Radiomics from magnetic resonance imaging may be used to predict the progression of white matter hyperintensities and identify associated risk factors.
Objective: The progression of white matter hyperintensities (WMH) varies considerably in adults. In this study, we aimed to predict the progression and related risk factors of WMH based on the radiomics of whole-brain white matter (WBWM).Methods: A retrospective analysis was conducted on 141 patient...
| Publicado en: | European Radiology Vol. 30; no. 6; pp. 3046 - 3059 |
|---|---|
| Autores principales: | , , , , |
| Formato: | diagnostic images pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2020
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=143397301&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 143397301 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Jun2020 vid: 30 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 143397301 143397301 NLM32086580 143397301 10.1007/s00330-020-06676-1 NLM32086580 143397301 ppf: 3046 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Radiomics from magnetic resonance imaging may be used to predict the progression of white matter hyperintensities and identify associated risk factors. aug: au: Shu, Zhenyu Xu, Yuyun Shao, Yuan Pang, Peipei Gong, Xiangyang affil: Department of Radiology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China sug: subj: Pathologic Processes Diagnosis Brain Pathology Magnetic Resonance Imaging Methods Risk Factors Disease Progression Predictive Value of Tests Aged Middle Age Female Male Retrospective Design Scales Human Funding Source Aged: 65+ years Middle Aged: 45-64 years Female Male ab: Objective: The progression of white matter hyperintensities (WMH) varies considerably in adults. In this study, we aimed to predict the progression and related risk factors of WMH based on the radiomics of whole-brain white matter (WBWM).Methods: A retrospective analysis was conducted on 141 patients with WMH who underwent two consecutive brain magnetic resonance (MR) imaging sessions from March 2014 to May 2018. The WBWM was segmented to extract and score the radiomics features at baseline. Follow-up images were evaluated using the modified Fazekas scale, with progression indicated by scores ≥ 1. Patients were divided into progressive (n = 65) and non-progressive (n = 76) groups. The progressive group was subdivided into any WMH (AWMH), periventricular WMH (PWMH), and deep WMH (DWMH). Independent risk factors were identified using logistic regression.Results: The area under the curve (AUC) values for the radiomics signatures of the training sets were 0.758, 0.749, and 0.775 for AWMH, PWMH, and DWMH, respectively. The AUC values of the validation set were 0.714, 0.697, and 0.717, respectively. Age and hyperlipidemia were independent predictors of progression for AWMH. Age and body mass index (BMI) were independent predictors of progression for DWMH, while hyperlipidemia was an independent predictor of progression for PWMH. After combining clinical factors and radiomics signatures, the AUC values were 0.848, 0.863, and 0.861, respectively, for the training set, and 0.824, 0.818, and 0.833, respectively, for the validation set.Conclusions: MRI-based radiomics of WBWM, along with specific risk factors, may allow physicians to predict the progression of WMH.Key Points: • Radiomics features detected by magnetic resonance imaging may be used to predict the progression of white matter hyperintensities. • Radiomics may be used to identify risk factors associated with the progression of white matter hyperintensities. • Radiomics may serve as non-invasive biomarkers to monitor white matter status. pubtype: Academic Journal doctype: diagnostic images pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|