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Goal: Critical closing pressure (CrCP) is the arterial blood pressure (ABP) threshold, below which small arterial vessels collapse and cerebral blood flow ceases. Here, we aim to compare three methods for CrCP estimation in scenario of a controlled increase in intracranial pressure (ICP), induced by infusion tests performed in patients with suspected normal pressure hydrocephalus (NPH). Methods: Computer recordings of directly-measured ICP, ABP, and transcranial Doppler cerebral blood flow velocity (CBFV), from 37 NPH patients undergoing infusion tests, were retrospectively analyzed. The CrCP was calculated with three methods: one with the first harmonics ratio of the pulse waveforms of ABP and CBFV (CrCPA) and two methods based on a model of cerebrovascular impedance, as functions of both cerebral perfusion pressure (CrCPinv), and of ABP (CrCPninv). Conclusion: All methods give similar results in response to ICP changes. In the case of individual CrCP measurements for each patient, CrCPA may provide negative, nonphysiological values. Invasive critical closing pressure is most sensitive to variations in ICP and CPP and can be used as an indicator of the cerebrospinal and the cerebrovascular system status during infusion tests. [ABSTRACT FROM PUBLISHER]

Objective: An increase in intracranial pressure (ICP) is frequently observed in patients with severe traumatic brain injury (TBI). The information derived from the observation of temporal changes in the mean ICP is insufficient for assessment of the compensatory reserve of the injured brain. This assessment can be achieved via continuous morphological analysis of the pulse waveform of the ICP. Methods: Continuous arterial blood pressure (ABP) and ICP recordings from 292 TBI patients were analyzed. The algorithm extracted morphological landmarks (peaks, troughs, and flats) from the ICP. Among the extracted peaks, P1, P2, and P3 were assigned through peak clustering. The performance of the proposed method was validated through a comparison of the algorithm-defined peaks and those manually identified by experienced observers. Results: The proposed algorithm successfully identified the three distinguishing peaks of the ICP with satisfactory accuracy (95.3%, 87.8%, and 87.5% for P1, P2, and P3, respectively), even from minimally filtered raw signals. Conclusion: The algorithm extracted the morphological features from both ABP and ICP recordings with high accuracy. Significance: The ABP and ICP pulse waveforms can be simultaneously analyzed in real time using the proposed algorithm. The morphological features from these signals may aid the continuous care of patients with TBI. [ABSTRACT FROM PUBLISHER]

Goal: The development of increasingly sophisticated cerebrospinal fluid (CSF) shunts calls for test beds that can reproduce an ever larger range of physiologic and pathophysiologic behaviors. In particular, upcoming smart and active devices will require extensive testing under complex dynamic conditions. Herein, we describe a test bed that allows for fast, cost effective, and realistic in vitro testing of active and passive, gravitational and nongravitational CSF shunts based on the hardware-in-the-loop principle. Methods: The shunt to be tested is placed in a dynamic in vitro setup that interfaces with a mathematical model of the patient's relevant physiology, which is evaluated numerically in real time. The model parameters can be identified using standard clinical tests. The test bed accounts for posture-dependent behavior and viscoelastic effects. Results: Simulations of infusion tests, of intracranial pressure modulation by cardiovascular action, and of the effects of postural changes show good agreement with published results. Evaluation of valves without and with gravitational units show in modeled sitting patients the expected behavior of overdrainage and avoidance thereof, respectively. Finally, a 24-h test cycle based on recorded patient data elucidates the interaction between patient and shunt system expressed by drainage rate and intracranial pressure during typical daily activities. Conclusion: We envision this test bed as a tool to quantify a shunt's performance within a realistic yet reproducible testing environment. Significance: The test bed can improve our understanding of the complex interaction between patient and shunt system and may catalyze the development of active shunts, while reducing the number of necessary in vivo experiments. [ABSTRACT FROM AUTHOR]

