Boundary conditions investigation to improve computer simulation of cerebrospinal fluid dynamics in hydrocephalus patients

Comprehensive Morphometric Analysis to Identify Key Neuroimaging Biomarkers for the Diagnosis of Adult Hydrocephalus Using Artificial Intelligence

BACKGROUND AND OBJECTIVES

Hydrocephalus involves abnormal cerebrospinal fluid accumulation in brain ventricles. Early and accurate diagnosis is crucial for timely intervention and preventing progressive neurological deterioration. The aim of this study was to identify key neuroimaging biomarkers for the diagnosis of hydrocephalus using artificial intelligence to develop practical and accurate diagnostic tools for neurosurgeons.

METHODS

Fifteen 1-dimensional (1-D) neuroimaging parameters and ventricular volume of adult patients with non-normal pressure hydrocephalus and healthy subjects were measured using manual image processing, and 10 morphometric indices were also calculated. The data set was analyzed using 8 machine, ensemble, and deep learning classifiers to predict hydrocephalus. SHapley Additive exPlanations (SHAP) feature importance analysis identified key neuroimaging diagnostic biomarkers.

RESULTS

Gradient Boosting achieved the highest performance, with an accuracy of 0.94 and an area under the curve of 0.97. SHAP analysis identified ventricular volume as the most important parameter. Given the challenges of measuring volume for clinicians, we identified key 1-D morphometric biomarkers that are easily measurable yet provide similar classifier performance. The results showed that the frontal-temporal horn ratio, modified Evan index, modified cella media index, sagittal maximum lateral ventricle height, and coronal posterior callosal angle are key 1-D diagnostic biomarkers. Notably, higher modified Evan index, modified cella media index, and sagittal maximum lateral ventricle height, and lower frontal-temporal horn ratio and coronal posterior callosal angle values were associated with hydrocephalus prediction. The results also elucidated the relationships between these key 1-D morphometric parameters and ventricular volume, providing potential diagnostic insights.

CONCLUSION

This study highlights the importance of a multifaceted diagnostic approach incorporating 5 easily measurable 1-D neuroimaging biomarkers for neurosurgeons to differentiate non-normal pressure hydrocephalus from healthy subjects. Incorporating our artificial intelligence model, interpreted through SHAP analysis, into routine clinical workflows may transform the diagnostic landscape for hydrocephalus by standardizing diagnosis and overcoming the limitations of visual evaluations, particularly in early stages and challenging cases.

Super-Resolving and Denoising 4D flow MRI of Neurofluids Using Physics-Guided Neural Networks

PURPOSE

To obtain high-resolution velocity fields of cerebrospinal fluid (CSF) and cerebral blood flow by applying a physics-guided neural network (div-mDCSRN-Flow) to 4D flow MRI.

METHODS

The div-mDCSRN-Flow network was developed to improve spatial resolution and denoise 4D flow MRI. The network was trained with patches of paired high-resolution and low-resolution synthetic 4D flow MRI data derived from computational fluid dynamic simulations of CSF flow within the cerebral ventricles of five healthy cases and five Alzheimer's disease cases. The loss function combined mean squared error with a binary cross-entropy term for segmentation and a divergence-based regularization term for the conservation of mass. Performance was assessed using synthetic 4D flow MRI in one healthy and one Alzheimer' disease cases, an in vitro study of healthy cerebral ventricles, and in vivo 4D flow imaging of CSF as well as flow in arterial and venous blood vessels. Comparison was performed to trilinear interpolation, divergence-free radial basis functions, divergence-free wavelets, 4DFlowNet, and our network without divergence constraints.

RESULTS

The proposed network div-mDCSRN-Flow outperformed other methods in reconstructing high-resolution velocity fields from synthetic 4D flow MRI in healthy and AD cases. The div-mDCSRN-Flow network reduced error by 22.5% relative to linear interpolation for in vitro core voxels and by 49.5% in edge voxels.

CONCLUSION

The results demonstrate generalizability of our 4D flow MRI super-resolution and denoising approach due to network training using flow patches and physics-based constraints. The mDCSRN-Flow network can facilitate MRI studies involving CSF flow measurements in cerebral ventricles and association of MRI-based flow metrics with cerebrovascular health.

