GNA14 and GNAQ somatic mutations cause spinal and intracranial extra-axial cavernous hemangiomas.

Extra-axial cavernous hemangiomas (ECHs) are complex vascular lesions mainly found in the spine and cavernous sinus. Their removal poses significant risk due to their vascularity and diffuse nature, and their genetic underpinnings remain incompletely understood. Our approach involved genetic analyses on 31 tissue samples of ECHs employing whole-exome sequencing and targeted deep sequencing. We explored downstream signaling pathways, gene expression changes, and resultant phenotypic shifts induced by these mutations, both in vitro and in vivo. In our cohort, 77.4% of samples had somatic missense variants in GNA14, GNAQ, or GJA4. Transcriptomic analysis highlighted significant pathway upregulation, with the GNAQ c.626A>G (p.Gln209Arg) mutation elevating PI3K-AKT-mTOR and angiogenesis-related pathways, while GNA14 c.614A>T (p.Gln205Leu) mutation led to MAPK and angiogenesis-related pathway upregulation. Using a mouse xenograft model, we observed enlarged vessels from these mutations. Additionally, we initiated rapamycin treatment in a 14-year-old individual harboring the GNAQ c.626A>G (p.Gln209Arg) variant, resulting in gradual regression of cutaneous cavernous hemangiomas and improved motor strength, with minimal side effects. Understanding these mutations and their pathways provides a foundation for developing therapies for ECHs resistant to current therapies. Indeed, the administration of rapamycin in an individual within this study highlights the promise of targeted treatments in treating these complex lesions.

Lymphatic endothelial cell-specific NRAS p.Q61R mutant embryos show abnormal lymphatic vessel morphogenesis.

Generalized lymphatic anomaly (GLA) and kaposiform lymphangiomatosis (KLA) are rare congenital disorders that arise through anomalous embryogenesis of the lymphatic system. A somatic activating NRAS p.Q61R variant has been recently detected in GLA and KLA tissues, suggesting that the NRAS p.Q61R variant plays an important role in the development of these diseases. To address this role, we studied the effect of the NRAS p.Q61R variant in lymphatic endothelial cells (LECs) on the structure of the lymphatics during embryonic and postnatal lymphangiogenesis applying inducible, LEC-specific NRAS p.Q61R variant in mice. Lox-stop-Lox NrasQ61R mice were crossed with Prox1-CreERT2 mice expressing tamoxifen-inducible Cre recombinase specifically in LECs. Whole-mount immunostaining of embryonic back skin using an antibody against the LEC surface marker VEGFR3 showed considerably greater lymphatic vessel width in LEC-specific NRAS p.Q61R mutant embryos than in littermate controls. These mutant embryos also showed a significant reduction in the number of lymphatic vessel branches. Furthermore, immunofluorescence staining of whole-mount embryonic back skin using an antibody against the LEC-specific nuclear marker Prox1 showed a large increase in the number of LECs in LEC-specific NRAS p.Q61R mutants. In contrast, postnatal induction of the NRAS p.Q61R variant in LECs did not cause abnormal lymphatic vessel morphogenesis. These results suggest that the NRAS p.Q61R variant in LECs plays a role in development of lymphatic anomalies. While this model does not directly reflect the human pathology of GLA and KLA, there are overlapping features, suggesting that further study of this model may help in studying GLA and KLA mechanisms.

Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies.

Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs.

Vimentin regulates nuclear segmentation in neutrophils.

Granulocytes are indispensable for various immune responses. Unlike other cell types in the body, the nuclei of granulocytes, particularly neutrophils, are heavily segmented into multiple lobes. Although this distinct morphological feature has long been observed, the underlying mechanism remains incompletely characterized. In this study, we utilize cryo-electron tomography to examine the nuclei of mouse neutrophils, revealing the cytoplasmic enrichment of intermediate filaments on the concave regions of the nuclear envelope. Aided by expression profiling and immuno-electron microscopy, we then elucidate that the intermediate-filament protein vimentin is responsible for such perinuclear structures. Of importance, exogenously expressed vimentin in nonimmune cells is sufficient to form cytoplasmic filaments wrapping on the concave nuclear surface. Moreover, genetic deletion of the protein causes a significant reduction of the number of nuclear lobes in neutrophils and eosinophils, mimicking the hematological condition of the Pelger-Huët anomaly. These results have uncovered a new component establishing the nuclear segmentation of granulocytes.

