Wireless Biliary Stent System With Wishbone-Array Resonant Magnetoelastic (WARM) Sensor and Conformal Magnetic Layer,

Wireless Biliary Stent System With Wishbone-Array Resonant Magnetoelastic (WARM) Sensor and Conformal Magnetic Layer,
WIRELESS BILIARY STENT SYSTEM WITH WISHBONE-ARRAY RESONANT
MAGNETOELASTIC (WARM) SENSOR AND CONFORMAL MAGNETIC LAYER
Scott R. Green1 and Yogesh B.Gianchandani1,2
Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, USA
2
Department of Electrical Engineering, University of Michigan, Ann Arbor, Michigan, USA
1
ABSTRACT
Stents are used to maintain bile duct patency after duct
narrowing occurs due to various pathologies. Unfortunately, stent
placement results in sludge accumulation within a variable
timeframe, leading to complications such as jaundice or liver
damage. This paper presents a system for wirelessly monitoring
the accumulation of sludge, comprising an integrated
magnetoelastic system with a sensor and biasing permanent
magnet layer that conform to the meshed topology and tubular
curvature of a biliary stent. The sensors have an active area of 7.5
mm x 29 mm and a mass of 9.1 mg. A 38% decrease in the
resonant frequency – from 61.6 kHz to 38.2 kHz – after application
of a sludge simulant totaling 20.9 mg - 2.3X the mass of the sensor
– was measured with the integrated system.
INTRODUCTION
Stents are mesh tubular structures used to impart and maintain
patency in a variety of vessels and ducts that have become
constricted as a result of stenotic pathology. Though the act of
implanting a stent relieves symptoms caused by the constriction,
in-stent restenosis – a reappearance of the narrowing, typically due
to the reaction of the body to the presence of the stent – is a risk
associated with all stenting procedures.
An example of a stent application area – and the focus of this
work – is the bile duct, which transports bile between the liver, gall
bladder, pancreas, and small intestine. The constriction relieved by
stent implantation is often due to pancreatitis, cholangitis, tumors,
or gallstones. Restenosis can occur in an average of 4-5 months
via formation of a bacterial matrix known as biliary “sludge” [1].
The timeframe for clinically significant restenosis to occur is
highly variable from case to case. Current techniques for
diagnosing a blockage are indirect and rely on detecting enzyme
levels that may not increase until after the blockage is significant.
The combined effect of the unknown pathogenesis time course and
the indirect testing methods can result in either unnecessary, prescheduled interventions or in untimely interventions after patients
exhibit outward symptoms of the blockage (and liver damage has
already occurred). As such, a direct method of diagnosis – such as
that shown in Fig. 1 – would enable timely intervention and
eliminate unnecessary procedures.
We have previously reported on magnetoelastic wireless
sensing of sludge accumulation utilizing externally applied AC
interrogative and stent-integrated DC biasing magnetic fields [2].
The magnetic fields cause a magnetoelastic sensor integrated with
the stent to resonate at a frequency that changes as local viscosity
increases and as sludge accumulates. The mechanical resonance
generates an oscillating magnetic field that can be measured with
an external pick-up coil. Our previous work utilized discrete
neodymium magnets to optimally bias the anisotropy of a ribbon
sensor – i.e. a rectangular strip of magnetoelastic material – that
was similar in design to sensors used in industrial/environmental
applications [3-5]. Although this combination was shown to be
effective in benchtop testing, the discrete nature of the magnet and
sensor components leaves room for improvement – especially with
regards to maintaining important distributed flexibility of the
biliary stent. Components that conform to or mimic the open,
flexible structure of the stent would lead to a system that is better
Figure 1: Conceptual diagram of in vivo magnetoelastic sensing of
sludge accumulation for biliary stents.
able to withstand and accommodate the deformations required
during catheter-based delivery, as well as lead to a system that
preserves the structural functionality of the stent. With this
viewpoint, this work focuses on an integrated magnetoelastic
system with a sensor and biasing permanent magnet layer that
conform to the meshed topology and tubular curvature of a biliary
stent. Further, we investigate the impact of structural patterning,
sensor shaping, and sensor material optimization.
