Perivascular spaces and where to find them - MR imaging and evaluation methods. / Perivaskuläre Räume und wo sie zu finden sind ­ MR-Bildgebung und Auswertungsmethoden.

BACKGROUND: Perivascular spaces (synonym: Virchow-Robin spaces) were first described over 150 years ago. They are defined as the fluid-filled spaces surrounding the small penetrating cerebral vessels. They gained growing scientific interest especially with the postulation of the so-called glymphatic system and their possible role in neurodegenerative and neuroinflammatory diseases. METHODS: PubMed was used for a systematic search with a focus on literature regarding MRI imaging and evaluation methods of perivascular spaces. Studies on human in-vivo imaging were included with a focus on studies involving healthy populations. No time frame was set. The nomenclature in the literature is very heterogeneous with terms like "large", "dilated", "enlarged" perivascular spaces whereas borders and definitions often remain unclear. This work generally talks about perivascular spaces. RESULTS: This review article discusses the morphologic MRI characteristics in different sequences. With the continual improvement of image quality, more and tinier structures can be depicted in detail. Visual analysis and semi or fully automated segmentation methods are briefly discussed. CONCLUSION: If they are looked for, perivascular spaces are apparent in basically every cranial MRI examination. Their physiologic or pathologic value is still under debate. KEY POINTS: · Perivascular spaces can be seen in basically every cranial MRI examination.. · Primarily T2-weighend sequences are used for visual analysis. Additional sequences are helpful for distinction from their differential diagnoses.. · There are promising approaches for the semi or fully automated segmentation of perivascular spaces with the possibility to collect more quantitative parameters.. CITATION FORMAT: · Seehafer S, Larsen N, Aludin S et al. Perivascular spaces and where to find them - MRI imaging and evaluation methods. Fortschr Röntgenstr 2024; DOI: 10.1055/a-2254-5651.

MRI signs of intracranial hypertension in morbidly obese and normal-weight individuals.

PURPOSE: Idiopathic intracranial hypertension (IIH) is associated with intracranial abnormalities, although not obligatory, which can be detected with cranial MRI. Obesity is an important risk factor for IIH and a pathogenetic link is suspected but the extent to which these MRI signs are already related to obesity has not yet been examined. We investigated whether IIH-MRI signs are present more often in obese individuals with a BMI > 30 kg/m² than in individuals of normal weight. MATERIALS AND METHODS: Brain MRI of 32 obese and 53 normal-weight participants from the Food-Chain-Plus cohort were analyzed for three main signs of IIH: (I) stenosis of the transverse sinus, (II) increased width of the optic nerve sheath, and (III) reduction of pituitary height. In addition, a scoring system for the MRI signs was applied. Furthermore, tortuosity of the optic nerve and flattening of the posterior globe were considered as additional MRI signs. RESULTS: Obese participants had a significantly higher MRI score (p < 0.001) than those in the normal-weight cohort, with significant differences in quantitative measurements of cerebral venous sinus stenosis (p < 0.001), widening of the optic nerve sheath (p < 0.05), and flattening of the pituitary gland (p < 0.05) also always being observed more frequently and in a more pronounced manner in the obese group. Furthermore, our findings correlated significantly with BMI and proportionately with hip and waist circumference. CONCLUSION: Obese individuals show a significantly higher prevalence of cerebral MRI signs related to IIH. This supports the hypothesis that obesity is a risk factor for possible intracranial hypertension and reinforces the suspicion that obesity is involved in the pathomechanism of IIH. KEY POINTS: · Obesity is associated with changes such as those seen in IIH.. · BMI, weight, and body measurements correlate with the expression of MRI signs of IIH.. · To prevent IIH symptoms in obesity, the pathomechanism must be further clarified..

Automatic lesion detection at Multiple Sclerosis patients - Comparison of 2D- and 3D-FLAIR-datasets.

