BACKGROUND: The aim of this study was to investigate the diagnostic value of ML techniques based on sMRI or/and fMRI for ADHD.
METHODS: We conducted a comprehensive search (from database creation date to March 2024) for relevant English articles on sMRI or/and fMRI-based ML techniques for diagnosing ADHD. The pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), summary receiver operating characteristic (SROC) curve and area under the curve (AUC) were calculated to assess the diagnostic value of sMRI or/and fMRI-based ML techniques. The I2 test was used to assess heterogeneity and the source of heterogeneity was investigated by performing a meta-regression analysis. Publication bias was assessed using the Deeks funnel plot asymmetry test.
RESULTS: Forty-three studies were included in the systematic review, 27 of which were included in our meta-analysis. The pooled sensitivity and specificity of sMRI or/and fMRI-based ML techniques for the diagnosis of ADHD were 0.74 (95 % CI 0.65-0.81) and 0.75 (95 % CI 0.67-0.81), respectively. SROC curve showed that AUC was 0.81 (95 % CI 0.77-0.84). Based on these findings, the sMRI or/and fMRI-based ML techniques have relatively good diagnostic value for ADHD.
CONCLUSIONS: Our meta-analysis specifically focused on ML techniques based on sMRI or/and fMRI studies. Since EEG-based ML techniques are also used for diagnosing ADHD, further systematic analyses are necessary to explore ML methods based on multimodal medical data.
CONCLUSIONS: sMRI or/and fMRI-based ML technique is a promising objective diagnostic method for ADHD.

A primary goal of neuroscience is to understand the relationship between the brain and behavior. While magnetic resonance imaging (MRI) examines brain structure and function under controlled conditions, digital phenotyping via portable automatic devices (PAD) quantifies behavior in real-world settings. Combining these two technologies may bridge the gap between brain imaging, physiology, and real-time behavior, enhancing the generalizability of laboratory and clinical findings. However, the use of MRI and data from PADs outside the MRI scanner remains underexplored. Herein, we present a Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic literature review that identifies and analyzes the current state of research on the integration of brain MRI and PADs. PubMed and Scopus were automatically searched using keywords covering various MRI techniques and PADs. Abstracts were screened to only include articles that collected MRI brain data and PAD data outside the laboratory environment. Full-text screening was then conducted to ensure included articles combined quantitative data from MRI with data from PADs, yielding 94 selected papers for a total of N = 14,778 subjects. Results were reported as cross-frequency tables between brain imaging and behavior sampling methods and patterns were identified through network analysis. Furthermore, brain maps reported in the studies were synthesized according to the measurement modalities that were used. Results demonstrate the feasibility of integrating MRI and PADs across various study designs, patient and control populations, and age groups. The majority of published literature combines functional, T1-weighted, and diffusion weighted MRI with physical activity sensors, ecological momentary assessment via PADs, and sleep. The literature further highlights specific brain regions frequently correlated with distinct MRI-PAD combinations. These combinations enable in-depth studies on how physiology, brain function and behavior influence each other. Our review highlights the potential for constructing brain-behavior models that extend beyond the scanner and into real-world contexts.

Vascular cognitive impairment (VCI) is the initial stage of vascular dementia (VaD). Early diagnosis and treatment of VCI are crucial to prevent the progression of VaD. In order to gain a better understanding of VCI, this study aimed to investigate the use of advanced imaging techniques such as structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI). These techniques allow researchers to observe the structural and functional changes in the brain that are associated with VCI. Functional magnetic resonance imaging (fMRI) and sMRI techniques have been widely used in studies focusing on gray matter, brain networks, and functional abnormalities during rest. By searching and summarizing recent literature, this study has provided valuable evidence on the use of advanced imaging techniques in understanding and treating VCI. The findings from this study can aid in the development of early intervention strategies for patients with VCI, potentially slowing down or even halting the progression of VCI to full-blown VaD.

UNASSIGNED: This review aims to the existing structural neuroimaging literature in Parkinson disease presenting with freezing of gait. The summary of this article provides an opportunity for a better understanding of the structural findings of freezing of gait in Parkinson disease based on MRI.
UNASSIGNED: This systematic review of literature follows the procedures as described by the guideline of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).
UNASSIGNED: Initial searches yielded 545 documents. After exclusions, 11 articles were included into our study. Current findings of structural MRI on freezing of gait in Parkinson disease are associated with structural damage between sensorimotor-related cortical grey matter structures and thalamus, but not cerebellum and smaller systems, as well as extensive injuries on white matter connecting between those structures.
UNASSIGNED: Current findings of structural MRI on freezing of gait in Parkinson disease are associated with structural damage between sensorimotor-related cortical grey matter structures and thalamus, but not cerebellum and smaller systems, as well as extensive injuries on white matter connecting between those structures.

To elucidate the relationship between the course of bipolar disorder (BD) and structural brain changes across the life span, we conducted a systematic review of longitudinal imaging studies in adolescent and adult BD patients.
Eleven studies with 329 BD patients and 277 controls met our PICOS criteria (participants, intervention, comparison, outcome and study design): BD diagnosis based on DSM criteria, natural course of disease, comparison of grey matter changes in BD individuals over ≥1-year interval between scans.
The selected studies yielded heterogeneous findings, partly due to varying patient characteristics, data acquisition and statistical models. Mood episodes were associated with greater grey matter loss in frontal brain regions over time. Brain volume decreased or remained stable in adolescent patients, whereas it increased in healthy adolescents. Adult BD patients showed increased cortical thinning and brain structural decline. In particular, disease onset in adolescence was associated with amygdala volume reduction, which was not reported in adult BD.
The evidence collected suggests that the progression of BD impairs adolescent brain development and accelerates structural brain decline across the lifespan. Age-specific changes in amygdala volume in adolescent BD suggest that reduced amygdala volume is a correlate of early onset BD. Clarifying the role of BD in brain development across the lifespan promises a deeper understanding of the progression of BD patients through different developmental episodes.

