Evidence map›Paper›PMID 24931097›Full record

ReviewSeminars in radiation oncology2014

Clinical applications for diffusion magnetic resonance imaging in radiotherapy.

Christina Tsien, Yue Cao, Thomas Chenevert

Registry-linked trialAbstract readReview
In one paragraph

Review in Seminars in radiation oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04022018 (Study on Adaptive Radiotherapy and Multimodal Information of Cervical Cancer Assisted by Artificial Intelligence), which is not on this map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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.

NCT04022018 naunknown statusnot on this mapstarted 2019, after this paper: background citation

Study on Adaptive Radiotherapy and Multimodal Information of Cervical Cancer Assisted by Artificial Intelligence

TypeinterventionalSponsorThe University of Hong Kong-Shenzhen HospitalRan2019 to 2022Enrolled122ConditionsCervical Cancer, Radiotherapy Side Effect, Biomarker, Artificial IntelligenceArmsAdaptive radiotherapy, no adaptive radiotherapy
3 · Its place in the literature

Who cites it

45 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Use of Radiomics in Characterizing Tumor Hypoxia.International journal of molecular sciences · 2025
    Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Recommendations for improved reproducibility of ADC derivation on behalf of the Elekta MRI-linac consortium image analysis working group.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2023
    Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Christina TsienDepartment of Radiation Oncology, University of Michigan Hospital and Health Systems, Ann Arbor, MI. Electronic address: ctsien@umich.edu.
Yue CaoDepartment of Radiation Oncology, University of Michigan Hospital and Health Systems, Ann Arbor, MI.
Thomas ChenevertDepartment of Radiology, University of Michigan Hospital and Health Systems, Ann Arbor, MI.

Funding

QUANTITATION OF HUMAN BRAIN TUMOR THERAPY RESPONSE BY MRP01CA085878 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ROSS, BRIAN D. · 2001 to 2017
$31.9M
Quantitative DW-MRI for Early Breast Cancer Treatment Response AssessmentU01CA166104 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHENEVERT, THOMAS L, GALBAN, CRAIG J · 2012 to 2019
$4.1M
Optimizing MRI for Radiation Therapy Treatment PlanningR01EB016079 · NIBIB · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BALTER, JAMES M, CAO, YUE · 2013 to 2022
$3.1M
Predicting Liver Function After IrradiationR01CA132834 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CAO, YUE · 2010 to 2015
$1.7M
Functional Imaging as a Biomaker for Neurotoxicity After Brain IrradiationR01NS064973 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CAO, YUE · 2009 to 2013
$1.7M
NCI NIH HHS P01 CA085878NCI NIH HHS R01 CA132834NCI NIH HHS U01 CA166104NIBIB NIH HHS R01 EB016079NINDS NIH HHS R01 NS064973
6 · The paper itself

Abstract

In this article, we review the clinical applications of diffusion magnetic resonance imaging (MRI) in the radiotherapy treatment of several key clinical sites, including those of the central nervous system, the head and neck, the prostate, and the cervix. Diffusion-weighted MRI (DWI) is an imaging technique that is rapidly gaining widespread acceptance owing to its ease and wide availability. DWI measures the mobility of water within tissue at the cellular level without the need of any exogenous contrast agent. For radiotherapy treatment planning, DWI improves upon conventional imaging techniques, by better characterization of tumor tissue properties required for tumor grading, diagnosis, and target volume delineation. Because DWI is also a sensitive marker for alterations in tumor cellularity, it has potential clinical applications in the early assessment of treatment response following radiation therapy.

Indexed as

Diffusion Magnetic Resonance ImagingHumansImage Interpretation, Computer-AssistedRadiation OncologyRadiotherapy, Image-GuidedRadiotherapy Planning, Computer-Assisted

Identifiers

PMID24931097
PMCPMC4170230

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Registered trials

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.