BACKGROUND: Multiple Sclerosis (MS) is a common autoimmune inflammatory disease of the central nervous system (CNS). Magnetic Resonance Imaging (MRI) allows a sensitive assessment of the CNS and is established for diagnostic, prognostic and (therapy-) monitoring purposes. Especially lesion counting in T2- or Fluid Attenuated Inversion Recovery (FLAIR)-weighted images plays a decisive role in clinical routine. Software-packages allowing an automatic evaluation of image data are increasingly established aiming a faster and improved workflow. These programs allow e.g. the counting, spatial attribution and volumetry of MS-lesions in FLAIR-weighted images. Research has shown that 3D-FLAIR-sequences are superior to 2D-FLAIR-sequences in visual evaluation of lesion burden in MS. An influence on the automatic analysis is expectable but not yet systematically studied. This work will therefore investigate the influence of 2D- and 3D datasets on the results of an automatic assessment. MATERIAL AND METHODS: In this prospective study, 80 Multiple Sclerosis patients underwent a clinically indicated routine MRI examination. The clinical routine protocol already including a 3D-FLAIR sequence was adapted by an additional 2D-FLAIR sequence also conform to the 2021 MAGNIMS-CMSCNAIMS consensus recommendations. To obtain a quantitative analysis for assessment of amount, dissemination and volume of the lesions, the acquired MR images were post-processed using the CE-certified Software mdbrain (mediaire, Berlin, Germany). The resulting data were statistically analysed using the paired t-test for normally distributed data and the Wilcoxon-signed-rank-test for not normally distributed data respectively. Demographic data and data such as the subtype, duration, severity and therapy of the disease were collected, pseudonymized and evaluated. RESULTS: There is a significant difference concerning the total number and lesion volume with more lesions being detected (2D: 29.7, +/- 20.22 sd; 3D: 40.1 +/- 31.67 sd; p < 0.0001) but lower total volume (2D: 6.24 +/- 6.11 sd; 3D: 5.39 +/- 6.37 sd; p < 0.0001) when using the 3D- sequence. Especially significantly more small lesions in the unspecific white matter and infratentorial region were detected by using the 3D-FLAIR sequence (p < 0.0001) compared to the 2D-FLAIR image. Main reason for the lower total volume in the 3D-FLAIR sequence was the calculated volume for periventricular lesions which was significantly beneath the calculated volume from the 2D-FLAIR sequence (p < 0.0001). CONCLUSION: Automatic lesion counting and volumetry is feasible with both 2D- and 3D-weightend FLAIR images. Still, it leads to partly significant differences even between two sequences that both are conform to the 2021 MAGNIMS-CMSCNAIMS consensus recommendations. This study contributes valuable insights into the impact of using different input data from the same patient for automated MS lesion evaluation.

Disease- and stage-specific alterations of the oral and fecal microbiota in Alzheimer's disease.

Microbial communities in the intestinal tract are suggested to impact the ethiopathogenesis of Alzheimer's disease (AD). The human microbiome might modulate neuroinflammatory processes and contribute to neurodegeneration in AD. However, the microbial compositions in patients with AD at different stages of the disease are still not fully characterized. We used 16S rRNA analyses to investigate the oral and fecal microbiota in patients with AD and mild cognitive impairment (MCI; n = 84), at-risk individuals (APOE4 carriers; n = 17), and healthy controls (n = 50) and investigated the relationship of microbial communities and disease-specific markers via multivariate- and network-based approaches. We found a slightly decreased diversity in the fecal microbiota of patients with AD (average Chao1 diversity for AD = 212 [SD = 66]; for controls = 215 [SD = 55]) and identified differences in bacterial abundances including Bacteroidetes, Ruminococcus, Sutterella, and Porphyromonadaceae. The diversity in the oral microbiota was increased in patients with AD and at-risk individuals (average Chao1 diversity for AD = 174 [SD = 60], for at-risk group = 195 [SD = 49]). Gram-negative proinflammatory bacteria including Haemophilus, Neisseria, Actinobacillus, and Porphyromonas were dominant oral bacteria in patients with AD and MCI and the abundance correlated with the cerebrospinal fluid biomarker. Taken together, we observed a strong shift in the fecal and the oral communities of patients with AD already prominent in prodromal and, in case of the oral microbiota, in at-risk stages. This indicates stage-dependent alterations in oral and fecal microbiota in AD which may contribute to the pathogenesis via a facilitated intestinal and systemic inflammation leading to neuroinflammation and neurodegeneration.

Standardization of a CT Protocol for Imaging Patients with Suspected COVID-19-A RACOON Project.