DESIGN AND MODELING
Wishbone-Array Sensor
Biliary stents generally reach their final in situ diameter via an
elastic self-expansion. This is in opposition to the plastic
expansion of typical balloon-assisted cardiac stents. The need for
large elastic diameter recovery in biliary stents leads to not only
the utilization of materials with superior elastic properties (e.g.
chrome-nickel Elgiloy or nickel-titanium Nitinol) but also to the
use of open diamond-shaped patterns. Often these patterns are
formed by braiding filaments into a tubular shape.
In keeping with the philosophy of mimicking the design of the
stent with the design of the magnetoelastic sensor, we would like
to use a material with superior elastic properties and to shape the
material in diamond-shaped patterns. Fortunately, MetglasTM
alloys are materials with excellent magnetostrictive properties as
well as excellent elastic properties. For instance, the 2826MB
alloy as used in this work is reported to have a yield strain of 1.6%
[6], which is even higher than most cold-reduced Elgiloy yield
strains of ~1% [7]. MetglasTM is not, however, readily available in
filament form. It is also likely that a resonant sensor fashioned
from braided filaments would have low structural coupling and
high damping at braid cross-over points, limiting efficiency as a
resonator. For these reasons, both the stent and sensor in this work
are batch-fabricated from foils of different base materials utilizing
a photochemical machining (PCM) process [2]. As shown in
Figure 2, an elongated wishbone-array pattern is used; this pattern
allows good mechanical flexibility for both the stent and sensor
while maintaining mechanical coupling and minimizing joint
damping for efficient resonant operation of the sensor. To ensure
that plastic strain in the sensor was avoided during deformation
that is required during catheter-based delivery, an FEA model was
limited to longitudinal motion. The model also predicts signal
amplitude trends for various sensor geometries.
Figure 2: LEFT: A portion of a wishbone-array sensor, along with
important dimensions. RIGHT: Stent with SrFe-PDMS coating.
utilized (Fig. 3). With the fabricated dimensions, FEA suggests
that the wishbone-array sensor can undergo a 50% reduction in
circumference without plastic strain that may result in degradation
of sensor performance.
Because the wishbone-array pattern represents a significant
departure from typical ribbon sensors – which are analyzed for this
application in detail in [2,8] – we developed an FEA tool that is
appropriate for estimating mode shapes and expected signal
amplitudes from sensors with complicated structures. The crux of
this tool is in its use of linearized constitutive equations describing
the coupling between flux, field strength, stress, and strain in a
magnetostrictive material:
G [C ][d ]T G
G
(1)
σ = [C ]ε −
B
μo μ r
G
[ d ][C ] G
1 G.
(2)
ε+
H =−
B
μo μr
μ0 μr
Equations (1) and (2) are versions of the so-called
“piezomagnetic” equations – a name that highlights their similarity
to piezoelectric equations – where σ is the stress vector, C is the
stiffness matrix, ε is the strain, d is the magnetostrictivity matrix, B
is the magnetic flux density vector, H is the field strength vector,
μ0 is the permeability of free space, and μr is the relative
permeability.
Magnetostrictive materials are nonlinear, but
linearization about an operating point in a resonant magnetoelastic
analysis is prudent, with a rationale analogous to that used in
small-signal models of transistor-based circuits. Equations (1) and
(2) are implemented in this work utilizing COMSOL Multiphysics
and coupled time-harmonic (frequency response) induction current
and stress-strain modes.
A detailed look at an FEA
implementation for magnetostrictive materials is in [9]; the
approach used in this work is modified for application to resonant
sensors. In Figure 4, calculated mode shapes for planar wishbonearray sensors are shown. The mode shapes displayed are at
frequencies corresponding to significant peaks in the measured
frequency response for the planar sensors, with the mode shape at
61.6 kHz resulting in the largest response amplitude. Note that the
mode shapes combine significant longitudinal and transverse
motion, whereas mode shapes of traditional ribbon sensors are
Figure 3: FEA calculated strain for
a single wishbone cell.
