title: Computer-aided volumetric assessment of malignant pleural mesothelioma on CT using a random walk-based method.
abstract: OBJECTIVE
  The aim of this study is to assess the performance of a computer-aided semi-automated algorithm we have adapted for the purpose of segmenting malignant pleural mesothelioma (MPM) on CT.
  
  
  METHODS
  Forty-five CT scans were collected from 15 patients (M:F [Formula: see text] 10:5, mean age 62.8 years) in a multi-centre clinical drug trial. A computer-aided random walk-based algorithm was applied to segment the tumour; the results were then compared to radiologist-drawn contours and correlated with measurements made using the MPM-adapted Response Evaluation Criteria in Solid Tumour (modified RECIST).
  
  
  RESULTS
  A mean accuracy (Sørensen-Dice index) of 0.825 (95% CI [0.758, 0.892]) was achieved. Compared to a median measurement time of 68.1 min (range [40.2, 102.4]) for manual delineation, the median running time of our algorithm was 23.1 min (range [10.9, 37.0]). A linear correlation (Pearson's correlation coefficient: 0.6392, [Formula: see text]) was established between the changes in modified RECIST and computed tumour volume.
  
  
  CONCLUSIONS
  Volumetric tumour segmentation offers a potential solution to the challenges in quantifying MPM. Computer-assisted methods such as the one presented in this study facilitate this in an accurate and time-efficient manner and provide additional morphological information about the tumour's evolution over time.
authors.affiliation: Institute of Biomedical Engineering, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, England. d.mitch.chen@gmail.com.|The Churchill Hospital, Oxford University Hospitals NHS Trust, Old Road, Headington, OX3 7LE, England. d.mitch.chen@gmail.com.
authors.forename: Mitchell
authors.identifier: http://orcid.org/0000-0002-3779-5615
authors.initials: M
authors.lastname: Chen
authors.affiliation: The Churchill Hospital, Oxford University Hospitals NHS Trust, Old Road, Headington, OX3 7LE, England.
authors.forename: Emma
authors.initials: E
authors.lastname: Helm
authors.affiliation: Institute of Biomedical Engineering, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, England.
authors.forename: Niranjan
authors.initials: N
authors.lastname: Joshi
authors.affiliation: The Churchill Hospital, Oxford University Hospitals NHS Trust, Old Road, Headington, OX3 7LE, England.
authors.forename: Fergus
authors.initials: F
authors.lastname: Gleeson
authors.affiliation: Institute of Biomedical Engineering, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, England.
authors.forename: Michael
authors.initials: M
authors.lastname: Brady
mesh_terms: D000368:Aged; D000465:Algorithms; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008654:Mesothelioma / Q000000981:diagnostic imaging*; D000086002:Mesothelioma, Malignant; D008875:Middle Aged; D010997:Pleural Neoplasms / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*; D047368:Tumor Burden
keywords: Computed tomography; Image processing; Malignant pleural mesothelioma; Quantitative tumour measurement; Therapy response assessment