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. Author manuscript; available in PMC: 2020 Nov 5.
Published in final edited form as: Ann Biomed Eng. 2018 Jan 5;46(3):452–463. doi: 10.1007/s10439-017-1968-4

AngleNav: MEMS Tracker to Facilitate CT-Guided Puncture

RUI LI 1, SHENG XU 2, WILLIAM F PRITCHARD 2, JOHN W KARANIAN 2, VENKATESH P KRISHNASAMY 2, BRADFORD J WOOD 2, ZION TSZ HO TSE 1,3
PMCID: PMC7641877  NIHMSID: NIHMS1044073  PMID: 29305735

Abstract

As a low-cost needle navigation system, AngleNav may be used to improve the accuracy, speed, and ease of CT-guided needle punctures. The AngleNav hardware includes a wireless device with a microelectromechanical (MEMS) tracker that can be attached to any standard needle. The physician defines the target, desired needle path and skin entry point on a CT slice image. The accuracy of AngleNav was first tested in a 3D-printed calibration platform in a benchtop setting. An abdominal phantom study was then performed in a CT scanner to validate the accuracy of the device’s angular measurement. Finally, an in vivo swine study was performed to guide the needle towards liver targets (n = 8). CT scans of the targets were used to quantify the angular errors and needle tip-to-targeting distance errors between the planned needle path and the final needle position. The MEMS tracker showed a mean angular error of 0.01° with a standard deviation (SD) of 0.62° in the benchtop setting. The abdominal phantom test showed a mean angular error of 0.87° with an SD of 1.19° and a mean tip-to-target distance error of 4.89 mm with an SD of 1.57 mm. The animal experiment resulted in a mean angular error of 6.6° with an SD of 1.9° and a mean tip-to-target distance error of 8.7 mm with an SD of 3.1 mm. These results demonstrated the feasibility of AngleNav for CT-guided interventional workflow. The angular and distance errors were reduced by 64.4 and 54.8% respectively if using AngleNav instead of freehand insertion, with a limited number of operators. AngleNav assisted the physicians to deliver accurate needle insertion during CT-guided intervention. The device could potentially reduce the learning curve for physicians to perform CT-guided needle targeting.

Keywords: CT-guided biopsy or ablation, MEMS sensor, Tracker, Angular tracking

INTRODUCTION

In conventional needle placement procedures, the physician manually orients the needle to match the needle’s physical angle with the planned computed tomography (CT) insertion angle. Needle placement errors can lead to missing the tumor or injury to vital structures. image guidance for needle placement procedures therefore is highly desirable for improving accuracy.

CT-guided needle placement is one of the most common techniques in interventional radiology. it is used for many procedures including biopsy, drainage, and ablation.2,17,19,44,48,49 One drawback of CT-guided therapies is ionizing radiation exposure.12,46 Cone Beam CT (CBCT) as an option on a fluoroscopy system, is an alternative method for CT-guided needle placement. CBCT integrated with needle guidance systems and fluoroscopy allows the physician to see needle locations in real time, relative to target locations, and surrounding organs.8,47

Needle guidance systems could improve needle puncture procedures by providing more accurate needle targeting,4,10,11,13,22,23,27,33,39,42,50 reducing needle deflection1 and the number of total needle passes,4,6,11,22,27,33,37,38,40,50 decreasing radiation expo-sure6,27,33,37,38,40,50 and procedural time,6,11,13,33,37,38,50 reducing the number of needle reposition-ings,4,6,11,22,27,33,37,38,40,50 and thus decreasing procedural risks.33,39,42,43 Many commercially available needle guidance systems utilize electromagnetic tracking,21,28 optical tracking,20 mechanical tracking,7,24 and inertial measurement tracking. Commercially available systems include Philips PercuNav, NeoRad SimpliCT, amedo-LNS, and CAScination CAS-oNE.3,5,15,30,35,36 However, needle guidance systems have not been widely adopted because of cost, ergo nomics, and increased procedure length and complexity.

