Faculty Bibliography

Impaired cerebral vascular reactivity (CVR) increases long-term stroke risk. Obstructive sleep apnoea (OSA) is associated with peripheral vascular dysfunction and vascular events. The aim of this trial was to evaluate the effect of continuous positive airway pressure (CPAP) withdrawal on CVR.41 OSA patients (88% male, mean age 57±10 years) were randomised to either subtherapeutic or continuation of therapeutic CPAP. At baseline and after 2 weeks, patients underwent a sleep study and magnetic resonance imaging (MRI). CVR was estimated by quantifying the blood oxygen level-dependent (BOLD) MRI response to breathing stimuli.OSA did recur in the subtherapeutic CPAP group (mean treatment effect apnoea-hypopnoea index +38.0 events·h^-1, 95% CI 24.2-52.0; p<0.001) but remained controlled in the therapeutic group. Although there was a significant increase in blood pressure upon CPAP withdrawal (mean treatment effect +9.37 mmHg, 95% CI 1.36-17.39; p=0.023), there was no significant effect of CPAP withdrawal on CVR assessed via BOLD MRI under either hyperoxic or hypercapnic conditions.Short-term CPAP withdrawal did not result in statistically significant changes in CVR as assessed by functional MRI, despite the recurrence of OSA. We thus conclude that, unlike peripheral endothelial function, CVR is not affected by short-term CPAP withdrawal.

OBJECTIVE:High breast density is a risk factor for breast cancer. The aim of this study was to develop a deep convolutional neural network (dCNN) for the automatic classification of breast density based on the mammographic appearance of the tissue according to the American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) Atlas. METHODS:In this study, 20,578 mammography single views from 5221 different patients (58.3 ± 11.5 years) were downloaded from the picture archiving and communications system of our institution and automatically sorted according to the ACR density (a-d) provided by the corresponding radiological reports. A dCNN with 11 convolutional layers and 3 fully connected layers was trained and validated on an augmented dataset. The model was finally tested on two different datasets against: i) the radiological reports and ii) the consensus decision of two human readers. None of the test datasets was part of the dataset used for the training and validation of the algorithm. RESULTS:The optimal number of epochs was 91 for medio-lateral oblique (MLO) projections and 94 for cranio-caudal projections (CC), respectively. Accuracy for MLO projections obtained on the validation dataset was 90.9% (CC: 90.1%). Tested on the first test dataset of mammographies (850 MLO and 880 CC), the algorithm showed an accordance with the corresponding radiological reports of 71.7% for MLO and of 71.0% for CC. The agreement with the radiological reports improved in the differentiation between dense and fatty breast for both projections (MLO = 88.6% and CC = 89.9%). In the second test dataset of 200 mammographies, a good accordance was found between the consensus decision of the two readers on both, the MLO-model (92.2%) and the right craniocaudal-model (87.4%). In the differentiation between fatty (ACR A/B) and dense breasts (ACR C/D), the agreement reached 99% for the MLO and 96% for the CC projections, respectively. CONCLUSIONS:The dCNN allows for accurate classification of breast density based on the ACR BI-RADS system. The proposed technique may allow accurate, standardized, and observer independent breast density evaluation of mammographies. ADVANCES IN KNOWLEDGE/CONCLUSIONS:Standardized classification of mammographies by a dCNN could lead to a reduction of falsely classified breast densities, thereby allowing for a more accurate breast cancer risk assessment for the individual patient and a more reliable decision, whether additional ultrasound is recommended.

OBJECTIVES/OBJECTIVE:To define normal signal intensity values of amide proton transfer-weighted (APTw) magnetic resonance (MR) imaging in different brain regions. MATERIALS AND METHODS/METHODS:= 2 μT, duration 2 s, 100% duty cycle) and 2D T2-weighted turbo spin echo (TSE) images were acquired. Postprocessing (image fusion, ROI measurements of APTw intensity values in 22 different brain regions) was performed and controlled by two independent neuroradiologists. Values were measured separately for each brain hemisphere. A subject was scanned both in prone and supine position to investigate differences between hemispheres. A mixed model on a 5% significance level was used to assess the effect of gender, brain region and side on APTw intensity values. RESULTS:= 0.24). APTw intensity values between the left and the right side were partially reversed after changing the position of one subject from supine to prone. CONCLUSION/CONCLUSIONS:We determined normal baseline APTw intensity values in different anatomical localizations in healthy subjects. APTw intensity values differed both between anatomical regions and between left and right brain hemisphere.

Recent research has focused on environmental effects that control tissue functionality and systemic metabolism. However, whether such stimuli affect human thermogenesis and body mass index (BMI) has not been explored. Here we show retrospectively that the presence of brown adipose tissue (BAT) and the season of conception are linked to BMI in humans. In mice, we demonstrate that cold exposure (CE) of males, but not females, before mating results in improved systemic metabolism and protection from diet-induced obesity of the male offspring. Integrated analyses of the DNA methylome and RNA sequencing of the sperm from male mice revealed several clusters of co-regulated differentially methylated regions (DMRs) and differentially expressed genes (DEGs), suggesting that the improved metabolic health of the offspring was due to enhanced BAT formation and increased neurogenesis. The conclusions are supported by cell-autonomous studies in the offspring that demonstrate an enhanced capacity to form mature active brown adipocytes, improved neuronal density and more norepinephrine release in BAT in response to cold stimulation. Taken together, our results indicate that in humans and in mice, seasonal or experimental CE induces an epigenetic programming of the sperm such that the offspring harbor hyperactive BAT and an improved adaptation to overnutrition and hypothermia.

The quantitative and non-invasive monitoring of cerebrospinal fluid (CSF) dynamics and composition may have high clinical relevance in the management of CSF disorders. In this study, we propose the use of the Intravoxel Incoherent Motion (IVIM) MRI for obtaining simultaneous measurements of CSF self-diffusion and fluid circulation. The rationale for this study was that turbulent fluid and mesoscopic fluid fluctuations can be modeled in a first approximation as a fast diffusion process. In this case, we expect that the fast fluid circulation and slower molecular diffusion dynamics can be quantified, assuming a bi-exponential attenuation pattern of the diffusion-weighted signal in MRI. IVIM indexes of fast and slow diffusion measured at different sites of the CSF system were systematically evaluated depending on both the phase of the heart cycle and the direction of the diffusion-encoding. The IVIM measurements were compared to dynamic measurements of fluid circulation performed by phase-contrast MRI. Concerning the dependence on the diffusion/flow-encoding direction, similar patterns were found both in the fraction of fast diffusion, f, and in the fluid velocity. Generally, we observed a moderate to high correlation between the fraction of fast diffusion and the maximum fluid velocity along the high-flow directions. Exploratory data analysis detected similarities in the dependency of the fraction of fast diffusion and of the velocity from the phase of the cardiac cycle. However, no significant differences were found between parameters measured during different phases of the cardiac cycle. Our results suggest that the fraction of fast diffusion may reflect CSF circulation. The bi-exponential IVIM model potentially allows us to disentangle the two diffusion components of the CSF dynamics by providing measurements of fluid cellularity (via the slow-diffusion coefficient) and circulation (via the fraction of fast-diffusion index).