Real-Time 3D Curved Needle Segmentation Using Combined B-Mode and Power Doppler Ultrasound. In: Golland P, Hata N, Barillot C, Hornegger J, Howe R, editors. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. Cham: Springer International Publishing; 2014. pp. 381-8. [DOI: 10.1007/978-3-319-10470-6_48]

Needle detection using ultrasound B-mode and power Doppler analyses

BACKGROUND

Ultrasound is employed in needle interventions to visualize the anatomical structures and track the needle. Nevertheless, needle detection in ultrasound images is a difficult task, specifically at steep insertion angles.

PURPOSE

A new method is presented to enable effective needle detection using ultrasound B-mode and power Doppler analyses.

METHODS

A small buzzer is used to excite the needle and an ultrasound system is utilized to acquire B-mode and power Doppler images for the needle. The B-mode and power Doppler images are processed using Radon transform and local phase analysis to initially detect the axis of the needle. The detection of the needle axis is improved by processing the power Doppler image using alpha shape analysis to define a region of interest (ROI) that contains the needle. Also, a set of feature maps are extracted from the ROI in the B-mode image. The feature maps are processed using a machine learning classifier to construct a likelihood image that visualizes the posterior needle likelihoods of the pixels. Radon transform is applied to the likelihood image to achieve an improved needle axis detection. Additionally, the region in the B-mode image surrounding the needle axis is analyzed to identify the needle tip using a custom-made probabilistic approach. Our method was utilized to detect needles inserted in ex vivo animal tissues at shallow [20° -40°), moderate [40° -60°), and steep [60° -85°] angles.

RESULTS

Our method detected the needles with failure rates equal to 0% and mean angle, axis, and tip errors less than or equal to 0.7°, 0.6 mm, and 0.7 mm, respectively. Additionally, our method achieved favorable results compared to two recently introduced needle detection methods.

CONCLUSIONS

The results indicate the potential of applying our method to achieve effective needle detection in ultrasound images. This article is protected by copyright. All rights reserved.

Shape Reconstruction Processes for Interventional Application Devices: State of the Art, Progress, and Future Directions

Soft and continuum robots are transforming medical interventions thanks to their flexibility, miniaturization, and multidirectional movement abilities. Although flexibility enables reaching targets in unstructured and dynamic environments, it also creates challenges for control, especially due to interactions with the anatomy. Thus, in recent years lots of efforts have been devoted for the development of shape reconstruction methods, with the advancement of different kinematic models, sensors, and imaging techniques. These methods can increase the performance of the control action as well as provide the tip position of robotic manipulators relative to the anatomy. Each method, however, has its advantages and disadvantages and can be worthwhile in different situations. For example, electromagnetic (EM) and Fiber Bragg Grating (FBG) sensor-based shape reconstruction methods can be used in small-scale robots due to their advantages thanks to miniaturization, fast response, and high sensitivity. Yet, the problem of electromagnetic interference in the case of EM sensors, and poor response to high strains in the case of FBG sensors need to be considered. To help the reader make a suitable choice, this paper presents a review of recent progress on shape reconstruction methods, based on a systematic literature search, excluding pure kinematic models. Methods are classified into two categories. First, sensor-based techniques are presented that discuss the use of various sensors such as FBG, EM, and passive stretchable sensors for reconstructing the shape of the robots. Second, imaging-based methods are discussed that utilize images from different imaging systems such as fluoroscopy, endoscopy cameras, and ultrasound for the shape reconstruction process. The applicability, benefits, and limitations of each method are discussed. Finally, the paper draws some future promising directions for the enhancement of the shape reconstruction methods by discussing open questions and alternative methods.

Integrating robot-assisted ultrasound tracking and 3D needle shape prediction for real-time tracking of the needle tip in needle steering procedures

BACKGROUND

Needle insertions have been used in several minimally invasive procedures for diagnostic and therapeutic purposes. Real-time position of the needle tip is an important information in needle steering systems.

METHODS

This work introduces a robot-assisted ultrasound tracking (R-AUST) system integrated with a needle shape prediction method to provide 3D position of the needle tip. The tracking system is evaluated in phantom and ex vivo beef liver tissues.

RESULTS

An average error of 0.60 mm was found for needle insertion tests inside the phantom tissue. The R-AUST integrated with shape prediction in the beef liver tissue was able to track the needle tip with an average and maximum error of 0.37 and 0.67 mm, respectively. The average error reported in this work is within the mean allowable needle placement error (<2.7 mm) in targeted procedures.

CONCLUSIONS

Integration of R-AUST tracking method with needle shape prediction results in a reasonably accurate real-time tracking suitable for ultrasound-guided needle insertions.

Three-dimensional therapy needle applicator segmentation for ultrasound-guided focal liver ablation

PURPOSE

Minimally invasive procedures, such as microwave ablation, are becoming first-line treatment options for early-stage liver cancer due to lower complication rates and shorter recovery times than conventional surgical techniques. Although these procedures are promising, one reason preventing widespread adoption is inadequate local tumor ablation leading to observations of higher local cancer recurrence compared to conventional procedures. Poor ablation coverage has been associated with two-dimensional (2D) ultrasound (US) guidance of the therapy needle applicators and has stimulated investigation into the use of three-dimensional (3D) US imaging for these procedures. We have developed a supervised 3D US needle applicator segmentation algorithm using a single user input to augment the addition of 3D US to the current focal liver tumor ablation workflow with the goals of identifying and improving needle applicator localization efficiency.