Bi-allelic loss-of-function variants in TMEM147 cause moderate to profound intellectual disability with facial dysmorphism and pseudo-Pelger-Huët anomaly.

The transmembrane protein TMEM147 has a dual function: first at the nuclear envelope, where it anchors lamin B receptor (LBR) to the inner membrane, and second at the endoplasmic reticulum (ER), where it facilitates the translation of nascent polypeptides within the ribosome-bound TMCO1 translocon complex. Through international data sharing, we identified 23 individuals from 15 unrelated families with bi-allelic TMEM147 loss-of-function variants, including splice-site, nonsense, frameshift, and missense variants. These affected children displayed congruent clinical features including coarse facies, developmental delay, intellectual disability, and behavioral problems. In silico structural analyses predicted disruptive consequences of the identified amino acid substitutions on translocon complex assembly and/or function, and in vitro analyses documented accelerated protein degradation via the autophagy-lysosomal-mediated pathway. Furthermore, TMEM147-deficient cells showed CKAP4 (CLIMP-63) and RTN4 (NOGO) upregulation with a concomitant reorientation of the ER, which was also witnessed in primary fibroblast cell culture. LBR mislocalization and nuclear segmentation was observed in primary fibroblast cells. Abnormal nuclear segmentation and chromatin compaction were also observed in approximately 20% of neutrophils, indicating the presence of a pseudo-Pelger-Huët anomaly. Finally, co-expression analysis revealed significant correlation with neurodevelopmental genes in the brain, further supporting a role of TMEM147 in neurodevelopment. Our findings provide clinical, genetic, and functional evidence that bi-allelic loss-of-function variants in TMEM147 cause syndromic intellectual disability due to ER-translocon and nuclear organization dysfunction.

Phylogenomic discordance is driven by wide-spread introgression and incomplete lineage sorting during rapid species diversification within rattlesnakes (Viperidae: Crotalus and Sistrurus).

Phylogenomics allows us to uncover the historical signal of evolutionary processes through time and estimate phylogenetic networks accounting for these signals. Insight from genome-wide data further allows us to pinpoint the contributions to phylogenetic signal from hybridization, introgression, and ancestral polymorphism across the genome. Here we focus on how these processes have contributed to phylogenetic discordance among rattlesnakes (genera Crotalus and Sistrurus), a group for which there are numerous conflicting phylogenetic hypotheses based on a diverse array of molecular datasets and analytical methods. We address the instability of the rattlesnake phylogeny using genomic data generated from transcriptomes sampled from nearly all known species. These genomic data, analyzed with coalescent and network-based approaches, reveal numerous instances of rapid speciation where individual gene trees conflict with the species tree. Moreover, the evolutionary history of rattlesnakes is dominated by incomplete speciation and frequent hybridization, both of which have likely influenced past interpretations of phylogeny. We present a new framework in which the evolutionary relationships of this group can only be understood in light of genome-wide data and network-based analytical methods. Our data suggest that network radiations, like seen within the rattlesnakes, can only be understood in a phylogenomic context, necessitating similar approaches in our attempts to understand evolutionary history in other rapidly radiating species.

Recurrent ancient geomagnetic field anomalies shed light on future evolution of the South Atlantic Anomaly.

The strength of the geomagnetic field has decreased rapidly over the past two centuries, coinciding with an increasing field asymmetry due to the growth of the South Atlantic Anomaly. The underlying processes causing the decrease are debated, which has led to speculation that the field is about to reverse. Here, we present a geomagnetic field model based on indirect observations over the past 9,000 y and identify potential ancient analogs. The model is constructed using a probabilistic approach that addresses problems with age uncertainties and smoothing of sedimentary data that have hampered previous attempts. We find evidence for recurrent hemispherical field asymmetries, related to quasiperiodic millennial-scale variations in the dipole moment. Our reconstruction indicates that minima in the dipole moment tend to coincide with geomagnetic field anomalies, similar to the South Atlantic Anomaly. We propose that the period around 600 BCE, characterized by a strongly asymmetric field, could provide an analog to the present-day field. The analogy implies that the South Atlantic Anomaly will likely disappear in next few hundred years, accompanied by a return to a more symmetric field configuration and possibly, a strengthening of the axial dipole field.

