Affiliations: [a] School of Nuclear Science and Technology, Xi’an Jiaotong University, China
| [b] Department of PET-CT, The First Affiliated Hospital, Medical College, Xi’an Jiaotong University, China
Correspondence:
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Corresponding author: Huasi Hu, School of Nuclear Science and Technology, Xi’an Jiaotong University, No. 28, Xianning West Road, Xi’an, Shaanxi 710049, People’s Republic of China. Tel.: +86 29 82668648; Fax: +86 29 82667802; E-mail: [email protected] and Youmin Guo, Department of PET-CT, The First Affiliated Hospital, Medical College, Xi’an Jiaotong University, No.227, Yanta West Road, Xi’an, Shaanxi 710061, People’s Republic of China. Tel.: +86 29 85324070; Fax: +86 29 85624743; E-mail: [email protected].
Abstract: Estimation of the pleural effusion’s volume is an important clinical issue. The existing methods cannot assess it accurately when there is large volume of liquid in the pleural cavity and/or the patient has some other disease (e.g. pneumonia). In order to help solve this issue, the objective of this study is to develop and test a novel algorithm using B-spline and local clustering level set method jointly, namely BLL. The BLL algorithm was applied to a dataset involving 27 pleural effusions detected on chest CT examination of 18 adult patients with the presence of free pleural effusion. Study results showed that average volumes of pleural effusion computed using the BLL algorithm and assessed manually by the physicians were 586 ml±339 ml and 604±352 ml, respectively. For the same patient, the volume of the pleural effusion, segmented semi-automatically, was 101.8% ±4.6% of that was segmented manually. Dice similarity was found to be 0.917±0.031. The study demonstrated feasibility of applying the new BLL algorithm to accurately measure the volume of pleural effusion.
Keywords: CT, pleural effusion, volume, B-spline, local clustering level set
