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Yoshiko Ramirez Ueno,Tsutomu Tamada,Satoru Takahashi,Utaru Tanaka,Keitaro Sofue,Tomonori Kanda,Munenobu Nogami,Yoshiharu Ohno,Nobuyuki Hinata,Masato Fujisawa,Takamichi Murakami 대한영상의학회 2018 Korean Journal of Radiology Vol.19 No.5
Computed diffusion-weighted MRI is a recently proposed post-processing technique that produces b-value images from diffusion-weighted imaging (DWI), acquired using at least two different b-values. This article presents an argument for computed DWI for prostate cancer by viewing four aspects of DWI: fundamentals, image quality and diagnostic performance, computing procedures, and future uses.
Sofue Keitaro,Shimada Ryuji,Ueshima Eisuke,Komatsu Shohei,Yamaguchi Takeru,Yabe Shinji,Ueno Yoshiko,Hori Masatoshi,Murakami Takamichi 대한영상의학회 2024 Korean Journal of Radiology Vol.25 No.1
Despite improvements in operative techniques and perioperative care, post-hepatectomy liver failure (PHLF) remains the most serious cause of morbidity and mortality after surgery, and several risk factors have been identified to predict PHLF. Although volumetric assessment using imaging contributes to surgical simulation by estimating the function of future liver remnants in predicting PHLF, liver function is assumed to be homogeneous throughout the liver. The combination of volumetric and functional analyses may be more useful for an accurate evaluation of liver function and prediction of PHLF than only volumetric analysis. Gadoxetic acid is a hepatocyte-specific magnetic resonance (MR) contrast agent that is taken up by hepatocytes via the OATP1 transporter after intravenous administration. Gadoxetic acid-enhanced MR imaging (MRI) offers information regarding both global and regional functions, leading to a more precise evaluation even in cases with heterogeneous liver function. Various indices, including signal intensity-based methods and MR relaxometry, have been proposed for the estimation of liver function and prediction of PHLF using gadoxetic acid-enhanced MRI. Recent developments in MR techniques, including high-resolution hepatobiliary phase images using deep learning image reconstruction and whole-liver T1 map acquisition, have enabled a more detailed and accurate estimation of liver function in gadoxetic acid-enhanced MRI.