A transient peak in marine sulfate after the 635-Ma snowball Earth.

SignificanceEarth system's response to major perturbations is of paramount interest. On the basis of multiple isotope compositions for pyrite, carbonate-associated sulfate, carbonates, and organics within, we inferred that the much-debated, enigmatic, extremely 13C-depleted calcite cements in the ∼635-Ma cap carbonates in South China preserve geochemical evidence for marine microbial sulfate reduction coupled to anaerobic oxidation of methane. This interpretation implies the existence of a brief interval of modern-level marine sulfate. We determined that this interval coincides with the earliest Ediacaran 17O-depletion episode, and both likely occurred within ∼50 ky since the onset of the 635-Ma meltdown, revealing an astonishing pace of transformation of the Earth system in the aftermath of Earth's latest snowball glaciation.

Fully learnable deep wavelet transform for unsupervised monitoring of high-frequency time series.

High-frequency (HF) signals are ubiquitous in the industrial world and are of great use for monitoring of industrial assets. Most deep-learning tools are designed for inputs of fixed and/or very limited size and many successful applications of deep learning to the industrial context use as inputs extracted features, which are a manually and often arduously obtained compact representation of the original signal. In this paper, we propose a fully unsupervised deep-learning framework that is able to extract a meaningful and sparse representation of raw HF signals. We embed in our architecture important properties of the fast discrete wavelet transform (FDWT) such as 1) the cascade algorithm; 2) the conjugate quadrature filter property that links together the wavelet, the scaling, and transposed filter functions; and 3) the coefficient denoising. Using deep learning, we make this architecture fully learnable: Both the wavelet bases and the wavelet coefficient denoising become learnable. To achieve this objective, we propose an activation function that performs a learnable hard thresholding of the wavelet coefficients. With our framework, the denoising FDWT becomes a fully learnable unsupervised tool that does not require any type of pre- or postprocessing or any prior knowledge on wavelet transform. We demonstrate the benefits of embedding all these properties on three machine-learning tasks performed on open-source sound datasets. We perform an ablation study of the impact of each property on the performance of the architecture, achieve results well above baseline, and outperform other state-of-the-art methods.

Cryogenic Electron-Beam Writing for Perovskite Metasurface.

Halide perovskites (HPs) metasurfaces have recently attracted significant interest due to their potential to not only further enhance device performance but also reveal the unprecedented functionalities and novel photophysical properties of HPs. However, nanopatterning on HPs is critically challenging as they are readily destructed by the organic solvents in the standard lithographic processes. Here, we present a novel, subtle, and fully nondestructive HPs metasurface fabrication strategy based on cryogenic electron-beam writing. This technique allows for high-precision patterning and in situ imaging of HPs with excellent compatibility. As a proof-of-concept, broadband absorption enhanced metasurfaces were realized by patterning nanopillar arrays on CH3NH3PbI3 film, which results in photodetectors with approximately 14-times improvement on responsivity and excellent stability. Our findings highlight the great feasibility of cryogenic electron-beam writing for producing perovskite metasurface and unlocking the unprecedented photoelectronic properties of HPs.

OTSUCNV: an adaptive segmentation and OTSU-based anomaly classification method for CNV detection using NGS data.

Copy-number variations (CNVs), which refer to deletions and duplications of chromosomal segments, represent a significant source of variation among individuals, contributing to human evolution and being implicated in various diseases ranging from mental illness and developmental disorders to cancer. Despite the development of several methods for detecting copy number variations based on next-generation sequencing (NGS) data, achieving robust detection performance for CNVs with arbitrary coverage and amplitude remains challenging due to the inherent complexity of sequencing samples. In this paper, we propose an alternative method called OTSUCNV for CNV detection on whole genome sequencing (WGS) data. This method utilizes a newly designed adaptive sequence segmentation algorithm and an OTSU-based CNV prediction algorithm, which does not rely on any distribution assumptions or involve complex outlier factor calculations. As a result, the effective detection of CNVs is achieved with lower computational complexity. The experimental results indicate that the proposed method demonstrates outstanding performance, and hence it may be used as an effective tool for CNV detection.

A systematic review to assess the utility of genomic autopsy using exome or genome sequencing in cases of congenital anomalies and perinatal death.

