Evaluation of a commercial deformable image registration algorithm for dual-energy CT processing.

Purpose: Several dual-energy computed tomography (DECT) techniques require a deformable image registration to correct for motion between the acquisition of low and high energy data. However, current DECT software does not provide tools to assess registration accuracy or allow the user to export deformed images, presenting a unique challenge for image registration quality assurance (QA). This work presents a methodology to evaluate the accuracy of DECT deformable registration and to quantify the impact of registration errors on end-product images.

Investigating split-filter dual-energy CT for improving liver tumor visibility for radiation therapy.

Purpose: Accurate liver tumor delineation is crucial for radiation therapy, but liver tumor volumes are difficult to visualize with conventional single-energy CT. This work investigates the use of split-filter dual-energy CT (DECT) for liver tumor visibility by quantifying contrast and contrast-to-noise ratio (CNR).

Methods: Split-filter DECT contrast-enhanced scans of 20 liver tumors including cholangiocarcinomas, hepatocellular carcinomas, and liver metastases were acquired.

Investigating a novel split-filter dual-energy CT technique for improving pancreas tumor visibility for radiation therapy.

Purpose: Tumor delineation using conventional CT images can be a challenge for pancreatic adenocarcinoma where contrast between the tumor and surrounding healthy tissue is low. This work investigates the ability of a split-filter dual-energy CT (DECT) system to improve pancreatic tumor contrast and contrast-to-noise ratio (CNR) for radiation therapy treatment planning.

Materials And Methods: Multiphasic scans of 20 pancreatic tumors were acquired using a split-filter DECT technique with iodinated contrast medium, OMNIPAQUE .