Figure 4: FEA calculated
mode shape and frequency
predictions.
Conformal Magnetic Layer
To achieve optimal magnetomechanical coupling, the
magnetoelastic material must be biased with a DC magnetic field.
This field offsets the as-fabricated anisotropy of the magnetic
domains in the material, and the optimal field is dependent not
only on the material of the sensor, but also on the feature sizes or
aspect ratio of the final sensor. The process of selecting a bias
field magnitude can be considered analogous to selecting an
operating point for a transistor in an electrical circuit.
Our past work with integrated discrete magnets showed that
sensor performance is improved when the bias field is as uniform
as possible. This uniformity is difficult to achieve with integrated
discrete magnets, because the field strength will necessarily decay
as the distance from the magnets increases. However, if the
magnetized portion of the system were to be continuously
distributed, the field strength could be maintained more uniformly.
This improves the sensor performance and eradicates high
magnetic field gradients that lead to undesirable magnetic forces.
The distributed magnet is chosen in this work to be a layer of
strontium ferrite (SrFe) particles (~1 μm average diameter, Hoosier
Magnetics) suspended in polydimethylsiloxane (PDMS, Sylgard
184, Dow Corning). This choice is made again in keeping with
minimally altering the functionality and structure of the biliary
stent with the additional components. In this case, the polymersuspended particles can be applied in a thin, flexible layer
conforming exactly to the stent structure (Fig. 2).
Other polymers have been used as a base for SrFe particles in
microfabricated magnets described elsewhere [10]. SrFe particles
have the advantages of being chemically inert (owing to their
ceramic nature), and of being widely and inexpensively available
in very small particle sizes. The chemical inertness is especially
valuable in our implantable application. PDMS is chosen in this
work due to its generally accepted biocompatibility and due to
processing ease. In fact, the entire polymer-suspended magnet
fabrication process (as described later) is preferable in terms of
ease compared with alternative options such as sputtering or
electrodeposition of a thin-film magnetic layer.
FABRICATION
Wishbone-Array Sensor
The wishbone-array sensors for this work are batch fabricated
from a 28 μm thick foil of 2826MB MetglasTM utilizing the PCM
process. Feature sizes of the individual struts are 100 μm, which is
near the feature size limit for the technology. The overall size of
the active portion of the sensor (not including the anchor areas
discussed later) is 7.5 mm x 29 mm, with a mass of 9.1 mg.
PCM is a planar process, so the as-fabricated sensors are also
planar. Because the stent application calls for a tubular shape, and
the lateral dimension of the sensor is larger than the diameter of the
stent, the sensor must be curved into a tubular or semi-tubular
shape to best match the stent geometry. Initial attempts to add
curvature to the sensor via mechanical stress proved catastrophic
for the sensor signal. Instead, the tubular shape is achieved in this
work by placing the sensor against the inner wall of a fixture tube
and annealing for 30 minutes. Various final radii can be achieved
by either changing the fixture tube radius or by changing the
anneal temperature. For instance, a 4.6 mm radius results from
annealing at 375 oC for 30 minutes inside a 3.6 mm radius tube,
while a 1.6 mm radius results from annealing inside a 1.25 mm
radius tube. Lower temperatures lead to lesser final curvature.
Conformal Magnetic Layer
To form the conformal magnetic layer, the PDMS is first
mixed in a 10:1 base-to-curing-agent ratio. Subsequently, the SrFe
particles are introduced in 1:1, 3:1, or 1:3 SrFe-to-PDMS by
weight ratios and mixed in by hand until the mixture is consistent
(usually about 1 minute of mixing time). The mixture is then
poured or spread into a mold containing the stent. The stent is then
pealed out of the mold, with a conformal layer of the magnetic
suspension adhered due to surface tension. The layer is then cured
for 30 minutes at 60 oC. Thicker layers can be built up by
repeating the process. Finally, the layer is magnetized uniformly
along the long axis of the stent using a benchtop pulse magnetizer.