AngleNav has the goal to improve the accuracy, speed, and ease of needle placement. It is a compact angular tracker based on microelectromechanical systems (MEMS) that provides angular needle guidance to the physician. The sensor inside AngleNav tracked the needle’s angular information. This was then transferred to the smartphone application via Bluetooth connection for display of the angular readings. AngleNav could potentially provide a simple method to assist physicians with CT-guided therapies.

MATERIALS AND METHODS

MEMS-Based Measurement Unit and Software

The overview of the system design architecture is shown in Fig. 1. The inertial measurement unit is attached to a needle guide, and is responsible for detecting and recording the orientation of the needle. The magnetometer helps to improve the accuracy of the angular measurement. The medical image provides the positional information of the needle. The digital data of the angular information (i.e., pitch, roll and yaw) from the inertial measurement unit is transferred into the micro-controller, wherein the data is integrated and processed into the guidance information displayed on the AngleNav software smartphone platform.

FIGURE 1.

FIGURE 1.

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Overview of the AngleNav system design architecture and tracker design, (c) showing its use (1) and the needle channel (2). The description of each part in (3) is shown in Table 1.

The tracker consists of an MEMS-based measurement unit, a microprocessor, and a Bluetooth communication module that wirelessly transmits tracking information to an external computer display (Fig. 2c). The MEMS-based measurement unit contains a gyroscope, a magnetometer sensor, and an accelerometer to provide angular measurements on three axes. The microprocessor manages data fusion from different sensors, digital signal processing as well as communications between each part of the tracker. The tracker case was designed in Solidworks and printed with a Formlab® 3D printer (Formlabs Inc, Somerville, MA). The case was designed with a needle channel that allows the needle to be aligned with the tracker. The rechargeable battery in the tracker provides 4 h of continuous use of the tracker after 1 h of charging. The tracker case was made to be disposable but can also be reusable with a sterilization cover bag.

FIGURE 2.

FIGURE 2.

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3D printed station for calibration of the tracker reading.

AngleNav is a smartphone software application developed by NIH Center for Interventional Oncology for needle tracking, providing an accurate predicted path for needle insertion. The angular orientation of the needle is displayed in the application. The angle calculation is based on the rotational angle of pitch, roll and yaw of the needle. In this way, the AngleNav provides real-time visual and auditory guidance to the physicians during operation.

Benchtop Test

The purpose of the benchtop test is to calibrate the needle in a rigid and controlled environment. A 3D-printed evaluation platform, comprised of a series of holes that point at the center cross which is situated underneath the arch. The directions of the holes are organized so that the accuracy of needle can be evaluated in two dimensions. The three-dimensional X-Y- Z Cartesian coordinate system is defined in Fig. 2a. On the XZ plane, the holes are evenly distributed so that insertion angles are ranges from 0° to 180° (Fig. 2). On the XY plane, the holes are organized into four sets of rows; the first row is at 0° with respect to the XZ plane and the other three are at 10°, 20° and 30° to the XZ plane respectively.

A digital level was used to adjust the flatness of the platform before the calibration. If the platform is uneven, the four screws at each corner are used for leveling. During the evaluation process, the needle was held firmly with the tracker when going through a specific hole with a corresponding incline angle (e.g., 30°) until it hit the targeting cross. The positional information of the needle was then sent to the AngleNav smartphone application to display the angular reading (e.g., 29.9°). The reading was then compared to the actual inclined angle of the needle and the accuracy of the tracker was evaluated. The typical range for acceptable accuracy is ± 1°. If the performance of the tracker is outside this range, the AngleNav has a function to calibrate the tracker to an acceptable level of accuracy. For the benchtop test, 200 insertions were performed in the 3D-printed evaluation platform. Two statistical analyses were carried out to investigate the angular accuracy of the needle insertions.

Potential Clinical Workflow (Fig. 3)

FIGURE 3.

FIGURE 3.

