title: Assessment of pulmonary vasculature volume with automated threshold-based 3D quantitative CT volumetry: in vitro and in vivo validation.
abstract: OBJECTIVE
  To validate the ability of threshold-based 3D CT volumetry to enable measurement of volume of visible pulmonary vessels on CT.
  
  
  METHODS
  In vivo, 3D CT volumetry was validated in seven phantoms that consisted of silicone tubes embedded in a foam block. With the true volume value as reference standard, the accuracy of CT measurement at various lower thresholds of -600 HU, -500 HU, -300 HU and -200 HU were compared. The volume measurements obtained when filled with varied concentration of iodinated contrast media (1:100, 1:200 and 1:500) were also compared. In vivo validation was performed in sixteen patients (9 men, 7 women; mean age, 52.1 years). Inter-scan and inter-observer agreement and reproducibility for pulmonary vasculature volume measurement were evaluated with Bland-Altman analysis.
  
  
  RESULTS
  In vitro, the mean value measured under lower threshold of -300 HU (relative error=1.5%) were the closest to the true values and have no signiﬁcant difference (P=0.375). There were no signiﬁcant differences among the phantom measurement values with different filled concentration (1:100, 1:200 and 1:500). In vivo, the inter-scan reproducibility of volume measurements was good, with a correlation coefficient of 0.82 and ICC (intraclass correlation coefficient) of 0.86. Inter-observer agreement was excellent with a correlation coefficient of 0.91 and ICC of 0.95.
  
  
  CONCLUSIONS
  The threshold-based 3D quantitative CT volumetry enables accurate and reproducible measurement of pulmonary vessels volume.
authors.affiliation: Department of Radiology, First Hospital of Tsinghua University, No 6, Jiuxianqiao 1 Jiefang, Chaoyang District, Beijing, China.
authors.forename: Jingzhe
authors.initials: J
authors.lastname: Liu
authors.forename: Qingyu
authors.initials: Q
authors.lastname: Wu
authors.forename: Yufeng
authors.initials: Y
authors.lastname: Xu
authors.forename: Yan
authors.initials: Y
authors.lastname: Bai
authors.forename: Zhibo
authors.initials: Z
authors.lastname: Liu
authors.forename: Hongyin
authors.initials: H
authors.lastname: Li
authors.forename: Jiemin
authors.initials: J
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D009929:Organ Size; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D011651:Pulmonary Artery / Q000000981:diagnostic imaging*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*