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Risk prediction model of radiation encephalopathy based on MRI white matter high signal load
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H. Ge   , Y. Zhang , G. Tong |
| Department of Radiation Oncology, The Affiliated Hospital, Medical University, China , tongguoqin@hospital.edu.cn |
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Abstract: (17 Views) |
Background: A prediction model of Radiation Encephalopathy (RE) based on White Matter Hyperintensity (WMH) load of Magnetic Resonance Imaging (MRI) was constructed. Materials and Methods: One hundred and fifty-three patients with head and neck malignant tumor (nasopharyngeal carcinoma, intracranial tumor) who received radiotherapy were retrospectively included and divided into RE group (n=17) and non-RE group (n=136). E(Apolipoprotein E (APOE)ε4 gene expression was detected, and radiotherapy dose, Fazekas score, V30 and maximum dose (Dmax) were collected. Logistic regression was used to screen the risk factors, and ROC curve was used to evaluate the predictive efficacy. Results: APOE ε4 carriers, radiotherapy dose, Fazekas score, V30 and Dmax were independent risk factors for RE (P<0.05). The area under the curve (AUC) of the joint prediction model is 0.921, and the prediction efficiency is better than that of a single index. Conclusion: The model based on MRI-WMH load combined with radiation dosimetry parameters has high prediction accuracy, which can screen the high-risk population of RE at an early stage and provide reference for clinical individualized radiotherapy. |
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| Keywords: Magnetic resonance imaging, white matter hyperintensities, radiation injuries, apolipoprotein e4, dose-response relationship, radiation, head and neck neoplasms. |
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Full-Text [PDF 879 kb]
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Type of Study: Original Research |
Subject:
Radiation Biology
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