Multi-parametric MRI for radiotherapy simulation

Tian Li; Jihong Wang; Yingli Yang; Carri K. Glide-Hurst; Ning Wen; Jing Cai

doi:10.1002/mp.16256

Multi-parametric MRI for radiotherapy simulation

Tian Li, Jihong Wang, Yingli Yang, Carri K. Glide-Hurst, Ning Wen, Jing Cai

Research output: Journal article publication › Review article › Academic research › peer-review

7 Citations (Scopus)

Abstract

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

Original language	English
Pages (from-to)	5273-5293
Number of pages	21
Journal	Medical Physics
Volume	50
Issue number	8
DOIs	https://doi.org/10.1002/mp.16256
Publication status	Published - 29 Jan 2023

Keywords

artificial intelligence
machine learning
mpMRI
MRI simulation
MRI-guided radiotherapy
MRI-linac
multi-parametric MRI

ASJC Scopus subject areas

Biophysics
Radiology Nuclear Medicine and imaging

More information

10.1002/mp.16256

http://hdl.handle.net/10397/107666

Cite this

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title = "Multi-parametric MRI for radiotherapy simulation",

abstract = "Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.",

keywords = "artificial intelligence, machine learning, mpMRI, MRI simulation, MRI-guided radiotherapy, MRI-linac, multi-parametric MRI",

author = "Tian Li and Jihong Wang and Yingli Yang and Glide-Hurst, {Carri K.} and Ning Wen and Jing Cai",

note = "Funding Information: This research was partly supported by research grants from General Research Fund from the University Grants Committee (GRF15104822, GRF15102118, GRF15102219), Health and Medical Research Fund from the Food and Health Bureau (HMRF 07183266), The Government of the Hong Kong Special Administrative Region, the National Cancer Institute of the National Institutes of Health (R01 CA204189, R01 CA226899, R01 HL153720), and a Research Scholar Grant from the American Cancer Society (RSG‐15‐137‐01‐CCE). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agents. Publisher Copyright: {\textcopyright} 2023 American Association of Physicists in Medicine.",

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doi = "10.1002/mp.16256",

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AU - Li, Tian

AU - Wang, Jihong

AU - Yang, Yingli

AU - Glide-Hurst, Carri K.

AU - Wen, Ning

AU - Cai, Jing

N1 - Funding Information: This research was partly supported by research grants from General Research Fund from the University Grants Committee (GRF15104822, GRF15102118, GRF15102219), Health and Medical Research Fund from the Food and Health Bureau (HMRF 07183266), The Government of the Hong Kong Special Administrative Region, the National Cancer Institute of the National Institutes of Health (R01 CA204189, R01 CA226899, R01 HL153720), and a Research Scholar Grant from the American Cancer Society (RSG‐15‐137‐01‐CCE). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agents. Publisher Copyright: © 2023 American Association of Physicists in Medicine.

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Y1 - 2023/1/29

N2 - Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

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KW - artificial intelligence

KW - machine learning

KW - mpMRI

KW - MRI simulation

KW - MRI-guided radiotherapy

KW - MRI-linac

KW - multi-parametric MRI

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Multi-parametric MRI for radiotherapy simulation

Abstract

Keywords

ASJC Scopus subject areas

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