ReviewThe British journal of radiology2015
Validation of functional imaging as a biomarker for radiation treatment response.
Review in The British journal of radiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed, 32 citations in OpenAlex.
- Treatment-integrated imaging, radiomics, and personalised radiotherapy: the future is at hand.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2022Review
- Investigation of atovaquone-induced spatial changes in tumour hypoxia assessed by hypoxia PET/CT in non-small cell lung cancer patients.EJNMMI research · 2021Article
- Potential role of functional imaging in predicting outcome for patients treated with carbon ion therapy: a review.The British journal of radiology · 2021Article
- Does a 6-point scale approach to post-treatment 18F-FDG PET-CT allow to improve response assessment in head and neck squamous cell carcinoma? A multicenter study.European journal of hybrid imaging · 2020Article
- Identification of Potential MR-Derived Biomarkers for Tumor Tissue Response toTranslational oncology · 2018Article
- Overexpression of Receptor Tyrosine Kinase EphB4 Triggers Tumor Growth and Hypoxia in A375 Melanoma Xenografts: Insights from Multitracer Small Animal Imaging Experiments.Molecules (Basel, Switzerland) · 2018Article
- Combining Radiotherapy With Anti-angiogenic Therapy and Immunotherapy; A Therapeutic Triad for Cancer?Frontiers in immunology · 2018Review
- Recent advances in radiation oncology.Ecancermedicalscience · 2017Review
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 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Major advances in radiotherapy techniques, increasing knowledge of tumour biology and the ability to translate these advances into new therapeutic approaches are important goals towards more individualized cancer treatment. With the development of non-invasive functional and molecular imaging techniques such as positron emission tomography (PET)-CT scanning and MRI, there is now a need to evaluate potential new biomarkers for tumour response prediction, for treatment individualization is not only based on morphological criteria but also on biological tumour characteristics. The goal of individualization of radiotherapy is to improve treatment outcome and potentially reduce chronic treatment toxicity. This review gives an overview of the molecular and functional imaging modalities of tumour hypoxia and tumour cell metabolism, proliferation and perfusion as predictive biomarkers for radiation treatment response in head and neck tumours and in lung tumours. The current status of knowledge on integration of PET/CT/MRI into treatment management and bioimage-guided adaptive radiotherapy are discussed.
Indexed as
Identifiers
What OpenQuestion holds
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.