Hiroyuki Uetani
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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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Recent Articles
1.
Hayashi H, Kiyosue H, Tamura Y, Yonemura M, Uchiumi S, Watanabe Y, et al.
J Neuroendovasc Ther
. 2025 Feb;
19(1).
PMID: 40007972
Objective: Duplication of extracranial cerebral arteries is a rare anatomical variant, most commonly observed in the vertebral artery. However, duplication of the cervical internal carotid artery (ICA) is extremely rare....
2.
Murakami H, Mizutani H, Nakahara K, Uetani H, Kaku Y, Nakajima M, et al.
Cureus
. 2025 Feb;
16(12):e76708.
PMID: 39898149
Spinal arteriovenous fistula (SAVF), including spinal dural arteriovenous fistula and spinal extradural arteriovenous fistula (SEAVF), is a rare spinal vascular disorder characterized by abnormal intradural and extradural arteriovenous shunting, often...
3.
Shiraishi K, Nakaura T, Yoshida N, Matsuo K, Kobayashi N, Hokamura M, et al.
J Comput Assist Tomogr
. 2025 Jan;
PMID: 39761494
Objective: This preliminary study aims to assess the image quality of enhanced-resolution deep learning reconstruction (ER-DLR) in magnetic resonance cholangiopancreatography (MRCP) and compare it with non-ER-DLR MRCP images. Methods: Our...
4.
Uchimura R, Khant Z, Hayashi H, Nagayama Y, Uetani H, Kaku Y, et al.
J Comput Assist Tomogr
. 2025 Jan;
PMID: 39761489
Objective: Discriminating between hemorrhage and iodine extravasation can pose challenges in conventional computed tomography (CCT) images following preoperative embolization for meningioma. This study aimed to assess the efficacy of dual-energy...
5.
Sasaki G, Uetani H, Kuroda J, Kitajima M, Ishiuchi S, Sato K, et al.
Neuroradiology
. 2024 Dec;
PMID: 39699645
Purpose: In the 2016 WHO Classification of Lymphoid Tissue Neoplasms, co-expression of MYC and BCL2 is newly designated as double expressor lymphoma. Patients with primary central nervous system lymphoma with...
6.
Shiraishi K, Nakaura T, Kobayashi N, Uetani H, Nagayama Y, Kidoh M, et al.
Magn Reson Imaging
. 2024 Dec;
117:110308.
PMID: 39667642
Purposes: This study aimed to assess the effectiveness of Super-Resolution Deep Learning Reconstruction (SR-DLR) -a deep learning-based technique that enhances image resolution and quality during MRI reconstruction- in improving the...
7.
Mochizuki J, Hata Y, Nakaura T, Hashimoto K, Uetani H, Nagayama Y, et al.
Circ Rep
. 2024 Dec;
6(12):564-572.
PMID: 39659635
Background: This study aimed to determine whether spectral imaging with dual-energy computed tomography (CT) can improve diagnostic performance for coronary plaque characterization. Methods And Results: We conducted a retrospective analysis...
8.
Kobayashi N, Nakaura T, Yoshida N, Nagayama Y, Kidoh M, Uetani H, et al.
Eur Radiol
. 2024 Nov;
PMID: 39613960
Purpose: The purpose of this study is to estimate the extent to which the implementation of deep learning reconstruction (DLR) may reduce the risk of radiation-induced cancer from CT examinations,...
9.
Nakaura T, Yoshida N, Kobayashi N, Nagayama Y, Uetani H, Kidoh M, et al.
Acad Radiol
. 2024 Nov;
PMID: 39521632
Rationale And Objectives: To evaluate the performance of various multimodal large language models (LLMs) in the Japanese Diagnostic Radiology Board Examinations (JDRBE) both with and without images. Materials And Methods:...
10.
Oda S, Chikamoto A, Khant Z, Uetani H, Kidoh M, Nagayama Y, et al.
Acad Radiol
. 2024 Oct;
32(1):112-119.
PMID: 39366804
Rationale And Objectives: Efficient communication between radiologists and clinicians ordering computed tomography (CT) examinations is crucial for managing high-risk incidental CT findings (ICTFs). Herein, we introduced a Radiologist's Alert and...