ArticleMedical physics2017
Incorporation of pre-therapy
Article in Medical physics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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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
21 citing papers in PubMed.
- Integrating deep learning and multi-omics features in radiation pneumonitis prediction for lung cancer patients using PET/CT.BMC medical imaging · 2025Article
- Radiomics approach for identifying radiation-induced normal tissue toxicity in the lung.Scientific reports · 2024Article
- CT-based different regions of interest radiomics analysis for acute radiation pneumonitis in patients with locally advanced NSCLC after chemoradiotherapy.Clinical and translational radiation oncology · 2024Article
- Role of radiomics in the diagnosis and treatment of gastrointestinal cancer.World journal of gastroenterology · 2022Review
- IntegratingThoracic cancer · 2022Article
- Radiation and immune checkpoint inhibitor-mediated pneumonitis risk stratification in patients with locally advanced non-small cell lung cancer: role of functional lung radiomics?Discover oncology · 2022Article
- A Semiautomated Chart Review for Assessing the Development of Radiation Pneumonitis Using Natural Language Processing: Diagnostic Accuracy and Feasibility Study.JMIR medical informatics · 2021Article
- Artificial Intelligence and Radiomics in Head and Neck Cancer Care: Opportunities, Mechanics, and Challenges.American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting · 2021Article
- Implementation of FDG-PET/CT imaging methodology for quantification of inflammatory response in patients with locally advanced non-small cell lung cancer: results from the ACRIN 6668/RTOG 0235 trial.American journal of nuclear medicine and molecular imaging · 2021Article
- Prediction of Locoregional Recurrence-Free Survival of Oesophageal Squamous Cell Carcinoma After Chemoradiotherapy Based on an Enhanced CT-Based Radiomics Model.Frontiers in oncology · 2021Article
- Application of Radiomics for the Prediction of Radiation-Induced Toxicity in the IMRT Era: Current State-of-the-Art.Frontiers in oncology · 2020Review
- Radiomics for radiation oncologists: are we ready to go?BJR open · 2020Review
- Development and Validation of a Radiomics Nomogram Model for Predicting Postoperative Recurrence in Patients With Esophageal Squamous Cell Cancer Who Achieved pCR After Neoadjuvant Chemoradiotherapy Followed by Surgery.Frontiers in oncology · 2020Article
- Effects of variability in radiomics software packages on classifying patients with radiation pneumonitis.Journal of medical imaging (Bellingham, Wash.) · 2020Article
- Radiomics Analysis of PET and CT Components of PET/CT Imaging Integrated with Clinical Parameters: Application to Prognosis for Nasopharyngeal Carcinoma.Molecular imaging and biology · 2019Article
- A prospective study of the feasibility of FDG-PET/CT imaging to quantify radiation-induced lung inflammation in locally advanced non-small cell lung cancer patients receiving proton or photon radiotherapy.European journal of nuclear medicine and molecular imaging · 2019Article
- Correlation of Functional Lung Heterogeneity and Dosimetry to Radiation Pneumonitis using Perfusion SPECT/CT and FDG PET/CT Imaging.International journal of radiation oncology, biology, physics · 2018Article
- Challenges and Promises of PET Radiomics.International journal of radiation oncology, biology, physics · 2018Review
- A review on radiomics and the future of theranostics for patient selection in precision medicine.The British journal of radiology · 2018Review
- Radiation Pneumonitis: Old Problem, New Tricks.Cancers · 2018Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
purposeTo determine whether the addition of standardized uptake value (SUV) from PET scans to CT lung texture features could improve a radiomics-based model of radiation pneumonitis (RP) diagnosis in patients undergoing radiotherapy. METHODS AND MATERIALS: Anonymized data from 96 esophageal cancer patients (18 RP-positive cases of Grade ≥ 2) were collected including pre-therapy PET/CT scans, pre-/post-therapy diagnostic CT scans and RP status. Twenty texture features (first-order, fractal, Laws' filter and gray-level co-occurrence matrix) were calculated from diagnostic CT scans and compared in anatomically matched regions of the lung. Classifier performance (texture, SUV, or combination) was assessed by calculating the area under the receiver operating characteristic curve (AUC). For each texture feature, logistic regression classifiers consisting of the average change in texture feature value and the pre-therapy SUV standard deviation (SUV
resultsWhile clinical parameters (mean lung dose, smoking history, tumor location) were not significantly different among patients with and without symptomatic RP, SUV and texture parameters were significantly associated with RP status. AUC for single-texture feature classifiers alone ranged from 0.58 to 0.81 and 0.53 to 0.71 in high-dose (≥ 30 Gy) and low-dose (< 10 Gy) regions of the lungs, respectively. AUC for SUV
conclusionsAddition of SUV
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Registered trials
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