ArticleStrahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]2019
Radiomic analysis of planning computed tomograms for predicting radiation-induced lung injury and outcome in lung cancer patients treated with robotic stereotactic body radiation therapy.
Article in Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al], 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.
- Risk stratification of pulmonary toxicities in the combination of whole lung irradiation and high-dose chemotherapy for Ewing sarcoma patients with lung metastases: a review.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2020Pooled it
- Outcomes of Hypofractional Tomotherapy in Patients with Stage III Nonsmall Cell Lung Cancer Who Are Not Eligible for Surgery or Concurrent Chemoradiation.BioMed research international · 2020Trial
- RaFiST: a radiomics model for non-invasive stratification of tumor fibrosis and prognostic prediction in non-small cell lung cancer.European radiology · 2026Article
- Radiomics-based explainable artificial intelligence to predict treatment response following lung stereotactic body radiation therapy.The British journal of radiology · 2025Article
- A Clinical-Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung Adenocarcinoma.Current oncology (Toronto, Ont.) · 2025Article
- Article
- Construction and evaluation of a predictive model for radiation-induced lung injury in lung cancer: a meta-analysis.American journal of translational research · 2025Review
- Machine learning in image-based outcome prediction after radiotherapy: A review.Journal of applied clinical medical physics · 2025Review
- Review
- Radiomics in stereotactic body radiotherapy for non-small cell lung cancer: a systematic review and radiomic quality score study.Radiation oncology journal · 2024Article
- A PET/CT radiomics model for predicting distant metastasis in early-stage non-small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study.Radiation oncology (London, England) · 2024Article
- Radiomics of skeletal muscle helps to predict gastrointestinal toxicity in locally advanced rectal cancer patients receiving neoadjuvant chemoradiotherapy.Clinical and translational radiation oncology · 2024Article
- CT-based radiomics prediction of complete response after stereotactic body radiation therapy for patients with lung metastases.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2023Article
- 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 review on advances inInsights into imaging · 2022Review
- Combining computed tomography and biologically effective dose in radiomics and deep learning improves prediction of tumor response to robotic lung stereotactic body radiation therapy.Medical physics · 2021Article
- Risk factors for radiation-induced lung injury in patients with advanced non-small cell lung cancer: implication for treatment strategies.World journal of surgical oncology · 2021Article
- Radiomics for prediction of radiation-induced lung injury and oncologic outcome after robotic stereotactic body radiotherapy of lung cancer: results from two independent institutions.Radiation oncology (London, England) · 2021Article
- Precision radiotherapy for non-small cell lung cancer.Journal of biomedical science · 2020Review
- Early differential diagnosis model for acute radiation pneumonitis based on multiple parameters.Bioscience reports · 2020Article
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo predict radiation-induced lung injury and outcome in non-small cell lung cancer (NSCLC) patients treated with robotic stereotactic body radiation therapy (SBRT) from radiomic features of the primary tumor.
methodsIn all, 110 patients with primary stage I/IIa NSCLC were analyzed for local control (LC), disease-free survival (DFS), overall survival (OS) and development of local lung injury up to fibrosis (LF). First-order (histogram), second-order (GLCM, Gray Level Co-occurrence Matrix) and shape-related radiomic features were determined from the unprocessed or filtered planning CT images of the gross tumor volume (GTV), subjected to LASSO (Least Absolute Shrinkage and Selection Operator) regularization and used to construct continuous and dichotomous risk scores for each endpoint.
resultsContinuous scores comprising 1-5 histogram or GLCM features had a significant (p = 0.0001-0.032) impact on all endpoints that was preserved in a multifactorial Cox regression analysis comprising additional clinical and dosimetric factors. At 36 months, LC did not differ between the dichotomous risk groups (93% vs. 85%, HR 0.892, 95%CI 0.222-3.590), while DFS (45% vs. 17%, p < 0.05, HR 0.457, 95%CI 0.240-0.868) and OS (80% vs. 37%, p < 0.001, HR 0.190, 95%CI 0.065-0.556) were significantly lower in the high-risk groups. Also, the frequency of LF differed significantly between the two risk groups (63% vs. 20% at 24 months, p < 0.001, HR 0.158, 95%CI 0.054-0.458).
conclusionRadiomic analysis of the gross tumor volume may help to predict DFS and OS and the development of local lung fibrosis in early stage NSCLC patients treated with stereotactic radiotherapy.
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