Publications by authors named "Shun Hayasaka"

Purpose: Late arterial phase images of SD 8, SD 10, and SD 12 were acquired in the 3-phase dynamic study of the liver in combination with hybrid iterative reconstruction. We evaluated the low-contrast detectability by adding a simulated tumor to these images and aimed to formulate a standard image quality.

Methods: We prepared images with and without signal for 60 series of 20 samples, each with 3 image quality types (total: 120 series).

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Although the liver is a regenerating organ, excessive loss of liver volume (LV) can cause fatal liver failure. It is unclear whether LV is correlated with age; however, it is known that liver function decreases with age. In addition, the gender-related role of LV remains unclear.

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Purpose: To assess whether fusion 3D-CTA images can be corrected using non-rigid registration (NRR) for gastroenterology imaging.

Methods: This study included 55 patients before gastroenterology surgery who underwent preoperative 3D-CTA prior to gastroenterological surgery. We recorded the coordinate of measurement points on the arterial vessels (X, Y, and Z) in each portal phase, original image of the arterial phase, and arterial phase with NRR.

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Computed tomography arterial portography (CTAP) is widely used with a fixed scan timing and contrast medium quantity; however, these parameters are not necessarily optimal. In this study, CTAP scan timing was analyzed by different bolus tracking methods to monitor the inflow of the contrast medium in real-time. A total of 249 patients who underwent CTAP were assessed.

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Purpose: We developed a novel digital phantom-creation tool that will help formulate the standard shooting method for a three-phase dynamic liver study. Here, we present data demonstrating the usefulness of this tool in the assessment of low-contrast detectability and visibility.

Methods: We performed a visual evaluation by adding a spherical digital phantom with a diameter of 8 mm and a computed tomography (CT) value difference of 10 Hounsfield unit (HU) to images taken using filtered back projection and seven types of adaptive iterative dose reduction 3D (Weak, Mild, eMild, Standard, eStandard, Strong, and eStrong).

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