Interpretation of update to the response assessment in neuro-oncology criteria for high- and low-grade gliomas in adults (RANO 2.0) from the perspective of imaging medicine
|更新时间:2025-12-15
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Interpretation of update to the response assessment in neuro-oncology criteria for high- and low-grade gliomas in adults (RANO 2.0) from the perspective of imaging medicine
Interpretation of update to the response assessment in neuro-oncology criteria for high- and low-grade gliomas in adults (RANO 2.0) from the perspective of imaging medicine
The response assessment in neuro-oncology (RANO) criteria are widely used in clinical trials and practice. However
in the process of using RANO standards
various criteria of RANO-high grade glioma (RANO-HGG)
modified RANO (mRANO)and immunotherapy RANO (iRANO) lead to differences in the response assessment
and also increase the uncertainty of which set of criteria to be used for the clinical assessment. In September 2023
the RANO working group developed a new version of the update to the response assessment in neuro-oncology criteria for all gliomas in adults (RANO 2.0)
in which
magnetic resonance imaging (MRI) is the main examination method for the assessment of treatment response of neuro-oncology
and with the diversification of neuro-oncology treatment methods
the imaging manifestations of neuro-oncology treatment response are becoming more complex than before. This article introduced the core imaging contents with the detailed illustration of the technical and diagnostic key points in the MRI evaluation in the RANO 2.0
and aimed to provide help for the rational application of imaging medicine in the assessment of treatment response of adult gliomas.
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Related Author
HUANG Xing
LIANG Yan
YI Chuang
WANG Yan
REN Junjie
LI Weilan
BA Zhufei
LIU Tao
Related Institution
Department of Radiology, Jilin Provincial People's Hospital
Department of Medical Imaging, North China University of Science and Technology Affiliated Hospital
Department of Cardiothoracic Surgery, KaiLuan General Hospital
Department of Radiology, Cancer Hospital of Dalian University of Technology, Liaoning Cancer Hospital & Institute
Department of Computing Science and Artificial Intelligence, Liaoning Normal University