Evidence map›Paper›PMID 36994167›Full record

ArticleArXiv2023

Deep Learning in MRI-guided Radiation Therapy: A Systematic Review.

Zach Eidex, Yifu Ding, Jing Wang, Elham Abouei, Richard L J Qiu, Tian Liu, Tonghe Wang, Xiaofeng Yang

Abstract readPreprint
In one paragraph

Article in ArXiv, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Zach EidexDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA.
Yifu DingDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA.
Jing WangDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA.
Elham AboueiDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA.
Richard L J QiuDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA.
Tian LiuDepartment of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, NY.
Tonghe WangDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY.
Xiaofeng YangDepartment of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
eXtended Modular ANthropomorphic (XMAN) phantom for Imaging and Treatment Optimization in Radiotherapy.R01EB032680 · NIBIB · UNIVERSITY OF MARYLAND BALTIMORE · PI REN, LEI, YANG, XIAOFENG · 2022 to 2025
$2.4M
Multiparametric MRI-guided Prostate HDR Brachytherapy with Focal Tumor BoostR01CA215718 · NCI · EMORY UNIVERSITY · PI YANG, XIAOFENG · 2018 to 2022
$1.8M
Artificial Intelligence Driven Platform for PET/MR ImagingR56EB033332 · NIBIB · EMORY UNIVERSITY · PI MAO, HUI, YANG, XIAOFENG · 2022 to 2022
$764k
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA215718NIBIB NIH HHS R01 EB032680NIBIB NIH HHS R56 EB033332
6 · The paper itself

Abstract

MRI-guided radiation therapy (MRgRT) offers a precise and adaptive approach to treatment planning. Deep learning applications which augment the capabilities of MRgRT are systematically reviewed. MRI-guided radiation therapy offers a precise, adaptive approach to treatment planning. Deep learning applications which augment the capabilities of MRgRT are systematically reviewed with emphasis placed on underlying methods. Studies are further categorized into the areas of segmentation, synthesis, radiomics, and real time MRI. Finally, clinical implications, current challenges, and future directions are discussed.

Identifiers

PMID36994167
PMCPMC10055493

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.