Optimization of number and range of shunt valve performance levels in infant hydrocephalus: a machine learning analysis

Shunt surgery is the main treatment modality for hydrocephalus, the leading cause of brain surgery in children. The efficacy of shunt surgery, particularly in infant hydrocephalus, continues to present serious challenges in achieving improved outcomes. The crucial role of correct adjustments of valve performance levels in shunt outcomes has been underscored. However, there are discrepancies in the performance levels of valves from different companies. This study aims to address this concern by optimizing both the number and range of valve performance levels for infant hydrocephalus, aiming for improved shunt surgery outcomes. We conducted a single-center cohort study encompassing infant hydrocephalus cases that underwent initial shunt surgery without subsequent failure or unimproved outcomes. An unsupervised hierarchical machine learning method was utilized for clustering and reporting the valve drainage pressure values for all patients within each identified cluster. The optimal number of clusters corresponds to the number of valve performance levels, with the valve drainage pressure ranges within each cluster indicating the pressure range for each performance level. Comparisons based on the Silhouette coefficient between 3-7 clusters revealed that this coefficient for the 4-cluster (4-performance level) was at least 28.3% higher than that of other cluster formations in terms of intra-cluster similarity. The Davies-Bouldin index for the 4-performance level was at least 37.2% lower than that of other configurations in terms of inter-cluster dissimilarity. Cluster stability, indicated by a Jaccard index of 71% for the 4-performance level valve, validated the robustness, reliability, and repeatability of our findings. Our suggested optimized drainage pressure ranges for each performance level (1.5-5.0, 5.0-9.0, 9.0-15.0, and 15.0-18.0 cm H2O) may potentially assist neurosurgeons in improving clinical outcomes for patients with shunted infantile hydrocephalus.

Feasibility of assessing non-invasive intracranial compliance using FSI simulation-based and MR elastography-based brain stiffness

Intracranial compliance (ICC) refers to the change in intracranial volume per unit change in intracranial pressure (ICP). Magnetic resonance elastography (MRE) quantifies brain stiffness by measuring the shear modulus. Our objective is to investigate the relationship between ICC and brain stiffness through fluid-structure interaction (FSI) simulation, and to explore the feasibility of using MRE to assess ICC based on brain stiffness. This is invaluable due to the clinical importance of ICC, as well as the fast and non-invasive nature of the MRE procedure. We employed FSI simulation in hydrocephalus patients with aqueductal stenosis to non-invasively calculate ICP which is the basis of the calculation of ICC and FSI-based brain stiffness. The FSI simulated parameters used have been validated with experimental data. Our results showed that there is no relationship between FSI simulated-based brain stiffness and ICC in hydrocephalus patients. However, MRE-based brain stiffness may be sensitive to changes in intracranial fluid dynamic parameters such as cerebral perfusion pressure (CPP), cerebral blood flow (CBF), and ICP, as well as to mechano-vascular changes in the brain, which are determining parameters in ICC assessment. Although optimism has been found regarding the assessment of ICC using MRE-based brain stiffness, especially for acute-onset brain disorders, further studies are necessary to clarify their direct relationship.

Computational Fluid Dynamics of Cerebrospinal Fluid

Cerebrospinal fluid (CSF) plays a critical role in the healthy function of the brain, yet the mechanics of CSF flow remain poorly understood. Computational fluid dynamics is a powerful tool capable of resolving the spatiotemporal evolution of CSF pressures and velocities, but technical and methodological limitations have limited the clinical use of CFD to date. With improvements in medical imaging, computational power, and machine learning, however, CFD may be on the cusp of breaking through into the medical mainstream. In this chapter, we will review the applications of CFD of CSF, present our methodological recommendations for conducting CFD of CSF, present the results of a novel CFD methodology incorporating patient-specific tissue displacements, and discuss the barriers and pathways to clinically useful CFD simulation.

Impact of thermodynamical rotational flow of cerebrospinal fluid in the presence of elasticity

OBJECTIVE

To explore the experimental justification of cerebrospinal fluid (CSF) amplitude and elastic fluctuations of ventricles, we extend our previous computational study to models with rotational flow and suitable boundary conditions. In the present study, we include an elastic effect due to the interaction with the thermal solutal model which accounts for CSF motion which flows rotationally due to hydrocephalus flows within the spinal canal.

