Frood, R, Palkhi, E, Barnfield, M et al. (3 more authors) (2018) Can MR textural analysis improve the prediction of extracapsular nodal spread in patients with oral cavity cancer? European Radiology, 28 (12). pp. 5010-5018. ISSN 0938-7994
Abstract
Objective: To explore the utility of MR texture analysis (MRTA) for detection of nodal extracapsular spread (ECS) in oral cavity squamous cell carcinoma (SCC).
Methods: 115 patients with oral cavity SCC treated with surgery and adjuvant (chemo)radiotherapy were identified retrospectively. First-order texture parameters (entropy, skewness and kurtosis) were extracted from tumour and nodal regions of interest (ROIs) using proprietary software (TexRAD). Nodal MR features associated with ECS (flare sign, irregular capsular contour; local infiltration; nodal necrosis) were reviewed and agreed in consensus by two experienced radiologists. Diagnostic performance characteristics of MR features of ECS were compared with primary tumour and nodal MRTA prediction using histology as the gold standard. Receiver operating characteristic (ROC) and regression analyses were also performed.
Results: Nodal entropy derived from contrast-enhanced T1-weighted images was significant in predicting ECS (p = 0.018). MR features had varying accuracy: flare sign (70%); irregular contour (71%); local infiltration (66%); and nodal necrosis (64%). Nodal entropy combined with irregular contour was the best predictor of ECS (p = 0.004, accuracy 79%).
Conclusion: First-order nodal MRTA combined with imaging features may improve ECS prediction in oral cavity SCC.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018, European Society of Radiology. This is an author produced version of a paper published in European Radiology. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Magnetic resonance imaging; Mouth neoplasms; Lymphatic metastases |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Inst of Biomed & Clin Sciences (LIBACS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Jul 2018 13:13 |
Last Modified: | 05 Jun 2019 00:43 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/s00330-018-5524-x |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:132953 |