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Simulation of a new respiratory phase sorting method for 4D-imaging using optical surface information towards precision radiotherapy
BACKGROUND: Respiratory signal detection is critical for 4-dimensional (4D) imaging. This study proposes and evaluates a novel phase sorting method using optical surface imaging (OSI), aiming to improve the precision of radiotherapy. METHOD: Based on 4D Extended Cardiac-Torso (XCAT) digital phantom,...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10311359/ https://www.ncbi.nlm.nih.gov/pubmed/37290392 http://dx.doi.org/10.1016/j.compbiomed.2023.107073 |
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author | Dong, Zhengkun Yu, Shutong Szmul, Adam Wang, Jingyuan Qi, Junfeng Wu, Hao Li, Junyu Lu, Zihong Zhang, Yibao |
author_facet | Dong, Zhengkun Yu, Shutong Szmul, Adam Wang, Jingyuan Qi, Junfeng Wu, Hao Li, Junyu Lu, Zihong Zhang, Yibao |
author_sort | Dong, Zhengkun |
collection | PubMed |
description | BACKGROUND: Respiratory signal detection is critical for 4-dimensional (4D) imaging. This study proposes and evaluates a novel phase sorting method using optical surface imaging (OSI), aiming to improve the precision of radiotherapy. METHOD: Based on 4D Extended Cardiac-Torso (XCAT) digital phantom, OSI in point cloud format was generated from the body segmentation, and image projections were simulated using the geometries of Varian 4D kV cone-beam-CT (CBCT). Respiratory signals were extracted respectively from the segmented diaphragm image (reference method) and OSI respectively, where Gaussian Mixture Model and Principal Component Analysis (PCA) were used for image registration and dimension reduction respectively. Breathing frequencies were compared using Fast-Fourier-Transform. Consistency of 4DCBCT images reconstructed using Maximum Likelihood Expectation Maximization algorithm was also evaluated quantitatively, where high consistency can be suggested by lower Root-Mean-Square-Error (RMSE), Structural-Similarity-Index (SSIM) value closer to 1, and larger Peak-Signal-To-Noise-Ratio (PSNR) respectively. RESULTS: High consistency of breathing frequencies was observed between the diaphragm-based (0.232 Hz) and OSI-based (0.251 Hz) signals, with a slight discrepancy of 0.019Hz. Using end of expiration (EOE) and end of inspiration (EOI) phases as examples, the mean±1SD values of the 80 transverse, 100 coronal and 120 sagittal planes were 0.967, 0,972, 0.974 (SSIM); 1.657 ± 0.368, 1.464 ± 0.104, 1.479 ± 0.297 (RMSE); and 40.501 ± 1.737, 41.532 ± 1.464, 41.553 ± 1.910 (PSNR) for the EOE; and 0.969, 0.973, 0.973 (SSIM); 1.686 ± 0.278, 1.422 ± 0.089, 1.489 ± 0.238 (RMSE); and 40.535 ± 1.539, 41.605 ± 0.534, 41.401 ± 1.496 (PSNR) for EOI respectively. CONCLUSIONS: This work proposed and evaluated a novel respiratory phase sorting approach for 4D imaging using optical surface signals, which can potentially be applied to precision radiotherapy. Its potential advantages were non-ionizing, non-invasive, non-contact, and more compatible with various anatomic regions and treatment/imaging systems. |
format | Online Article Text |
id | pubmed-10311359 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103113592023-08-01 Simulation of a new respiratory phase sorting method for 4D-imaging using optical surface information towards precision radiotherapy Dong, Zhengkun Yu, Shutong Szmul, Adam Wang, Jingyuan Qi, Junfeng Wu, Hao Li, Junyu Lu, Zihong Zhang, Yibao Comput Biol Med Article BACKGROUND: Respiratory signal detection is critical for 4-dimensional (4D) imaging. This study proposes and evaluates a novel phase sorting method using optical surface imaging (OSI), aiming to improve the precision of radiotherapy. METHOD: Based on 4D Extended Cardiac-Torso (XCAT) digital phantom, OSI in point cloud format was generated from the body segmentation, and image projections were simulated using the geometries of Varian 4D kV cone-beam-CT (CBCT). Respiratory signals were extracted respectively from the segmented diaphragm image (reference method) and OSI respectively, where Gaussian Mixture Model and Principal Component Analysis (PCA) were used for image registration and dimension reduction respectively. Breathing frequencies were compared using Fast-Fourier-Transform. Consistency of 4DCBCT images reconstructed using Maximum Likelihood Expectation Maximization algorithm was also evaluated quantitatively, where high consistency can be suggested by lower Root-Mean-Square-Error (RMSE), Structural-Similarity-Index (SSIM) value closer to 1, and larger Peak-Signal-To-Noise-Ratio (PSNR) respectively. RESULTS: High consistency of breathing frequencies was observed between the diaphragm-based (0.232 Hz) and OSI-based (0.251 Hz) signals, with a slight discrepancy of 0.019Hz. Using end of expiration (EOE) and end of inspiration (EOI) phases as examples, the mean±1SD values of the 80 transverse, 100 coronal and 120 sagittal planes were 0.967, 0,972, 0.974 (SSIM); 1.657 ± 0.368, 1.464 ± 0.104, 1.479 ± 0.297 (RMSE); and 40.501 ± 1.737, 41.532 ± 1.464, 41.553 ± 1.910 (PSNR) for the EOE; and 0.969, 0.973, 0.973 (SSIM); 1.686 ± 0.278, 1.422 ± 0.089, 1.489 ± 0.238 (RMSE); and 40.535 ± 1.539, 41.605 ± 0.534, 41.401 ± 1.496 (PSNR) for EOI respectively. CONCLUSIONS: This work proposed and evaluated a novel respiratory phase sorting approach for 4D imaging using optical surface signals, which can potentially be applied to precision radiotherapy. Its potential advantages were non-ionizing, non-invasive, non-contact, and more compatible with various anatomic regions and treatment/imaging systems. Elsevier 2023-08 /pmc/articles/PMC10311359/ /pubmed/37290392 http://dx.doi.org/10.1016/j.compbiomed.2023.107073 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Dong, Zhengkun Yu, Shutong Szmul, Adam Wang, Jingyuan Qi, Junfeng Wu, Hao Li, Junyu Lu, Zihong Zhang, Yibao Simulation of a new respiratory phase sorting method for 4D-imaging using optical surface information towards precision radiotherapy |
title | Simulation of a new respiratory phase sorting method for 4D-imaging using optical surface information towards precision radiotherapy |
title_full | Simulation of a new respiratory phase sorting method for 4D-imaging using optical surface information towards precision radiotherapy |
title_fullStr | Simulation of a new respiratory phase sorting method for 4D-imaging using optical surface information towards precision radiotherapy |
title_full_unstemmed | Simulation of a new respiratory phase sorting method for 4D-imaging using optical surface information towards precision radiotherapy |
title_short | Simulation of a new respiratory phase sorting method for 4D-imaging using optical surface information towards precision radiotherapy |
title_sort | simulation of a new respiratory phase sorting method for 4d-imaging using optical surface information towards precision radiotherapy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10311359/ https://www.ncbi.nlm.nih.gov/pubmed/37290392 http://dx.doi.org/10.1016/j.compbiomed.2023.107073 |
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