Data · dataset · 2016
Quantification of CT-assessed radiation-induced lung damage in lung cancer patients treated with or without chemotherapy and cetuximab
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Background and Purpose : Prediction models for radiation-induced lung damage (RILD) are still unsatisfactory, with clinical toxicity endpoints that are difficult to quantify objectively.
Description
We therefore evaluated RILD more objectively, quantitatively and on a continuous scale measuring the lung tissue density changes per voxel. Material and methods : Patients treated with radiotherapy (RT) alone, sequential and concurrent chemo-RT with and without the addition of cetuximab were studied.
Follow-up computed tomography (CT) scans were co-registered using deformable registration to baseline CT scans. CT density changes were correlated to the RT dose delivered in every part of the lungs. Results : One hundred and seventeen lung cancer patients were included.
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Mean dose to tumor was 60 Gy (range 45–79.2 Gy). Dose response curves showed a linear increase in the dose region between 0 and 65 Gy having a slope (based on coefficients of the multilevel model) expressed as a lung density increase per dose of 0.86 (95% CI 0.73–0.99), 1.31 (95% CI 1.19–1.43), 1.39 (95% CI 1.28–1.50) and 2.07 (95% CI 1.93–2.21) for patients treated only with RT (N=19), sequential chemo-RT (N=30), concurrent chemo-RT (N=49), and concurrent chemo-RT with cetuximab (N=19), respectively.
Conclusions : CT density changes allow quantitative assessment of lung damage after fractionated RT, giving complementary information to standard used clinical endpoints. Patients receiving cetuximab showed a significantly larger dose response compared with other treatments.
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- Repository landing page tandf.figshare.com/articles/dataset/Quantification_of_CT_assessed_radiation_induc… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.1569691 ↗
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Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.3109/0284186x.2015.1080856 doi.org/10.3109/0284186x.2015.1080856 ↗
publication · from DataCite
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- DataCite API api.datacite.org/dois/10.6084/m9.figshare.1569691 ↗
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Topics
- Stated by source
- Biological sciences · Clinical medicine
- From keywords
- Cancer · Medicine & Health
- Inferred from text
- Computed tomography 75%
Provenance · 1 source records, 13 field assertions
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|---|---|---|---|
| DataCite | 10.6084/m9.figshare.1569691 | 11 d ago | JSON v1 |
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| concepts[field].fos:clinical-medicine | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Medicine'] |
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