1,721,122 research outputs found
The intracranial Windkessel implies arteriovenous pulsatile coupling increased by venous resistances
Full text linkVarious detailed models of cerebral circulation have been proposed, recently fostered by the hypothesized relationship between extracranial venous drainage impairment and neurodegenerative diseases. However, some basic model is missing, analogous to the 2-element Windkessel (WK) of the systemic circulation. This theoretical study focuses, in the simplest way, on the dependence of intracranial venous pressure (VP) pulsatility on the intracranial arterial 2-element WK and the venous resistance RV. The WK compliance is shown to exert an arteriovenous capacitive coupling (AV-CC), agumented by RV increments. The WK was estimated based on the intracranial arterial pressure (AP) and flow (ФICA) waves of an open database of 3325 virtual subjects. A normal RV was estimated imposing a mean VP of 10 mmHg, doubled to mimic hindered extracranial veins. The AP to VP transfer function showed: i) a gain almost proportional to RV; ii) a zero slightly below heart rate (HR) corresponding to the arterial WK pole; iii) a mid-frequency derivative band up to the AV-CC pole, the frequency of which was almost inversely proportional to RV; iv) full coupling at high frequencies, yet above the pulse harmonic content, at normal HR. In conclusion, besides the well-known effect of venous hindering on the mean VP, the results of this model support the hypothesis that abnormal pulsatility of cerebral veins may play a significant role in cerebrovascular imbalance and related neurodegeneration
The Strange Cerebrovascular Windkessel: a Simplified Model
No full textChronic cerebrospinal venous insufficiency (CCSVI) has been focused as a hypothetical concause in neurodegeneration. Mechanisms related to venous stasis are mainly considered; conversely, effects on venous pulse in the stiff intracranial (IC) compartment are poorly understood. Insight is here sought through a hyper-simplified model, including the IC arterial Windkessel (WK) and the arterio-venous capacitive coupling. The IC-WK was dimensioned by an open database. The resulting arterio-venous propagation of pulse showed phase anticipation and amplification of higher harmonics, which effect were noticeably augmented in CCSVI
Vascular dysfunction and autonomic failure are associated in a porcine model of septic shock and resuscitation
No full textAcute inflammation and sepsis are known to impair endothelial functions and autonomic nervous system (ANS)-based regulatory mechanisms. Our objective is to assess the effectiveness of standard resuscitation at vascular level and to investigate if there is any association between vascular and autonomic alterations. Six pigs underwent to a protocol of polymicrobial septic shock and resuscitation (fluids and noradrenaline). The characteristic arterial time constant au was computed in aorta and in the femoral artery, together with estimates of total arterial compliance and peripheral resistance. Baroreflex sensitivity was computed to assess ANS functionality. Septic shock induced a severe vascular disarray and ANS dysfunction, which resulted correlated. This compromised condition was not resolved by resuscitation. Measures of vascular function and ANS activity may represent useful end-points to guide the resuscitation, in combination with standard hemodynamic and clinical markers
Vascular Decoupling in Septic Shock: The Combined Role of Autonomic Nervous System, Arterial Stiffness, and Peripheral Vascular Tone
Full text linkBackground: Acute inflammation and sepsis are known to induce changes in vascular properties, leading to increased arterial stiffness; at the same time, the autonomic nervous system (ANS) also affects vascular properties by modulating the arterial smooth muscle tone, and it is widely reported that sepsis and septic shock severely impair ANS activity. Currently, clinical guidelines are mainly concerned to resuscitate septic shock patients from hypotension, hypovolemia, and hypoperfusion; however, if the current resuscitation maneuvers have a beneficial effect also on vascular properties and autonomic functionality is still unclear. The objective of this work is to assess the effects of standard resuscitation at vascular level and to verify if there is any association between alterations in vascular properties and ANS activity. Methods: Six pigs underwent a protocol of polymicrobial septic shock and resuscitation (fluids and noradrenaline). The arterial blood pressure (ABP) waveform was recorded in the central aorta and in the peripheral radial and femoral artery. The characteristic arterial time constant was computed at the three arterial sites based on the two-element Windkessel model, to characterize the overall arterial vascular tree. Moreover, independent estimates of total arterial compliance (AC) and total peripheral resistance (TPR) were performed. Baroreflex sensitivity (BRS), low frequency (LF, 0.04–0.15 Hz) spectral power of diastolic blood pressure, and indices of heart rate variability (HRV) were computed to assess ANS functionality. Results: Septic shock induced a severe vascular disarray, decoupling the usual pressure wave propagation from central to peripheral sites; this phenomenon appeared as an inversion of the physiological pulse pressure (PP) amplification, with a higher PP in the central aorta than in the peripheral arteries. The time constant was decreased, together with AC and TPR. ANS dysfunction was described by a reduced BRS, decreased LF power, and suppressed HRV. This compromised condition was not resolved by administration of fluids and noradrenaline. Thus, a persistent vascular and autonomic dysfunction were reported also in the resuscitated animals, and they were found to be significantly correlated. Conclusion: Measures of vascular function and ANS activity could add information to standard hemodynamic and clinical markers, and the current resuscitation strategies could benefit from the adjunction of these additional functional indices
Opening the black box of machine learning in radiology: can the proximity of annotated cases be a way?
