Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Health Technology and Informatics | en_US |
| dc.contributor.advisor | Cai, Jing (HTI) | en_US |
| dc.contributor.advisor | Ren, Ge (HTI) | en_US |
| dc.creator | Chen, Zhi | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/13797 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Anatomy-wise computed tomography-derived lung ventilation imaging for precise functional lung avoidance radiation therapy | en_US |
| dcterms.abstract | Background: Functional lung avoidance radiotherapy (FLART) is an innovative approach aimed at preserving lung function during treatment planning. It achieves this by minimizing radiation exposure to the high functional volume (HFV) of the lung. To create an accurate treatment plan, FLART combines functional lung images (ventilation/perfusion images). However, the current standard clinical techniques for lung ventilation imaging rely on radioactive gases or aerosols, such as Single Photon Emission Computed Tomography (SPECT) with Tc-99m or Positron Emission Tomography (PET) with Ga-68. While effective in assessing pre-treatment pulmonary function, these methods require additional imaging scans and the injection of radioactive material, resulting in extra costs and radiation dose. | en_US |
| dcterms.abstract | Purpose: To propose an anatomy-wise lung ventilation imaging method (CTVIAW) that integrates information from lung parenchyma and tumor-blocked pulmonary segments based on planning computed tomography (CT) images for FLART. | en_US |
| dcterms.abstract | Methods and materials: Our study involves the development and application of the CTVIAW method in radiotherapy treatment planning. In the first part, CTVIAW was developed by considering the underlying causes of impaired pulmonary ventilation, specifically pulmonary parenchymal injury and airway blockages. First, an Atlas-based method was developed to divide the lung volume into 18 pulmonary segments. Then, each segment was visually inspected to determine if the connected airway branch was blocked. The blocked segments were considered functionally lost (assigned a value of 0). For unblocked segments, we used a super-voxel-based method to assess functional ability of the pulmonary parenchymal to generate the final CTVIAW. To evaluate the accuracy of our Atlas-based pulmonary segments segmentation, we utilized CT images from 150 patients as a patient library to generate pulmonary segmentations using a bronchial tree-based method. Additionally, we manually segmented pulmonary segments in 14 patients and used them as a reference for comparison (using the Dice similarity coefficient index, DSC). For CTVIAW evaluation, we analyzed 66 patients who had 4DCT and SPECT/PET as lung references ventilation images (RefVI). The Spearman’s correlation coefficient was calculated to assess the similarities between CTVIAW and the RefVI. Out of the sixty-six patients, eleven exhibited airway blockages caused by tumors. These tumor-blocked segments were then compared to the low functional volume (LFV) obtained from the RefVI for these specific eleven patients. In the second part, the CTVIAW was employed to guide treatment planning. The lung was further divided into HFV, recoverable LFV (rLFV, tumor-blocked segments with potential high functional value by analyzing with super-voxel-based method), and unrecoverable LFV (uLFV, the remaining LFV) instead of the traditional HFV and LFV volumes. The rLFV requires protection as the HFV during the planning. Five patients underwent weekly 4DCT and found with tumor shrinkage were selected to create three intensity-modulated photon plans to evaluate the efficiency of our plan strategy: an anatomical-based plan (aPlan), a functional-guided plan (fPlan) that considered only HFV, and a functional-guided plan (rfPlan) that protected both HFV and rLFV. | en_US |
| dcterms.abstract | Results: For the pulmonary segments segmentation, the Atlas-based method achieved a mean DSC value of 0.70 ± 0.11 for left lung and 0.72 ± 0.11 for the right lung when compared to manual segmentations. The LFV in the RefVI and the tumor-blocked segments had a high overlap similarity coefficient value of 0.90 ± 0.07. The novel CTVIAW method demonstrated a mean Spearman’s correlation coefficient of 0.59 (range: 0.31 to 0.82) with the RefVI. For the 11 patients with tumor-blocked segments, the mean Spearman correlation between CTVIAW and RefVI was 0.72 ± 0.05. This correlation was higher than the correlation between the super-voxel-based method (CTVIsvd, without considering the airway blockage) and RefVI (0.51± 0.14). For the comparison of the five patients’ treatment plans, the V5, V20 and mean dose of the HFV in fPlan were 10.6% ± 25.3%, 14.3% ± 9.5%, and 10.0% ± 9.3% lower, respectively, than those in aPlan. The overall HFV dose in the recoverable functional-guided plan (rfPlan) was similar to that in fPlan. By incorporating dose constraints for rLFV, the dose of rLFV in rfPlan was lower than in both fPlan and aPlan. Specifically, the V5, V20, and mean dose of rLFV in rfPlan were lower than in aPlan by 0.3% ± 0.5%, 12.1% ± 8.4%, and 13.0% ± 6.4%, respectively. Notably, these parameters in rfPlan were substantially lower than in fPlan by 1.0% ± 2.1%, 14.9% ± 9.8%, and 15.9% ± 6.5%, respectively. Regarding other evaluation parameters, all three plans showed comparable results and remained within tolerance. | en_US |
| dcterms.abstract | Conclusions: In this study, we developed a novel anatomy-wise lung ventilation imaging method to generate surrogate ventilation images directly from CT images for precise functional lung avoidance radiotherapy planning. Unlike traditional methods, CTVIAW considers both air transport and lung parenchymal features, providing a comprehensive understanding of impaired lung ventilation. Importantly, during treatment planning, CTVIAW can be used to identify and reduce radiation dose to the potential recoverable region. This region may regain high function if the tumor shrinks post-treatment. This is the first time that recoverable regions have been incorporated into the treatment planning process, potentially preserving more lung function for patients. The findings contribute to the development of personalized and precise treatment planning methods. | en_US |
| dcterms.extent | xxvii, 120 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2025 | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.accessRights | open access | en_US |
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