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Estimating lung ventilation directly from 4D CT Hounsfield unit values.

John Kipritidis1, Michael S Hofman2, Shankar Siva2

  • 1Radiation Physics Laboratory, Sydney Medical School, University of Sydney, Sydney, NSW 2006, Australia.

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|January 10, 2016
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Summary
This summary is machine-generated.

A new Hounsfield unit (HU)-based method for computed tomography ventilation imaging (CTVI) shows improved accuracy compared to traditional deformable image registration (DIR)-based methods. This streamlined CTVI approach offers a more reliable way to assess lung ventilation in cancer patients.

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Area of Science:

  • Medical Imaging
  • Pulmonary Function Assessment
  • Radiotherapy

Background:

  • Computed tomography ventilation imaging (CTVI) traditionally uses deformable image registration (DIR) to visualize lung air-volume changes from 4DCT scans.
  • DIR-based CTVI is sensitive to image artifacts and parameter choices, limiting clinical validation.
  • A novel, streamlined CTVI approach estimates blood-gas exchange using time-averaged 4DCT Hounsfield unit (HU) values, bypassing the need for DIR.

Purpose of the Study:

  • To quantify the accuracy of the novel HU-based CTVI method.
  • To compare the HU-based CTVI method against DIR-based CTVI techniques.
  • To validate the HU-based CTVI method using high-resolution (68)Ga positron emission tomography (Galligas PET) scans in lung cancer patients.

Main Methods:

  • Analyzed Galligas 4D-PET/CT scans from 25 lung cancer patients undergoing radiation therapy.
  • Generated three CTVI types: HU-based (CTV IHU¯), DIR-based density changes (CTV IDIR-HU), and DIR-based volume changes (CTV IDIR-Jac).
  • Quantified accuracy via voxel-wise Spearman correlation (r) and separation of mean voxel values between defect/nondefect regions compared to Galligas PET.

Main Results:

  • The HU-based CTVI (CTV IHU¯) demonstrated superior accuracy with a mean Spearman correlation of 0.50 ± 0.17 compared to DIR-based methods (r=0.42 ± 0.20 for CTV IDIR-HU, r=0.19 ± 0.23 for CTV IDIR-Jac).
  • CTV IHU¯ showed statistically significant separation of mean ventilation values between clinical defect and nondefect regions.
  • Qualitative assessment showed concordance with Galligas PET for emphysema, but overestimation in tumor-obstructed regions and limitations in abnormal lung morphology.

Conclusions:

  • The HU-based CTVI method improves voxel-wise correlation with Galligas PET over DIR-based approaches.
  • This method shows promise as a useful approximation for lung ventilation estimation, particularly within specific HU ranges (-1000 to -600).
  • Further clinical verification may establish HU-based CTVI as a straightforward and reproducible tool for free-breathing 4DCT lung ventilation assessment.