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Comparison between conventional and tracker-assisted CT-guided clinical work flow. (a) shows the conventional procedure. More intermittent CT scans (steps 3–5 as shown in the orange arrows) are likely required in this workflow, lengthening the procedure. Treatments that require multiple needle insertions for multiple targets repeat steps 3–7 (green arrows). (b) Tracker-assistance shows the alternative method for step 4, in which online monitoring of needle position provides instant feedback, potentially reducing the number of confirmatory CT scans for positioning and improving the efficiency of CT in guiding needle placement.

Step 1

Pre-scan preparation: The target area on the patient is sterilized. A CT-compatible, a radio-opaque grid sheet is placed on the sterilized area to be used to define the skin entry point (Fig. 5e).

FIGURE 5.

FIGURE 5.

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Comparison of the angular measurement (a) using the phantom, (b) in-axial plane angle measured by CT compared to (c) the smartphone application’s reading. In (c), the smartphone displays: (1) X, Y, Z as angles of rotation about the roll, pitch and yaw, (2) time function enables creation of a needle time log/event, (3) acceleration of the angular movement, (4) velocity of the angular movement, (5) output function logs out the file and data can be transferable to a computer. The schematic diagram of beeping vs angle deviation is shown in (d) and needle alignment and insertion are shown in (e).

Step 2

Planning scan acquisition: Needle path planning by target and skin entry point identification.

Step 3

Needle insertion: The physician first places the needle tip on the skin entry point (based on the grid position in the CT scan). The needle is then pivoted to the planned angle using the gyroscope device and is inserted into the patient with adjustment as needed, to maintain the intended angle (via audible and visual feedback).

Step 4

Real-time needle tracking: In standard CT-guided procedures, intermediate CT evaluation is required to confirm the needle’s position relative to the target. This is essential for the physician to adjust the angle of insertion accordingly, when the target moves, such as under natural respiration. The smartphone application displays the needle angular information and provides audio feedback, allowing the physician to follow both visual and auditory guidance in the procedure. Compared with the standard method, the MEMS tracker can provide real-time measurement of the needle’s orientation, which may greatly shorten procedure time and increase insertion accuracy.

Step 5

Needle advancement. Step 4 and step 5 were repeated until the needle tip was reasonably close to the target. While intermediate and final CT scans to confirm position may be required with use of the AngleNav, the frequency of intermediate scans during needle insertion may be reduced.

Step 6

Biopsy and/or ablation.

Step 7

Repeated insertions for multiple targets. Steps 3–7 are repeated for more than one specific target.

In the results section, all the CT images are analyzed and interpreted as the way shown in Fig. 4. Moreover, Table 2 shows the definition of symbols for results and discussion section. The yellow line indicates the planned insertion pathway and the red line indicates the actual insertion pathway.

FIGURE 4.

FIGURE 4.

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Interpretation of the CT image. The yellow line shows the planned pathway and the red line shows the actual insertion pathway. The blue lines indicate each parameter.

TABLE 2.

Definitions of symbols.

PD: planned insertion depth
AD: actual insertion depth
AE: axial insertion distance error
RE: radial insertion distance error
TTE: tip-to-target insertion distance error
ARE: angular insertion error
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Needle advancement is an iterative process and requires high level of physician operating skill. Step 4 is a time-consuming process because the physicians need to confirm the real-time needle location. The MEMS tracker with software navigation may shorten the operation time by giving physicians simultaneous and continuous feedback of the relative angle during insertion from the skin to the target. The MEMS tracker may reduce the human errors in needle orientation and number of needle path corrections, especially in procedures which require multiple ablations at different locations. Finally, this method may reduce the number of unnecessary needle re-insertions by providing accurate needle targeting.

CT Abdominal Phantom

After the tracker passed the benchtop accuracy evaluation, the AngleNav accuracy and functionality was further evaluated using an abdominal phantom (CRIS Triple Modality 3D Abdominal Phantom Model 057A) in a CT scanner (MX8000 IDT 16-Detector CT, Philips, Cleveland, OH) (Fig. 5a). The CT phantom was made of silicone, and the needle can be easily inserted and held firmly. In one test, the smartphone application showed an angular reading of 50.03° while the CT image shows the needle was positioned at 50.00° (Fig. 5b). The difference between these two values was hardly measureable (~0.03°), and likely within the error of measurements. In total, there were 25 insertions performed.

