Cerebral cavernous malformations (CCMs) are clusters of dilated capillaries that affect around 0.5% of the population. CCMs exist in two forms, sporadic and familial. Mutations in three documented genes, KRIT1(CCM1), CCM2, and PDCD10(CCM3), cause the autosomal dominant form of the disease, and somatic mutations in these same genes underlie lesion development in the brain. Murine models with constitutive or induced loss of respective genes have been applied to study disease pathobiology and therapeutic manipulations. We aimed to analyze the phenotypic characteristic of two main groups of models, the chronic heterozygous models with sensitizers promoting genetic instability, and the acute neonatal induced homozygous knockout model. Acute model mice harbored a higher lesion burden than chronic models, more localized in the hindbrain, and largely lacking iron deposition and inflammatory cell infiltrate. The chronic model mice showed a lower lesion burden localized throughout the brain, with significantly greater perilesional iron deposition, immune B- and T-cell infiltration, and less frequent junctional protein immunopositive endothelial cells. Lesional endothelial cells in both models expressed similar phosphorylated myosin light chain immunopositivity indicating Rho-associated protein kinase activity. These data suggest that acute models are better suited to study the initial formation of the lesion, while the chronic models better reflect lesion maturation, hemorrhage, and inflammatory response, relevant pathobiologic features of the human disease.

Background Cerebral cavernous malformations (CCMs) are hemorrhagic brain lesions, where murine models allow major mechanistic discoveries, ushering genetic manipulations and preclinical assessment of therapies. Histology for lesion counting and morphometry is essential yet tedious and time consuming. We herein describe the application and validations of X-ray micro-computed tomography (micro-CT), a nondestructive technique allowing three-dimensional CCM lesion count and volumetric measurements, in transgenic murine brains. New Method We hereby describe a new contrast soaking technique not previously applied to murine models of CCM disease. Volumetric segmentation and image processing paradigm allowed for histologic correlations and quantitative validations not previously reported with the micro-CT technique in brain vascular disease. Results Twenty-two hyper-dense areas on micro-CT images, identified as CCM lesions, were matched by histology. The inter-rater reliability analysis showed strong consistency in the CCM lesion identification and staging (K=0.89, p<0.0001) between the two techniques. Micro-CT revealed a 29% greater CCM lesion detection efficiency, and 80% improved time efficiency. Comparison with Existing Method Serial integrated lesional area by histology showed a strong positive correlation with micro-CT estimated volume (r2= 0.84, p<0.0001). Conclusions Micro-CT allows high throughput assessment of lesion count and volume in pre-clinical murine models of CCM. This approach complements histology with improved accuracy and efficiency, and can be applied for lesion burden assessment in other brain diseases.

A retrospective analysis published by the German Institute for Quality and Efficiency in Health Care (IQWiG) in 2018 concluded that no filter for non‐randomized studies (NRS) achieved sufficient sensitivity (≥92%), a precondition for comprehensive information retrieval. New NRS filters are therefore required, taking into account the challenges related to this study type. Our evaluation focused on the development of study filters for NRS with a control group (“controlled NRS”), as this study type allows the calculation of an effect size. In addition, we assumed that due to the more explicit search syntax, controlled NRS are easier to identify than non‐controlled ones, potentially resulting in better performance measures of study filters for controlled NRS. Our aim was to develop study filters for identifying controlled NRS in PubMed and Ovid MEDLINE. We developed two new search filters that can assist clinicians and researchers in identifying controlled NRS in PubMed and Ovid MEDLINE. The reference set was based on 2110 publications in Medline extracted from 271 Cochrane reviews and on 4333 irrelevant references. The first filter maximizes sensitivity (92.42%; specificity 79.67%, precision 68.49%) and should be used when a comprehensive search is needed. The second filter maximizes specificity (92.06%; precision 82.98%, sensitivity 80.94%) and should be used when a more focused search is sufficient.

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