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Title: Validating and improving CT ventilation imaging by correlating with ventilation 4D-PET/CT using {sup 68}Ga-labeled nanoparticles

Purpose: CT ventilation imaging is a novel functional lung imaging modality based on deformable image registration. The authors present the first validation study of CT ventilation using positron emission tomography with{sup 68}Ga-labeled nanoparticles (PET-Galligas). The authors quantify this agreement for different CT ventilation metrics and PET reconstruction parameters. Methods: PET-Galligas ventilation scans were acquired for 12 lung cancer patients using a four-dimensional (4D) PET/CT scanner. CT ventilation images were then produced by applying B-spline deformable image registration between the respiratory correlated phases of the 4D-CT. The authors test four ventilation metrics, two existing and two modified. The two existing metrics model mechanical ventilation (alveolar air-flow) based on Hounsfield unit (HU) change (V{sub HU}) or Jacobian determinant of deformation (V{sub Jac}). The two modified metrics incorporate a voxel-wise tissue-density scaling (ρV{sub HU} and ρV{sub Jac}) and were hypothesized to better model the physiological ventilation. In order to assess the impact of PET image quality, comparisons were performed using both standard and respiratory-gated PET images with the former exhibiting better signal. Different median filtering kernels (σ{sub m} = 0 or 3 mm) were also applied to all images. As in previous studies, similarity metrics included the Spearman correlation coefficient r within themore » segmented lung volumes, and Dice coefficient d{sub 20} for the (0 − 20)th functional percentile volumes. Results: The best agreement between CT and PET ventilation was obtained comparing standard PET images to the density-scaled HU metric (ρV{sub HU}) with σ{sub m} = 3 mm. This leads to correlation values in the ranges 0.22 ⩽ r ⩽ 0.76 and 0.38 ⩽ d{sub 20} ⩽ 0.68, with r{sup ¯}=0.42±0.16 and d{sup ¯}{sub 20}=0.52±0.09 averaged over the 12 patients. Compared to Jacobian-based metrics, HU-based metrics lead to statistically significant improvements in r{sup ¯} and d{sup ¯}{sub 20} (p < 0.05), with density scaled metrics also showing higher r{sup ¯} than for unscaled versions (p < 0.02). r{sup ¯} and d{sup ¯}{sub 20} were also sensitive to image quality, with statistically significant improvements using standard (as opposed to gated) PET images and with application of median filtering. Conclusions: The use of modified CT ventilation metrics, in conjunction with PET-Galligas and careful application of image filtering has resulted in improved correlation compared to earlier studies using nuclear medicine ventilation. However, CT ventilation and PET-Galligas do not always provide the same functional information. The authors have demonstrated that the agreement can improve for CT ventilation metrics incorporating a tissue density scaling, and also with increasing PET image quality. CT ventilation imaging has clear potential for imaging regional air volume change in the lung, and further development is warranted.« less
;  [1] ;  [2] ; ; ;  [3]
  1. Radiation Physics Laboratory, Sydney Medical School, University of Sydney, Sydney NSW 2006 (Australia)
  2. Department of Radiation Oncology, Peter MacCallum Cancer Centre, and Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville VIC 3052 (Australia)
  3. Centre for Cancer Imaging, Peter MacCallum Cancer Centre and Department of Medicine, University of Melbourne, Melbourne VIC 3002 (Australia)
Publication Date:
OSTI Identifier:
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 41; Journal Issue: 1; Other Information: (c) 2014 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States