A Wireless Monitoring System for Hydrocephalus Shunts A. Narayanaswamy1, M. Nourani1, L. Tamil1, S. Bianco2
Abstract— Patients with Hydrocephalus are usually treated by diverting the excess Cerebrospinal Fluid (CSF) to other parts of the body using shunts. More than 40 percentage of shunts implanted fail within the first two years. Obstruction in the shunts is one of the major causes of failure (45 percent) and the detection of obstruction reduces the complexity of the revision surgery. This paper describes a proposed wireless monitoring system for clog detection and flow measurement in shunts. A prototype was built using multiple pressure sensors along the shunt catheters for sensing the location of clog and flow rate. Regular monitoring of flow rates can be used to adjust the valve in the shunt to prevent over drainage or under drainage of CSF. The accuracy of the flow measurement is more than 90 percent. I.
INTRODUCTION
A. Background & Prior Work Hydrocephalus [1] (also informally called “water on the brain”) is a condition characterized by an excessive accumulation of Cerebrospinal Fluid (CSF) in the brain, which results in an abnormal widening of spaces (ventricles) in the brain [2]. CSF is a clear and colorless fluid which contains 99% water and small quantities of glucose and protein [3] and is produced in the brain and the spinal cord continuously. The viscosity and density of CSF is very close to that of water. CSF is a Newtonian fluid with viscosity range between 0.7 mPa.s - 1 mPa.s at 37º C [4]. The specific gravity of CSF in normal human being at 37º C is between 1.0063-1.0075 [5]. It is believed that about 500 ml of CSF is produced in a day at the rate of 0.3 ml/min - 0.5 ml/min. The amount of CSF present in brain at a given time is about 150 ml [6]. Any condition that blocks the normal flow or absorption will result in an over accumulation of CSF, and the resulting pressure of CSF against brain causes Hydrocephalus. Hydrocephalus is usually treated by surgically inserting a shunt system which diverts excess CSF from the brain to another area of the body like the abdominal cavity as shown in Fig. 2. A shunt consists of a (i) proximal catheter which is placed within the ventricle inside the brain, (ii) valve to regulate the flow of CSF, and (iii) distal catheter which is placed usually within the abdominal cavity and connected to the valve. The valve is programmable using an external device. This enables the surgeons to pre-select one of the pressure settings (often between 0.294 kPa -1.96 kPa) for the opening pressure of the valve non-invasively [7].
1. Quality of Life Technology Laboratory, the University of Texas at Dallas, Richardson, TX 75080. Emails: {asn107020, nourani, tamil}@utdallas.edu. 2. Arlington Memorial Hospital, Arlington, TX 76012. Email: [email protected].
978-1-4244-9270-1/15/$31.00 ©2015 IEEE
There has been active research to make smart shunts since 1980’s. In 1988, Rekate et al. published a proposal for a smart shunt design [8] with CSF flow control. The paper also explains the role of physician in flow adjustment, hardware size, device size and implant location. Two platforms of the system with battery powering and external powering are described. Unfortunately at that time, the system cannot be realized because of the technology limitation. There are many patent literatures from the major shunt manufacturers describing ways to improve the shunt performance. A feedback control is used on a pump-based smart shunt as described by Medtronic in patents from 2006 to 2008 [9]. Another patent from Medtronic in 2001 describes a sensor based implantable monitoring system that could be used for valve control [10]. Codman and Shurtleff in 2012 describe a mechanical valve with a pressure sensor and an actuator replacing the magnetic adjustment mechanism used in the present shunts [11]. The system can be operated under an algorithm or can be controlled by the physician. Practical implementation of the monitoring system requires miniaturization of the sensors, wireless powering, and sending the data to an external monitoring system. Micro-electro-mechanical systems (MEMS) technology has proven to be very successful in reducing the size and power consumption of implantable sensing systems. Some of the related works for this research are found in [12] and [13]. A capacitive implantable pressure sensor system for a biomedical application is described in [12]. In [13] multiple MEMS sensors attached to a bio compatible substrate that is folded in to a catheter like structure is described. B. Motivation and Contribution More than 100 shunt related surgeries are performed daily in the US alone. There are many varieties of shunts in the market from different manufacturers. In spite of major advances in technology over the last 50 years, shunt remains relatively unchanged. The present day shunt system comes with fixed or adjustable valve. The fixed pressure valves require revision when flow requirement in shunt changes. The programmable variable pressure valves help to prevent revision surgery. But none of these valves provide any feedback if there is a shunt complication, location of complication in the shunt or valve or the flow rate. Generally, shunt systems require monitoring and regular medical follow up. When complications occur, the shunt requires some type of revision, mostly shunt replacement which is a costly process. Over-draining or under-draining are other complications that can occur in the shunt. About 45% of the shunt complications occur due to the obstruction in the shunt or shunt malfunctioning [14]. The obstruction of flow of CSF at proximal catheter is the most common mechanical complication (64%) in shunt [15]. Strong motivation for the proposed research comes from
