Diagnostic value of six MRI features for central neurocytoma
- 30.04.2018
- Head and Neck
Erschienen in:
- Verfasst von
- Xiaodan Li
- Liuji Guo
- Sen Sheng
- Yikai Xu
- Lichao Ma
- Xiang Xiao
- Zhiguang Si
- Yanping Chen
- Yuankui Wu
- Erschienen in
- European Radiology | Ausgabe 10/2018
Abstract
Objectives
To increase our understanding of the imaging features of central neurocytoma (CN) and improve the preoperative MRI diagnosis accuracy.
Methods
Preoperative MR images of 30 CNs and another 68 intraventricular non-CN tumours were analysed by one experienced neuroradiologist retrospectively to identify previously reported features and new features of CN. Six blinded radiologists independently reviewed all these MRI images, and scored all characteristic features on a five-point scale. Diagnostic value was assessed by the area under the receiver operating characteristic curve (AUC); sensitivity, specificity and accuracy were also calculated.
Results
In addition to the ‘scalloping’ sign, ‘broad-based attachment’ sign and ‘soap-bubble’ sign, three new MRI features of CN were identified, including the ‘peripheral cysts’ sign, ‘fluid-fluid level’ sign and the ‘gemstone’ sign. The scalloping sign showed the highest AUC value (0.82), followed by the peripheral cysts sign (0.75) and broad-based attachment sign (0.75). The scalloping sign exhibited the highest specificity (82%), followed by the fluid-fluid level sign (79%) and gemstone (78%) sign. The broad-based attachment sign (85%) was the most sensitive feature, followed by the soap-bubble sign (84%) and peripheral cysts sign (77%).
Conclusion
There are six characteristic MRI features that help to improve the preoperative diagnostic accuracy of CN.
Key Points
• This study is the largest magnetic resonance imaging (MRI) cohort on central neurocytoma (CN).
• Three new features helpful for the diagnosis of CN were reported.
• Diagnostic value of six MRI features of CN was preliminarily determined.
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- Titel
- Diagnostic value of six MRI features for central neurocytoma
- Verfasst von
-
Xiaodan Li
Liuji Guo
Sen Sheng
Yikai Xu
Lichao Ma
Xiang Xiao
Zhiguang Si
Yanping Chen
Yuankui Wu
- Publikationsdatum
- 30.04.2018
- Verlag
- Springer Berlin Heidelberg
- Erschienen in
-
European Radiology / Ausgabe 10/2018
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084 - DOI
- https://doi.org/10.1007/s00330-018-5442-y
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