ReviewThe British journal of radiology2014
The role of texture analysis in imaging as an outcome predictor and potential tool in radiotherapy treatment planning.
Review in The British journal of radiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 2 of them syntheses that pooled 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.
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
51 citing papers in PubMed, 2 syntheses or guidelines pooled it, 100 citations in OpenAlex.
- Repeatability and Reproducibility of Radiomic Features: A Systematic Review.International journal of radiation oncology, biology, physics · 2018Pooled it
- Clinical applications of textural analysis in non-small cell lung cancer.The British journal of radiology · 2018Pooled it
- [Molecular cancer · 2026Article
- A CT-based radiomics model for predicting pain relief after radiotherapy in patients with bone metastases: a dual-center study.Frontiers in oncology · 2026Article
- Diagnostic, Therapeutic, and Prognostic Applications of Artificial Intelligence (AI) in the Clinical Management of Brain Metastases (BMs).Brain sciences · 2025Review
- Article
- The prognostic value of [Clinical physiology and functional imaging · 2025Article
- Texture Analysis in Volumetric Imaging for Dentomaxillofacial Radiology: Transforming Diagnostic Approaches and Future Directions.Journal of imaging · 2024Review
- Article
- The Application of Radiomics and AI to Molecular Imaging for Prostate Cancer.Journal of personalized medicine · 2024Review
- Prognostic value of different discretization parameters inJournal of medical imaging (Bellingham, Wash.) · 2024Article
- Article
- MRI radiomics-based decision support tool for a personalized classification of cervical disc degeneration: a two-center study.Frontiers in physiology · 2023Article
- Highlighting Functional Mass Spectrometry Imaging Methods in Bioanalysis.Journal of proteome research · 2022Review
- Article
- Multiple analyses suggests texture features can indicate the presence of tumor in the prostate tissue.Physical and engineering sciences in medicine · 2022Article
- Machine intelligence in non-invasive endocrine cancer diagnostics.Nature reviews. Endocrinology · 2022Review
- Evaluation of microvascular permeability of skeletal muscle and texture analysis based on DCE-MRI in alloxan-induced diabetic rabbits.European radiology · 2021Article
- Classification of neoplastic and inflammatory brain disease using MRI texture analysis in 119 dogs.Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association · 2021Article
- Combining machine learning and texture analysis to differentiate mediastinal lymph nodes in lung cancer patients.Physical and engineering sciences in medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predicting a tumour's response to radiotherapy prior to the start of treatment could enhance clinical care management by enabling the personalization of treatment plans based on predicted outcome. In recent years, there has been accumulating evidence relating tumour texture to patient survival and response to treatment. Tumour texture could be measured from medical images that provide a non-invasive method of capturing intratumoural heterogeneity and hence could potentially enable a prior assessment of a patient's predicted response to treatment. In this article, work presented in the literature regarding texture analysis in radiotherapy in relation to survival and outcome is discussed. Challenges facing integrating texture analysis in radiotherapy planning are highlighted and recommendations for future directions in research are suggested.
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.