Hydrocephalus is characterized by an excessive accumulation of cerebrospinal fluid (CSF). Therapeutically, an artificial pressure relief valve (so-called shunt) is implanted which opens in case of increased intracranial pressure (ICP) and drains CSF into another body compartment. Today, available shunts are of a mechanical nature and drainage depends on the pressure drop across the shunt. According to the latest data, craniospinal compliance is considered to be even more important than mean ICP alone. In addition, ICP is not constant but varies due to several influences. In fact, heartbeat-related ICP waveform patterns depend on volume changes in the cranial vessels during a heartbeat and changes its shape as a function of craniospinal compliance. In this paper, we present an electromechanical shunt approach, which changes the CSF drainage as a function of the current ICP waveform. A series of 12 infusion tests in patients were analyzed and revealed a trend between the compliance and specific features of the ICP waveform. For waveform analysis of patient data, an existing signal processing algorithm was improved (using a Moore machine) and was implemented on a low-power microcontroller within the electromechanical shunt. In a test rig, the ICP waveforms were replicated and the decisions of the ICP analysis algorithm were verified. The proposed control algorithm consists of a cascaded integral controller which determines the target ICP from the measured waveform, and a faster inner-loop integral controller that keeps ICP close to the target pressure. Feedforward control using measurement data of the patient’s position was implemented to compensate for changes in hydrostatic pressure during change in position. A model-based design procedure was used to lay out controller parameters in a simple model of the cerebrospinal system. Successful simulation results have been obtained with this new approach by keeping ICP within the target range for a healthy waveform. [ABSTRACT FROM PUBLISHER]

We demonstrate the first automated, volumetric mosaicing algorithm for optical coherence tomography (OCT) that both accommodates 6-degree-of-freedom rigid transformations and implements a bundle adjustment step amenable to generating large fields of view with endoscopic and freehand imaging systems. Our mosaicing algorithm exploits the known, rigid connection between a combined white light and OCT imaging system to reduce the computational complexity of traditional volumetric mosaicing pipelines. Specifically, the search for 3-D point correspondences is replaced by two, 2-D processing steps: We first coregister a pair of white light images in 2-D and then generate a surface map based on the volumetric OCT data, which is used to convert 2-D image homographies into 3-D volumetric transformations. A significant benefit of our dual-modality approach is its tolerance for feature-poor datasets such as bladder tissue; in contrast, approaches to mosaic feature-rich volumes with significant variations in the local intensity gradient (e.g., retinal data containing prolific vasculature) are not suitable for such feature-poor datasets. We demonstrate the performance of our algorithm using ex vivo bladder tissue and a custom tissue-mimicking phantom. The algorithm shows excellent performance over the range of volume-to-volume transformations expected during endoscopic examination and comparable accuracy with several orders of magnitude superior run times than an open-source gold-standard algorithm (N-SIFT). We anticipate the proposed algorithm can benefit bladder surveillance and surgical planning. Furthermore, its generality gives it broad applicability and potential to extend the use of OCT to clinical applications relevant to large organs typically imaged with freehand, forward-viewing endoscopes. [ABSTRACT FROM PUBLISHER]

The long-term monitoring of intracranial pressure (ICP) is important for the management of acute and chronic neuropathological conditions which include head injury, traumatic brain injury, hydrocephalus, etc. In this study, we developed an implantable device for measuring ICP over long periods of time in an animal model of blast-induced brain injury. The performance of the device was first evaluated in vitro and subsequently utilized to measure ICP in rats exposed to blast overpressures. The effects of blast-induced brain injury on ICP were measured for six days. A significant difference was observed between the injured group and the nonexposed control group. ICP in injured animals showed a biphasic transient increase; an immediate increase within the first 1–3 h and a more gradual elevation occurring two days after the blast. The ability to monitor changes of ICP continuously over long periods after brain injury and during the course of treatment may improve the prognosis after injury and can also serve as a tool in determining the therapeutic effectiveness of new drugs. [ABSTRACT FROM PUBLISHER]

