A semi-automated toolkit for analysis of liver cancer treatment response using Perfusion CT
Naydenova E, Cifor A, Hill E, Franklin J, Sharma RA, Schnabel JA (2014)
Publication Type: Conference contribution
Publication year: 2014
Journal
Publisher: Springer Verlag
Book Volume: 8676
Pages Range: 23-32
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Cambridge, MA, USA
ISBN: 9783319136912
DOI: 10.1007/978-3-319-13692-9_3
Abstract
Delineation of hepatic tumours is challenging in CT due to limited inherent tissue contrast, leading to significant intra-/interobserver variability. Perfusion CT (pCT) allows quantitative assessment of enhancement patterns in normal and abnormal liver. This study aims to develop a semi-automated perfusion analysis toolkit that classifies hepatic tissue based on perfusion-derived parameters. pCT data from patients with hepatic metastases were used in this study. Tumour motion was minimized through image registration; perfusion parameters were derived and then employed in the training of a machine learning algorithm used to classify hepatic tissue. This method was found to deliver promising results for 10 data sets, with recorded sensitivity and specificity of the tissue classification in the ranges of 0.92–0.99 and 0.98– 0.99 respectively. This semi-automated method could be used to analyze response over the treatment course, as it is not based on intensity values.
Involved external institutions
University of Oxford
United Kingdom (GB)
Oxford University Hospitals NHS Foundation Trust
United Kingdom (GB)
United Kingdom (GB)
Oxford University Hospitals NHS Foundation Trust
United Kingdom (GB)
How to cite
APA:
Naydenova, E., Cifor, A., Hill, E., Franklin, J., Sharma, R.A., & Schnabel, J.A. (2014). A semi-automated toolkit for analysis of liver cancer treatment response using Perfusion CT. In Hiroyuki Yoshida, Janne J. Näppi, Sanjay Saini (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 23-32). Cambridge, MA, USA: Springer Verlag.
MLA:
Naydenova, Elina, et al. "A semi-automated toolkit for analysis of liver cancer treatment response using Perfusion CT." Proceedings of the 6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014, Cambridge, MA, USA Ed. Hiroyuki Yoshida, Janne J. Näppi, Sanjay Saini, Springer Verlag, 2014. 23-32.
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