PURPOSE: Exome or genome sequencing (ES or GS) can identify genetic causes of otherwise unexplained congenital anomaly and perinatal death (PND) but is not routine practice. The evidence base for "genomic autopsy" after termination of pregnancy for fetal anomaly (TOPFA) and PND has been synthesized to determine the value of this investigation. METHODS: We conducted a systematic review and meta-analysis of studies meeting prespecified inclusion criteria and containing ≥10 cases of TOPFA or PND (with or without major congenital abnormality), in which ES or GS was conducted. We determined test performance, including diagnostic yield, accuracy, and reliability. We also reported outcomes associated with clinical utility and harms, where described. RESULTS: From 2245 potentially eligible studies, 32 publications were eligible and had data extracted, representing 2120 cases that could be meta-analyzed. No diagnostic accuracy or comparative studies were identified, although some analysis of concordance between different ES/GS methodologies could be performed. Studies reporting parent-related outcomes or long-term follow-up did not do so in a systematic or quantifiable manner. CONCLUSION: Evidence suggests that approximately one-fourth to one-third of fetal losses associated with TOPFA or unexplained PND are associated with a genetic cause identifiable on ES or GS-albeit this estimate varies depending on phenotypic and background risk factors. Despite the large body of evidence on ES and GS, little research has attempted to validate the accuracy of testing, nor measure the clinical or societal outcomes in families that follow the diagnostic investigation in this context.

Pathological Findings in Fetuses Terminated for Suspected Lower Urinary Tract Obstruction: Experience From a High-Risk Fetal Center in Canada.

PURPOSE: Pregnancies complicated by prenatally suspected lower urinary tract obstruction (LUTO) can be associated with high rates of terminations due to potentially poor outcomes. Herein, we assessed autopsy findings of fetuses terminated for suspected LUTO to evaluate the prenatal diagnostic accuracy and spectrum of underlying pathologies. MATERIALS AND METHODS: We performed a retrospective review of all pregnancies referred to a high-risk fetal center in a universal access to care health care system for suspected LUTO that opted for termination of pregnancy between 2009 and 2022. Ultrasound features, genetic investigations, placental findings, and distribution of postmortem diagnoses were assessed. RESULTS: Of a total of 190 pregnancies with suspected LUTO evaluated during the study period, 79 (42%) were terminated. We excluded 35 fetuses with incomplete data, resulting in 44 available for analysis. Pregnancies were terminated at a mean gestation of 22 ± 5 weeks. A LUTO diagnosis was confirmed in 37 (84.1%) fetuses (35 males, 2 females), and the remaining 7 showed other pathologies. Pulmonary hypoplasia was found in 62.2% (n = 23) and placental pathologies in 56.8% of confirmed LUTO compared to 33.4% and 71.4% in non-LUTO cases, respectively. Overall, a total of 31 fetuses underwent additional prenatal investigations with genetic anomalies detected only in fetuses with a confirmed LUTO diagnosis (13.6%). CONCLUSIONS: In our health care system, almost half of prenatally suspected LUTO pregnancies are terminated. The sonographic diagnostic accuracy for LUTO is reasonable at 84%. However, the remaining 16% still had significant pathologies. Genetic abnormalities are uncommon and rarely the trigger for pregnancy terminations.

Use of Latent Class Analysis to Predict Intensive Care Unit Admission and Mortality in Children with a Major Congenital Anomaly.

OBJECTIVE: To define major congenital anomaly (CA) subgroups and assess outcome variability based on defined subgroups. STUDY DESIGN: This population-based cohort study used registries in Denmark for children born with a major CA between January 1997 and December 2016, with follow-up until December 2018. We performed a latent class analysis (LCA) using child and family clinical and sociodemographic characteristics present at birth, incorporating additional variables occurring until age of 24 months. Cox proportional hazards regression models estimated hazard ratios (HRs) of pediatric mortality and intensive care unit (ICU) admissions for identified LCA classes. RESULTS: The study included 27 192 children born with a major CA. Twelve variables led to a 4-class solution (entropy = 0.74): (1) children born with higher income and fewer comorbidities (55.4%), (2) children born to young mothers with lower income (24.8%), (3) children born prematurely (10.0%), and (4) children with multiorgan involvement and developmental disability (9.8%). Compared with those in Class 1, mortality and ICU admissions were highest in Class 4 (HR = 8.9, 95% CI = 6.4-12.6 and HR = 4.1, 95% CI = 3.6-4.7, respectively). More modest increases were observed among the other classes for mortality and ICU admissions (Class 2: HR = 1.7, 95% CI = 1.1-2.5 and HR = 1.3, 95% CI = 1.1-1.4, respectively; Class 3: HR = 2.5, 95% CI = 1.5-4.2 and HR = 1.5, 95% CI = 1.3-1.9, respectively). CONCLUSIONS: Children with a major CA can be categorized into meaningful subgroups with good discriminative ability. These groupings may be useful for risk-stratification in outcome studies.

