High Strain Accelerated Fatigue Failure Testing of ... - ASM International

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© 2005 ASM International. All Rights Reserved. Medical Device Materials II (#05107G)

High Strain Accelerated Fatigue Failure Testing of NiTi Implantable Devices B. Shuman, C. Finger Spiration Inc, Redmond, WA Ken Perry EchoBio, Bainbridge Island WA

Abstract

Introduction

Accelerated testing, using frequencies higher than clinically observed, has been used to reduce time and cost of fatigue testing. Unfortunately, changes in a device design or manufacturing process may require repeating fatigue testing to show that the change does not adversely affect the specified device lifetime. OBJECTIVE: There were three main objectives of this study: To test implantable Nitinol (NiTi) devices in an accelerated fatigue failure test at frequencies and strains higher than seen clinically; To investigate the use of this testing to decrease fatigue testing time; To investigate the use of higher strains as a screening tool for design or processes that may affect fatigue lifetime. METHODS: Different groups of NiTi devices were built with different processing parameters. Quality of electropolish, radius of curvature and pre-test strain were varied and tested against a control group to obtain fatigue lifetime or StrainNumber of cycles to failure (S-N) curves. The resulting S-N curves were generated for each group of data. The S-N curves were overlaid to determine the relative difference in fatigue life between a test group and its control group. RESULTS: The divergence of the two fatigue lifetime (S-N) curves reveals which processes or designs produce devices with longer fatigue life. For certain testing groups, optimal fatigue testing strain values can highlight the differences between groups better than other fatigue testing strain values. Accelerated high strain testing produced results in 1 day of testing while clinically equivalent strain testing took 28 days. CONCLUSIONS: High strain fatigue testing can produce relevant fatigue data much faster than testing at clinically equivalent strains. Optimal strains for determining the difference in fatigue life between processes or designs can be determined by overlaying the S-N curves for two or more groups of samples. Future design and process changes or improvements can be tested using an optimal alternating strain based on the divergence of the S-N curves. The results of the testing could be used to determine if the new design or process has compromised the fatigue lifetime of the device.

Medical device implants experience cyclic strains resulting from the in-vivo conditions in which they are implanted. Accelerated fatigue testing is commonly used to determine the fatigue resistance of a medical device design and, by definition, utilizes frequencies higher than clinically observed. These tests usually subject the test samples to clinically equivalent strains and take weeks to complete. The results typically show if a design “passes” the specified fatigue life rather than showing what the fatigue life of the design actually is or how it compares to fatigue life of other designs. The objective of this study is to investigate the use of accelerated fatigue testing in combination with strains higher than clinically observed. The study includes the investigation of optimal mean and alternating fatigue strains for use in generating fatigue data used to discern the difference between different designs or processes. Fatigue life curves are generated for samples from the different designs and processes and compared to determine if the groups have different fatigue lifetimes. Methods: Testing was performed on NiTi anchors of the Spiration® Intra-Bronchial Valve (IBV™) Device shown in Fig. 1 (www.spirationinc.com). These devices are intended to be used in human airways to block the flow of air to diseased areas of the lung tissue. The samples tested were processed with different properties. Quality of electropolish (EP), radius of curvature and pre-test strain were varied to obtain different testing groups. Each group was fatigue tested along with a control group to obtain a fatigue lifetime curve.



Fatigue Testing the IBV devices: Testing was performed using a high frequency linear motor and custom data acquisition software. The samples were fixtured such that the anchor tip aligned with and was parallel to the axis of movement. Each anchor rested against one of ten actuator pads that were fixed to the motor. Electrical current was run through the anchor and actively monitored to determine when the sample had failed. Figure 3 shows how the devices were fixtured against the actuator.

Figure 1: The Spiration® Intra-Bronchial Valve (IBV™). The arrow points to one anchor Range of deflection and strain The mean fatigue strains were chosen to mimic in-vivo mean strain as closely as possible. Figure 2 below shows a section of the force-deflection curve of the IBV Device that was chosen for the operating range of fatigue testing.

Force-Displacement Curve

Relative Force

0.0006 0.0005 0.0004 0.0003 0.0002 0.0001 0

1 2 3 4

0

0.5

1

1.5

Displacement (mm)

Figure 3: Test setup showing 10 different devices being tested Preliminary testing was performed to determine the optimal test frequency, mean strain and alternating strain. Tests were run at different frequencies while contact between the part and actuator was monitored. The contact between the sample and the actuators was verified in two ways. First the voltage across the part was monitored. If the voltage was erratic, then the sample was jumping off of the actuator pad. Second, a strobe light was used to confirm that the samples were actually moving at the designated frequency. If the anchor was not contacting the actuator, the frequency was faster than the response frequency of the sample, and was reduced. Fatigue testing was then performed by cycling samples at various mean and alternating deflections in 37 ºC air at 40 Hz. Optimal mean and alternating strains were determined based on the differences between the S-N curve of the test groups. Using the optimal testing parameters, tests were performed to determine the sensitivity of the test method. Test sensitivity was determined by testing groups that were hypothesized to have different fatigue lifetimes, but had no observable difference in surface characteristics under SEM. Finally, the relative difference in fatigue life between the sample groups and their control groups was tested. Results and Discussion

Figure 2 Force deflection curve for the fatigue test, N=4. Actual force values were removed for proprietary reasons An FEA model was used to relate the fatigue testing conditions to the estimated material strains. Based on the FEA and material tensile tests the fatigue test deflections resulted in strains spanning between the austenite and martensite phase of the material. Therefore, a non-linear FEA solver, ABAQUS, was used.