In general, the 1:1 SrFe:PDMS ratio offered the best combination
of workability and remnant strength of the ratios tested.
Stent
The stent is also batch fabricated using the PCM process, in
this case from a 100 μm thick foil of Elgiloy. As intended, the
feature sizes and patterns are identical to those of the sensor (Fig.
2). The overall stent size is 5 mm (dia.) x 40 mm.
System Assembly
Lateral portions of the wishbone-array sensor are connected to
the active area with single struts. These areas act as anchors, and
the single struts isolate the vibrating active area from the anchors.
The anchors are bonded to the stent with a thin layer of PDMS.
Subsequently, the stent is rolled into a tubular shape and the
resulting seam where the edges of the stent adjoin is also bonded
with a thin layer of PDMS. The process is shown in Figure 5, and
assemblies are shown in Figures 6 and 7.
EXPERIMENTAL METHODS AND RESULTS
Isolated Sensors
Prior to integration, as-cast planar sensors were evaluated
using a uniform but variable bias field applied by Helmholtz coils
located coaxially with the long axis of the sensor. For all tests, a
swept-frequency network analyzer signal was amplified and sent
through a transmit coil, while the same analyzer measured the
EMF generated on a receive coil. The sensors were located
concentrically with these coils. Results from the initial evaluation
for the largest modal response of four sensors are shown in Figure
8. The optimal bias field – where the amplitude of the response is
largest (10 mV) – is around 5 Oe. A clear dependence of resonant
frequency on bias field can be seen – a manifestation of the ΔE
effect. The frequency and amplitude show repeatable performance
across the tested sensors, as do frequencies and amplitudes from
other modes, indicating a repeatable PCM fabrication process.
The sensors were then thermally treated either above (375 oC)
or below (325 oC) the material Curie temperature (353 oC) and
either remained planar or were given curvature. The resulting
frequency characteristics are shown in Fig. 9. Post-treatment
evaluation showed lower optimal biasing field (~1.5 Oe) and
Figure 6: Assembled Figure 7: Assembled sensor, stent, and
sensor, stent, and magnet layer. The stent seam is not
magnet layer.
bonded here for clarity.
improved signal level (up to 13.5 mV p-p). This important result
shows that thermal treatment facilitates thinner SrFe-PDMS layers,
which simplifies fabrication and minimizes concerns about large
chronically implanted magnetic fields.
As-cast and thermally treated sensors were compressed
through 1.5 mm diameter tubes – a circumferential deformation of
at least 37% – without signal degradation. The repeatable
performance of this test across both as-cast and thermally treated
sensors implies that the thermal treatment process does not lead to
impaired mechanical properties. The slight discrepancy with the
FEA model predictions may be due to an imperfect correlation
between the onset of plastic strain and the onset of strains that
change the magnetomechanical properties of the material.
Bile viscosity changes are precursors to sludge accumulation,
so sensor response to viscosity was evaluated (Fig. 10). The tested
viscosity range is much greater than the physiological range of bile
(1-12 cP), but the results show that sensitivity and signal amplitude
is maintained over a very large range that might be suitable for
other applications. Note that a 2.5 mm x 37.5 mm ribbon sensor
resonant frequency will drop by only 6% over this viscosity range.
Accumulation of sludge results in a mass-loading effect on
the sensor. This process was simulated by the application of two
different materials – paraffin and a spray-on acrylate terpolymer –
to as-cast and thermally treated wishbone-array sensors, as well as
to 2.5 mm x 37.5 mm ribbon sensors. As shown in Figure 11, each
of the sensor types reacts similarly in terms of resonant frequency
to both sludge simulants. Further, the full scale range of each
sensor type extends into the “critical zone”, where accumulation
begins to significantly narrow the cross-sectional flow area.
Integrated System
The integrated system, which consists of a curved wishbonearray sensor and a SrFe-PDMS coated stent, was evaluated in a
manner similar to the isolated sensors but without the bias field
supplied by the Helmholtz coils. In this way, all biasing of the
sensor was provided by the conformal SrFe-PDMS magnetic layer.
