title: Validating and improving CT ventilation imaging by correlating with ventilation 4D-PET/CT using 68Ga-labeled nanoparticles.
abstract: OBJECTIVE
  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 (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 (VHU) or Jacobian determinant of deformation (VJac). The two modified metrics incorporate a voxel-wise tissue-density scaling (ρVHU and ρVJac) 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 (σm = 0 or 3 mm) were also applied to all images. As in previous studies, similarity metrics included the Spearman correlation coefficient r within the segmented lung volumes, and Dice coefficient d20 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 (ρVHU) with σm = 3 mm. This leads to correlation values in the ranges 0.22 ≤ r ≤ 0.76 and 0.38 ≤ d20 ≤ 0.68, with r = 0.42 ± 0.16 and d20 = 0.52 ± 0.09 averaged over the 12 patients. Compared to Jacobian-based metrics, HU-based metrics lead to statistically significant improvements in r and d20 (p < 0.05), with density scaled metrics also showing higher r than for unscaled versions (p < 0.02). r and d20 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.
authors.affiliation: Radiation Physics Laboratory, Sydney Medical School, University of Sydney, Sydney NSW 2006, Australia.
authors.forename: John
authors.initials: J
authors.lastname: Kipritidis
authors.affiliation: Department of Radiation Oncology, Peter MacCallum Cancer Centre, and Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville VIC 3052, Australia.
authors.forename: Shankar
authors.initials: S
authors.lastname: Siva
authors.affiliation: Centre for Cancer Imaging, Peter MacCallum Cancer Centre and Department of Medicine, University of Melbourne, Melbourne VIC 3002, Australia.
authors.forename: Michael S
authors.initials: MS
authors.lastname: Hofman
authors.affiliation: Centre for Cancer Imaging, Peter MacCallum Cancer Centre and Department of Medicine, University of Melbourne, Melbourne VIC 3002, Australia.
authors.forename: Jason
authors.initials: J
authors.lastname: Callahan
authors.affiliation: Centre for Cancer Imaging, Peter MacCallum Cancer Centre and Department of Medicine, University of Melbourne, Melbourne VIC 3002, Australia.
authors.forename: Rodney J
authors.initials: RJ
authors.lastname: Hicks
authors.affiliation: Radiation Physics Laboratory, Sydney Medical School, University of Sydney, Sydney NSW 2006, Australia.
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Keall
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging / Q000503:physiopathology; D005260:Female; D056973:Four-Dimensional Computed Tomography / Q000379:methods*; D005710:Gallium Radioisotopes; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging / Q000503:physiopathology*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D064847:Multimodal Imaging; D053758:Nanoparticles; D049268:Positron-Emission Tomography; D012123:Pulmonary Ventilation
chemical_list: D005710:Gallium Radioisotopes