829
the fact that at present there is no reliable method to determine the location of the shunt malfunctioning. When there is a shunt obstruction, all the points along the shunt course are suspect during revision [16]. The key contribution of our work is twofold. First, we detect the location of the blockage and identify the specific part of the shunt that needs to be replaced reducing the complication of the revision surgery and shortening the recovery time. Second, we determine the flow rate of CSF that can provide an indication of over-drainage or underdrainage in the shunt, another potential cause of complications. The system can also determine the posture of the patient and hence the flow variation due to the activity of patients is found out and the valve can be controlled for optimum flow. In addition, the results of our monitoring system over period of time can provide the medical staff more information about the health condition of the patient. II. SYSTEM DESIGN A shunt catheter is a flexible but sturdy tube made with bio-compatible material. It is about 1 mm in inner diameter and 0.5 mm wall thickness. The basic requirement of the sensing system is that it should be able to fit into the current shunt system without affecting its functionality. In the shunts, the sensors can be placed in the inner walls of the catheter and the transducer of the sensors is in direct contact with the CSF. Battery powering makes the system bulky and presents more challenges in the surgical procedure. To avoid this situation, a battery-less system with RF power harvesting is proposed. In the proposed design in Fig. 1, a transponder can be placed near the valve of the shunt (Fig. 2) to which the sensors are connected. The electrical connections/wiring from sensors to the transponder can be done as surface trace on the inner wall of catheter or through the tubing. For data collection and initiating measurements, the external reader must be brought close to the transponder just above the skin. The external reader powers the transponder and which in turn provides the excitation voltage to the sensors. When the measurement is completed, the data is fed back to the receiver. A. Sensors In general a number of sensors can be added to the inside wall of the shunt catheters to measure the pressure at various locations. Also parameters such as Intracranial pressure (ICP) and intra-abdominal pressure (IAP) at different body postures are useful information for the doctors to determine the health of the patient. Surgical procedure for the insertion and revision surgery decides the spatial resolution for the detection of clog. The minimum requirement is to accurately determine if the clog/failure is in the 1) proximal catheter, 2) valve, or 3) distal catheter. This requires a minimum of four pressure sensors as shown in Fig. 2, S1 (measures ventricular ICP) and S2 placed inside the proximal catheter and S3 and S4 (measures IAP) inside the distal catheter. This splits detection region in to: i) above S1, ii) between S1 & S2, iii) flow control valve between S2 & S3, iv) between S3 & S4 and, v) below S4. This approach will reduce the complexity when revision surgery becomes inevitable. In
general, if there are k pressure sensors, it splits the shunt system in to k+1 region which will give us k+1 possible locations of clog. With more sensors we will get higher precision of the clog location, but they require more electrical connections which will increase the cost of such implantable system. Skin S1 S2 Data RFID Transponder
RFID Reader
Sensor Interface
Power Sn Inside the human body
Figure 1. Block diagram of the proposed system.
B. Clog Detection and Flow Measurement Pressure acting on liquid at any point in a tube is constant in all direction; so there is always a static pressure of the liquid column acting on the sensors. When there is no flow, the pressure measured by the sensors is this static pressure. But there is a drop in pressure due to friction and velocity [17] when the CSF flows through the tube. By calculating the pressure drop between two sensors, the flow rate is determined. When there is a shunt failure due to clog, there is a liquid column in sensors above the clog location while it is not present below the clog. Hence the pressure value will be lower in the sensors below the clog compared to sensors above the clog. By comparing these values, one can determine the presence of the clog as well as the location of the clog. In our particular application (CSF shunts) such condition is measured when the patient is in standing position. From the pressure readings of the sensors, flow can be computed using Bernoulli’s theorem [18]. In fluid mechanics, head is a concept that relates the energy in a fluid to the height of an equivalent static column of that fluid. Bernoulli’s equation for laminar flow in terms of head for any of the two sensors in the system in Fig. 2 is given as: 𝑷𝟏 𝝆𝒈
+
𝒖𝟏 𝟐 𝟐𝒈
+ 𝒛𝟏 + 𝒉𝒇𝟏 =
𝑷𝟐 𝝆𝒈
+
𝒖𝟐 𝟐 𝟐𝒈
+ 𝒛𝟐 + 𝒉𝒇𝟐 .
