“Just Accepted” papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review ...

Neurodegenerative diseases likely share common underlying pathobiology. Although prior work has identified susceptibility loci associated with various dementias, few, if any, studies have systematically evaluated shared genetic risk across several neurodegenerative diseases. Using genome-wide association data from large studies (total n = 82,337 cases and controls), we utilized a previously validated approach to identify genetic overlap and reveal common pathways between progressive supranuclear palsy (PSP), frontotemporal dementia (FTD), Parkinson’s disease (PD) and Alzheimer’s disease (AD). In addition to the MAPT H1 haplotype, we identified a variant near the chemokine receptor CXCR4 that was jointly associated with increased risk for PSP and PD. Using bioinformatics tools, we found strong physical interactions between CXCR4 and four microglia related genes, namely CXCL12, TLR2, RALB, and CCR5. Evaluating gene expression from post-mortem brain tissue, we found that expression of CXCR4 and microglial genes functionally related to CXCR4 was dysregulated across a number of neurodegenerative diseases. Furthermore, in a mouse model of tauopathy, expression of CXCR4 and functionally associated genes was significantly altered in regions of the mouse brain that accumulate neurofibrillary tangles most robustly. Beyond MAPT, we show dysregulation of CXCR4 expression in PSP, PD, and FTD brains, and mouse models of tau pathology. Our multi-modal findings suggest that abnormal signaling across a ‘network’ of microglial genes may contribute to neurodegeneration and may have potential implications for clinical trials targeting immune dysfunction in patients with neurodegenerative diseases.

BACKGROUND AND PURPOSE: The traditionally described Dandy-Walker malformation comprises a range of cerebellar and posterior fossa abnormalities with variable clinical severity. We aimed to establish updated imaging criteria for Dandy-Walker malformation on the basis of cerebellar development. MATERIALS AND METHODS: In this multicenter study, retrospective MR imaging examinations from fetuses and children previously diagnosed with Dandy-Walker malformation or vermian hypoplasia were re-evaluated, using the choroid plexus/tela choroidea location and the fastigial recess shape to differentiate Dandy-Walker malformation from vermian hypoplasia. Multiple additional measures of the posterior fossa and cerebellum were also obtained and compared between Dandy-Walker malformation and other diagnoses. RESULTS: Four hundred forty-six examinations were analyzed (174 fetal and 272 postnatal). The most common diagnoses were Dandy-Walker malformation (78%), vermian hypoplasia (14%), vermian hypoplasia with Blake pouch cyst (9%), and Blake pouch cyst (4%). Most measures were significant differentiators of Dandy-Walker malformation from non-Dandy-Walker malformation both pre- and postnatally (P < .01); the tegmentovermian and fastigial recess angles were the most significant quantitative measures. Posterior fossa perimeter and vascular injury evidence were not significant differentiators pre- or postnatally (P > .3). The superior posterior fossa angle, torcular location, and vermian height differentiated groups postnatally (P < .01), but not prenatally (P > .07). CONCLUSIONS: As confirmed by objective measures, the modern Dandy-Walker malformation phenotype is best defined by inferior predominant vermian hypoplasia, an enlarged tegmentovermian angle, inferolateral displacement of the tela choroidea/choroid plexus, an obtuse fastigial recess, and an unpaired caudal lobule. Posterior fossa size and torcular location should be eliminated from the diagnostic criteria. This refined phenotype may help guide future study of the numerous etiologies and varied clinical outcomes.

Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and the Fetal Brain Tissue Annotation (FeTA) Challenge 2021 helped to establish an excellent standard of fetal brain segmentation. However, FeTA 2021 was a single center study, limiting real-world clinical applicability and acceptance. The multi-center FeTA Challenge 2022 focused on advancing the generalizability of fetal brain segmentation algorithms for magnetic resonance imaging (MRI). In FeTA 2022, the training dataset contained images and corresponding manually annotated multi-class labels from two imaging centers, and the testing data contained images from these two centers as well as two additional unseen centers. The multi-center data included different MR scanners, imaging parameters, and fetal brain super-resolution algorithms applied. 16 teams participated and 17 algorithms were evaluated. Here, the challenge results are presented, focusing on the generalizability of the submissions. Both in- and out-of-domain, the white matter and ventricles were segmented with the highest accuracy (Top Dice scores: 0.89, 0.87 respectively), while the most challenging structure remains the grey matter (Top Dice score: 0.75) due to anatomical complexity. The top 5 average Dices scores ranged from 0.81-0.82, the top 5 average 95 ^th percentile Hausdorff distance values ranged from 2.3-2.5mm, and the top 5 volumetric similarity scores ranged from 0.90-0.92. The FeTA Challenge 2022 was able to successfully evaluate and advance generalizability of multi-class fetal brain tissue segmentation algorithms for MRI and it continues to benchmark new algorithms.