Hiroyuki Uetani
Overview
Explore the profile of Hiroyuki Uetani including associated specialties, affiliations and a list of published articles.
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77
Citations
436
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0
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Recent Articles
11.
Hokamura M, Nakaura T, Yoshida N, Uetani H, Shiraishi K, Kobayashi N, et al.
Eur J Radiol
. 2024 Jul;
178:111587.
PMID: 39002269
Objectives: This study aims to assess the effectiveness of super-resolution deep-learning-based reconstruction (SR-DLR), which leverages k-space data, on the image quality of lumbar spine magnetic resonance (MR) bone imaging using...
12.
Kobayashi N, Nakaura T, Shiraishi K, Uetani H, Nagayama Y, Kidoh M, et al.
J Comput Assist Tomogr
. 2024 May;
49(1):125-132.
PMID: 38718419
Objective: The purpose of this study was to evaluate the usefulness of the injection pressure-to-injection rate (IPIR) ratio for the early detection of contrast extravasation at the venipuncture site during...
13.
Hayashi H, Kiyosue H, Tamura Y, Ueda H, Yonemura M, Sasaki G, et al.
J Vasc Interv Radiol
. 2024 Mar;
35(7):979-988.e1.
PMID: 38537737
Purpose: To assess the different adjunctive catheter techniques required to achieve complete occlusion of renal arteriovenous malformations (rAVMs) of different angioarchitectural types. Materials And Methods: Overall, data on 18 patients...
14.
Hokamura M, Uetani H, Hamasaki T, Nakaura T, Morita K, Yamashita Y, et al.
Neuroradiology
. 2024 Mar;
66(7):1123-1130.
PMID: 38480538
Purpose: We aimed to evaluate the effect of deep learning-based reconstruction (DLR) on high-spatial-resolution three-dimensional T2-weighted fast asymmetric spin-echo (HR-3D T2-FASE) imaging in the preoperative evaluation of cerebellopontine angle (CPA)...
15.
Sasaki G, Uetani H, Nakaura T, Nakahara K, Morita K, Nagayama Y, et al.
J Comput Assist Tomogr
. 2024 Feb;
48(5):819-825.
PMID: 38346820
Objective: The aim of this study was to assess the utility of the combined use of 3D wheel sampling and deep learning-based reconstruction (DLR) for intracranial high-resolution (HR)-time-of-flight (TOF)-magnetic resonance...
16.
Shinojima N, Yano S, Uchida D, Mizukami N, Mabe H, Kawashima J, et al.
J Clin Neurosci
. 2024 Jan;
120:138-146.
PMID: 38244528
Craniopharyngiomas are difficult to resect completely, recurrence is frequent, and hypothalamic/pituitary function may be affected after surgery. Therefore, the ideal treatment for craniopharyngiomas is local control with preservation of hypothalamic...
17.
Inoue H, Kuroda J, Uetani H, Matsuyama T, Kaku Y, Shinojima N, et al.
Neuroradiology
. 2024 Jan;
66(3):325-332.
PMID: 38200284
Purpose: Leptomeningeal enhancement (LME) suggests leptomeningeal dissemination (LMD) of tumor cells, which is a complication of end-stage glioblastoma, and is associated with a poor prognosis. However, magnetic resonance imaging (MRI)...
18.
Harada K, Shinojima N, Yamamoto H, Itoyama M, Uchida D, Dekita Y, et al.
Cureus
. 2024 Jan;
16(1):e51605.
PMID: 38173946
Chordoma is a rare tumor that arises from chordal tissue during fetal life. Recently, the concept of poorly differentiated chordoma, a subtype of chordoma characterized by loss of / with...
19.
Hokamura M, Uetani H, Nakaura T, Matsuo K, Morita K, Nagayama Y, et al.
Neuroradiology
. 2023 Dec;
66(2):217-226.
PMID: 38148334
Purpose: The aim of this study is to assess the effect of super-resolution deep learning-based reconstruction (SR-DLR), which uses k-space properties, on image quality of intracranial time-of-flight (TOF) magnetic resonance...
20.
Kaku Y, Ohmori Y, Kameno K, Uchikawa H, Takemoto Y, Kawano T, et al.
Neurosurgery
. 2023 Dec;
PMID: 38108408
Background And Objectives: The choice between inhalational and total intravenous anesthesia (TIVA) in revascularization surgery for Moyamoya disease (MMD) remains a topic of debate. Anesthesia methods have changed with the...