ArticlePhysics and imaging in radiation oncology2023
On the correction of respiratory motion-induced image reconstruction errors in positron-emission tomography-guided radiation therapy.
Article in Physics and imaging in radiation oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Clinical validation of a unified data-driven respiratory motion correction technique inEJNMMI physics · 2026Article
- A novel personalized time-varying biomechanical model for estimating lung tumor motion and deformation.Medical physics · 2025Article
- Device-Less Data-Driven Cardiac and Respiratory Gating Using LAFOV PET Histo Images.Diagnostics (Basel, Switzerland) · 2024Article
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Abstract
Background and purpose: Free breathing (FB) positron emission tomography (PET) images are routinely used in radiotherapy for lung cancer patients. Respiration-induced artifacts in these images compromise treatment response assessment and obstruct clinical implementation of dose painting and PET-guided radiotherapy. The purpose of this study is to develop a blurry image decomposition (BID) method to correct motion-induced image-reconstruction errors in FB-PETs. Materials and methods: Assuming a blurry PET is represented as an average of multi-phase PETs. A four-dimensional computed-tomography image is deformably registered from the end-inhalation (EI) phase to other phases. With the registration-derived deformation maps, PETs at other phases can be deformed from a PET at the EI phase. To reconstruct the EI-PET, the difference between the blurry PET and the average of the deformed EI-PETs is minimized using a maximum-likelihood expectation-maximization algorithm. The developed method was evaluated with computational and physical phantoms as well as PET/CT images acquired from three patients. Results: The BID method increased the signal-to-noise ratio from 1.88 ± 1.05 to 10.5 ± 3.3 and universal-quality index from 0.72 ± 0.11 to 1.0 for the computational phantoms, and reduced the motion-induced error from 69.9% to 10.9% in the maximum of activity concentration and from 317.5% to 8.7% in the full width at half maximum of the physical PET-phantom. The BID-based corrections increased the maximum standardized-uptake values by 17.7 ± 15.4% and reduced tumor volumes by 12.5 ± 10.4% on average for the three patients. Conclusions: The proposed image-decomposition method reduces respiration-induced errors in PET images and holds potential to improve the quality of radiotherapy for thoracic and abdominal cancer patients.
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