A super-voxel-based method for generating surrogate lung ventilation images from CT
Purpose: This study aimed to develop and evaluate CTVISVD, a super-voxel-based method for surrogate computed tomography ventilation imaging (CTVI).Methods and Materials: The study used four-dimensional CT (4DCT) and single-photon emission computed tomography (SPECT) images and corresponding lung mas...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-04-01
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| Series: | Frontiers in Physiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphys.2023.1085158/full |
| _version_ | 1827944646280478720 |
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| author | Zhi Chen Yu-Hua Huang Feng-Ming Kong Feng-Ming Kong Wai Yin Ho Ge Ren Jing Cai |
| author_facet | Zhi Chen Yu-Hua Huang Feng-Ming Kong Feng-Ming Kong Wai Yin Ho Ge Ren Jing Cai |
| author_sort | Zhi Chen |
| collection | DOAJ |
| description | Purpose: This study aimed to develop and evaluate CTVISVD, a super-voxel-based method for surrogate computed tomography ventilation imaging (CTVI).Methods and Materials: The study used four-dimensional CT (4DCT) and single-photon emission computed tomography (SPECT) images and corresponding lung masks from 21 patients with lung cancer obtained from the Ventilation And Medical Pulmonary Image Registration Evaluation dataset. The lung volume of the exhale CT for each patient was segmented into hundreds of super-voxels using the Simple Linear Iterative Clustering (SLIC) method. These super-voxel segments were applied to the CT and SPECT images to calculate the mean density values (Dmean) and mean ventilation values (Ventmean), respectively. The final CT-derived ventilation images were generated by interpolation from the Dmean values to yield CTVISVD. For the performance evaluation, the voxel- and region-wise differences between CTVISVD and SPECT were compared using Spearman’s correlation and the Dice similarity coefficient index. Additionally, images were generated using two deformable image registration (DIR)-based methods, CTVIHU and CTVIJac, and compared with the SPECT images.Results: The correlation between the Dmean and Ventmean of the super-voxel was 0.59 ± 0.09, representing a moderate-to-high correlation at the super-voxel level. In the voxel-wise evaluation, the CTVISVD method achieved a stronger average correlation (0.62 ± 0.10) with SPECT, which was significantly better than the correlations achieved with the CTVIHU (0.33 ± 0.14, p < 0.05) and CTVIJac (0.23 ± 0.11, p < 0.05) methods. For the region-wise evaluation, the Dice similarity coefficient of the high functional region for CTVISVD (0.63 ± 0.07) was significantly higher than the corresponding values for the CTVIHU (0.43 ± 0.08, p < 0.05) and CTVIJac (0.42 ± 0.05, p < 0.05) methods.Conclusion: The strong correlation between CTVISVD and SPECT demonstrates the potential usefulness of this novel method of ventilation estimation for surrogate ventilation imaging. |
| first_indexed | 2024-03-13T10:33:26Z |
| format | Article |
| id | doaj.art-d43e160569aa4c5ca8455fb15f9154b9 |
| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-03-13T10:33:26Z |
| publishDate | 2023-04-01 |
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| series | Frontiers in Physiology |
| spelling | doaj.art-d43e160569aa4c5ca8455fb15f9154b92023-05-18T09:00:09ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2023-04-011410.3389/fphys.2023.10851581085158A super-voxel-based method for generating surrogate lung ventilation images from CTZhi Chen0Yu-Hua Huang1Feng-Ming Kong2Feng-Ming Kong3Wai Yin Ho4Ge Ren5Jing Cai6Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, ChinaDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, ChinaDepartment of Clinical Oncology, Queen Mary Hospital, Hong Kong, ChinaDepartment of Clinical Oncology, The University of Hong Kong, Hong Kong, ChinaDepartment of Nuclear Medicine, Queen Mary Hospital, Hong Kong, ChinaDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, ChinaDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, ChinaPurpose: This study aimed to develop and evaluate CTVISVD, a super-voxel-based method for surrogate computed tomography ventilation imaging (CTVI).Methods and Materials: The study used four-dimensional CT (4DCT) and single-photon emission computed tomography (SPECT) images and corresponding lung masks from 21 patients with lung cancer obtained from the Ventilation And Medical Pulmonary Image Registration Evaluation dataset. The lung volume of the exhale CT for each patient was segmented into hundreds of super-voxels using the Simple Linear Iterative Clustering (SLIC) method. These super-voxel segments were applied to the CT and SPECT images to calculate the mean density values (Dmean) and mean ventilation values (Ventmean), respectively. The final CT-derived ventilation images were generated by interpolation from the Dmean values to yield CTVISVD. For the performance evaluation, the voxel- and region-wise differences between CTVISVD and SPECT were compared using Spearman’s correlation and the Dice similarity coefficient index. Additionally, images were generated using two deformable image registration (DIR)-based methods, CTVIHU and CTVIJac, and compared with the SPECT images.Results: The correlation between the Dmean and Ventmean of the super-voxel was 0.59 ± 0.09, representing a moderate-to-high correlation at the super-voxel level. In the voxel-wise evaluation, the CTVISVD method achieved a stronger average correlation (0.62 ± 0.10) with SPECT, which was significantly better than the correlations achieved with the CTVIHU (0.33 ± 0.14, p < 0.05) and CTVIJac (0.23 ± 0.11, p < 0.05) methods. For the region-wise evaluation, the Dice similarity coefficient of the high functional region for CTVISVD (0.63 ± 0.07) was significantly higher than the corresponding values for the CTVIHU (0.43 ± 0.08, p < 0.05) and CTVIJac (0.42 ± 0.05, p < 0.05) methods.Conclusion: The strong correlation between CTVISVD and SPECT demonstrates the potential usefulness of this novel method of ventilation estimation for surrogate ventilation imaging.https://www.frontiersin.org/articles/10.3389/fphys.2023.1085158/fullventilation4DCTsuper-voxelradiotherapylung cancer |
| spellingShingle | Zhi Chen Yu-Hua Huang Feng-Ming Kong Feng-Ming Kong Wai Yin Ho Ge Ren Jing Cai A super-voxel-based method for generating surrogate lung ventilation images from CT Frontiers in Physiology ventilation 4DCT super-voxel radiotherapy lung cancer |
| title | A super-voxel-based method for generating surrogate lung ventilation images from CT |
| title_full | A super-voxel-based method for generating surrogate lung ventilation images from CT |
| title_fullStr | A super-voxel-based method for generating surrogate lung ventilation images from CT |
| title_full_unstemmed | A super-voxel-based method for generating surrogate lung ventilation images from CT |
| title_short | A super-voxel-based method for generating surrogate lung ventilation images from CT |
| title_sort | super voxel based method for generating surrogate lung ventilation images from ct |
| topic | ventilation 4DCT super-voxel radiotherapy lung cancer |
| url | https://www.frontiersin.org/articles/10.3389/fphys.2023.1085158/full |
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