METHODS

Using an analytical pertubation method, we have attempted a new model to justify CSF flow movement using the influences of wall temperature difference.

RESULTS

This paper presents results from a computational study of the biomechanics of hydrocephalus, with special emphasis on a reassessment of the parenchymal elastic module. CSF amplitude in hydrocephalus patients is 2.7 times greater than that of normal subjects.

CONCLUSIONS

This finding suggests a non-linear mechanical system to present the hydrocephalic condition using a numerical model. The results can be useful to relieve the complexities in the mechanism of hydrocephalus and can shed light to support clinically for a convincing simulation.

Why Intracranial Compliance Is Not Utilized as a Common Practical Tool in Clinical Practice

Intracranial compliance (ICC) holds significant potential in neuromonitoring, serving as a diagnostic tool and contributing to the evaluation of treatment outcomes. Despite its comprehensive concept, which allows consideration of changes in both volume and intracranial pressure (ICP), ICC monitoring has not yet established itself as a standard component of medical care, unlike ICP monitoring. This review highlighted that the first challenge is the assessment of ICC values, because of the invasive nature of direct measurement, the time-consuming aspect of non-invasive calculation through computer simulations, and the inability to quantify ICC values in estimation methods. Addressing these challenges is crucial, and the development of a rapid, non-invasive computer simulation method could alleviate obstacles in quantifying ICC. Additionally, this review indicated the second challenge in the clinical application of ICC, which involves the dynamic and time-dependent nature of ICC. This was considered by introducing the concept of time elapsed (TE) in measuring the changes in volume or ICP in the ICC equation (volume change/ICP change). The choice of TE, whether short or long, directly influences the ICC values that must be considered in the clinical application of the ICC. Compensatory responses of the brain exhibit non-monotonic and variable changes in long TE assessments for certain disorders, contrasting with the mono-exponential pattern observed in short TE assessments. Furthermore, the recovery behavior of the brain undergoes changes during the treatment process of various brain disorders when exposed to short and long TE conditions. The review also highlighted differences in ICC values across brain disorders with various strain rates and loading durations on the brain, further emphasizing the dynamic nature of ICC for clinical application. The insight provided in this review may prove valuable to professionals in neurocritical care, neurology, and neurosurgery for standardizing ICC monitoring in practical application related to the diagnosis and evaluation of treatment outcomes in brain disorders.

A mathematical framework for the dynamic interaction of pulsatile blood, brain, and cerebrospinal fluid

BACKGROUND

Shedding light on less-known aspects of intracranial fluid dynamics may be helpful to understand the hydrocephalus mechanism. The present study suggests a mathematical framework based on in vivo inputs to compare the dynamic interaction of pulsatile blood, brain, and cerebrospinal fluid (CSF) between the healthy subject and the hydrocephalus patient.

METHOD

The input data for the mathematical formulations was pulsatile blood velocity, which was measured using cine PC-MRI. Tube law was used to transfer the created deformation by blood pulsation in the vessel circumference to the brain domain. The pulsatile deformation of brain tissue with respect to time was calculated and considered to be inlet velocity in the CSF domain. The governing equations in all three domains were continuity, Navier-Stokes, and concentration. We used Darcy law with defined permeability and diffusivity values to define the material properties in the brain.

RESULTS

We validated the preciseness of the CSF velocity and pressure through the mathematical formulations with cine PC-MRI velocity, experimental ICP, and FSI simulated velocity and pressure. We used the analysis of dimensionless numbers including Reynolds, Womersley, Hartmann, and Peclet to evaluate the characteristics of the intracranial fluid flow. In the mid-systole phase of a cardiac cycle, CSF velocity had the maximum value and CSF pressure had the minimum value. The maximum and amplitude of CSF pressure, as well as CSF stroke volume, were calculated and compared between the healthy subject and the hydrocephalus patient.

CONCLUSION

The present in vivo-based mathematical framework has the potential to gain insight into the less-known points in the physiological function of intracranial fluid dynamics and the hydrocephalus mechanism.