In Vivo Study

All procedures were performed under a protocol approved by the Institutional Animal Care and Use Committee using one healthy castrated male Yorkshire domestic swine study (54 kg). The animal was sedated with intramuscular ketamine (25 mg/kg), midazolam (0.5 mg/kg), and glycopyrrolate (0.01 mg/kg); anesthetized with propofol (1 mg/kg IV) and then intubated and maintained under general anesthesia with isoflurane throughout the procedure. Multiple 1.5 mm stainless steel balls were inserted through a needle under ultrasound imaging guidance, to serve as targets. With the animal on the CT scanner table, a radiopaque grid was placed on the skin of the upper abdomen over the liver to guide skin entry point selection (Fig. 5e). After insertion planning, the laser line acted as a reference for in-plane insertions. The needle was maintained in the axial plane during insertion, with the AngleNav reporting deviation from horizontal. An 18-gauge needle was used by physicians to perform the insertions, with or without tracking assistance. CT scans were obtained after each insertion for measurement of accuracy. Following completion of the study, the animal was euthanized.

RESULTS

Benchtop Test

A scatterplot shows the slope coefficient between the measured angle and actual angle to be 1.0053 and R2 as 0.9999. This defines a strong linear relationship between these two quantities. Furthermore, the Bland-Altman plot (Fig. 6a) shows the mean targeting accuracy of 0.01° with maximum absolute error of 1.35° and an SD of 0.62°.

FIGURE 6.

FIGURE 6.

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Statistical analysis between the measured angle and actual angle. (a) shows the data analysis on benchtop test, (b) shows the data analysis on abdominal phantom study.

CT Abdominal Phantom Study

Figure 6b shows the statistical analysis of all 25 insertions. A scatterplot shows the slope coefficient between the actual angle and measured angle to be 1.0011 and R2 as 0.9994. This means there is a strong linear relationship between these two quantities. Furthermore, the Bland-Altman plot shows the mean angular accuracy of 0.86° with a maximum absolute error of 2° and SD of 1.20°. Based on the analysis of the CT images (Fig. 7I), the mean tip-to-target distance error is 4.89 mm with an SD of 1.57 mm.

FIGURE 7.

FIGURE 7.

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(I) shows three examples of needle insertions performed in the phantom: (a-c) show relative positions of needles with respect to the target; (d-f) are the quantitative analysis of needle trajectories. (II, III) show the results from the tracker-assisted and cognitive guided freehand needle insertion respectively. The yellow lines show the planned needle trajectory and the red lines show the actual insertion pathway. The yellow squares show the position of the target and the red circles show the position of the needle tip. On the right-hand side of each image, the six parameters are displayed: PD, AD, RE, AE, TTE and ARE.

Figure 7I shows three insertion examples. The tip-to-target insertion distance error (TTE) for three insertions are 8.6, 2.2 and 3.1 mm respectively. The angular insertion errors (ARE) for each of the three insertions are 1.9°, 1.1° and 1.1° respectively. Taking the first insertion as an example, quantitative analysis shows the ARE is 1.9°, the planned insertion depth (PD) is 95.2 mm, and the actual insertion depth (AD) is 90.0 mm. The tip-to-target distance error is 8.6 mm.

In Vivo Study

At first, the physician followed traditional freehand cognitive guidance, and conducted insertions on four targets inside the liver, as a single pass. Second, the physician followed the tracker-assisted clinical work-flow and conducted insertions on eight targets inside the liver.

Overall, a mean angular error of 6.6° (SD = 1.9°) and a mean tip-to-target distance error of 8.7 mm (SD = 3.1 mm) were achieved for in-plane insertion in three liver targets by the tracker-assisted insertions (Fig. 7II). In comparison, a mean angular error of 18.6° (SD = 11.0°) and a mean tip-to-target distance error of 19.3 mm (SD = 8.0 mm) were achieved in four liver targets by the radiologist’s freehand cognitive guidance (Fig. 7III).