Full text linkMachine learning (ML) and deep learning (DL) systems, currently employed in medical image analysis, are data-driven models often considered as black boxes. However, improved transparency is needed to translate automated decision-making to clinical practice. To this aim, we propose a strategy to open the black box by presenting to the radiologist the annotated cases (ACs) proximal to the current case (CC), making decision rationale and uncertainty more explicit. The ACs, used for training, validation, and testing in supervised methods and for validation and testing in the unsupervised ones, could be provided as support of the ML/DL tool. If the CC is localised in a classification space and proximal ACs are selected by proper metrics, the latter ones could be shown in their original form of images, enriched with annotation to radiologists, thus allowing immediate interpretation of the CC classification. Moreover, the density of ACs in the CC neighbourhood, their image saliency maps, classification confidence, demographics, and clinical information would be available to radiologists. Thus, encrypted information could be transmitted to radiologists, who will know model output (what) and salient image regions (where) enriched by ACs, providing classification rationale (why). Summarising, if a classifier is data-driven, let us make its interpretation data-driven too
Optimal flow conditions of a tracheobronchial model to reengineer lung structures
No full textThe high demand for lung transplants cannot be matched by an adequate number of lungs from donors. Since fully ex-novo lungs are far from being feasible, tissue engineering is actively considering implantation of engineered lungs where the devitalized structure of a donor is used as scaffold to be repopulated by stem cells of the receiving patient. A decellularized donated lung is treated inside a bioreactor where transport through the tracheobronchial tree (TBT) will allow for both deposition of stem cells and nourishment for their subsequent growth, thus developing new lung tissue. The key concern is to set optimally the boundary conditions to utilize in the bioreactor. We propose a predictive model of slow liquid ventilation, which combines a one-dimensional (1-D) mathematical model of the TBT and a solute deposition model strongly dependent on fluid velocity across the tree. With it, we were able to track and drive the concentration of a generic solute across the airways, looking for its optimal distribution. This was given by properly adjusting the pumps’ regime serving the bioreactor. A feedback system, created by coupling the two models, allowed us to derive the optimal pattern. The TBT model can be easily invertible, thus yielding a straightforward flow/pressure law at the inlet to optimize the efficiency of the bioreactor
Assessment of fnirs signal processing pipelines: Towards clinical applications
Full text linkFeatured Application: In neurodegenerative diseases and neurorehabilitation, follow-up requires instrumental evidence besides clinical cognitive and motor scores. fMRI is frequently not suitable, either because patients are not eligible for an MRI or because it is prone to motion artifacts. The fNIRS technique attenuates these limitations since brain activations can be measured in a more versatile experimental setting, even if restricted to cortical activity. Therefore, the roadmap towards full clinical acceptance of fNIRS aims to provide an additional and more flexible solution to fMRI when not available or feasible, but it needs standard signal processing and protocols. This study provides comparisons of alternative processing methods in the above applicative perspective. Abstract: Functional Near-Infrared Spectroscopy (fNIRS) captures activations and inhibitions of cortical areas and implements a viable approach to neuromonitoring in clinical research. Compared to more advanced methods, continuous wave fNIRS (CW-fNIRS) is currently used in clinics for its simplicity in mapping the whole sub-cranial cortex. Conversely, it often lacks hardware reduction of confounding factors, stressing the importance of a correct signal processing. The proposed pipeline includes movement artifact reduction (MAR), bandpass filtering (BPF), and principal component analysis (PCA). Eight MAR algorithms were compared among 23 young adult volunteers under motor-grasping task. Single-subject examples are shown followed by the percentage in energy reduction (ERD%) statistics by single steps and cumulative values. The block average of the hemodynamic response function was compared with generalized linear model fitting. Maps of significant activation/inhibition were illustrated. The mean ERD% of pre-processed signals concerning the initial raw signal energy reached 4%. A tested multichannel MAR variant showed overcorrection on 4-fold more expansive windows. All of the MAR algorithms found similar activations in the contra-lateral motor area. In conclusion, single channel MAR algorithms are suggested followed by BPF and PCA. The importance of whole cortex mapping for fNIRS integration in clinical applications was also confirmed by our results
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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