Pregnancy outcomes in patients with familial Mediterranean fever: systematic review and meta-analysis.

OBJECTIVE: The relationship between FMF and pregnancy outcomes remains unclear. This systematic review and meta-analysis aimed to clarify this association. METHODS: Electronic databases-PubMed, Web of Science, Cochrane, and EMBASE-were searched on 20 December 2022, using specific search terms. Case-control, cohort, and randomized clinical trial studies comparing patients with FMF and healthy controls were considered eligible. We excluded systematic reviews, meta-analyses, case series with fewer than five cases, republished articles without new findings on pregnancy outcomes, studies targeting paternal FMF, and those not published in English. The results were summarized in the form of odds ratios (ORs) and 95% CIs, using a random-effects model. This study was registered in the University hospital Medical Information Network Clinical Trials Registry (Japan) as UMIN000049827. RESULTS: The initial electronic search identified 611 records, of which 9 were included in this meta-analysis (177 735 pregnancies, 1242 with FMF, and 176 493 healthy controls). FMF was significantly associated with increased odds of preterm deliveries (OR, 1.67; 95% CI, 1.05-2.67; I2 = 22%) and insignificantly associated with increased odds of fetal growth restriction (OR, 1.45; 95% CI, 0.90-2.34; I2 = 0%) and hypertensive disorders during pregnancy (OR, 1.28; 95% CI, 0.87-1.87; I2 = 0%). CONCLUSION: FMF was significantly associated with preterm delivery and insignificantly associated with fetal growth restriction and hypertensive disorders. All of the included studies were observational studies. Treatment characteristics were not fully collected from the articles, and further analysis of treatments for FMF in pregnancy is still warranted.

Novel copy number variations and phenotypes of infantile epileptic spasms syndrome.

We summarize the copy number variations (CNVs) and phenotype spectrum of infantile epileptic spasms syndrome (IESS) in a Chinese cohort. The CNVs were identified by genomic copy number variation sequencing. The CNVs and clinical data were analyzed. 74 IESS children with CNVs were enrolled. 35 kinds of CNVs were identified. There were 11 deletions and 5 duplications not reported previously in IESS, including 2 CNVs not reported in epilepsy. 87.8% were de novo, 9.5% were inherited from mother and 2.7% from father. Mosaicism occurred in one patient with Xq21.31q25 duplication. 16.2% (12/74) were 1p36 deletion, and 20.3% (15/74) were 15q11-q13 duplication. The age of seizure onset ranged from 17 days to 24 months. Seizure types included epileptic spasms, focal seizures, tonic seizures, and myoclonic seizures. All patients displayed developmental delay. Additional features included craniofacial anomaly, microcephaly, congenital heart defects, and hemangioma. 29.7% of patients were seizure-free for more than 12 months, and 70.3% still had seizures after trying 2 or more anti-seizure medications. In conclusion, CNVs is a prominent etiology of IESS. 1p36 deletion and 15q duplication occurred most frequently. CNV detection should be performed in patients with IESS of unknown causes, especially in children with craniofacial anomalies and microcephaly.

Isotope Effects and the Atmosphere.

Chemical physics plays a large role in determining the isotopic compositions of gases in Earth's atmosphere, which in turn provide fundamental insights into the sources, sinks, and transformations of atmospheric gases and particulates and their influence on climate. This review focuses on the kinetic and photolysis isotope effects relevant to understanding the isotope compositions of atmospheric ozone, carbon dioxide, methane, nitrous oxide, and other gases and their historical context. The discussion includes non-mass-dependent isotope compositions of oxygen-containing species and a brief overview of the recent growth of clumped isotope measurements at natural isotopic abundances, that is, of molecules containing more than one rare isotope. The intention is to introduce chemistry researchers to the field of using isotope compositions as tracers of atmospheric chemistry and climate both today and back in time through ice and rock records and to highlight the outstanding research questions to which experimental and theoretical physical chemists can contribute.

