SynthesisAging clinical and experimental research2023
Diagnostic performance of MRI radiomics for classification of Alzheimer's disease, mild cognitive impairment, and normal subjects: a systematic review and meta-analysis.
Synthesis in Aging clinical and experimental research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 4 of them syntheses that pooled it.
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Who cites it
21 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Pre-operative MRI-Based Radiomics for Predicting Telomerase Reverse Transcriptase Promoter Mutation Status in Glioma Patients: A Systematic Review and Meta-analysis.Neurosurgical review · 2026Pooled it
- Pooled it
- Convolutional neural network models of structural MRI for discriminating categories of cognitive impairment: a systematic review and meta-analysis.BMC neurology · 2025Pooled it
- Prediction of the treatment response and local failure of patients with brain metastasis treated with stereotactic radiosurgery using machine learning: A systematic review and meta-analysis.Neurosurgical review · 2024Pooled it
- Towards a Multidimensional Model of Neurocognitive Disorders (MOND Model): Integrating Evidence from a Critical Review into a Model for Future Research.Journal of personalized medicine · 2026Review
- Screening for Alzheimer's disease in the community using an AI-driven screening platform: design of the PREDICTOM study.The journal of prevention of Alzheimer's disease · 2026Article
- Olfactory radiomics signatures link pTau217 to cognitive impairment in probable Alzheimer's disease: a multi-cohort machine learning study.Alzheimer's research & therapy · 2026Article
- Automatic identification of different stage of Alzheimer's disease using multimodal MRI and artificial intelligence.BMC medical imaging · 2026Article
- PyCaret machine learning library with three preprocessing steps after eLORETA source estimation predicts Alzheimer's disease.Neuroimage. Reports · 2026Article
- Imaging Diagnosis of Mild Cognitive Impairment: A Bibliometric Analysis (1999-2024).Brain and behavior · 2025Article
- Article
- Review
- Different Neuroimaging Measurement Techniques for the Cerebellum in Alzheimer's Disease: VolBrain-Horos Comparison.Current medical imaging · 2025Article
- Integrating artificial intelligence with Gamma Knife radiosurgery in treating meningiomas and schwannomas: a review.Neurosurgical review · 2025Review
- Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson's disease patients.BMC medical imaging · 2025Article
- Developments in MRI radiomics research for vascular cognitive impairment.Insights into imaging · 2025Review
- Peripheral blood heat shock protein 27 correlates with information processing speed and executive function, potentially serving as a marker for mild cognitive impairment in patients with type 2 diabetes mellitus.Diabetology & metabolic syndrome · 2025Article
- Heat shock protein 90α may serve as a biomarker for mild cognitive impairment in type 2 diabetes mellitus patients without diabetic nephropathy.Frontiers in immunology · 2025Article
- Research progress on brain network imaging biomarkers of subjective cognitive decline.Frontiers in neuroscience · 2025Review
- Disparities in the diagnostic efficacy of radiomics models in predicting various degrees of cognitive impairment in patients with cerebral small vessel disease.BMC medical imaging · 2024Article
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlzheimer's disease (AD) is a debilitating neurodegenerative disease. Early diagnosis of AD and its precursor, mild cognitive impairment (MCI), is crucial for timely intervention and management. Radiomics involves extracting quantitative features from medical images and analyzing them using advanced computational algorithms. These characteristics have the potential to serve as biomarkers for disease classification, treatment response prediction, and patient stratification. Of note, Magnetic resonance imaging (MRI) radiomics showed a promising result for diagnosing and classifying AD, and MCI from normal subjects. Thus, we aimed to systematically evaluate the diagnostic performance of the MRI radiomics for this task. METHODS AND MATERIALS: A comprehensive search of the current literature was conducted using relevant keywords in PubMed/MEDLINE, Embase, Scopus, and Web of Science databases from inception to August 5, 2023. Original studies discussing the diagnostic performance of MRI radiomics for the classification of AD, MCI, and normal subjects were included. Method quality was evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and the Radiomics Quality Score (RQS) tools.
resultsWe identified 13 studies that met the inclusion criteria, involving a total of 5448 participants. The overall quality of the included studies was moderate to high. The pooled sensitivity and specificity of MRI radiomics for differentiating AD from normal subjects were 0.92 (95% CI [0.85; 0.96]) and 0.91 (95% CI [0.85; 0.95]), respectively. The pooled sensitivity and specificity of MRI radiomics for differentiating MCI from normal subjects were 0.74 (95% CI [0.60; 0.85]) and 0.79 (95% CI [0.70; 0.86]), respectively. Also, the pooled sensitivity and specificity of MRI radiomics for differentiating AD from MCI were 0.73 (95% CI [0.64; 0.80]) and 0.79 (95% CI [0.64; 0.90]), respectively.
conclusionMRI radiomics has promising diagnostic performance in differentiating AD, MCI, and normal subjects. It can potentially serve as a non-invasive and reliable tool for early diagnosis and classification of AD and MCI.
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Registered trials
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 OpenQuestion graph.