(1)
where P1, and P2 are the are the pressure measured by sensors S1 and S2. u1, and u2 are the velocity of liquid at those two points in the tube. If area of the tube is same at the two points, then u1 = u2 = u. z1, and z2 are the potential head at these two points from an arbitrary equipotential plane shown in Fig. 2. hf is the head loss due to friction, and ρ is the density of the fluid. All the pressure components are converted to heads for simplifying the calculation. Considering the cross sectional area of the tube is uniform throughout, the frictional loss between two points in the tube is proportional to the length of the tube and the velocity of liquid, and it is zero at the start of the tube and maximum at the end of the tube. Velocity of the CSF flow in shunt is very low (̴1 cm/sec), velocity head is much less compared to frictional head and is neglected in calculation. Velocity is
830
calculated from the drop of pressure between two sensors due to friction. The Bernoulli’s equation can be rewritten for calculating the velocity: 𝑢=√
2𝑔𝐷(𝜌𝑔∆𝑧−Δp))
(2)
𝑓𝐿
where u is the velocity of the liquid in the tube, g is the acceleration due to gravity= 9.81 m/s2, L is the length of the tube between the two points, f is the frictional factor, D is the diameter of the tube, Δp is the pressure difference between two sensors which can be any pair from the four sensors and ∆z is the corresponding hydrostatic pressure difference. From this equation, it is clear that gravity plays a role in the velocity. As the patient moves from a standing to supine position ∆z in (2) reduces and hence the flow rate. Total Head line
S1 Proximal catheter Valve
S2 S3
III. PROTOTYPE DESIGN A commercially available piezoresistive membrane based flow-through pressure sensors from Honeywell (26PCAFG6G) are used in the prototype system. These sensors need to be provided with an excitation (voltage) for measurement. The membrane based pressure sensors can be either absolute pressure sensors or gage pressure sensors. Gage pressure sensors are zero referenced to ambient pressure and absolute pressure sensors are zero referenced to vacuum. In the real application, since the ambient pressure outside the catheter surrounded by body fluids and tissue is different a gage pressure sensor cannot be used. Due to the non availability of commercially available absolute pressure sensors and since the prototype is tested outside of the human body, gage pressure sensors will suffice for the testing of the proof of concept. Due to process variation, there is an offset at atmospheric pressure and it is different for each sensors. All the four pressure sensors are calibrated by measuring the offset voltage at atmospheric pressure. During animal testing/ implantable phase, the gage sensors must be replaced with absolute pressure sensors. A prototype resembling an actual shunt system was built using an Intravenous (IV) bag and the shunt catheter. Since the density and viscosity of water is very similar to that of CSF, water is used to test the proof of concept. The pressure sensor was media compatible with water. The flow control valve is placed between sensor S2 and S3 to control the flow of liquid mimicking the real shunt system.
Distal catheter
S4 Equipotential plane Pressure measured by sensors Pressure drop due to friction and velocity
Figure 2. Sensor placement and Pressure measured by the sensors at a constant CSF flow.
When measuring pressure for clog detection, the person should be in a sitting or standing position. Maintaining proper posture during measurement is necessary as the pressure measurement is sensitive to height. The pressure readings of the sensors at different positions (standing, sitting and supine) must be measured after surgery and should be set as reference readings. After implant, in addition to the pressure loss due to friction, there can be local losses in pressure due to bends, entanglements, junctions, valve etc. A general theory to quantify these losses is not feasible at individual level. Bends and location of bends in the implanted shunt cannot be predicted, so it has to be treated accordingly. The effects of bends can be ignored as there is no possibility of turbulence at the bends at the very low velocity of CSF flow. Since there is loss of pressure at the valve, sensor pairs in either proximal catheter (S1&S2) and distal catheter (S3&S4) should be used for flow calculation. The flow measurement can be done at a position which has the reference pressure reading taken after surgery.
The sensors are wired to a custom designed sensor interface printed circuit board (PCB). The PCB is connected to a LF transponder of the EZ430 TMS37157 kit from Texas Instruments [19]. The RFID transponder board harvests power from the RF waves from the EZ430 TMS37157 external reader device. The sensors are powered one at a time to conserve power. The differential sensor output is converted into single ended signal and amplified. This signal is converted to digital value. After all the four sensor measurements are completed, the ADC values are sent to the reader as a single data package. The RFID transponder and the sensor interface circuit in the block diagram in Fig. 1 form the implantable unit. This unit is the one that will undergo clinical trial in the future. IV. EXPERIMENTAL RESULTS The measured pressure from the proof of concept system is shown in Fig. 3. The graph shows the pressure readings of the sensors at clogged and unclogged condition. The clog shown in this graph is between sensors S3 and S4. The pressure reading of S3 is the highest as it has the highest static column of liquid when clogged. When there is no clog, there is no static column of liquid in the catheter and hence the reduction of pressure. The set up was tested for clogs at different locations in the shunt and the system recognized the clogs in each of those conditions.
831
robust, but the flow measurement can be error prone. Pressure sensor offsets drifts with time, so in an implant system, zeroing this offset is difficult and can cause error in flow measurement over time.
4
Pressure (kPa)
2 0
-2 -4
P1
Clog between S3 and S4
No clog
V. CONCLUSION
P2 P3
-6
P4
-8 0
20
40
60
80
100
No: of samples
Figure 3. Pressure variation for clogged and unclogged shunt.