CT protocols that diagnose COVID-19 vary in regard to the associated radiation exposure and the desired image quality (IQ). This study aims to evaluate CT protocols of hospitals participating in the RACOON (Radiological Cooperative Network) project, consolidating CT protocols to provide recommendations and strategies for future pandemics. In this retrospective study, CT acquisitions of COVID-19 patients scanned between March 2020 and October 2020 (RACOON phase 1) were included, and all non-contrast protocols were evaluated. For this purpose, CT protocol parameters, IQ ratings, radiation exposure (CTDIvol), and central patient diameters were sampled. Eventually, the data from 14 sites and 534 CT acquisitions were analyzed. IQ was rated good for 81% of the evaluated examinations. Motion, beam-hardening artefacts, or image noise were reasons for a suboptimal IQ. The tube potential ranged between 80 and 140 kVp, with the majority between 100 and 120 kVp. CTDIvol was 3.7 ± 3.4 mGy. Most healthcare facilities included did not have a specific non-contrast CT protocol. Furthermore, CT protocols for chest imaging varied in their settings and radiation exposure. In future, it will be necessary to make recommendations regarding the required IQ and protocol parameters for the majority of CT scanners to enable comparable IQ as well as radiation exposure for different sites but identical diagnostic questions.

Regional and interhemispheric differences of neuronal representations in dentate gyrus and CA3 inferred from expression of zif268.

The hippocampal formation is one of the best studied brain regions for spatial and mnemonic representations. These representations have been reported to differ in their properties for individual hippocampal subregions. One approach that allows the detection of neuronal representations is immediate early gene imaging, which relies on the visualization of genomic responses of activated neuronal populations, so called engrams. This method permits the within-animal comparison of neuronal representations across different subregions. In this work, we have used compartmental analysis of temporal activity by fluorescence in-situ hybridisation (catFISH) of the immediate early gene zif268/erg1 to compare neuronal representations between subdivisions of the dentate gyrus and CA3 upon exploration of different contexts. Our findings give an account of subregion-specific ensemble sizes. We confirm previous results regarding disambiguation abilities in dentate gyrus and CA3 but in addition report novel findings: Although ensemble sizes in the lower blade of the dentate gyrus are significantly smaller than in the upper blade both blades are responsive to environmental change. Beyond this, we show significant differences in the representation of familiar and novel environments along the longitudinal axis of dorsal CA3 and most interestingly between CA3 regions of both hemispheres.

MRI Signs of Parkinson's Disease and Atypical Parkinsonism. / Magnetresonanztomografische Zeichen des idiopathischen Parkinson-Syndroms sowie atypischer Parkinson-Syndrome.

BACKGROUND: Diagnosis of Parkinson's disease and atypical parkinsonism is based on clinical evaluation of the patient's symptoms and on magnetic resonance imaging (MRI) of the brain, which can be supplemented by nuclear medicine techniques. MRI plays a leading role in the differentiation between Parkinson's disease and atypical parkinsonism. While atypical parkinsonism is characterized by relatively specific MRI signs, imaging of Parkinson's disease previously lacked such signs. However, high-field MRI and new optimized MRI sequences now make it possible to define specific MRI signs of Parkinson's disease and have significant potential regarding differentiated imaging, early diagnosis, and imaging of disease progression. METHODS: PubMed was selectively searched for literature regarding the definition and discussion of specific MRI signs of Parkinson's disease, as well as the most common types of atypical parkinsonism with a leading motor component. No time frame was set, but the search was particularly focused on current literature. RESULTS: This review article discusses the different MRI signs of Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy. The pathogenesis of the MRI signs is described, and imaging examples are given. The technical aspects of image acquisition are briefly defined, and the different signs are discussed and compared with regard to their diagnostic significance according to current literature. CONCLUSION: The MRI signs of Parkinson's disease, which can be defined with high-field MRI and new optimized MRI sequences, enable differentiated structural image interpretation and consecutive diagnostic workup. Despite the fact that the signs are in need of further validation by bigger studies, they have the potential to achieve significant diagnostic relevance regarding the imaging of Parkinson's disease and atypical parkinsonism. KEY POINTS: · High-field MRI and specialized sequences make it possible to define specific MRI signs for neurodegenerative disorders. · Cerebral alterations can be detected in prodromal stages of Parkinson's disease. · The combination of specific MRI signs makes it possible to differentiate between Parkinson's disease and atypical parkinsonism. CITATION FORMAT: · Aludin S, Schmill LA. MRI Signs of Parkinson's Disease and Atypical Parkinsonism. Fortschr Röntgenstr 2021; 193: 1403 - 1410.