Neural simulation pipeline: Enabling container-based simulations on-premise and in public clouds

In this study, we explore the simulation setup in computational neuroscience. We use GENESIS, a general purpose simulation engine for sub-cellular components and biochemical reactions, realistic neuron models, large neural networks, and system-level models. GENESIS supports developing and running computer simulations but leaves a gap for setting up today's larger and more complex models. The field of realistic models of brain networks has overgrown the simplicity of earliest models. The challenges include managing the complexity of software dependencies and various models, setting up model parameter values, storing the input parameters alongside the results, and providing execution statistics. Moreover, in the high performance computing (HPC) context, public cloud resources are becoming an alternative to the expensive on-premises clusters. We present Neural Simulation Pipeline (NSP), which facilitates the large-scale computer simulations and their deployment to multiple computing infrastructures using the infrastructure as the code (IaC) containerization approach. The authors demonstrate the effectiveness of NSP in a pattern recognition task programmed with GENESIS, through a custom-built visual system, called RetNet(8 × 5,1) that uses biologically plausible Hodgkin-Huxley spiking neurons. We evaluate the pipeline by performing 54 simulations executed on-premise, at the Hasso Plattner Institute's (HPI) Future Service-Oriented Computing (SOC) Lab, and through the Amazon Web Services (AWS), the biggest public cloud service provider in the world. We report on the non-containerized and containerized execution with Docker, as well as present the cost per simulation in AWS. The results show that our neural simulation pipeline can reduce entry barriers to neural simulations, making them more practical and cost-effective.

CSF Dynamics: Implications for Hydrocephalus and Glymphatic Clearance

Beyond its neuroprotective role, CSF functions to rid the brain of toxic waste products through glymphatic clearance. Disturbances in the circulation of CSF and glymphatic exchange are common among those experiencing HCP syndrome, which often results from SAH. Normally, the secretion of CSF follows a two-step process, including filtration of plasma followed by the introduction of ions, bicarbonate, and water. Arachnoid granulations are the main site of CSF absorption, although there are other influencing factors that affect this process. The pathway through which CSF is through to flow is from its site of secretion, at the choroid plexus, to its site of absorption. However, the CSF flow dynamics are influenced by the cardiovascular system and interactions between CSF and CNS anatomy. One, two, and three-dimensional models are currently methods researchers use to predict and describe CSF flow, both under normal and pathological conditions. They are, however, not without their limitations. "Rest-of-body" models, which consider whole-body compartments, may be more effective for understanding the disruption to CSF flow due to hemorrhages and hydrocephalus. Specifically, SAH is thought to prevent CSF flow into the basal cistern and paravascular spaces. It is also more subject to backflow, caused by the presence of coagulation cascade products. In regard to the fluid dynamics of CSF, scar tissue, red blood cells, and protein content resulting from SAH may contribute to increased viscosity, decreased vessel diameter, and increased vessel resistance. Outside of its direct influence on CSF flow, SAH may result in one or both forms of hydrocephalus, including noncommunicating (obstructive) and communicating (nonobstructive) HCP. Imaging modalities such as PC-MRI, Time-SLIP, and CFD model, a mathematical model relying on PC-MRI data, are commonly used to better understand CSF flow. While PC-MRI utilizes phase shift data to ultimately determine CSF speed and flow, Time-SLIP compares signals generated by CSF to background signals to characterizes complex fluid dynamics. Currently, there are gaps in sufficient CSF flow models and imaging modalities. A prospective area of study includes generation of models that consider "rest-of-body" compartments and elements like arterial pulse waves, respiratory waves, posture, and jugular venous posture. Going forward, imaging modalities should work to focus more on patients in nature in order to appropriately assess how CSF flow is disrupted in SAH and HCP.

Computational fluid dynamics model to predict the dynamical behavior of the cerebrospinal fluid through implementation of physiological boundary conditions

