ArticleInternational journal of computer assisted radiology and surgery2015
A 3D computer-assisted treatment planning system for breast cancer brachytherapy treatment.
Article in International journal of computer assisted radiology and surgery, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
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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
2 citing papers in PubMed, 4 citations in OpenAlex.
- An inverse planning simulated annealing algorithm with adaptive weight adjustment for LDR pancreatic brachytherapy.International journal of computer assisted radiology and surgery · 2022Article
- Automatic seed picking for brachytherapy postimplant validation with 3D CT images.International journal of computer assisted radiology and surgery · 2017Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeBrachytherapy is an option for treatment of breast cancer in some cases. This modality requires patient-specific dosimetry based on CT simulator scans. A 3D computer-assisted breast brachytherapy treatment planning system called Vision was developed and tested.
methodsThe brachytherapy treatment planning system used volume estimation and dose analysis with advanced 3D visualization. The patient treatment volume reconstruction was designed to ensure high-volume accuracy requirement of radioactive seed implantation procedure for this treatment. The system enables interactive placement of radioactive seeds embedded in original patient CT images with 3D display.
resultsThe system achieved 99.73% accuracy in volume estimation measured against the true volume and is statistically significantly more accurate than current existing commercial software at the p = 0.05 level.
conclusionA virtual 3D environment was developed to perform volume measurements, seed placements, and dose distribution planning and analysis based on 2D contours on patient CT images. This system was demonstrated to be feasible and accurate in a clinical setting.
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Registered trials
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