A sex-specific association of leukocyte telomere length with thigh muscle mass.

OBJECTIVES: Telomeres are DNA-protein complexes at the ends of linear chromosomes that protect against DNA degradation. Telomeres shorten during normal cell divisions and therefore, telomere length is an indicator of mitotic-cell age. In humans, telomere shortening is a potential biomarker for disease risk, progression and premature death. Physical activity has been associated with longer leukocyte telomere length (LTL) in some studies. In the current study the relationship between LTL, thigh muscle mass and adipose tissue distribution was explored. METHODS: We performed anthropometric measurements and magnetic resonance imaging (MRI) measurements of the thigh in 149 healthy subjects (77 male, 72 female). LTL was measured using qPCR. Additionally, the subjects answered a questionnaire concerning their training behaviour. RESULTS: In male subjects, LTL was significantly associated with thigh muscle mass, independent of age and body mass index (p=0.006). In addition, a slight association of LTL with weekly endurance units in the male group was found. These relations could not be observed in females. CONCLUSIONS: In conclusion, we observed a sex-specific association of LTL and thigh muscle mass in healthy males. The reason of this sex-specific association is currently unclear, but could be related to different training effects and/or hormonal pathways in men and women.

Fractal-Based Analysis of Arteriovenous Malformations (AVMs).

Arteriovenous malformations (AVMs) are cerebrovascular lesions consisting of a pathologic tangle of the vessels characterized by a core termed the nidus, which is the "nest" where the fistulous connections occur. AVMs can cause headache, stroke, and/or seizures. Their treatment can be challenging requiring surgery, endovascular embolization, and/or radiosurgery as well. AVMs' morphology varies greatly among patients, and there is still a lack of standardization of angioarchitectural parameters, which can be used as morphometric parameters as well as potential clinical biomarkers (e.g., related to prognosis).In search of new diagnostic and prognostic neuroimaging biomarkers of AVMs, computational fractal-based models have been proposed for describing and quantifying the angioarchitecture of the nidus. In fact, the fractal dimension (FD) can be used to quantify AVMs' branching pattern. Higher FD values are related to AVMs characterized by an increased number and tortuosity of the intranidal vessels or to an increasing angioarchitectural complexity as a whole. Moreover, FD has been investigated in relation to the outcome after Gamma Knife radiosurgery, and an inverse relationship between FD and AVM obliteration was found.Taken altogether, FD is able to quantify in a single and objective value what neuroradiologists describe in qualitative and/or semiquantitative way, thus confirming FD as a reliable morphometric neuroimaging biomarker of AVMs and as a potential surrogate imaging biomarker. Moreover, computational fractal-based techniques are under investigation for the automatic segmentation and extraction of the edges of the nidus in neuroimaging, which can be relevant for surgery and/or radiosurgery planning.

Real-time estimation of the optimal coil placement in transcranial magnetic stimulation using multi-task deep learning.

Transcranial magnetic stimulation (TMS) has emerged as a promising neuromodulation technique with both therapeutic and diagnostic applications. As accurate coil placement is known to be essential for focal stimulation, computational models have been established to help find the optimal coil positioning by maximizing electric fields at the cortical target. While these numerical simulations provide realistic and subject-specific field distributions, they are computationally demanding, precluding their use in real-time applications. In this paper, we developed a novel multi-task deep neural network which simultaneously predicts the optimal coil placement for a given cortical target as well as the associated TMS-induced electric field. Trained on large amounts of preceding numerical optimizations, the Attention U-Net-based neural surrogate provided accurate coil optimizations in only 35 ms, a fraction of time compared to the state-of-the-art numerical framework. The mean errors on the position estimates were below 2 mm, i.e., smaller than previously reported manual coil positioning errors. The predicted electric fields were also highly correlated (r> 0.97) with their numerical references. In addition to healthy subjects, we validated our approach also in glioblastoma patients. We first statistically underlined the importance of using realistic heterogeneous tumor conductivities instead of simply adopting values from the surrounding healthy tissue. Second, applying the trained neural surrogate to tumor patients yielded similar accurate positioning and electric field estimates as in healthy subjects. Our findings provide a promising framework for future real-time electric field-optimized TMS applications.

Wall Enhancement of Coiled Intracranial Aneurysms Is Associated with Aneurysm Recanalization: A Cross-Sectional Study.

BACKGROUND AND PURPOSE: Wall enhancement of untreated intracranial aneurysms on MR imaging is thought to predict aneurysm instability. Wall enhancement or enhancement of the aneurysm cavity in coiled intracranial aneurysms is discussed controversially in the literature regarding potential healing mechanisms or adverse inflammatory reactions. Our aim was to compare the occurrence of aneurysm wall enhancement and cavity enhancement between completely occluded intracranial aneurysms and recanalized aneurysms after initially complete coil embolization. MATERIALS AND METHODS: In this single-center cross-sectional study, we evaluated intracranial aneurysms after successful coil embolization for aneurysm recanalization, wall enhancement, and cavity enhancement with 3T MR imaging. We then compared the incidence of wall enhancement and cavity enhancement of completely occluded aneurysms with aneurysms with recanalization using the χ2 test and performed a multivariate linear regression analysis with recanalization size as an independent variable. RESULTS: We evaluated 59 patients (mean age, 54.7 [SD, 12.4] years; 48 women) with 60 intracranial aneurysms and found a significantly higher incidence of wall enhancement in coiled aneurysms with recanalization (n=38) compared with completely occluded aneurysms (n = 22, P = .036). In addition, there was a significantly higher incidence of wall enhancement in aneurysms with recanalization of >3 mm (P = .003). In a multivariate linear regression analysis, wall enhancement (P = .010) and an increase of overall aneurysm size after embolization (P < .001) were significant predictors of recanalization size (corrected R 2= 0.430, CI 95%). CONCLUSIONS: The incidence of aneurysm wall enhancement is increased in coiled intracranial aneurysms with recanalization and is associated with recanalization size.

White matter integrity and functional connectivity of the default mode network in acute stroke are associated with cognitive outcome three months post-stroke.

BACKGROUND: Knowledge about factors that are associated with post-stroke cognitive outcome is important to identify patients with high risk for impairment. We therefore investigated the associations of white matter integrity and functional connectivity (FC) within the brain's default-mode network (DMN) in acute stroke patients with cognitive outcome three months post-stroke. METHODS: Patients aged between 18 and 85 years with an acute symptomatic MRI-proven unilateral ischemic middle cerebral artery infarction, who had received reperfusion therapy, were invited to participate in this longitudinal study. All patients underwent brain MRI within 24-72 h after symptom onset, and participated in a neuropsychological assessment three months post-stroke. We performed hierarchical regression analyses to explore the incremental value of baseline white matter integrity and FC beyond demographic, clinical, and macrostructural information for cognitive outcome. RESULTS: The study cohort comprised 34 patients (mean age: 64 ± 12 years, 35% female). The initial median National Institutes of Health Stroke Scale (NIHSS) score was 10, and significantly improved three months post-stroke to a median NIHSS = 1 (p < .001). Nonetheless, 50% of patients showed cognitive impairment three months post-stroke. FC of the non-lesioned anterior cingulate cortex of the affected hemisphere explained 15% of incremental variance for processing speed (p = .007), and fractional anisotropy of the non-lesioned cingulum of the affected hemisphere explained 13% of incremental variance for cognitive flexibility (p = .033). CONCLUSIONS: White matter integrity and functional MRI markers of the DMN in acute stroke explain incremental variance for post-stroke cognitive outcome beyond demographic, clinical, and macrostructural information.