Volume 15 Supplement 1
Tumour characterisation, staging and operability assessment in ovarian carcinoma: whole body diffusion-weighted MRI versus CT
© Michielsen et al. 2015
Published: 2 October 2015
To prospectively evaluate whole body diffusion-weighted MRI (WB-DWI/MRI) for tumour characterisation, staging and prediction of complete (R0)-resection compared with computed tomography (CT) in patients with suspected ovarian carcinoma.
One-hundred-sixty-six patients suspected for ovarian carcinoma underwent 3T WB-DWI/MRI using 2 b-values (b=0-1000 s/mm2), T2-weighted and contrast-enhanced T1-weighted sequences in addition to contrast-enhanced CT. WB-DWI/MRI and CT were independently and blindly evaluated and correlated with pathological findings at surgery as reference standard. Superiority was assessed using two-tailed McNemar tests for following parameters: characterisation of the malignant nature and primary origin of the ovarian mass, assessment of disease extent according to FIGO stage and prediction of R0-resection according to predefined operability criteria. Inter observer agreement for WB-DWI/MRI and CT was determined using Cohen’s kappa statistics.
For characterisation of malignancy, WB-DWI/MRI showed significantly higher accuracy compared with CT (93 versus 82%, p=0.001). WB-DWI/MRI correctly depicted a non-ovarian malignant mass in 24/32 (75%) of cases compared to only 6/32 (19%) for CT (p<0.001). WB-DWI/MRI assigned more ovarian carcinoma patients to the correct FIGO stage (71/94, 76%) compared with CT (39/94, 41%). For prediction of R0-resection, WB-DWI/MRI showed significantly higher sensitivity (95 versus 80%), specificity (92 versus 74%) and accuracy (94 versus 77%) compared with CT (p=0.039, p=0.012 and p<0.001, respectively). Interobserver agreement was moderate to almost perfect (κ=0.53-1.00) for WB-DWI/MRI and slight to moderate (κ=0.04-0.52) for CT.
WB-DWI/MRI is superior to CT for lesion characterisation, staging and operability assessment of ovarian cancer justifying its development for pre-operative assessment of ovarian cancer patients.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.