This review article summarizes the recent advances in the diagnostic studies of autism spectrum disorders (ASDs) considering some of the most influential research articles from the last two decades. ASD is a heterogeneous neurodevelopmental disorder characterized by abnormalities in social interaction, communication, and behavioral patterns as well as some unique strengths and differences. The current diagnosis systems are based on autism diagnostic observation schedule (ADOS) or autism diagnostic interview-revised (ADI-R), but biological markers are also important for an effective diagnosis of ASDs. The amalgamation of neuroimaging techniques, such as structural and functional magnetic resonance imaging (sMRI and fMRI), with machine-learning and deep-learning approaches helps throw new light on typical biological markers of ASDs at the early stage of life. To assess the performance of a deep neural network, we develop a light-weighted CNN model for ASD classification. The overall accuracy, precision, and F1-score of the proposed model are 99.92%, 99.93% and 99.92%, respectively. All the neuroimaging studies we have reviewed can be divided into 3 categories, viz. thickness, volume and functional connectivity-based studies. We conclude with a discussion of the major findings of considered studies and promising directions for future research in this field.

BACKGROUND: Catatonia is a complex psychomotor disorder characterized by motor, affective, and behavioral symptoms. Despite being known for almost 150 years, its pathomechanisms are still largely unknown.
METHODS: A systematic research on PubMed, Web of Science, and Scopus was conducted to identify neuroimaging studies conducted on group or single individuals with catatonia. Overall, 33 studies employing structural magnetic resonance imaging (sMRI, n = 11), functional magnetic resonance imaging (fMRI, n = 10), sMRI and fMRI (n = 2), functional near-infrared spectroscopy (fNIRS, n = 1), single positron emission computer tomography (SPECT, n = 4), positron emission tomography (PET, n = 4), and magnetic resonance spectroscopy (MRS, n = 1), and 171 case reports were retrieved.
RESULTS: Observational sMRI studies showed numerous brain changes in catatonia, including diffuse atrophy and signal hyperintensities, while case-control studies reported alterations in fronto-parietal and limbic regions, the thalamus, and the striatum. Task-based and resting-state fMRI studies found abnormalities located primarily in the orbitofrontal, medial prefrontal, motor cortices, cerebellum, and brainstem. Lastly, metabolic and perfusion changes were observed in the basal ganglia, prefrontal, and motor areas. Most of the case-report studies described widespread white matter lesions and frontal, temporal, or basal ganglia hypoperfusion.
CONCLUSIONS: Catatonia is characterized by structural, functional, perfusion, and metabolic cortico-subcortical abnormalities. However, the majority of studies and case reports included in this systematic review are affected by considerable heterogeneity, both in terms of populations and neuroimaging techniques, which calls for a cautious interpretation. Further elucidation, through future neuroimaging research, could have great potential to improve the description of the neural motor and psychomotor mechanisms underlying catatonia.

UNASSIGNED: Converging evidence from structural and functional magnetic resonance imaging (MRI) studies points to amygdala alteration as crucial in the development of paediatric bipolar disorder (pBP). The high number of recent studies prompted us to comprehensively evaluate findings. We aimed to systematically review structural and functional MRI studies investigating the amygdala in patients with pBP and in youth at high-risk (HR) for developing pBP.
UNASSIGNED: We searched PubMed from any time to 25 September 2020 using: \'amygdala AND (MRI OR magnetic resonance imaging) AND bipolar AND (pediatr* OR child OR children OR childhood OR adolescent OR adolescents OR adolescence OR young OR familial OR at-risk OR sibling* OR offspring OR high risk)\'. In this review, we adhered to the PRISMA statement.
UNASSIGNED: Amygdala hyperactivity to emotional stimuli is the most commonly reported finding in youth with pBP and HR compared to healthy peers (HC), whereas findings from structural MRI studies are inconsistent.
UNASSIGNED: Hyperactivation of the amygdala might be an endophenotype of pBP.

Alzheimer\'s disease (AD) is a heterogeneous disease with different subtypes. Studying AD subtypes from brain structure, neuropathology, and cognition are of great importance for AD heterogeneity research. Starting from the study of constructing AD subtypes based on the features of T1-weighted structural magnetic resonance imaging, this paper introduces the major connections between the subtype definition and analysis strategies, including brain region-based subtype definition, and their demographic, neuropathological, and neuropsychological characteristics. The advantages and existing problems are analyzed, and reasonable improvement schemes are prospected. Overall, this review offers a more comprehensive view in the field of atrophy subtype in AD, along with their advantages, challenges, and future prospects, and provide a basis for improving individualized AD diagnosis.

Magnetic resonance imaging (MRI) plays a central role in the management and evaluation of patients with epilepsy. It is important that structural MRI scans are optimally acquired and carefully reviewed by trained experts within the context of all available clinical data. The aim of this review is to discuss the essentials of MRI that will be useful to health care providers specialized in epilepsy, as outlined by the competencies and learning objectives of the recently developed ILAE curriculum. This review contains information on basic MRI principles, sequences, field strengths and safety, when to perform and repeat an MRI, epilepsy MRI protocol (HARNESS-MRI) and the basic reading guidelines, and common epileptic pathologies. More advanced topics such as MRI-negative epilepsy, functional MRI and diffusion-weighted imaging are also briefly discussed. Although the available resources can differ markedly across different centers, it is the hope that this review can provide general guidance in the everyday practice of using MRI for patients with epilepsy.