ReviewDer Radiologe2019
Image guidance: past and future of radiotherapy.
Review in Der Radiologe, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
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.
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Who cites it
12 citing papers in PubMed, 27 citations in OpenAlex.
- A Review of the Australian MRI Linac Program: From Pie in the Sky to Research Milestone.Journal of medical imaging and radiation oncology · 2026Review
- Automated quality assurance of imaging dose and protocol adherence in computed tomography radiotherapy planning using TotalSegmentator-based segmentation.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- Past present and future of radiosensitization in cervical cancer.Frontiers in oncology · 2026Review
- Enhancing patient positioning accuracy: evaluating daily cone beam computed tomography in the halcyon system.Japanese journal of clinical oncology · 2025Article
- Salvage percutaneous high-dose-rate brachyablation after stereotactic body radiation therapy for early-stage non-small cell lung cancer.Journal of contemporary brachytherapy · 2024Article
- Gumbel distribution-based technique enables quantitative comparison between streak metal artifacts of multidetector row CT and cone-beam CT: a phantom study.Physical and engineering sciences in medicine · 2023Article
- Automatic delineation of organ at risk in cervical cancer radiotherapy based on ensemble learning.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2022Article
- The first internal electromagnetic motion monitoring implementation for stereotactic liver radiotherapy in China: procedures and preliminary results.Journal of cancer research and clinical oncology · 2022Article
- Dose accumulation for MR-guided adaptive radiotherapy: From practical considerations to state-of-the-art clinical implementation.Frontiers in oncology · 2022Review
- Streamlining the image-guided radiotherapy process for proton beam therapy.The British journal of radiology · 2021Article
- Evaluation of novel AI-based extended field-of-view CT reconstructions.Medical physics · 2021Article
- Trimodality PET/CT/MRI and Radiotherapy: A Mini-Review.Frontiers in oncology · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Image guidance has been playing a decisive role throughout the history of radiotherapy, but developments in 3D-and 4D imaging data acquisition using computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) have significantly boosted the precision of conformal radiotherapy. An overarching aim of radiotherapy is conforming the treatment dose to the tumor in order to optimally limit a high radiation dose outside the target. Stereotactic, intensity modulated, and adaptive radiotherapy are all largely based on appropriately using imaging information both before and during treatment delivery using on-board imaging devices. While pretreatment imaging for planning has reached a very high level in the past two decades, the next step will be to further refine and accelerate imaging during treatment delivery, resulting in adaptation of the dose fluence during a patient's treatment in various scenarios, some of which are discussed in this article.
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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.