Improvements in cerebrospinal fluid (CSF) draining techniques for treatment of hydrocephalus are urgently sought after to substitute for current CSF shunts that are plagued by high failure rates. The passive check valve aims to restore near natural CSF draining operations while mitigating possible failure mechanisms caused by finite leakage or low resilience that frequently constrain practical implementation of miniaturized valves. A simple hydrogel diaphragm structures core passive valve operations and enforce valve sealing properties to substantially lower reverse flow leakage. Experimental measurements demonstrate realization of targeted cracking pressures (PT ≈ 20–110 mmH2O) and operation at –800 < ΔP < 600 mmH2O without observable degradation or leakage. [ABSTRACT FROM PUBLISHER]

This paper reports a novel method for deformable registration of digital anatomical surfaces. The method capitalizes upon the iterative local affine iterative closest point (ICP) approach that applies an affine transformation per surface vertex along with a regularization constraint to force neighboring surface vertices to undergo similar transformations. More robust vertex correspondence with respect to simple closest point was obtained by exploiting local shape similarity metrics, which includes vertex distance, surface normal, and local curvature. The local curvature was mean shifted at run-time, during the iterative optimization, to make the point correspondence process less dependent upon the surface noise and resolution. The experimental validation was performed on three surface datasets (femur, hemi-pelvic bone, and liver). The registration results showed that the proposed method outperforms, across all the three surface datasets (rmse: 0.19 mm, 0.30 mm, 0.61 mm), global affine ICP (rmse: 2.89 mm, 3.95 mm, and 8.30 mm), local affine ICP (rmse: 0.31 mm, 1.61 mm, and 1.63 mm) and coherent point drift (rmse: 1.99 mm, 2.39 mm, and 4.78 mm) methods. As a whole, the mean-shifted curvature increased the registration accuracy by about 20%. [ABSTRACT FROM PUBLISHER]

Transcatheter aortic valve implantation (TAVI) is a minimally invasive alternative to conventional aortic valve replacement for severe aortic stenosis in high-risk patients in which a stent-based bioprosthetic valve is delivered into the heart via a catheter. TAVI relies largely on single-plane fluoroscopy for intraoperative navigation and guidance, which provides only gross imaging of anatomical structures. Inadequate imaging leading to suboptimal valve positioning contributes to many of the early complications experienced by TAVI patients, including valve embolism, coronary ostia obstruction, paravalvular leak, heart block, and secondary nephrotoxicity from excessive contrast use. Improved visualization can be provided using intraoperative registration of a CT-derived surface to transesophageal echo (TEE) images. In this study, the accuracy and robustness of a surface-based registration method suitable for intraoperative use are evaluated, and the performances of different TEE surface extraction methods are compared. The use of cross-plane TEE contours demonstrated the best accuracy, with registration errors of less than 5  mm. This guidance system uses minimal intraoperative interaction and workflow modification, does not require tool calibration or additional intraoperative hardware, and can be implemented at all cardiac centers at extremely low cost. [ABSTRACT FROM PUBLISHER]

Nowadays, the Intracranial Pressure (ICP) monitoring has become the most common method of investigation for both traumatic and chronic neural pathologies. ICP signals are typically triphasic, that is, in a single waveform, three subpeaks can be identified. This work outlines a new algorithm to identify subpeaks from the ICP recordings and to extract a number of 20 meaningful parameter trends. The validity of the implemented method has been proved through a comparison between the automatic subpeaks identification by the algorithm and the manually marked subpeaks by a neurosurgeon. The automatic marking system has identified subpeaks for the 63.74% (mean value) of pulse waves, providing the position and amplitude of each identified subpeak within a tolerance of ±7 samples. This automatic system provides a feature set to be used by classification software to obtain more precise and easier diagnosis in all those cases that involve brain damages or diseases. [ABSTRACT FROM PUBLISHER]