The flow rate is measured using Thomas Scientific 3500 Traceable ultra-low flow meter. This instrument displays the instantaneous flow rate and the total volumetric flow. The instantaneous flow rate is set and the pressure measurements are taken for a period of 10 minutes. The flow rate is measured by taking the mean of the volumetric flow displayed by the instrument. The mean of the pressure reading for 10 minute period is used to find the calculated flow rate. In the real time system, the flow rate is calculated using the mean of 20 readings taken at 2 samples per second. Velocity and volumetric flow are calculated using (2). Fig. 4 shows the measured and calculated volumetric flow rates through the shunt at different frictional pressure loss between P4-P3. From the graph it is evident that when flow rate increases, pressure drop due to friction will increase. In reality, the obstruction in shunt happens gradually over time and this increases resistance and hence a decrease in flow. The measured pressure drop also decreases due to the flow rate reduction. So, in general, this method can be used for calculating the reduced flow when the system is partially obstructed. The calculated flow rate (from our system) has less than 10% error compared to the ground truth flow rate measured. An error bar is created for the uncertainty in calculated flow rate using the σ of the P4-P3 reading at different valve settings.
This paper presents a proof of concept system for a wireless clog monitoring and flow measurement for Hydrocephalus shunts. The experimental result verifies the technique suggested in the paper to determine the location of clog and flow measurement is appropriate for the requirements. The wireless powering and data transfer was done through commercially available off the shelf development board. Future directions include exploring circuit techniques to improve the accuracy of flow measurement, design a valve control mechanism to adjust the flow rate of CSF at different body postures. REFERENCES [1] [2] [3] [4]
[5] [6]
[7] [8] [9]
[10]
[11]
25.00 Measured (flow meter)
[12]
20.00
Flow rate (ml/min)
Calculated (our system) 15.00
[13] 10.00
[14] 5.00
0.00 0.100
0.200
0.300
0.400 0.500 Frictional Pressure drop (kPa)
0.600
[15]
0.700
Figure 4. Measured, calculated flow rate at different P4-P3 with error bar.
[16]
The maximum power consumed by the transponder for signal conditioning, data transfer and the sensor excitation is 10.1 mW at 3.3 V. The power consumption of the custom designed sensor interface circuit for sensor excitation and amplification is 1.55 mW. The clog measurement system is
[17] [18] [19]
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G. Cinalli, W.J. Maixner, C. Sainte-Rose, Pediatric Hydrocephalus, Milan, Springer-Verlag, 2006. http://www.nhfonline.org/info.php?id=facts M.S. Greenberg, Handbook of Neurosurgery, New York, Thieme, 2010 I.G. Bloomfield, I.H Johnston, L.E Bilston. Effects of proteins, blood cells and glucose on the viscosity of cerebrospinal fluid. Pediatr Neurosurg 28: pp. 246 –251, 1998. E. Levin, S. Muravchick, M.I. Gold. Density of human cerebrospinal fluid and tetracaine solutions. Anesth Analg: pp. 814-817, 1981. Metwally Emam et al “A novel microdevice for the treatment of hydrocephalus: design and fabrication of an array of microvalves and microneedles”, Microsystem Technologies, Vol.14, pp. 371–378, 2008 http://www.hydroassoc.org/hydrocephalus-education-andsupport/learning-about-hydrcephalus/treatment-of-hydrocephalus/ W.H. Ko, C.W Meyrick, H.L Rekate. Cerebrospinal-Fluid ControlSystem. Proc. IEEE` pp. 1226-1235, 1988. W. Bertrand, D.Harper, L. Speckman, A. Kiehl, R. Scheer. Implantable cerebral spinal fluid drainage system. U.S. Patent 7309330, issued Dec. 18, 2007. K. Miesel, L. Stylos. Intracranial monitoring and therapy delivery control device, system, and method. U.S. Patent 6248080, issued Jun. 19, 2001 L. Ludin, C. Mauge. Programmable shunt with electromechanical valve actuator. U.S. Patent US8123714, issued Feb. 28, 2012. A. Ginggen, Y. Tardy, R. Crivelli, T. Bork, P. Renaud, "A Telemetric Pressure Sensor System for Biomedical Applications," IEEE Transactions on Biomedical Engineering, pp. 1374-1381, April 2008. C. Li, P.M.Wu, J. Han, C.H. Ahn, “A flexible polymer tube lab-chip integrated with microsensors for smart microcatheter,” Biomed. Microdevices pp. 671-679, 2008. A. Ahmed, G. Sandlas, P . Kothari, D . Sarda, A. Gupta, P. Karkera, P . Joshi, “Outcome analysis of shunt surgery in hydrocephalus,” J Indian Association Pediatric Surg, pp. 98-101, 2009. A.L. Albright, I.F. Pollack, P.D. Adelson, Principles and Practice of Pediatric Neurosurgery, New York, Thieme, 1999. S.R. Browd, B.T. Ragel “Failure of Cerebrospinal Fluid Shunts: Part I: Obstruction and Mechanical Failure,” Pediatric Neurol, 34: 2, 2006. R.J. Houghtalen, A.O. Akan, N. Hwang, Fundamentals of Hydraulic Engineering Systems, 4th ed. New Jersey, Prentice-Hall, 2009. H. Lamb, Hydrodynamics, 6th ed. Cambridge, Cambridge Univ. Press, 1953. http://www.ti.com/tool/ez430-tms37157
Abstract— Patients with Hydrocephalus are usually treated by diverting the excess Cerebrospinal Fluid (CSF) to other parts of the body using shunts. More than 40 percentage of shunts implanted fail within the first two years. Obstruction in the shunts is one of the major causes of failure (45 percent) and the detection of obstruction reduces the complexity of the revision surgery. This paper describes a proposed wireless monitoring system for clog detection and flow measurement in shunts. A prototype was built using multiple pressure sensors along the shunt catheters for sensing the location of clog and flow rate. Regular monitoring of flow rates can be used to adjust the valve in the shunt to prevent over drainage or under drainage of CSF. The accuracy of the flow measurement is more than 90 percent. I.