Cerebrospinal fluid (CSF) dynamics play an important role in maintaining a stable central nervous system environment and are influenced by different physiological processes. Multiple studies have investigated these processes but the impact of each of them on CSF flow is not well understood. A deeper insight into the CSF dynamics and the processes impacting them is crucial to better understand neurological disorders such as hydrocephalus, Chiari malformation, and intracranial hypertension. This study presents a 3D computational fluid dynamics (CFD) model which incorporates physiological processes as boundary conditions. CSF production and pulsatile arterial and venous volume changes are implemented as inlet boundary conditions. At the outlets, 2-element windkessel models are imposed to simulate CSF compliance and absorption. The total compliance is first tuned using a 0D model to obtain physiological pressure pulsations. Then, simulation results are compared with in vivo flow measurements in the spinal subarachnoid space (SAS) and cerebral aqueduct, and intracranial pressure values reported in the literature. Finally, the impact of the distribution of and total compliance on CSF pressures and velocities is evaluated. Without respiration effects, compliance of 0.17 ml/mmHg yielded pressure pulsations with an amplitude of 5 mmHg and an average value within the physiological range of 7-15 mmHg. Also, model flow rates were found to be in good agreement with reported values. However, when adding respiration effects, similar pressure amplitudes required an increase of compliance value to 0.51 ml/mmHg, which is within the range of 0.4-1.2 ml/mmHg measured in vivo. Moreover, altering the distribution of compliance over the four different outlets impacted the local flow, including the flow through the foramen magnum. The contribution of compliance to each outlet was directly proportional to the outflow at that outlet. Meanwhile, the value of total compliance impacted intracranial pressure. In conclusion, a computational model of the CSF has been developed that can simulate CSF pressures and velocities by incorporating boundary conditions based on physiological processes. By tuning these boundary conditions, we were able to obtain CSF pressures and flows within the physiological range.

Long-term recovery behavior of brain tissue in hydrocephalus patients after shunting

The unpredictable complexities in hydrocephalus shunt outcomes may be related to the recovery behavior of brain tissue after shunting. The simulated cerebrospinal fluid (CSF) velocity and intracranial pressure (ICP) over 15 months after shunting were validated by experimental data. The mean strain and creep of the brain had notable changes after shunting and their trends were monotonic. The highest stiffness of the hydrocephalic brain was in the first consolidation phase (between pre-shunting to 1 month after shunting). The viscous component overcame and damped the input load in the third consolidation phase (after the fifteenth month) and changes in brain volume were stopped. The long-intracranial elastance (long-IE) changed oscillatory after shunting and there was not a linear relationship between long-IE and ICP. We showed the long-term effect of the viscous component on brain recovery behavior of hydrocephalic brain. The results shed light on the brain recovery mechanism after shunting and the mechanisms for shunt failure.

A Clinical Study on the Treatment of Recurrent Chiari (Type I) Malformation with Syringomyelia Based on the Dynamics of Cerebrospinal Fluid

Objective. Combining the dynamics of cerebrospinal fluid, our study investigates the clinical effects of syringomyelia after the combination of fourth ventricle-subarachnoid shunt (FVSS) for recurrent Chiari (type I) malformations after cranial fossa decompression (foramen magnum decompression (FMD)). Methods. From December 2018 to December 2020, 15 patients with recurrent syringomyelia following posterior fossa decompression had FVSS surgery. Before and after the procedure, the clinical and imaging data of these individuals were retrospectively examined. Results. Following FVSS, none of the 15 patients experienced infection, nerve injury, shunt loss, or obstruction. 13 patients improved dramatically after surgery, while 2 patients improved significantly in the early postoperative period, but the primary symptoms returned 2 months later. The Japanese Orthopedic Association (JOA) score was $12.67\pm 3.95$ , which was considerably better than preoperatively ( $t=3.69$ , $P$ 0.001). The MRI results revealed that the cavities in 13 patients were reduced by at least 50% compared to the cavities measured preoperatively. The shrinkage rate of syringomyelia was 86.67% (13/15). One patient’s cavities nearly vanished following syringomyelia. The size of the cavity in the patient remain unchanged, and the cavity’s maximal diameter was significantly smaller than the size measured preoperatively ( $P<0.001$ ) PC-MRI results indicated that the peak flow rate of cerebrospinal fluid at the central segment of the midbrain aqueduct and the foramen magnum in patients during systole and diastole were significantly reduced after surgery ( $P<0.05$ ). Conclusion. After posterior fossa decompression, FVSS can effectively restore the smooth circulation of cerebrospinal fluid and alleviate clinical symptoms in patients with recurrent Chiari (type I) malformation and syringomyelia. It is a highly effective way of treatment.

