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» Authors » Junichi Hiratsuka

Junichi Hiratsuka

Explore the profile of Junichi Hiratsuka including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 52
Citations 470
Followers 0
Related Specialties
Oncology
Radiology
Environmental Health
Top 10 Co-Authors
Takanori Masuda
Tomoyasu Sato
Shinichi Arao
Yoshinori Funama
Kazuo Awai
Koji Ono
Takeshi Nakaura
Eisaku Yoden
Atsushi Ono
Nobuhiko Kamitani
Published In
Radiat Prot Dosimetry
J Radiat Res
Appl Radiat Isot
Int J Clin Oncol
Rev Sci Instrum
Affiliations
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Recent Articles
1.
Prediction of endovascular leaks after thoracic endovascular aneurysm repair though machine learning applied to pre-procedural computed tomography angiographs
Masuda T, Baba Y, Nakaura T, Funama Y, Sato T, Masuda S, et al.
Phys Eng Sci Med . 2024 May; 47(3):1087-1094. PMID: 38696098
To predict endoleaks after thoracic endovascular aneurysm repair (TEVAR) we submitted patient characteristics and vessel features observed on pre- operative computed tomography angiography (CTA) to machine-learning. We evaluated 1-year follow-up...
2.
Using Patient-Specific Contrast Enhancement Optimizer Simulation Software During the Transcatheter Aortic Valve Implantation-Computed Tomography Angiography in Patients With Aortic Stenosis
Masuda T, Nakaura T, Higaki T, Funama Y, Matsumoto Y, Sato T, et al.
J Comput Assist Tomogr . 2024 Apr; 48(5):759-762. PMID: 38595080
Objectives: This study assessed whether patient-specific contrast enhancement optimizer simulation software (p-COP) can reduce the contrast material (CM) dose compared with the conventional body weight (BW)-tailored scan protocol during transcatheter...
3.
Can Machine Learning Identify the Intravenous Contrast Dose and Injection Rate Needed for Optimal Enhancement on Dynamic Liver Computed Tomography?
Masuda T, Nakaura T, Funama Y, Sato T, Nagayama Y, Kidoh M, et al.
J Comput Assist Tomogr . 2023 Jun; 47(4):530-538. PMID: 37380150
Objectives: This study aimed to investigate whether machine learning (ML) is useful for predicting the contrast material (CM) dose required to obtain a clinically optimal contrast enhancement in hepatic dynamic...
4.
Usefulness of electrocardiogram mA modulation during the electrocardiogram-gated CT scan in paediatrics with high heart rate for different helical pitch: a phantom-based assessment study
Masuda T, Funama Y, Nakaura T, Sato T, Oku T, Gotanda R, et al.
Radiat Prot Dosimetry . 2023 Jun; 199(12):1295-1300. PMID: 37337642
We investigated the effect of electrocardiographic (ECG) mA-modulation of ECG-gated scans of computed tomography (CTA) on radiation dose and image noise at high heart rates (HR) above 100 bpm between...
5.
Effect of patient characteristics on vessel enhancement on arterio-venous fistula CT angiography in a retrospective cohort study
Masuda T, Nakaura T, Funama Y, Sato T, Masuda S, Yoshiura T, et al.
Medicine (Baltimore) . 2023 Mar; 102(12):e33328. PMID: 36961162
To evaluate the effects of various patient characteristics on vessel enhancement on arterio-venous fistula (AVF) computed tomography (CT) angiography (AVF-CT angiography). A total of 127 patients with suspected or confirmed...
6.
RADIATION DOSE REDUCTION AT LOW TUBE VOLTAGE WITH CORONARY ARTERY BYPASS GRAFT COMPUTED TOMOGRAPHY ANGIOGRAPHY BASED ON THE CONTRAST NOISE RATIO INDEX
Masuda T, Nakaura T, Funama Y, Sato T, Masuda S, Gotanda R, et al.
Radiat Prot Dosimetry . 2023 Mar; 199(6):527-532. PMID: 36881907
To compare the radiation dose and diagnostic ability of the 100-kVp protocol, based on the contrast noise ratio (CNR) index, during coronary artery bypass graft (CABG) vessels with those of...
7.
Usefulness of large beam-shaping filters at different tube voltages of newborn chest CT
Masuda T, Funama Y, Nakaura T, Sato T, Urayama K, Kiguchi M, et al.
Phys Eng Sci Med . 2023 Jan; 46(1):289-293. PMID: 36633769
Background: To investigate optimizing the use of different beam shaping filters (viz. small, medium and large) when using different tube voltages during the newborn chest computed tomography (CT) on a...
8.
COMPARISON OF THE 64- AND 80-DETECTOR ROW COMPUTED TOMOGRAPHY AMONG THE CT NUMBER AND RADIATION DOSE DURING LOWER EXTREMITY COMPUTED TOMOGRAPHY ANGIOGRAPHY
Moriwake R, Masuda T, Yamamoto A, Ikenaga H, Yoshida K, Takei Y, et al.
Radiat Prot Dosimetry . 2023 Jan; 199(4):356-362. PMID: 36609697
To compare the computed tomography (CT) number and the radiation dose between the 64 (group A) and 80-detector row (group B) during lower extremity computed tomography angiography (LE-CTA). We enrolled...
9.
COMPARISON OF PEDIATRIC LENS DOSE MEASUREMENTS BETWEEN AXIAL SCAN MODE WITHOUT ACTIVE COLLIMATOR AND HELICAL SCAN MODE WITH ACTIVE COLLIMATOR BY USING A 64 DETECTOR-ROW COMPUTED TOMOGRAPHY SCANNER
Masuda T, Funama Y, Nakaura T, Sato T, Urayama K, Kiguchi M, et al.
Radiat Prot Dosimetry . 2022 Oct; 198(19):1522-1527. PMID: 36193882
To investigate the pediatric eye lens entrance surface dose for both axial scan modes without an active collimator and helical scan modes with an active collimator on 64 detector-row computed...
10.
Prediction of Aortic Contrast Enhancement on Dynamic Hepatic Computed Tomography-Performance Comparison of Machine Learning Methods and Simulation Software
Masuda T, Nakaura T, Higaki T, Funama Y, Sato T, Masuda S, et al.
J Comput Assist Tomogr . 2022 Mar; 46(2):183-189. PMID: 35297575
Objectives: The aim of this study was to compare prediction ability between ensemble machine learning (ML) methods and simulation software for aortic contrast enhancement on dynamic hepatic computed tomography. Methods:...