INTRODUCTION
A. Background & Prior Work Hydrocephalus [1] (also informally called “water on the brain”) is a condition characterized by an excessive accumulation of Cerebrospinal Fluid (CSF) in the brain, which results in an abnormal widening of spaces (ventricles) in the brain [2]. CSF is a clear and colorless fluid which contains 99% water and small quantities of glucose and protein [3] and is produced in the brain and the spinal cord continuously. The viscosity and density of CSF is very close to that of water. CSF is a Newtonian fluid with viscosity range between 0.7 mPa.s - 1 mPa.s at 37º C [4]. The specific gravity of CSF in normal human being at 37º C is between 1.0063-1.0075 [5]. It is believed that about 500 ml of CSF is produced in a day at the rate of 0.3 ml/min - 0.5 ml/min. The amount of CSF present in brain at a given time is about 150 ml [6]. Any condition that blocks the normal flow or absorption will result in an over accumulation of CSF, and the resulting pressure of CSF against brain causes Hydrocephalus. Hydrocephalus is usually treated by surgically inserting a shunt system which diverts excess CSF from the brain to another area of the body like the abdominal cavity as shown in Fig. 2. A shunt consists of a (i) proximal catheter which is placed within the ventricle inside the brain, (ii) valve to regulate the flow of CSF, and (iii) distal catheter which is placed usually within the abdominal cavity and connected to the valve. The valve is programmable using an external device. This enables the surgeons to pre-select one of the pressure settings (often between 0.294 kPa -1.96 kPa) for the opening pressure of the valve non-invasively [7].
1. Quality of Life Technology Laboratory, the University of Texas at Dallas, Richardson, TX 75080. Emails: {asn107020, nourani, tamil}@utdallas.edu. 2. Arlington Memorial Hospital, Arlington, TX 76012. Email: [email protected].
978-1-4244-9270-1/15/$31.00 ©2015 IEEE
There has been active research to make smart shunts since 1980’s. In 1988, Rekate et al. published a proposal for a smart shunt design [8] with CSF flow control. The paper also explains the role of physician in flow adjustment, hardware size, device size and implant location. Two platforms of the system with battery powering and external powering are described. Unfortunately at that time, the system cannot be realized because of the technology limitation. There are many patent literatures from the major shunt manufacturers describing ways to improve the shunt performance. A feedback control is used on a pump-based smart shunt as described by Medtronic in patents from 2006 to 2008 [9]. Another patent from Medtronic in 2001 describes a sensor based implantable monitoring system that could be used for valve control [10]. Codman and Shurtleff in 2012 describe a mechanical valve with a pressure sensor and an actuator replacing the magnetic adjustment mechanism used in the present shunts [11]. The system can be operated under an algorithm or can be controlled by the physician. Practical implementation of the monitoring system requires miniaturization of the sensors, wireless powering, and sending the data to an external monitoring system. Micro-electro-mechanical systems (MEMS) technology has proven to be very successful in reducing the size and power consumption of implantable sensing systems. Some of the related works for this research are found in [12] and [13]. A capacitive implantable pressure sensor system for a biomedical application is described in [12]. In [13] multiple MEMS sensors attached to a bio compatible substrate that is folded in to a catheter like structure is described. B. Motivation and Contribution More than 100 shunt related surgeries are performed daily in the US alone. There are many varieties of shunts in the market from different manufacturers. In spite of major advances in technology over the last 50 years, shunt remains relatively unchanged. The present day shunt system comes with fixed or adjustable valve. The fixed pressure valves require revision when flow requirement in shunt changes. The programmable variable pressure valves help to prevent revision surgery. But none of these valves provide any feedback if there is a shunt complication, location of complication in the shunt or valve or the flow rate. Generally, shunt systems require monitoring and regular medical follow up. When complications occur, the shunt requires some type of revision, mostly shunt replacement which is a costly process. Over-draining or under-draining are other complications that can occur in the shunt. About 45% of the shunt complications occur due to the obstruction in the shunt or shunt malfunctioning [14]. The obstruction of flow of CSF at proximal catheter is the most common mechanical complication (64%) in shunt [15]. Strong motivation for the proposed research comes from
829
