Evidence mapPaperPMID 41353704Full record

ArticlePain and therapy2026

Prediction of Postherpetic Neuralgia in Patients with Acute and Subacute Herpetic Neuralgia Using Structural Magnetic Resonance Imaging: A Retrospective Study.

Dan Wu, Bo Peng, Yingjie Hua, Wujun Geng, Bing Huang, Siyu Lu, Junlin Chen, Keyi He, Yuxi Wang, Qiaoyin Rao and 5 more

Abstract read
In one paragraph

Article in Pain and therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Dan Wu *Zhejiang Key Laboratory of Imaging and Interventional Medicine, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, People's Republic of China.
Bo Peng *Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, People's Republic of China.
Yingjie HuaZhejiang Key Laboratory of Imaging and Interventional Medicine, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, People's Republic of China.
Wujun GengDepartment of Pain, The First Affiliated Hospital of Wenzhou Medical University, Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision Brain Health), Wenzhou Medical University, Wenzhou, People's Republic of China.
Bing HuangDepartment of Pain Medicine, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China.
Siyu LuZhejiang Key Laboratory of Imaging and Interventional Medicine, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, People's Republic of China.
Junlin ChenZhejiang Key Laboratory of Imaging and Interventional Medicine, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, People's Republic of China.
Keyi HeSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, People's Republic of China.
Yuxi WangSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, People's Republic of China.
Qiaoyin RaoZhejiang Key Laboratory of Imaging and Interventional Medicine, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, People's Republic of China.
Zubo JiangDepartment of Pain, Qingdao Municipal Hospital, Qingdao, Shandong, People's Republic of China.
Chuanguang WangZhejiang Key Laboratory of Imaging and Interventional Medicine, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, People's Republic of China.
Yakang DaiSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, People's Republic of China.
Jiansong JiZhejiang Key Laboratory of Imaging and Interventional Medicine, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, People's Republic of China. jjstcty@wmu.edu.cn.
Zhongwei ZhaoZhejiang Key Laboratory of Imaging and Interventional Medicine, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, People's Republic of China. 21617461@qq.com.ORCID http://orcid.org/0009-0004-8640-4600

Funding

Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences and Peking Union Medical College 2024ZL1291Lishui Science and Technology Plan Project 2022SJZC020Medical Science and Technology Project of Zhejiang Province 2024KY564
6 · The paper itself

Abstract

introductionThis study integrated structural magnetic resonance imaging (sMRI) of the brain with clinical characteristics to identify the "vulnerable brain regions" and risk factors associated with the development of postherpetic neuralgia (PHN) in patients with acute and subacute herpetic neuralgia. Furthermore, the study explored the combined predictive performance of these neuroimaging and clinical indicators.

methodsFrom February 2023 to January 2025, a total of 214 hospitalized patients with acute and subacute herpetic neuralgia were enrolled. Follow-up was conducted via telephone or outpatient visits, revealing that 116 patients (54.98%) developed PHN, while 95 did not. Clinical data and magnetic resonance imaging (MRI) data were collected for all participants. T1-weighted structural MRI images underwent preprocessing procedures including N4 bias field correction, skull stripping, brain tissue segmentation, and parcellation. Gray matter volume (GMV) values were extracted from 90 predefined regions of interest (ROIs) for further analysis. Group differences were assessed using two-tailed Student's t-tests or the non-parametric Kruskal-Wallis H test, as appropriate. Features showing significant intergroup differences in GMV were integrated with clinical variables to train machine learning models, and receiver-operating characteristic (ROC) curve analysis was employed to evaluate their predictive performance for PHN.

resultsSignificant differences were observed between the PHN and Non-PHN groups in several clinical variables, including age, body mass index (BMI), age ≥ 50 years, disease duration, admission Numeric Rating Scale (NRS) score, hospitalization during the acute phase (< 1 month), involved dermatome, and total Charlson Comorbidity Index (CCI) score (all P < 0.05). In terms of neuroimaging findings, GMV differed significantly between the two groups in the following brain regions: the left inferior frontal gyrus (triangular part), fusiform gyrus, Heschl's gyrus, and superior temporal gyrus; the right orbital part of the inferior frontal gyrus, lentiform nucleus (globus pallidus); and the bilateral cingulate gyrus, hippocampus, and caudate nucleus (P < 0.05, corrected for multiple comparisons using the false discovery rate [FDR] method). The combined model integrating T1-weighted MRI features and clinical characteristics achieved an area under the ROC curve (AUC) of 0.748 (95% CI 0.677-0.816) for predicting the occurrence of PHN.

conclusionThis study is the first to innovatively integrate sMRI to identify "vulnerable brain regions" associated with the transition from acute and subacute herpetic neuralgia to PHN. By combining GMV metrics with clinical features, the study provides a novel approach for predicting the development of PHN.

Indexed as

Herpes zoster (HZ)NeuroimagingPostherpetic neuralgia (PHN)Receiver operating characteristic(ROC)Voxel-based morphometry (VBM)

Identifiers

PMID41353704
PMCPMC12804461

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.