Evidence map›Paper›PMID 39441404›Full record

ReviewInsights into imaging2024

The role of MRI in radiotherapy planning: a narrative review "from head to toe".

Simona De Pietro, Giulia Di Martino, Mara Caroprese, Angela Barillaro, Sirio Cocozza, Roberto Pacelli, Renato Cuocolo, Lorenzo Ugga, Francesco Briganti, Arturo Brunetti and 2 more

Abstract readReview
In one paragraph

Review in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Synthetic MRI from radiotherapy planning CT images for Head-and-Neck Cancer.Journal of applied clinical medical physics · 2026
    Article
  2. Article
  3. Article
  4. Multimodal PET-MR segmentation for glioblastoma: complementarity for treatment planning and recurrence definition.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Multi-contrast 4DMR via MR multitasking: Early clinical experience and implication for liver stereotactic body radiation therapy.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2025
    Article
  14. 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

12 authors.

Simona De Pietro *Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Giulia Di Martino *Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Mara CaropreseDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Angela BarillaroDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Sirio CocozzaDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy. sirio.cocozza@unina.it.ORCID http://orcid.org/0000-0002-0300-5160
Roberto PacelliDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Renato CuocoloDepartment of Medicine, Surgery and Dentistry, University of Salerno, Baronissi, Italy.
Lorenzo UggaDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Francesco BrigantiDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Arturo BrunettiDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Manuel ConsonDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Andrea ElefanteDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last few years, radiation therapy (RT) techniques have evolved very rapidly, with the aim of conforming high-dose volume tightly to a target. Although to date CT is still considered the imaging modality for target delineation, it has some known limited capabilities in properly identifying pathologic processes occurring, for instance, in soft tissues. This limitation, along with other advantages such as dose reduction, can be overcome using magnetic resonance imaging (MRI), which is increasingly being recognized as a useful tool in RT clinical practice. This review has a two-fold aim of providing a basic introduction to the physics of MRI in a narrative way and illustrating the current knowledge on its application "from head to toe" (i.e., different body sites), in order to highlight the numerous advantages in using MRI to ensure the best therapeutic response. We provided a basic introduction for residents and non-radiologist on the physics of MR and reported evidence of the advantages and future improvements of MRI in planning a tailored radiotherapy treatment "from head to toe". CRITICAL RELEVANCE STATEMENT: This review aims to help understand how MRI has become indispensable, not only to better characterize and evaluate lesions, but also to predict the evolution of the disease and, consequently, to ensure the best therapeutic response. KEY POINTS: MRI is increasingly gaining interest and applications in RT planning. MRI provides high soft tissue contrast resolution and accurate delineation of the target volume. MRI will increasingly become indispensable for characterizing and evaluating lesions, and to predict the evolution of disease.

Indexed as

Magnetic resonance imagingRadiation oncologyRadiotherapy planning

Identifiers

PMID39441404
PMCPMC11499544

What OpenQuestion holds

Textmetadata
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.