Evidence map›Paper›PMID 40386564›Full record

ArticleAdvances in radiation oncology2025

Internal Target Volume Estimation for Liver Cancer Radiation Therapy Using an Ultra Quality 4-Dimensional Magnetic Resonance Imaging.

Yen-Peng Liao, Haonan Xiao, Peilin Wang, Tian Li, Todd A Aguilera, Justin D Visak, Andrew R Godley, You Zhang, Jing Cai, Jie Deng

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Article in Advances in radiation oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Yen-Peng LiaoDepartment of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas.
Haonan XiaoDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China.
Peilin WangDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China.
Tian LiDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China.
Todd A AguileraDepartment of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas.
Justin D VisakDepartment of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas.
Andrew R GodleyDepartment of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas.
You ZhangDepartment of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas.
Jing CaiDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China.
Jie DengDepartment of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Accurate internal target volume (ITV) estimation is essential for effective and safe radiation therapy in liver cancer. This study evaluates the clinical value of an ultraquality 4-dimensional magnetic resonance imaging (UQ 4D-MRI) technique for ITV estimation. Methods and Materials: The UQ 4D-MRI technique maps motion information from a low spatial resolution dynamic volumetric MRI onto a high-resolution 3-dimensional MRI used for radiation treatment planning. It was validated using a motion phantom and data from 13 patients with liver cancer. ITV generated from UQ 4D-MRI (ITV Results: Phantom studies showed a displacement measurement difference of <5% between UQ 4D-MRI and single-slice 2-dimensional cine MRI. In patient studies, the maximum superior-inferior displacements of the tumor on UQ 4D-MRI showed no significant difference compared with single-slice 2-dimensional cine imaging ( Conclusions: UQ 4D-MRI enables accurate motion assessment for liver tumors, facilitating precise ITV delineation for radiation treatment planning. Despite uncertainties from artificial intelligence-based delineation and variations in patients' respiratory patterns, UQ 4D-MRI excels at capturing tumor motion trajectories, potentially improving treatment planning accuracy and reducing margins in liver cancer radiation therapy.

Identifiers

PMID40386564
PMCPMC12083997

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