ArticleThe British journal of radiology2019
Dosimetric assessment of tumor control probability in intensity and volumetric modulated radiotherapy plans.
Article in The British journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Automated contouring of gross tumor volume lymph nodes in lung cancer by deep learning.BMC cancer · 2025Article
- Pretreatment patient-specific quality assurance prediction based on 1D complexity metrics and 3D planning dose: classification, gamma passing rates, and DVH metrics.Radiation oncology (London, England) · 2023Article
- A Dosimetric and Radiobiological Comparison of Intensity Modulated Radiotherapy, Volumetric Modulated Arc Therapy and Helical Tomotherapy Planning Techniques in Synchronous Bilateral Breast Cancer.Asian Pacific journal of cancer prevention : APJCP · 2022Article
- The impact of target positioning error and tumor size on radiobiological parameters in robotic stereotactic radiosurgery for metastatic brain tumors.Radiological physics and technology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objective: Radiobiological models have been used to calculate the outcomes of treatment plans based on dose-volume relationship. This study examines several radiobiological models for the calculation of tumor control probability (TCP) of intensity modulated radiotherapy plans for the treatment of lung, prostate, and head and neck (H&N) cancers.
methods: Dose volume histogram (DVH) data from the intensity modulated radiotherapy plans of 36 lung, 26 prostate, and 87 H&N cases were evaluated. The Poisson, Niemierko, and Marsden models were used to calculate the TCP of each disease group treatment plan. The calculated results were analyzed for correlation and discrepancy among the three models, as well as different treatment sites under study.
results: The median value of calculated TCP in lung plans was 61.9% (34.1-76.5%), 59.5% (33.5-73.9%) and 32.5% (0.0-93.9%) with the Poisson, Niemierko, and Marsden models, respectively. The median value of calculated TCP in prostate plans was 85.1% (56.4-90.9%), 81.2% (56.1-88.7%) and 62.5% (28.2-75.9%) with the Poisson, Niemierko, and Marsden models, respectively. The median value of calculated TCP in H&N plans was 94.0% (44.0-97.8%) and 94.3% (0.0-97.8%) with the Poisson and Niemierko models, respectively. There were significant differences between the calculated TCPs with the Marsden model in comparison with either the Poisson or Niemierko model (p < 0.001) for both lung and prostate plans. The TCPs calculated by the Poisson and Niemierko models were significantly correlated for all three tumor sites.
conclusion: There are variations with different radiobiological models. Understanding of the correlation and limitation of a TCP model with dosimetric parameters can help develop the meaningful objective functions for plan optimization, which would lead to the implementation of outcome-based planning. More clinical data are needed to refine and consolidate the model for accuracy and robustness. ADVANCES IN KNOWLEDGE:: This study has tested three radiobiological models with varied disease sites. It is significant to compare different models with the same data set for better understanding of their clinical applicability.
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.