METHODS

The algorithm is initialized by creating a spherical search space of line segments around a manually chosen seed point that is selected by a user on the needle applicator visualized in a 3D US image. The most probable trajectory is chosen by maximizing the count and intensity of threshold voxels along a line segment and is filtered using the Otsu method to determine the tip location. Homogeneous tissue mimicking phantom images containing needle applicators were used to optimize the parameters of the algorithm prior to a four-user investigation on retrospective 3D US images of patients who underwent microwave ablation for liver cancer. Trajectory, axis localization, and tip errors were computed based on comparisons to manual segmentations in 3D US images.

RESULTS

Segmentation of needle applicators in ten phantom 3D US images was optimized to median (Q1, Q3) trajectory, axis, and tip errors of 2.1 (1.1, 3.6)°, 1.3 (0.8, 2.1) mm, and 1.3 (0.7, 2.5) mm, respectively, with a mean ± SD segmentation computation time of 0.246 ± 0.007 s. Use of the segmentation method with a 16 in vivo 3D US patient dataset resulted in median (Q1, Q3) trajectory, axis, and tip errors of 4.5 (2.4, 5.2)°, 1.9 (1.7, 2.1) mm, and 5.1 (2.2, 5.9) mm based on all users.

CONCLUSIONS

Segmentation of needle applicators in 3D US images during minimally invasive liver cancer therapeutic procedures could provide a utility that enables enhanced needle applicator guidance, placement verification, and improved clinical workflow. A semi-automated 3D US needle applicator segmentation algorithm used in vivo demonstrated localization of the visualized trajectory and tip with less than 5° and 5.2 mm errors, respectively, in less than 0.31 s. This offers the ability to assess and adjust needle applicator placements intraoperatively to potentially decrease the observed liver cancer recurrence rates associated with current ablation procedures. Although optimized for deep and oblique angle needle applicator insertions, this proposed workflow has the potential to be altered for a variety of image-guided minimally invasive procedures to improve localization and verification of therapy needle applicators intraoperatively.

Active Localization and Tracking of Needle and Target in Robotic Image-Guided Intervention Systems

This paper describes a framework of algorithms for the active localization and tracking of flexible needles and targets during image-guided percutaneous interventions. The needle and target configurations are tracked by Bayesian filters employing models of the needle and target motions and measurements of the current system state obtained from an intra-operative imaging system which is controlled by an entropy-minimizing active localization algorithm. Versions of the system were built using particle and unscented Kalman filters and their performance was measured using both simulations and hardware experiments with real magnetic resonance imaging data of needle insertions into gel phantoms. Performance of the localization algorithms is given in terms of accuracy of the predictions and computational efficiency is discussed.

Methods for Improving the Curvature of Steerable Needles in Biological Tissue

OBJECTIVE

Robotic needle steering systems have the potential to improve percutaneous interventions such as radiofrequency ablation of liver tumors, but steering techniques described to date have not achieved sufficiently small radius of curvature in biological tissue to be relevant to this application. In this study, the impact of tip geometry on steerable needle curvature was examined.

METHODS

Finite-element simulations and experiments with bent-tip needles in ex vivo liver tissue were performed. Motivated by the results of this analysis, a new articulated-tip steerable needle was designed, in which a distal section is actively switched by a robotic system between a straight tip (resulting in a straight path) and a bent tip (resulting in a curved path).

RESULTS

Selection of tip length and angle can greatly improve curvature, with radius of curvature below 5 cm in liver tissue possible through judicious selection of these parameters. An articulated-tip mechanism allows the tip length and angle to be increased, while the straight configuration allows the needle tip to still pass through an introducer sheath and rotate inside the body.

CONCLUSION

Validation testing in liver tissue shows that the new articulated-tip steerable needle achieves smaller radius of curvature compared to bent-tip needles described in previous work.

SIGNIFICANCE

Steerable needles with optimized tip parameters, which can generate tight curves in liver tissue, increase the clinical relevance of needle steering to percutaneous interventions.

Remote Electromagnetic Vibration of Steerable Needles for Imaging in Power Doppler Ultrasound

Robotic needle steering systems for minimally invasive medical procedures require complementary medical imaging systems to track the needles in real time. Ultrasound is a promising imaging modality because it offers relatively low-cost, real-time imaging of the needle. Previous methods applied vibration to the base of the needle using a voice coil actuator, in order to make the needle visible in power Doppler ultrasound. We propose a new method for needle tip vibration, using electromagnetic actuation of small permanent magnets placed inside the needle to improve needle tip visibility in power Doppler imaging. Robotic needle insertion experiments using artificial tissue and ex vivo porcine liver showed that the electromagnetic tip vibration method can generate a stronger Doppler response compared to the previous base vibration method, resulting in better imaging at greater needle depth in tissue. It also eliminates previous issues with vibration damping along the shaft of the needle.

Three-Dimensional Needle Shape Estimation in TRUS-Guided Prostate Brachytherapy Using 2-D Ultrasound Images

In this paper, we propose an automated method to reconstruct the three-dimensional (3-D) needle shape during needle insertion procedures using only 2-D transverse ultrasound (US) images. Using a set of transverse US images, image processing and random sample consensus are used to locate the needle within each image and estimate the needle shape. The method is validated with an in vitro needle insertion setup and a transparent tissue phantom, where two orthogonal cameras are used to capture the true 3-D needle shape for verification. Results showed that the use of at least three images obtained at 75% of the maximum insertion depth or greater allows for maximum needle shape estimation errors of less than 2 mm. In addition, the needle shape can be calculated consistently as long as the needle can be identified in 30% of the transverse US images obtained. Application to permanent prostate brachytherapy is also presented, where the estimated needle shape is compared to manual segmentation and sagittal US images. Our method is intended to help to assess needle placement during manual or robot-assisted needle insertion procedures after the needle has been inserted.