AUTHOR=Cao Xueqin , Wen Donglin , Yu Shangchen , Zheng Hua , Wu Gang , Zhang Xianwei 

TITLE=MRI-based radiomics features uncover the micro-change of dorsal root ganglia lesion for patients with post-herpetic neuralgia

JOURNAL=Frontiers in Neurology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2023.1257648

DOI=10.3389/fneur.2023.1257648

ISSN=1664-2295

ABSTRACT=Objective: To identify and validate MRI-based radiomic signatures of dorsal root ganglia (DRG) lesions in post-herpetic neuralgia (PHN). Method: This prospective diagnostic study was conducted between January 2021 and February 2022. Lesioned DRG in patients with PHN and normal DRG in age-, sex-, height-, and weight-matched healthy controls were selected for assessment and divided into two groups (8:2) randomly: training and testing sets. The least absolute shrinkage and selection operator algorithm was employed to generate feature signatures and construct a model, followed by the assessment of model efficacy using the area under the curve (AUC) of the receiver operating characteristic (ROC), as well as sensitivity and specificity metrics. Results: The present investigation involved 30 patients diagnosed with postherpetic neuralgia (PHN), consisting of 18 males and 12 females (mean age 60.70 ± 10.18 years), as well as 30 healthy controls, comprising 18 males and 12 females (mean age 58.13 ± 10.54 years). A total of 98 DRG were randomly divided into two groups (8:2), namely a training set (n=78) and a testing set (n=20). Five radiomic features were chosen to construct the models. In the training dataset, the area under the curve (AUC) was 0.847, while the sensitivity and specificity were 71.79% and 97.44%, respectively. In the test dataset, the AUC was 0.87, and the sensitivity and specificity were 80.00% and 100.00%, respectively. Conclusions: An MRI-based radiomic signatures model has the capacity to uncover the micro-change of damaged DRG in individuals afflicted with postherpetic neuralgia.