the fact that at present there is no reliable method to determine the location of the shunt malfunctioning. When there is a shunt obstruction, all the points along the shunt course are suspect during revision [16]. The key contribution of our work is twofold. First, we detect the location of the blockage and identify the specific part of the shunt that needs to be replaced reducing the complication of the revision surgery and shortening the recovery time. Second, we determine the flow rate of CSF that can provide an indication of over-drainage or underdrainage in the shunt, another potential cause of complications. The system can also determine the posture of the patient and hence the flow variation due to the activity of patients is found out and the valve can be controlled for optimum flow. In addition, the results of our monitoring system over period of time can provide the medical staff more information about the health condition of the patient. II. SYSTEM DESIGN A shunt catheter is a flexible but sturdy tube made with bio-compatible material. It is about 1 mm in inner diameter and 0.5 mm wall thickness. The basic requirement of the sensing system is that it should be able to fit into the current shunt system without affecting its functionality. In the shunts, the sensors can be placed in the inner walls of the catheter and the transducer of the sensors is in direct contact with the CSF. Battery powering makes the system bulky and presents more challenges in the surgical procedure. To avoid this situation, a battery-less system with RF power harvesting is proposed. In the proposed design in Fig. 1, a transponder can be placed near the valve of the shunt (Fig. 2) to which the sensors are connected. The electrical connections/wiring from sensors to the transponder can be done as surface trace on the inner wall of catheter or through the tubing. For data collection and initiating measurements, the external reader must be brought close to the transponder just above the skin. The external reader powers the transponder and which in turn provides the excitation voltage to the sensors. When the measurement is completed, the data is fed back to the receiver. A. Sensors In general a number of sensors can be added to the inside wall of the shunt catheters to measure the pressure at various locations. Also parameters such as Intracranial pressure (ICP) and intra-abdominal pressure (IAP) at different body postures are useful information for the doctors to determine the health of the patient. Surgical procedure for the insertion and revision surgery decides the spatial resolution for the detection of clog. The minimum requirement is to accurately determine if the clog/failure is in the 1) proximal catheter, 2) valve, or 3) distal catheter. This requires a minimum of four pressure sensors as shown in Fig. 2, S1 (measures ventricular ICP) and S2 placed inside the proximal catheter and S3 and S4 (measures IAP) inside the distal catheter. This splits detection region in to: i) above S1, ii) between S1 & S2, iii) flow control valve between S2 & S3, iv) between S3 & S4 and, v) below S4. This approach will reduce the complexity when revision surgery becomes inevitable. In
general, if there are k pressure sensors, it splits the shunt system in to k+1 region which will give us k+1 possible locations of clog. With more sensors we will get higher precision of the clog location, but they require more electrical connections which will increase the cost of such implantable system. Skin S1 S2 Data RFID Transponder
RFID Reader
Sensor Interface
Power Sn Inside the human body
Figure 1. Block diagram of the proposed system.
B. Clog Detection and Flow Measurement Pressure acting on liquid at any point in a tube is constant in all direction; so there is always a static pressure of the liquid column acting on the sensors. When there is no flow, the pressure measured by the sensors is this static pressure. But there is a drop in pressure due to friction and velocity [17] when the CSF flows through the tube. By calculating the pressure drop between two sensors, the flow rate is determined. When there is a shunt failure due to clog, there is a liquid column in sensors above the clog location while it is not present below the clog. Hence the pressure value will be lower in the sensors below the clog compared to sensors above the clog. By comparing these values, one can determine the presence of the clog as well as the location of the clog. In our particular application (CSF shunts) such condition is measured when the patient is in standing position. From the pressure readings of the sensors, flow can be computed using Bernoulli’s theorem [18]. In fluid mechanics, head is a concept that relates the energy in a fluid to the height of an equivalent static column of that fluid. Bernoulli’s equation for laminar flow in terms of head for any of the two sensors in the system in Fig. 2 is given as: 𝑷𝟏 𝝆𝒈
+
𝒖𝟏 𝟐 𝟐𝒈
+ 𝒛𝟏 + 𝒉𝒇𝟏 =
𝑷𝟐 𝝆𝒈
+
𝒖𝟐 𝟐 𝟐𝒈
+ 𝒛𝟐 + 𝒉𝒇𝟐 .