Samples that were EP and samples that were not EP processed had significant differences in surface characteristics under SEM. However, samples with different pre-test strain could not be differentiated under SEM.



Figure 4. SEM image representing all Electropolished sample, both pre-test strained and non-strained samples

1/2 Amp. Alt. Strain

The samples from the pre-test strain group were strained to 7% for 5 cycles prior to fatigue testing. The control group was strained to 7% once prior to fatigue testing. When the pre-test strained samples were fatigue tested, they lasted longer than the control group. The differences are more detectable at higher alternating strains and less detectable at lower alternating strains as shown in Fig. 7.

2.0% 1.8% 1.6% 1.4% 1.2% 1.0% 0.8% 0.6% 0.4% 0.2% 0.0% 1E+3

Control Pre-Test Strained 1E+4

1E+5

1E+6

1E+7

1E+8

Cycles to failure

Figure 7. S-N curves for Pre-test strained (strained 5 times) samples versus control samples (strained once). Open markers indicate samples that did not fail.

Figure 5. SEM image of a sample that was electropolished ½ the normal time

Figure 6. SEM image of sample without electropolish

Statistically, the groups were indistinguishable at lower strains, however, at high ½ amplitude alternating strains (1.7%), the T-test p-value was 0.03. Thus, the results of the test sensitivity testing showed that the test was sensitive enough to show a difference in fatigue life when SEM observation could not. This conclusion was based only on the more conservative, low cycle fatigue data. The apparent bimodal behavior of this group of data was not investigated. Testing the Effect of Bend Radius Testing was performed on samples that had a slightly different geometry. The geometrical difference was related to the bend radius of the part at location of the highest strain. It was hypothesized that the geometry could be correlated to fatigue resistance due to differences in strain concentrations. The data, which was acquired at an effective mean strain of 1.4% and an effective ½ amplitude alternating strain of 1.4%, is displayed in Fig. 8.



Fatigue life of different radius IBV anchors vs. Bend Radius

S-N Curve for EP vs 1/2 Time EP and no EP 2.0% 1/2 Amp. Alt. Strain

Radius (mm)

2.53 2.03 1.53 1.03 0.53 0.03 1000

10000

100000

Cycles to failure

1.5% 1.0% 0.5% 0.0% 1E+3

1E+4

1E+5

1E+6

EP 1/2 EP No EP Series3 1E+7 1E+8

Cycles to Failure (n)

The results of this data show no correlation between bend radius and cycles to failure. Prior work1 2 3 4 has shown martensitic phase transformation to increase fatigue resistance under certain circumstances. It is possible, however not investigated here, that the decreased bend radii increased fatigue resistance by inducing local martensitic phase transformation at the point of highest strain. Strain induced martensite may play a more significant role in increasing the fatigue life of samples with a smaller radius. Samples with a larger radius do not have the martensite advantage, however, they have less strain. Martensite strain transformation could be “leveling the playing field”. Testing the Affect of Electropolish Preliminary testing was performed to determine the optimal mean and alternating strain that would best discern the differences between electropolished and non-electropolished sample groups. High alternating strains and low mean strains resulted in larger differences between the groups. This is likely due to the geometry of the IBV device. Therefore, an effective mean strain of 2.7% was selected for the fatigue testing. The next set of testing was run at the selected mean strain while the alternating strain was varied for three groups: EP, ½ time EP and no EP samples. Figure 9 shows the resulting S-N curve for the three groups of data.

Figure 9. S-N curve for EP, ½ time EP and No EP devices. Open markers indicate samples that did not fail. Electropolishing has been shown to reduce micro cracking thus it was expected that the fatigue life would increase significantly. Accordingly, Fig. 9 shows the difference in fatigue resistance between devices that were electropolished and devices that were not. The difference in fatigue life is shown at different alternating strains. The difference between samples that have been electropolished for ½ the amount of time as the EP group can also be differentiated, however, the results are more ambiguous at higher strains. The S-N data shown in Fig. 9 was used to test other groups of non-EP samples at the optimal ½ amplitude alternating strain of 1.1%. Figure 10 shows the relative difference in fatigue life between three groups of samples using an effective ½ amplitude alternating strain of 1.1% and a mean strain of 2.7%.

Cycles to failure (n)

Figure 8. Regression analysis of bend radius and cycles to failure, R2