The AngleNav reduced the mean angular insertion error (ARE) and tip-to-target distance insertion error (TTE) by 64.4 and 54.8% during CT-guided needle procedures (Table 3).

TABLE 3.

Statistical analysis between two insertion methods.

Insertion methods Mean ARE (°) Maximum ARE (°) Standard deviation of ARE
Angular error (°)
 AngleNav tracker (a)   6.6   9.4   1.9
 Free hand cognitive guidance (b) 18.6 34.8 11.0
 Improvement (1 – a/b) (%) 64.4 73.0 83.2
Insertion methods Mean TTE (mm) Maximum TTE (mm) Standard deviation of TTE
Tip-to-target distance error (mm)
 AngleNav tracker (a)   8.7 14.4   3.1
 Free hand cognitive guidance (b) 19.3 29.0   8.0
 Improvement (1 – a/b) (%) 54.8 50.3 61.2
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Figure 8a shows all eight tracker-assisted insertions. In (a), (1) shows the average planned insertion distance (PD) is 67.3 mm, which is only 1.5 mm longer than the actual insertion distance (AD). (3) and (4) shows the tip-to-target insertion distance error (TTE) as well as the angular insertion error (ARE) varies in a range which is consistent with the numbers in Table 3.

FIGURE 8.

FIGURE 8.

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In (a), (1) shows the comparison between the PD and AD; (2) shows the comparison between the AE and RE; (3, 4) show the trends of TTE and ARE. (b) Shows the comparison of ARE and TTE between the tracker-assisted and freehand procedures.

DISCUSSION

The CT abdominal phantom experiment showed a mean angular error of 0.87° (SD = 1.19°) while the in vivo experiment showed a mean angular error of 6.60° (SD = 1.9°). The errors could be attributed to the tissue deformation, respiration motion, and human deployment error. In most cases, the physician was able to orient the needle to the planed angle accurately under the guidance of AngleNav. However, tissue could be deformed during insertions in both phantom and in vivo study. After the needle was released, tissue resistance often changed the angle of the needle, resulting in much larger errors in the validation CT scans. In addition, the respiration motion of the swine could cause difficulty in reaching the target.

Both factors may have influenced free-hand insertions potentially more than AngleNav, contributing to an artificial error, which might not be reproduced in clinical use, theoretically. Also, with audible feedback of any kind whatsoever, more attention may have been paid to keeping the needle steadily in the same plane, which might over-emphasized the improvement seen. In the animal experiment, insertions under the visual and auditory guidance by AngleNav showed a mean angular error of 6.60° (SD = 1.9°) compared to a mean angular error of 18.6° (SD = 11.0°) by the radiologist’s freehand insertions. AngleNav also reduced the average time needed to complete the CT-guided procedure.

Comparison with Other Navigation Systems Designed for CT-Guided Interventions

In the field of CT-guided interventions, a variety of methods have been applied to improve the accuracy of the conventional freehand needle insertion. Some research has been conducted with robotic systems. For example, Mbalisike et al.32 proposed a novel robotic guidance system for microwave thermoablation. The study claimed that the smallest tip deviation from the target tumor was 5.3 mm. Meanwhile, the tip-to-target errors shown by other groups such as Dou et al.9 (1.5 ± 1.7 mm), Kettenbach et al.25 (2.3 ± 0.8 mm), and Martinez et al.31 (1.8 ± 1.1 mm) are smaller than our current system. However, the downside of these robotic systems is cost, complexity, workflow, and the need for repetitive needle adjustments. Moreover, these robotic systems require a lengthy registration process as well as extensive operator and staff training.

Leschka et al.29 reported that a Cone Beam CT (CBCT)-guided procedure achieved a mean tip-to-tar-get distance error of 2.8 mm. Another study conducted by Schulz et al.45 had a tip-to-target error which was less than 4.5 mm. The accuracy from those studies is comparable to our results. However, the CBCT-guided procedure reported by Schulz et al. can only accommodate a maximum needle diameter of 15G while the presented device has no limitation on the needle size. Moreover, the CBCT-guided procedure provides no audio guidance to the user like AngleNav.