For the integrated system, sensitivity to viscosity over a
physiologically appropriate range was measured even as mass was
added. This experimental process showed that the normalized
frequency response of the sensor to viscosity changes was not
significantly affected by mass buildup (Fig. 12). Application of
the acrylate terpolymer sludge simulant as a mass load showed that
the frequency and signal amplitude of the integrated sensor reacted
to mass loads similarly to those of the isolated sensors (Fig. 13).
DISCUSSION
Fig. 5: Fabrication process. A) PCM patterning of Elgiloy (stent)
and MetglasTM (sensor). B) Stent coated in SrFe-PDMS layer and
magnetized. Sensor annealed in a tube. C) Sensor anchors
bonded to stent with PDMS. D) Stent seam bonded with PDMS.
Three important advantages of the wishbone-array sensor
over typical ribbon sensors in this application are made clear by
this work. First, the fine features sizes and large open area of the
pattern present little obstruction to bile flow, which is the primary
objective of a biliary stent. Second, the sensors are much more
accommodating of the large deformations required for catheter-
Figure 8: Evaluation of four as-cast planar
wishbone-array sensors. The points in
these figures represent the mean of three
trials, and the error bars represent the
minimum and maximum recorded values.
Figure 9: Characterization of wishbonearray sensors after thermal treatment.
Figure 10: Isolated sensor response to
changes in viscosity.
Fig. 11: Isolated wishbone and ribbon sensor Figure 13: Response of the system to mass
response to mass loading from different buildup. Mass added to the sensor was
Figure 12: Response of the system to sludge simulants. The curve is determined difficult to separate from mass added to the
with a least-squares regression using the stent, so the equation for the curve in Fig. 11
viscosity changes as mass accumulates.
points and an equation of the form shown.
was used to back-calculate the mass load.
based delivery. Third, the sensors have a higher sensitivity to
Research Fellowship, the NSF ERC for Wireless Integrated
viscosity changes, which is a clinically relevant parameter in many
Microsystems (WIMS), and the University of Michigan. Y.
pathological conditions [11]. The principal disadvantage of the
Gianchandani acknowledges support through the IR/D program
wishbone-array sensor, at least with the present design, is the
while working at the National Science Foundation. The findings
smaller signal amplitude. However, preliminary results show that
do not necessarily reflect the views of the NSF.
the signal amplitude scales with the overall sensor length, so this
disadvantage may be mitigated with a longer sensor design.
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models imply that the sludge simulants used in this work represent
[2] S. R. Green, et al., “Photochemically Patterned Biliary Stents with
a worst-case scenario, as biofilms like sludge are likely to be less
Integrated Permanent Magnets and Deformable Assembly Features
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CONCLUSION
This work integrates a flexible wishbone-array magnetoelastic
sensor and conformal magnetic layer with a biliary stent as a
wireless system that monitors the stent environment. The system
is sensitive to physiologically appropriate viscosity changes,
showing a 7% decrease in resonant frequency in 10 cP fluid. The
system also is capable of measuring mass buildup that is associated
with sludge accumulation, showing a 38% decrease in the resonant
frequency after an applied mass load of 20.9 mg, or 2.3X the mass
of the sensor. The integrated system is robust to deformations
required for delivery and provides a uniform biasing layer that
minimally affects stent mechanics. With appropriate scaling, the
sensing methodology may be applicable in any stent, including
cardiovascular and esophageal stents. Additionally, the improved
viscosity sensitivity of the wishbone-array sensor may find use in
industrial applications like monitoring oil refinement.
ACKNOWLEDGEMENTS
The authors acknowledge Dr. Grace Elta and Dr. Richard
Kwon for discussions regarding stent usage. Mark Richardson
assisted with test setup design and implementation. Metglas Inc.,
Hoosier Magnetics, and Dow Corning provided samples for this
project. This work was supported in part by a NSF Graduate
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