Protean Regulation of Leukocyte Function by Nuclear Lamins.

The leukocyte nucleus must be sufficiently elastic to squeeze through tissue barriers during migration, but not so collapsible as to risk damaging chromatin. The proper balance is struck in part by the composition of the nuclear lamina, a flexible meshwork composed mainly of intermediate filaments woven from type A and type B lamin proteins, that is located subjacent to the inner nuclear membrane. There is now increasing evidence that, in addition to influencing nuclear shape and stiffness and cell migration, lamins and lamin-interacting proteins may also interact functionally with chromatin to influence leukocyte gene expression, differentiation, and effector function, including T cell differentiation, B cell somatic hypermutation, and the formation of neutrophil extracellular traps (NETosis).

Five-Year Serial Brain MRI Analysis of Military Members Exposed to Chronic Sub-Concussive Overpressures.

BACKGROUND: The Canadian Special Operations Forces Command conducts explosives operations and training which exposes members to explosive charges at close proximity. This 5-year longitudinal trial was conducted in follow-up to our initial trial which examined military breachers with MRI and EEG pre and post blast exposure. PURPOSE: To examine brain MRI findings in military personnel exposed to multiple repeated blast exposures. STUDY TYPE: Five-year longitudinal prospective trial. POPULATION: Ninety-two males aged 23-42 with an average of 9.4 years of blast exposure. FIELD STRENGTH/SEQUENCE: 3 T brain MRI/T1-weighted 3D with reconstruction in three planes, T2-weighted, T2-weighted fluid attenuated inversion recovery (FLAIR) 3D with reconstruction in three planes, T2-weighted gradient spin echo (GRE), saturation weighted images, DWI and ADC maps, diffusion tensor imaging. ASSESSMENT: All MRI scans were interpreted by the two neuroradiologists and one neuroradiology Fellow in a blinded fashion using a customized neuroradiology reporting form. STATISTICAL TESTS: Matching parametric statistics represented the number of participants whose brain parameters improved or deteriorated over time. Odds ratio (OR) and 95% confidence intervals (CI) were computed using log regression modeling to determine volume loss, white matter lesions, hemosiderosis, gliosis, cystic changes and enlarged Virchow Robin (VR) spaces. A Kappa (κ) statistic with a 95% CI was calculated to determine rater variability between readers. RESULTS: A significant deterioration was observed in volume loss (OR = 1.083, 95% CI 0.678-1.731, permutation test), white matter changes (OR: 0.754, 95% CI 0.442-1.284, permutation test), and enlargement of VR spaces (OR: 0.775, 95% CI 0.513-1.171). Interrater reliability was low: κ = 0.283, 0.156, and 0.557 for volume loss, white matter changes, and enlargement of VR spaces, respectively. DATA CONCLUSION: There were significant changes in brain volume, white matter lesions, and enlargement of VR spaces. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

AI-Enhanced Detection of Clinically Relevant Structural and Functional Anomalies in MRI: Traversing the Landscape of Conventional to Explainable Approaches.

Anomaly detection in medical imaging, particularly within the realm of magnetic resonance imaging (MRI), stands as a vital area of research with far-reaching implications across various medical fields. This review meticulously examines the integration of artificial intelligence (AI) in anomaly detection for MR images, spotlighting its transformative impact on medical diagnostics. We delve into the forefront of AI applications in MRI, exploring advanced machine learning (ML) and deep learning (DL) methodologies that are pivotal in enhancing the precision of diagnostic processes. The review provides a detailed analysis of preprocessing, feature extraction, classification, and segmentation techniques, alongside a comprehensive evaluation of commonly used metrics. Further, this paper explores the latest developments in ensemble methods and explainable AI, offering insights into future directions and potential breakthroughs. This review synthesizes current insights, offering a valuable guide for researchers, clinicians, and medical imaging experts. It highlights AI's crucial role in improving the precision and speed of detecting key structural and functional irregularities in MRI. Our exploration of innovative techniques and trends furthers MRI technology development, aiming to refine diagnostics, tailor treatments, and elevate patient care outcomes. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 1.