False alarms produced by patient monitoring systems in intensive care units are a major issue that causes alarm fatigue, waste of human resources, and increased patient risks. While alarms are typically triggered by manually adjusted thresholds, the trend and patterns observed prior to threshold crossing are generally not used by current systems. This study introduces and evaluates, a smart alarm detection system for intracranial pressure signal (ICP) that is based on advanced pattern recognition methods. Models are trained in a supervised fashion from a comprehensive dataset of 4791 manually labeled alarm episodes extracted from 108 neurosurgical patients. The comparative analysis provided between spectral regression, kernel spectral regression, and support vector machines indicates the significant improvement of the proposed framework in detecting false ICP alarms in comparison to a threshold-based technique that is conventionally used. Another contribution of this work is to exploit an adaptive discretization to reduce the dimensionality of the input features. The resulting features lead to a decrease of 30% of false ICP alarms without compromising sensitivity. [ABSTRACT FROM PUBLISHER]

Regulation of intracranial pressure (ICP) is vital to proper brain function. Pathologic conditions such as traumatic brain injury and hydrocephalus can cause lethal changes in ICP through an imbalance of fluid passage into and out of the craniospinal space. The relationship between craniospinal volume and pressure determines to a large extent whether such imbalance can be compensated or if it will lead to neuronal damage. Phantom models are predisposed for the evaluation of medical procedures and devices that alter volume in the spinal or cranial space. However, current phantoms have substantial limitations in the reproduction of craniospinal pressure–volume relationships, which need to be overcome prior to their deployment outside the basic research setting. We present herein a novel feedback controlled phantom for the reproduction of any physiologic or pathologic pressure–volume relation. We compare its performance to those of existing passive methods, showing that it follows reference curves more precisely during both infusion of large volumes and fast oscillatory volume changes. [ABSTRACT FROM PUBLISHER]

We describe herein a novel life-size phantom model of the intracranial cavity and its validation. The cerebrospinal fluid (CSF) domains including ventricular, cysternal, and subarachnoid spaces were derived via magnetic resonance imaging. Brain mechanical properties and cranio-spinal compliance were set based on published data. Both bulk and pulsatile physiologic CSF flow were modeled. Model validation was carried out by comparisons of flow and pressure measurements in the phantom with published in vivo data of healthy subjects. Physiologic intracranial pressure with 10 mmHg mean and 0.4 mmHg peak pulse amplitude was recorded in the ventricles. Peak CSF flow rates of 0.2 and 2 ml/s were measured in the cerebral aqueduct and subarachnoid space, respectively. The phantom constitutes a first-of-its-kind approach to modeling physiologic intracranial dynamics in vitro. Herein, we describe the phantom design and manufacturing, definition and implementation of its operating parameters, as well as the validation of the modeled dynamics. [ABSTRACT FROM PUBLISHER]

The current gold standard to determine intracranial pressure (ICP) involves an invasive procedure for direct access to the intracranial compartment. The risks associated with this invasive procedure include intracerebral hemorrhage, infection, and discomfort. We previously proposed an innovative data-mining framework of noninvasive ICP (NICP) assessment. The performance of the proposed framework relies on designing a good mapping function. We attempt to achieve performance gain by adopting various linear and nonlinear mapping functions. Our results demonstrate that a nonlinear mapping function based on the kernel spectral regression technique significantly improves the performance of the proposed data-mining framework for NICP assessment in comparison to other linear mapping functions. [ABSTRACT FROM PUBLISHER]

Myogenic autoregulation of cerebral blood flow is one of the mechanisms affecting cerebral hemodynamics. Short or long-lasting changes in intracranial pressure (ICP) are believed to reveal the responses of the cerebral system to myogenic stimuli. Through the incorporation of a theoretical model into the experimental measurements of cerebrovascular distensibility and compliance in patients with traumatic brain injury (TBI), the current study is an attempt to explain ICP dynamics in either presence or absence of cerebral autoregulation. The pulse wave velocity and transfer function between arterial blood pressure and ICP were utilized as the major tools to reflect variations in the mechanical properties of distant cerebral artries/arteriols. The results imply that different states of cerebral autoregulation and associated regimes within the cerebrovascular system can lead to different types of interrelationship between the slow variations of ICP, cerebral arterial distensibility, and compliance. Consequently, each of these classes may require different types of treatment on patients with TBI. [ABSTRACT FROM AUTHOR]