A New Definition for Intracranial Compliance to Evaluate Adult Hydrocephalus After Shunting

The clinical application of intracranial compliance (ICC), ∆V/∆P, as one of the most critical indexes for hydrocephalus evaluation was demonstrated previously. We suggest a new definition for the concept of ICC (long-term ICC) where there is a longer amount of elapsed time (up to 18 months after shunting) between the measurement of two values (V1 and V2 or P1 and P2). The head images of 15 adult patients with communicating hydrocephalus were provided with nine sets of imaging in nine stages: prior to shunting, and 1, 2, 3, 6, 9, 12, 15, and 18 months after shunting. In addition to measuring CSF volume (CSFV) in each stage, intracranial pressure (ICP) was also calculated using fluid–structure interaction simulation for the noninvasive calculation of ICC. Despite small increases in the brain volume (16.9%), there were considerable decreases in the ICP (70.4%) and CSFV (80.0%) of hydrocephalus patients after 18 months of shunting. The changes in CSFV, brain volume, and ICP values reached a stable condition 12, 15, and 6 months after shunting, respectively. The results showed that the brain tissue needs approximately two months to adapt itself to the fast and significant ICP reduction due to shunting. This may be related to the effect of the “viscous” component of brain tissue. The ICC trend between pre-shunting and the first month of shunting was descending for all patients with a “mean value” of 14.75 ± 0.6 ml/cm H2O. ICC changes in the other stages were oscillatory (nonuniform). Our noninvasive long-term ICC calculations showed a nonmonotonic trend in the CSFV–ICP graph, the lack of a linear relationship between ICC and ICP, and an oscillatory increase in ICC values during shunt treatment. The oscillatory changes in long-term ICC may reflect the clinical variations in hydrocephalus patients after shunting.

A one-dimensional model for the pulsating flow of cerebrospinal fluid in the spinal canal

The monitoring of intracranial pressure (ICP) fluctuations, which is needed in the context of a number of neurological diseases, requires the insertion of pressure sensors, an invasive procedure with considerable risk factors. Intracranial pressure fluctuations drive the wave-like pulsatile motion of cerebrospinal fluid (CSF) along the compliant spinal canal. Systematically derived simplified models relating the ICP fluctuations with the resulting CSF flow rate can be useful in enabling indirect evaluations of the former from non-invasive magnetic resonance imaging (MRI) measurements of the latter. As a preliminary step in enabling these predictive efforts, a model is developed here for the pulsating viscous motion of CSF in the spinal canal, assumed to be a linearly elastic compliant tube of slowly varying section, with a Darcy pressure-loss term included to model the fluid resistance introduced by the trabeculae, which are thin collagen-reinforced columns that form a web-like structure stretching across the spinal canal. Use of Fourier-series expansions enables predictions of CSF flow rate for realistic anharmonic ICP fluctuations. The flow rate predicted using a representative ICP waveform together with a realistic canal anatomy is seen to compare favourably with in vivo phase-contrast MRI measurements at multiple sections along the spinal canal. The results indicate that the proposed model, involving a limited number of parameters, can serve as a basis for future quantitative analyses targeting predictions of ICP temporal fluctuations based on MRI measurements of spinal-canal anatomy and CSF flow rate.

Refined Temporal-to-Frontal Horn Shunt for Treatment of Trapped Temporal Horn After Surgery of Peri- or Intraventricular Tumor: A Case Series Study

Background

Trapped temporal horn (TTH) is a localized hydrocephalus that can be treated with cerebrospinal fluid diversion. Refined temporal-to-frontal horn shunt (RTFHS) through the parieto-occipital approach is rarely reported in the literature and its effectiveness remains unclear. The aim of the present study is to investigate the efficacy and outcome of RTFHS for treatment of TTH.

Materials and Methods

We consecutively enrolled 10 patients who underwent RTFHS for TTH after surgical resection of peri- or intraventricular tumors from February 2018 to March 2021. Clinical, radiological, and follow-up data were collected and analyzed. The most common underlying pathology was meningioma (n=4), followed by central neurocytoma (n=3), thalamic glioblastoma (n=2), and anaplastic ependymoma (n=1).

