首页|A Prediction Model for Detecting Dysthyroid Optic Neuropathy Based on Clinical Factors and Imaging Markers of the Optic Nerve and Cerebrospinal Fluid in the Optic Nerve Sheath

A Prediction Model for Detecting Dysthyroid Optic Neuropathy Based on Clinical Factors and Imaging Markers of the Optic Nerve and Cerebrospinal Fluid in the Optic Nerve Sheath

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Objective:This study aimed to develop and test a model for predicting dysthyroid optic neuropathy(DON)based on clinical factors and imaging markers of the optic nerve and cerebrospinal fluid(CSF)in the optic nerve sheath.Methods:This retrospective study included patients with thyroid-associated ophthalmopathy(TAO)without DON and patients with TAO accompanied by DON at our hospital.The imaging markers of the optic nerve and CSF in the optic nerve sheath were measured on the water-fat images of each patient and,together with clinical factors,were screened by Least absolute shrinkage and selection operator.Subsequently,we constructed a prediction model using multivariate logistic regression.The accuracy of the model was verified using receiver operating characteristic curve analysis.Results:In total,80 orbits from 44 DON patients and 90 orbits from 45 TAO patients were included in our study.Two variables(optic nerve subarachnoid space and the volume of the CSF in the optic nerve sheath)were found to be independent predictive factors and were included in the prediction model.In the development cohort,the mean area under the curve(AUC)was 0.994,with a sensitivity of 0.944,specificity of 0.967,and accuracy of 0.901.Moreover,in the validation cohort,the AUC was 0.960,the sensitivity was 0.889,the specificity was 0.893,and the accuracy was 0.890.Conclusions:A combined model was developed using imaging data of the optic nerve and CSF in the optic nerve sheath,serving as a noninvasive potential tool to predict DON.

dysthyroid optic neuropathymagnetic resonance imagingwater-fat sequenceoptic nerveoptic nerve subarachnoid space

Hong-yu WU、Ban LUO、Gang YUAN、Qiu-xia WANG、Ping LIU、Ya-li ZHAO、Lin-han ZHAI、Wen-zhi LV、Jing ZHANG、Lang CHEN

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Department of Radiology,Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430030,China

Department of Ophthalmology,Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430030,China

Department of Endocrinology,Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430030,China

Department of Medical Imaging,Guangdong Second Provincial General Hospital,Guangzhou 510317,China

Department of Radiology,Sir Run Run Shaw Hospital Affiliated with the School of Medicine of Zhejiang University,Hangzhou 310000,China

Department of Artificial Intelligence,Julei Technology Company,Wuhan 430030,China

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National Natural Science Foundation of China

81771793

2024

10.1007/s11596-024-2890-2

当代医学科学(英文)
华中科技大学同济医学院

当代医学科学(英文)

影响因子：0.748
ISSN：2096-5230
年,卷(期)：2024.44(4)