Some other groups have shown that a laser guidance system can be an alternative solution to improve accuracy.34 Until now, such laser-based systems do not have complete navigation abilities such as real-time tracking of the needle movement. Moreover, these systems require patients to remain still during trajectory planning and needle placement.

Optical tracking is commonly used in surgery with high accuracy.14,16 A device reported by Hassfeld et al.20 achieved a tip-to-target distance error was less than 2 mm. However, the main constraint for optical systems are (1) the requirement of the line of sight between the cameras and the tracking markers mounted on the instrument, and (2) its compatibility with different needle instruments.

Electromagnetic tracking is another popular modality which can be used in biopsy and ablation procedures. In one study by Penzkofer et al.23,41 patients underwent image-guided interventions using EM-tracking technology with an accuracy of 3.1 ± 2.1 mm. However, the performance of electromagnetic tracking is affected by the presence of metal or other magnetic objects, neither of which affect the operation of AngleNav. EM tracking also has a limited workspace.

Finally, some navigation systems embrace the idea of fusion between several imaging modalities such as CT and ultrasound. The complex registration required for this is the main hurdle for the wide application of such systems. Registration between the pre-operative images and navigation system is often based on fiducial markers, so the whole procedure is time-consuming and may be longer than the conventional freehand intervention. Even experienced physicians must invest significant training and practice time26. The similarity to standard procedures and the ease of use of AngleNav could potentially shorten the learning curve for physicians performing CT-guided procedures.

With the assistance of AngleNav, the accuracy of angular insertion was improved by approximately 64.4% and accuracy of tip-to-target insertion distance was improved by 54.8%. The tracker-assisted CT-guided procedure provided real-time needle tracking and hence may reduce the number of intermediate scans for needle path confirmations. The study was limited to needle trajectories that lay within a single axial plane. Further study of the use of the device in off-plane insertions is needed. The light weight and compact design of the AngleNav tracker and the real-time angular feedback make its adoption into current CT-guided procedure workflow feasible. Future work will include study of the safety and efficacy of AngleNav in a clinical trial for biopsy and ablation, with attention towards standard procedural metrics. Although speculative, an accurate and simple method to improve needle accuracy could alter procedures such as tumor biopsy and ablation, where accuracy has become an important element to decipher tumor heterogeneity and appropriately tailored personalized therapies.

TABLE 1.

Specifications of hardware elements shown in Fig. 1.

Part Description Specifications
Tracker case Electronics and needle guide  37 mm (L) × 34 mm (W) × 19.7 mm (H)
Switch Microslide on/off  6.7 mm (L) × 2.9 mm (W) × 1.4 mm (H)
MEMS unit Measure angular, acceleration and magnetic info  30 mm(L) × 30 mm (W) × 1 mm (H), maximum range: acceleration: ± 16 g, angular speed measurement: ± 2000°/s. angular measurement: ± 180°, accuracy of angular reading: 0.01°
Bluetooth Communicate to PC/smartphone  Effective range: 10 m
Microprocessor Digital signal processing  MPU6050, comprised of triple-axis MEMS gyroscope and triple-axis MEMS accelerometer and 9-axis motion fusion by the on-chip digital motion processor
Battery Lithium battery  4-h continuous operation, 400 mAh
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ACKNOWLEDGMENTS

NIH does not endorse or recommend any commercial products, processes, or services. The content of this manuscript does not necessarily reflect the views or policies of the Department of Health and Human Services, nor do mention of trade names, commercial products, or organizations imply endorsement by the USA Government. This work was supported by the Center for Interventional Oncology in the Intramural Research Program of the National Institutes of Health (NIH), grants 1ZIDBC011242 and 1ZIDCL040015.

Footnotes

CONFLICT OF INTEREST

NIH and authors may own intellectual property in the field.

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