A deep‐learning‐based prediction model for the biodistribution of 90 Y microspheres in liver radioembolization-Reference-Cited by-同舟云学术

A deep‐learning‐based prediction model for the biodistribution of 90 Y microspheres in liver radioembolization

Published:2021-10-21 Issue:11 Volume:48 Page:7427-7438
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Medical Physics

Author:

Plachouris Dimitris¹,Tzolas Ioannis²,Gatos Ilias¹,Papadimitroulas Panagiotis¹³,Spyridonidis Trifon⁴,Apostolopoulos Dimitris⁴,Papathanasiou Nikolaos⁴,Visvikis Dimitris⁵,Plachouri Kerasia‐Maria⁶,Hazle John D.⁷,Kagadis George C.¹⁷

Affiliation:

1. Department of Medical Physics School of Medicine University of Patras Rion Greece

2. School of Electrical and Computer Engineering University of Patras Rion Greece

3. R&D Department Bioemission Technology Solutions Athens Greece

4. Department of Nuclear Medicine School of Medicine University of Patras Rion Greece

5. LaTIM, INSERM, UMR1101 Brest France

6. Department of Dermatology School of Medicine University of Patras Rion Greece

7. Department of Imaging Physics The University of Texas MD Anderson Cancer Center Houston Texas USA

Funder

European Regional Development Fund

European Social Fund

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.15270

Reference57 articles.

1. Transarterial Radioembolization (TARE) Agents beyond 90Y-Microspheres

2. The physics of radioembolization

3. (90)Y‐microsphere radioembolization: the method, clinical evidence and perspective;Spyridonidis T;Hell J Nucl Med,2020

4. A guide to 90Y radioembolization and its dosimetry

5. Correlation of Technetium-99m Macroaggregated Albumin and Yttrium-90 Glass Microsphere Biodistribution in Hepatocellular Carcinoma: A Retrospective Review of Pretreatment Single Photon Emission CT and Posttreatment Positron Emission Tomography/CT

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