ArticleFrontiers in oncology2019
PACE: A Probabilistic Atlas for Normal Tissue Complication Estimation in Radiation Oncology.
Article in Frontiers in oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Potential benefits of using radioactive ion beams for range margin reduction in carbon ion therapy.Scientific reports · 2022Article
- Radiation-Induced Esophagitis in Non-Small-Cell Lung Cancer Patients: Voxel-Based Analysis and NTCP Modeling.Cancers · 2022Article
- Radiation-Induced Dyspnea in Lung Cancer Patients Treated with Stereotactic Body Radiation Therapy.Cancers · 2021Article
- Article
- Probing thoracic dose patterns associated to pericardial effusion and mortality in patients treated with photons and protons for locally advanced non-small-cell lung cancer.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2021Article
- Atlas construction and spatial normalisation to facilitate radiation-induced late effects research in childhood cancer.Physics in medicine and biology · 2021Article
- NTCP Models for Severe Radiation Induced Dermatitis After IMRT or Proton Therapy for Thoracic Cancer Patients.Frontiers in oncology · 2020Article
- Increased Dose to Organs in Urinary Tract Associates With Measures of Genitourinary Toxicity in Pooled Voxel-Based Analysis of 3 Randomized Phase III Trials.Frontiers in oncology · 2020Article
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Authors and funding
5 authors.
Funding
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Abstract
In radiation oncology, the need for a modern Normal Tissue Complication Probability (NTCP) philosophy to include voxel-based evidence on organ radio-sensitivity (RS) has been acknowledged. Here a new formalism (Probabilistic Atlas for Complication Estimation, PACE) to predict radiation-induced morbidity (RIM) is presented. The adopted strategy basically consists in keeping the structure of a classical, phenomenological NTCP model, such as the Lyman-Kutcher-Burman (LKB), and replacing the dose distribution with a collection of RIM odds, including also significant non-dosimetric covariates, as input of the model framework. The theory was first demonstrated
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