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Anatomy-wise lung ventilation imaging for precise functional lung avoidance radiation therapy.

Publication ,  Journal Article
Chen, Z; Li, Z; Huang, Y-H; Teng, X; Zhang, J; Xiong, T; Dong, Y; Song, L; Ren, G; Cai, J
Published in: Phys Med Biol
February 12, 2025

Objective.This study aimed to propose a method for obtaining anatomy-wise lung ventilation image (VIaw) that enables functional assessment of lung parenchyma and tumor-blocked pulmonary segments. The VIawwas used to define multiple functional volumes of the lung and thereby support radiation treatment planning.Approach.A super-voxel-based method was employed for functional assessment of lung parenchyma to generate VIsvd. In the VIsvdof the 11 patients with tumor blockage of the airway, the functional value in tumor-blocked segments was set to 0 to generate the VIaw. The lung was divided into regions of high functional volume (HFV), unrecoverable low functional volume (LFV), and recoverable LFV (rLFV, the region in the tumor-blocked segment with a high function value based on the VIsvd) to design three intensity-modulated photon plans for five patients. These plans were an anatomical-lung-guided plan (aPlan), a functional-lung-guided plan (fPlan), and a recoverable functional-lung-guided plan (rfPlan) where the latter protected both HFV and rLFV.Main results.The LFV in the reference ventilation images and the tumor-blocked segments had a high overlap similarity coefficient value of 0.90 ± 0.07. The mean Spearman correlation between the VIawand reference ventilation images was 0.72 ± 0.05 for the patient with tumor blockage of the airway. TheV20 and mean dose of rLFV in rfPlan were lower than those in aPlan by 12.1 ± 8.4% and 13.0 ± 6.4%, respectively, and lower than those in fPlan by 14.9 ± 9.8% and 15.9 ± 6.5%, respectively.Significance.The VIawcan reach a moderate-strong correlation with reference ventilation images and thus can identify rLFV to support treatment planning to preserve lung function.

Duke Scholars

Published In

Phys Med Biol

DOI

EISSN

1361-6560

Publication Date

February 12, 2025

Volume

70

Issue

4

Location

England

Related Subject Headings

  • Tomography, X-Ray Computed
  • Respiration
  • Radiotherapy, Image-Guided
  • Radiotherapy Planning, Computer-Assisted
  • Pulmonary Ventilation
  • Nuclear Medicine & Medical Imaging
  • Male
  • Lung Neoplasms
  • Lung
  • Humans
 

Citation

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Chen, Z., Li, Z., Huang, Y.-H., Teng, X., Zhang, J., Xiong, T., … Cai, J. (2025). Anatomy-wise lung ventilation imaging for precise functional lung avoidance radiation therapy. Phys Med Biol, 70(4). https://doi.org/10.1088/1361-6560/adb123
Chen, Zhi, Zihan Li, Yu-Hua Huang, Xinzhi Teng, Jiang Zhang, Tianyu Xiong, Yanjing Dong, Liming Song, Ge Ren, and Jing Cai. “Anatomy-wise lung ventilation imaging for precise functional lung avoidance radiation therapy.Phys Med Biol 70, no. 4 (February 12, 2025). https://doi.org/10.1088/1361-6560/adb123.
Chen Z, Li Z, Huang Y-H, Teng X, Zhang J, Xiong T, et al. Anatomy-wise lung ventilation imaging for precise functional lung avoidance radiation therapy. Phys Med Biol. 2025 Feb 12;70(4).
Chen, Zhi, et al. “Anatomy-wise lung ventilation imaging for precise functional lung avoidance radiation therapy.Phys Med Biol, vol. 70, no. 4, Feb. 2025. Pubmed, doi:10.1088/1361-6560/adb123.
Chen Z, Li Z, Huang Y-H, Teng X, Zhang J, Xiong T, Dong Y, Song L, Ren G, Cai J. Anatomy-wise lung ventilation imaging for precise functional lung avoidance radiation therapy. Phys Med Biol. 2025 Feb 12;70(4).
Journal cover image

Published In

Phys Med Biol

DOI

EISSN

1361-6560

Publication Date

February 12, 2025

Volume

70

Issue

4

Location

England

Related Subject Headings

  • Tomography, X-Ray Computed
  • Respiration
  • Radiotherapy, Image-Guided
  • Radiotherapy Planning, Computer-Assisted
  • Pulmonary Ventilation
  • Nuclear Medicine & Medical Imaging
  • Male
  • Lung Neoplasms
  • Lung
  • Humans