(1)
where P1, and P2 are the are the pressure measured by sensors S1 and S2. u1, and u2 are the velocity of liquid at those two points in the tube. If area of the tube is same at the two points, then u1 = u2 = u. z1, and z2 are the potential head at these two points from an arbitrary equipotential plane shown in Fig. 2. hf is the head loss due to friction, and ρ is the density of the fluid. All the pressure components are converted to heads for simplifying the calculation. Considering the cross sectional area of the tube is uniform throughout, the frictional loss between two points in the tube is proportional to the length of the tube and the velocity of liquid, and it is zero at the start of the tube and maximum at the end of the tube. Velocity of the CSF flow in shunt is very low (̴1 cm/sec), velocity head is much less compared to frictional head and is neglected in calculation. Velocity is
830
calculated from the drop of pressure between two sensors due to friction. The Bernoulli’s equation can be rewritten for calculating the velocity: 𝑢=√
2𝑔𝐷(𝜌𝑔∆𝑧−Δp))
(2)
𝑓𝐿
where u is the velocity of the liquid in the tube, g is the acceleration due to gravity= 9.81 m/s2, L is the length of the tube between the two points, f is the frictional factor, D is the diameter of the tube, Δp is the pressure difference between two sensors which can be any pair from the four sensors and ∆z is the corresponding hydrostatic pressure difference. From this equation, it is clear that gravity plays a role in the velocity. As the patient moves from a standing to supine position ∆z in (2) reduces and hence the flow rate. Total Head line
S1 Proximal catheter Valve
S2 S3
III. PROTOTYPE DESIGN A commercially available piezoresistive membrane based flow-through pressure sensors from Honeywell (26PCAFG6G) are used in the prototype system. These sensors need to be provided with an excitation (voltage) for measurement. The membrane based pressure sensors can be either absolute pressure sensors or gage pressure sensors. Gage pressure sensors are zero referenced to ambient pressure and absolute pressure sensors are zero referenced to vacuum. In the real application, since the ambient pressure outside the catheter surrounded by body fluids and tissue is different a gage pressure sensor cannot be used. Due to the non availability of commercially available absolute pressure sensors and since the prototype is tested outside of the human body, gage pressure sensors will suffice for the testing of the proof of concept. Due to process variation, there is an offset at atmospheric pressure and it is different for each sensors. All the four pressure sensors are calibrated by measuring the offset voltage at atmospheric pressure. During animal testing/ implantable phase, the gage sensors must be replaced with absolute pressure sensors. A prototype resembling an actual shunt system was built using an Intravenous (IV) bag and the shunt catheter. Since the density and viscosity of water is very similar to that of CSF, water is used to test the proof of concept. The pressure sensor was media compatible with water. The flow control valve is placed between sensor S2 and S3 to control the flow of liquid mimicking the real shunt system.
Distal catheter
S4 Equipotential plane Pressure measured by sensors Pressure drop due to friction and velocity
Figure 2. Sensor placement and Pressure measured by the sensors at a constant CSF flow.
When measuring pressure for clog detection, the person should be in a sitting or standing position. Maintaining proper posture during measurement is necessary as the pressure measurement is sensitive to height. The pressure readings of the sensors at different positions (standing, sitting and supine) must be measured after surgery and should be set as reference readings. After implant, in addition to the pressure loss due to friction, there can be local losses in pressure due to bends, entanglements, junctions, valve etc. A general theory to quantify these losses is not feasible at individual level. Bends and location of bends in the implanted shunt cannot be predicted, so it has to be treated accordingly. The effects of bends can be ignored as there is no possibility of turbulence at the bends at the very low velocity of CSF flow. Since there is loss of pressure at the valve, sensor pairs in either proximal catheter (S1&S2) and distal catheter (S3&S4) should be used for flow calculation. The flow measurement can be done at a position which has the reference pressure reading taken after surgery.
The sensors are wired to a custom designed sensor interface printed circuit board (PCB). The PCB is connected to a LF transponder of the EZ430 TMS37157 kit from Texas Instruments [19]. The RFID transponder board harvests power from the RF waves from the EZ430 TMS37157 external reader device. The sensors are powered one at a time to conserve power. The differential sensor output is converted into single ended signal and amplified. This signal is converted to digital value. After all the four sensor measurements are completed, the ADC values are sent to the reader as a single data package. The RFID transponder and the sensor interface circuit in the block diagram in Fig. 1 form the implantable unit. This unit is the one that will undergo clinical trial in the future. IV. EXPERIMENTAL RESULTS The measured pressure from the proof of concept system is shown in Fig. 3. The graph shows the pressure readings of the sensors at clogged and unclogged condition. The clog shown in this graph is between sensors S3 and S4. The pressure reading of S3 is the highest as it has the highest static column of liquid when clogged. When there is no clog, there is no static column of liquid in the catheter and hence the reduction of pressure. The set up was tested for clogs at different locations in the shunt and the system recognized the clogs in each of those conditions.
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robust, but the flow measurement can be error prone. Pressure sensor offsets drifts with time, so in an implant system, zeroing this offset is difficult and can cause error in flow measurement over time.
4
Pressure (kPa)
2 0
-2 -4
P1
Clog between S3 and S4
No clog
V. CONCLUSION
P2 P3
-6
P4
-8 0
20
40
60
80
100
No: of samples
Figure 3. Pressure variation for clogged and unclogged shunt.
