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Taiga Goto

Publications and source records attributed to Taiga Goto.

2 recordsLinked to original sources

Improvement of low-contrast detectability in low-dose hepatic multidetector computed tomography using a novel adaptive filter: evaluation with a computer-simulated liver including tumors.

PURPOSE: The purpose of this study was to investigate how much radiation dose can be reduced without loss of low-contrast detectability with a newly developed adaptive noise reduction filter in hepatic multidetector computed tomography (MDCT) scans by using a computer-simulated liver phantom. MATERIALS AND METHODS: Simulated CT images, including liver and intrahepatic tumors, were mathematically constructed using a computer workstation to evaluate low-contrast detectability by the observer performance test. Milliampere second for construction of simulated images were 60, 80, 100, and 120 mAs (low dose) and 160 mAs (standard dose) at 120 kVp. Images with 60, 80, 100, and 120 mAs were postprocessed with the adaptive noise reduction filter. A total of 432 images were prepared and receiver operating characteristic (ROC) analysis was performed by 5 radiologists. The detectability of simulated tumor by radiologists was estimated with the area under the ROC curves (Az values). In addition, we visually evaluated CT images of 15 patients with chronic liver damage for graininess of the liver parenchyma, sharpness of the liver contour, conspicuity and marginal sharpness of the liver tumors, and overall image quality. RESULTS: The mean Az value at 0.777 (60 mAs), 0.828 (80 mAs), and 0.844 (100 mAs) without filter was significantly lower than that of 160 mAs without filter (P < 0.001, 60 mAs; P = 0.010, 80 mAs; P = 0.040, 100 mAs). There was no statistical difference between the mean Az value at 80 mAs with and 160 mAs without the adaptive noise reduction filter (P = 0.220) and 100 mAs with and 160 mAs without the adaptive noise reduction filter (P = 0.979). In the visual evaluation of patient livers, there was no statistical difference in the graininess and sharpness of the liver, the conspicuity and marginal sharpness of the tumor, and the overall image quality between standard-dose and filtered low-dose images (Wilcoxon signed rank test, P > 0.05). CONCLUSION: The radiation dose can be reduced by 50% without loss of nodule detectability by applying the adaptive noise reduction filter to simulated and patient liver images obtained at MDCT.

Aged↗

A computer-simulated liver phantom (virtual liver phantom) for multidetector computed tomography evaluation.

OBJECTIVE: The purpose of study was to develop a computer-simulated liver phantom for hepatic CT studies. A computer-simulated liver phantom was mathematically constructed on a computer workstation. MATERIALS AND METHODS: The computer-simulated phantom was calibrated using real CT images acquired by an actual four-detector CT. We added an inhomogeneous texture to the simulated liver by referring to CT images of chronically damaged human livers. The mean CT number of the simulated liver was 60 HU and we added numerous 5-to 10-mm structures with 60+/-10 HU/mm. To mimic liver tumors we added nodules measuring 8, 10, and 12 mm in diameter with CT numbers of 60+/-10, 60+/-15, and 60+/-20 HU. Five radiologists visually evaluated similarity of the texture of the computer-simulated liver phantom and a real human liver to confirm the appropriateness of the virtual liver images using a five-point scale. RESULTS: The total score was 44 in two radiologists, and 42, 41, and 39 in one radiologist each. They evaluated that the textures of virtual liver were comparable to those of human liver. CONCLUSIONS: Our computer-simulated liver phantom is a promising tool for the evaluation of the image quality and diagnostic performance of hepatic CT imaging.

Computer Simulation↗