Results

The mean Karnofsky performance scale (KPS) score and TTH volume at onset were 54.0 ± 15.1 (range 40-80) and 71.3 ± 33.2cm³ (range 31.7-118.6cm³), respectively. All patients (10/10, 100.0%) presented with periventricular brain edema (PVBE), while midline shift was observed in 9 patients (9/10, 90.0%). RTFHSs were implanted using valveless shunting catheters. No patients developed acute intracranial hemorrhage or new neurological deficit postoperatively. During the follow-up of 17.2 ± 13.7 months (range 3-39 months), all patients showed clinical and radiological improvement. The mean KPS score at the last follow-up was significantly increased to 88.0 ± 10.3 (range 70-100, p<0.0001). RTFHS resulted in significant complete remission in PVBE and midline shift in 8 (80.0%, p=0.0007) and 9 (100.0%, p=0.0001) patients, respectively. As the postoperative follow-up duration prolonged, the mean TTH volume decreased in a consistent, linear trend (p<0.0001). At last follow-up, the mean TTH volume was significantly reduced to 15.4 ± 11.5 cm³ (range 5.6-44.1 cm³, p=0.0003), resulting in a mean relative reduction of 77.2 ± 13.1% compared with the volume of TTH at onset. Over drainage was not observed during the follow-up. No patient suffered from proximal or distal shunt obstruction or shunt related infection, and the revision rate was 0%.

Conclusion

RTFHS seems to be safe and effective for the treatment of TTH with favorable outcomes. Advantages of this technique could be technically less complex and invasive, cost-effective, avoidance of various intraperitoneal complications, and maintaining a near-physiological CSF pathway.

Effect of Ventricular Elasticity Due to Congenital Hydrocephalus

Cerebrospinal fluid (CSF) is a symmetric flow transport that surrounds brain and central nervous system (CNS). Congenital hydrocephalusis is an asymmetric and unusual cerebrospinal fluid flow during fetal development. This dumping impact enhances the elasticity over the ventricle wall. Henceforth, compression change influences the force of brain tissues. This paper presents a mathematical model to establish the effects of ventricular elasticity through a porous channel. The current model is good enough for immediate use by a neurosurgeon. The mathematical model is likely to be a powerful tool for the better treatment of hydrocephalus and other brain biomechanics. The non-linear dimensionless governing equations are solved using a perturbation technique, and the outcome is portrayed graphically with the aid of MATLAB.

Hydrodynamic comparison of shunt and endoscopic third ventriculostomy in adult hydrocephalus using in vitro models and fluid-structure interaction simulation

OBJECTIVE

The comparison of the efficiency of shunt placement and endoscopic third ventriculostomy (ETV) in treating of adult hydrocephalus patients with various intensities and different obstruction intensities in the aqueduct of Sylvius (AS).

METHODS

In vitro models with separated ventricles were simulated and implemented for modeling shunt and ETV surgeries in one healthy subject and hydrocephalus patients with various intensities, as well as three different obstruction intensities in AS and under two cerebrospinal fluid (CSF) dynamic conditions. The fluid-structure interaction simulation was also carried out to validate in vitro results.

RESULTS

The efficiency of both methods in reducing the maximum CSF pressure in the subarachnoid space (MCPS) decreased by an increase in the patient's intensities. Contrary to shunting, the efficiency of ETV in reducing MCPS demonstrated a decline (8.3-16.4%) by an increase in obstruction levels in AS. Based on the findings, shunt efficiency in decreasing MCPS in patients with low intensity was more remarkable compared to ETV. However, ETV was more efficient than shunt in the patient with intracranial hypertension. Further, shunt placement and ETV led to a significant reduction in the amplitude of CSF pressure in the SAS (ACPS) in patients with sneezing, coughing, Valsalva maneuver, and exercising effects in contrast to other patients. Moreover, ACPS reduction was not related to the intensity of the disease in both treatment methods. In contrast to shunt, an increase in the obstruction level in AS led to a reduction in ACPS in ETV in both CSF dynamic conditions.

CONCLUSIONS

The noises from irregular disorders increased the discharging of CSF after shunt placement, and activities such as sneezing, coughing, Valsalva maneuvers, and exercising increased the risk of shunt overdrainage by 10.4~47.8%, especially in the patient with intracranial hypertension. Based on the proposed in vitro ETV and shunt models, an increase of head compliance was higher in ETV compared to the shunt. Eventually, an increase in the obstruction level of AS after ETV led to a decline in head compliance in contrast to shunt.