ArticleEuropean radiology2020
Radiomics from magnetic resonance imaging may be used to predict the progression of white matter hyperintensities and identify associated risk factors.
Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 32 citations in OpenAlex.
- Perivascular fat attenuation index at internal carotid artery stenosis: a biomarker of perivascular adipose tissue (PVAT) inflammation.Japanese journal of radiology · 2026Article
- Article
- Letter to the Editor Regarding: Quantitative Analysis of White Matter Hyperintensities as a Predictor of 1‑Year Risk for Ischemic Stroke Recurrence.Neurology and therapy · 2025Article
- Prediction of white matter hyperintensities evolution one-year post-stroke from a single-point brain MRI and stroke lesions information.Scientific reports · 2025Article
- Association between Life's Essential 8 and Cerebral Small Vessel Disease.Stroke and vascular neurology · 2024Article
- Radiomics with structural magnetic resonance imaging, surface morphometry features, neurology scales, and clinical metrics to evaluate the neurodevelopment of preschool children with corrected tetralogy of Fallot.Translational pediatrics · 2024Article
- Perivascular fat attenuation index value and plaque volume increased in non-target lesions of coronary arteries after stenting.European radiology · 2024Article
- Association of Life's essential 8 score with the risk of all-cause mortality and cardio-cerebrovascular mortality in patients with stroke.BMC cardiovascular disorders · 2024Article
- Associations between cerebral blood flow and progression of white matter hyperintensities.Frontiers in neuroimaging · 2024Article
- Is coronary artery calcium an independent risk factor for white matter hyperintensity?BMC neurology · 2023Article
- Predicting mild cognitive impairment progression to Alzheimer's disease based on machine learning analysis of cortical morphological features.Aging clinical and experimental research · 2023Article
- Predicting progression of white matter hyperintensity using coronary artery calcium score based on coronary CT angiography-feasibility and accuracy.Frontiers in aging neuroscience · 2023Article
- Hybrid model of CT-fractional flow reserve, pericoronary fat attenuation index and radiomics for predicting the progression of WMH: a dual-center pilot study.Frontiers in cardiovascular medicine · 2023Article
- Differential associations of lipoprotein(a) level with cerebral large artery and small vessel diseases.Stroke and vascular neurology · 2022Article
- The use of variable delay multipulse chemical exchange saturation transfer for separately assessing different CEST pools in the human brain at 7T.Magnetic resonance in medicine · 2022Article
- Detection of Microstructural Medial Prefrontal Cortex Changes Using Magnetic Resonance Imaging Texture Analysis in a Post-Traumatic Stress Disorder Rat Model.Frontiers in psychiatry · 2022Article
- Brain MRI radiomics analysis may predict poor psychomotor outcome in preterm neonates.European radiology · 2021Article
- Role of White Matter Hyperintensities and Related Risk Factors in Vascular Cognitive Impairment: A Review.Biomolecules · 2021Review
- Prediction of burden and management of renal calculi from whole kidney radiomics: a multicenter study.Abdominal radiology (New York) · 2021Article
- Comparing the Performance of Two Radiomic Models to Predict Progression and Progression Speed of White Matter Hyperintensities.Frontiers in neuroinformatics · 2021Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveThe 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).
methodsA 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.
resultsThe 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.
conclusionsMRI-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.
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