear tumor delineation.
  • Postprocessed perfusion blood volume (PBV) using u-CBCT enhances tumor detectability and differentiation.
  • Image fusion of u-CBCT and MRI data provides accurate image guidance for TCE, including tumor and feeding vessel identification and catheter tip localization.