The flow rate is measured using Thomas Scientific 3500 Traceable ultra-low flow meter. This instrument displays the instantaneous flow rate and the total volumetric flow. The instantaneous flow rate is set and the pressure measurements are taken for a period of 10 minutes. The flow rate is measured by taking the mean of the volumetric flow displayed by the instrument. The mean of the pressure reading for 10 minute period is used to find the calculated flow rate. In the real time system, the flow rate is calculated using the mean of 20 readings taken at 2 samples per second. Velocity and volumetric flow are calculated using (2). Fig. 4 shows the measured and calculated volumetric flow rates through the shunt at different frictional pressure loss between P4-P3. From the graph it is evident that when flow rate increases, pressure drop due to friction will increase. In reality, the obstruction in shunt happens gradually over time and this increases resistance and hence a decrease in flow. The measured pressure drop also decreases due to the flow rate reduction. So, in general, this method can be used for calculating the reduced flow when the system is partially obstructed. The calculated flow rate (from our system) has less than 10% error compared to the ground truth flow rate measured. An error bar is created for the uncertainty in calculated flow rate using the σ of the P4-P3 reading at different valve settings.
This paper presents a proof of concept system for a wireless clog monitoring and flow measurement for Hydrocephalus shunts. The experimental result verifies the technique suggested in the paper to determine the location of clog and flow measurement is appropriate for the requirements. The wireless powering and data transfer was done through commercially available off the shelf development board. Future directions include exploring circuit techniques to improve the accuracy of flow measurement, design a valve control mechanism to adjust the flow rate of CSF at different body postures. REFERENCES [1] [2] [3] [4]
[5] [6]
[7] [8] [9]
[10]
[11]
25.00 Measured (flow meter)
[12]
20.00
Flow rate (ml/min)
Calculated (our system) 15.00
[13] 10.00
[14] 5.00
0.00 0.100
0.200
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0.400 0.500 Frictional Pressure drop (kPa)
0.600
[15]
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Figure 4. Measured, calculated flow rate at different P4-P3 with error bar.
[16]
The maximum power consumed by the transponder for signal conditioning, data transfer and the sensor excitation is 10.1 mW at 3.3 V. The power consumption of the custom designed sensor interface circuit for sensor excitation and amplification is 1.55 mW. The clog measurement system is
[17] [18] [19]
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G. Cinalli, W.J. Maixner, C. Sainte-Rose, Pediatric Hydrocephalus, Milan, Springer-Verlag, 2006. http://www.nhfonline.org/info.php?id=facts M.S. Greenberg, Handbook of Neurosurgery, New York, Thieme, 2010 I.G. Bloomfield, I.H Johnston, L.E Bilston. Effects of proteins, blood cells and glucose on the viscosity of cerebrospinal fluid. Pediatr Neurosurg 28: pp. 246 –251, 1998. E. Levin, S. Muravchick, M.I. Gold. Density of human cerebrospinal fluid and tetracaine solutions. Anesth Analg: pp. 814-817, 1981. Metwally Emam et al “A novel microdevice for the treatment of hydrocephalus: design and fabrication of an array of microvalves and microneedles”, Microsystem Technologies, Vol.14, pp. 371–378, 2008 http://www.hydroassoc.org/hydrocephalus-education-andsupport/learning-about-hydrcephalus/treatment-of-hydrocephalus/ W.H. Ko, C.W Meyrick, H.L Rekate. Cerebrospinal-Fluid ControlSystem. Proc. IEEE` pp. 1226-1235, 1988. W. Bertrand, D.Harper, L. Speckman, A. Kiehl, R. Scheer. Implantable cerebral spinal fluid drainage system. U.S. Patent 7309330, issued Dec. 18, 2007. K. Miesel, L. Stylos. Intracranial monitoring and therapy delivery control device, system, and method. U.S. Patent 6248080, issued Jun. 19, 2001 L. Ludin, C. Mauge. Programmable shunt with electromechanical valve actuator. U.S. Patent US8123714, issued Feb. 28, 2012. A. Ginggen, Y. Tardy, R. Crivelli, T. Bork, P. Renaud, "A Telemetric Pressure Sensor System for Biomedical Applications," IEEE Transactions on Biomedical Engineering, pp. 1374-1381, April 2008. C. Li, P.M.Wu, J. Han, C.H. Ahn, “A flexible polymer tube lab-chip integrated with microsensors for smart microcatheter,” Biomed. Microdevices pp. 671-679, 2008. A. Ahmed, G. Sandlas, P . Kothari, D . Sarda, A. Gupta, P. Karkera, P . Joshi, “Outcome analysis of shunt surgery in hydrocephalus,” J Indian Association Pediatric Surg, pp. 98-101, 2009. A.L. Albright, I.F. Pollack, P.D. Adelson, Principles and Practice of Pediatric Neurosurgery, New York, Thieme, 1999. S.R. Browd, B.T. Ragel “Failure of Cerebrospinal Fluid Shunts: Part I: Obstruction and Mechanical Failure,” Pediatric Neurol, 34: 2, 2006. R.J. Houghtalen, A.O. Akan, N. Hwang, Fundamentals of Hydraulic Engineering Systems, 4th ed. New Jersey, Prentice-Hall, 2009. H. Lamb, Hydrodynamics, 6th ed. Cambridge, Cambridge Univ. Press, 1953. http://www.ti.com/tool/ez430-tms37157
