SynthesisTranslational psychiatry2020
Translating research findings into clinical practice: a systematic and critical review of neuroimaging-based clinical tools for brain disorders.
Synthesis in Translational psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
31 citing papers in PubMed, 2 syntheses or guidelines pooled it, 46 citations in OpenAlex.
- A systematic review of molecular signaling in the muscle-brain-gut axis: exercise-induced myokines and microbial metabolites as key mediators.Molecular biology reports · 2026Pooled it
- Technical and clinical validation of commercial automated volumetric MRI tools for dementia diagnosis-a systematic review.Neuroradiology · 2021Pooled it
- Shared genetic architecture of cortical morphology and psychiatric disorders: insights from a cross-trait analyses across 180 cortical regions.medRxiv : the preprint server for health sciences · 2026Article
- Vertexwise Cortical Deviation Mapping (VCDM): A precision approach to cortical thickness assessment in non-affective psychosis.Brain imaging and behavior · 2026Article
- The patterns of relapse and abstinence: using machine learning to identify a multidimensional signature of long-term outcome after inpatient alcohol withdrawal treatment.Frontiers in psychiatry · 2026Article
- A generalizable normative deep autoencoder for brain morphological anomaly detection: application to the multi-site StratiBip dataset on bipolar disorder in an external validation framework.Artificial intelligence in medicine · 2025Article
- Neurofind: using deep learning to make individualised inferences in brain-based disorders.Translational psychiatry · 2025Article
- Exploring Schizophrenia Classification Through Multimodal MRI and Deep Graph Neural Networks: Unveiling Brain Region-Specific Weight Discrepancies and Their Association With Cell-Type Specific Transcriptomic Features.Schizophrenia bulletin · 2024Article
- A generalizable normative deep autoencoder for brain morphological anomaly detection: application to the multi-site StratiBip dataset on bipolar disorder in an external validation framework.bioRxiv : the preprint server for biology · 2024Article
- Normal cohorts in automated brain atrophy estimation: how many healthy subjects to include?European radiology · 2024Article
- Comparison of Inter-Method Agreement and Reliability for Automatic Brain Volumetry Using Three Different Clinically Available Software Packages.Medicina (Kaunas, Lithuania) · 2024Article
- GPT-based normative models of brain sMRI correlate with dimensional psychopathology.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- ENIGMA's simple seven: Recommendations to enhance the reproducibility of resting-state fMRI in traumatic brain injury.NeuroImage. Clinical · 2024Review
- aXonica: A support package for MRI based Neuroimaging.Biotechnology notes (Amsterdam, Netherlands) · 2024Article
- Reliability of automated brain volumetric analysis: A test by comparing NeuroQuant and volBrain software.Brain and behavior · 2023Article
- Brain Anatomy-Guided MRI Analysis for Assessing Clinical Progression of Cognitive Impairment with Structural MRI.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
- A Systematic Review of the Barriers to the Implementation of Artificial Intelligence in Healthcare.Cureus · 2023Review
- Acquired Pedophilia: international Delphi-method-based consensus guidelines.Translational psychiatry · 2023Review
- Exploring Genetic and Neural Risk of Specific Reading Disability within a Nuclear Twin Family Case Study: A Translational Clinical Application.Journal of personalized medicine · 2023Article
- Classification and prediction of cognitive performance differences in older age based on brain network patterns using a machine learning approach.Network neuroscience (Cambridge, Mass.) · 2023Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 2 countries.
Funding
Abstract
A pivotal aim of psychiatric and neurological research is to promote the translation of the findings into clinical practice to improve diagnostic and prognostic assessment of individual patients. Structural neuroimaging holds much promise, with neuroanatomical measures accounting for up to 40% of the variance in clinical outcome. Building on these findings, a number of imaging-based clinical tools have been developed to make diagnostic and prognostic inferences about individual patients from their structural Magnetic Resonance Imaging scans. This systematic review describes and compares the technical characteristics of the available tools, with the aim to assess their translational potential into real-world clinical settings. The results reveal that a total of eight tools. All of these were specifically developed for neurological disorders, and as such are not suitable for application to psychiatric disorders. Furthermore, most of the tools were trained and validated in a single dataset, which can result in poor generalizability, or using a small number of individuals, which can cause overoptimistic results. In addition, all of the tools rely on two strategies to detect brain abnormalities in single individuals, one based on univariate comparison, and the other based on multivariate machine-learning algorithms. We discuss current barriers to the adoption of these tools in clinical practice and propose a checklist of pivotal characteristics that should be included in an "ideal" neuroimaging-based clinical tool for brain disorders.
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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.