Tumour subregion analysis of colorectal liver metastases using semi-automated clustering based on DCE-MRI: Comparison with histological subregions and impact on pharmacokinetic parameter analysis.
| Autor: | Franklin JM; Institute of Medical Imaging and Visualisation, Bournemouth University, UK; Radiology Department, Royal Bournemouth and Christchurch Hospitals NS Foundation Trust, UK. Electronic address: jfranklin@bournemouth.ac.uk., Irving B; Institute of Biomedical Engineering (Department of Engineering Science), University of Oxford, UK., Papiez BW; Institute of Biomedical Engineering (Department of Engineering Science), University of Oxford, UK., Kallehauge JF; Institute of Biomedical Engineering (Department of Engineering Science), University of Oxford, UK., Wang LM; Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, UK., Goldin RD; Centre for Pathology, Imperial College, London, UK., Harris AL; Department of Oncology, University of Oxford, UK., Anderson EM; Radiology Department, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, UK., Schnabel JA; Institute of Biomedical Engineering (Department of Engineering Science), University of Oxford, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, UK., Chappell MA; Institute of Biomedical Engineering (Department of Engineering Science), University of Oxford, UK., Brady M; Department of Oncology, University of Oxford, UK., Sharma RA; NIHR University College London Hospitals Biomedical Research Centre, UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6DD, UK., Gleeson FV; Radiology Department, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, UK. |
|---|---|
| Jazyk: | angličtina |
| Zdroj: | European journal of radiology [Eur J Radiol] 2020 May; Vol. 126, pp. 108934. Date of Electronic Publication: 2020 Mar 06. |
| DOI: | 10.1016/j.ejrad.2020.108934 |
| Abstrakt: | Purpose: To use a novel segmentation methodology based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to define tumour subregions of liver metastases from colorectal cancer (CRC), to compare these with histology, and to use these to compare extracted pharmacokinetic (PK) parameters between tumour subregions. Materials and Methods: This ethically-approved prospective study recruited patients with CRC and ≥1 hepatic metastases scheduled for hepatic resection. Patients underwent DCE-MRI pre-metastasectomy. Histological sections of resection specimens were spatially matched to DCE-MRI acquisitions and used to define histological subregions of viable and non-viable tumour. A semi-automated voxel-wise image segmentation algorithm based on the DCE-MRI contrast-uptake curves was used to define imaging subregions of viable and non-viable tumour. Overlap of histologically-defined and imaging subregions was compared using the Dice similarity coefficient (DSC). DCE-MRI PK parameters were compared for the whole tumour and histology-defined and imaging-derived subregions. Results: Fourteen patients were included in the analysis. Direct histological comparison with imaging was possible in nine patients. Mean DSC for viable tumour subregions defined by imaging and histology was 0.738 (range 0.540-0.930). There were significant differences between K trans and k Conclusion: We demonstrate good concordance of viable tumour segmentation based on pre-operative DCE-MRI with a post-operative histological gold-standard. This can be used to extract viable tumour-specific values from quantitative image analysis, and could improve treatment response assessment in clinical practice. (Copyright © 2020 Elsevier B.V. All rights reserved.) |
| Databáze: | MEDLINE |
| Externí odkaz: |
|
Full Text from ScienceDirect