In-plane ultrasonic needle tracking using a fiber-optic hydrophone

Enhanced Needle Visualization With Reflection Tuned Apodization Based on the Radon Transform for Ultrasound Imaging

In ultrasound (US)-guided interventions, accurately tracking and visualizing needles during in-plane insertions are significant challenges due to strong directional specular reflections. These reflections violate the geometrical delay and apodization estimations in the conventional delay and sum beamforming (DASB) degrading the visualization of needles. This study proposes a novel reflection tuned apodization (RTA) to address this issue and facilitate needle enhancement through DASB. The method leverages both temporal and angular information derived from the Radon transforms of the radio frequency (RF) data from plane-wave imaging to filter the specular reflections from the needle and their directivity. The directivity information is translated into apodization center maps through time-to-space mapping in the Radon domain, which is subsequently integrated into DASB. We assess the influence of needle angulations, projection angles in the Radon transform, needle gauge sizes, and the presence of multiple specular interfaces on the approach. The analysis shows that the method surpasses conventional DASB in enhancing the image quality of needle interfaces while preserving the diffuse scattering from the surrounding tissues without significant computational overhead. The work offers promising prospects for improved outcomes in US-guided interventions and better insights into characterizing US reflections with Radon transforms.

Model-Based Needle Identification Using Image Analysis and Needle Library Matching for Ultrasound-Guided Kidney Biopsy: A Feasibility Study

OBJECTIVE

The aim of the work described here was to determine the feasibility of using a novel biopsy needle detection technique that achieves high sensitivity and specificity in a trade-off of resolution, detectability and depth of imaging.

METHODS

The proposed needle detection method consists of a model-based image analysis, temporal needle projection and needle library matching: (i) Image analysis was formulated under the signal decomposition framework; (ii) temporal projection converted the time-resolved needle dynamics into a single image of the desired needle; and (iii) the enhanced needle structure was spatially refined by matching a long, straight linear object in the needle library. The efficacy was examined with respect to different needle visibility.

RESULTS

Our method effectively eliminated confounding effects of the background tissue artifacts more robustly than conventional methods, thus improving needle visibility even with the low contrast between the needle and tissue. The improvement in needle structure further resulted in an improvement in estimation performance for the trajectory angle and tip position.

CONCLUSION

Our three-step needle detection method can reliably detect needle position without the need for external devices, increasing the needle conspicuity and reducing motion sensitivity.

Bend-insensitive fiber optic ultrasonic tracking probe for cardiovascular interventions

BACKGROUND

Transesophageal echocardiography (TEE) is widely used to guide medical device placement in minimally invasive cardiovascular procedures. However, visualization of the device tip with TEE can be challenging. Ultrasonic tracking, enabled by an integrated fiber optic ultrasound sensor (FOUS) that receives transmissions from the TEE probe, is very well suited to improving device localization in this context. The problem addressed in this study is that tight deflections of devices such as a steerable guide catheter can result in bending of the FOUS beyond its specifications and a corresponding loss of ultrasound sensitivity.

PURPOSE

A bend-insensitive FOUS was developed, and its utility with ultrasonic tracking of a steerable tip during TEE-based image guidance was demonstrated.

METHODS

Fiberoptic ultrasound sensors were fabricated using both standard and bend insensitive single mode fibers and subjected to static bending at the distal end. The interference transfer function and ultrasound sensitivities were compared for both types of FOUS. The bend-insensitive FOUS was integrated within a steerable guide catheter, which served as an exemplar device; the signal-to-noise ratio (SNR) of tracking signals from the catheter tip with a straight and a fully deflected distal end were measured in a cardiac ultrasound phantom for over 100 frames.

RESULTS

With tight bending at the distal end (bend radius < 10 mm), the standard FOUS experienced a complete loss of US sensitivity due to high attenuation in the fiber, whereas the bend-insensitive FOUS had largely unchanged performance, with a SNR of 47.7 for straight fiber and a SNR of 36.8 at a bend radius of 3.0 mm. When integrated into the steerable guide catheter, the mean SNRs of the ultrasonic tracking signals recorded with the catheter in a cardiac phantom were similar for straight and fully deflected distal ends: 195 and 163.

CONCLUSION

The FOUS fabricated from bend-insensitive fiber overcomes the bend restrictions associated with the FOUS fabricated from standard single mode fiber, thereby enabling its use in ultrasonic tracking in a wide range of cardiovascular devices.

Enhancement of instrumented ultrasonic tracking images using deep learning

PURPOSE

Instrumented ultrasonic tracking provides needle localisation during ultrasound-guided minimally invasive percutaneous procedures. Here, a post-processing framework based on a convolutional neural network (CNN) is proposed to improve the spatial resolution of ultrasonic tracking images.

METHODS

The custom ultrasonic tracking system comprised a needle with an integrated fibre-optic ultrasound (US) transmitter and a clinical US probe for receiving those transmissions and for acquiring B-mode US images. For post-processing of tracking images reconstructed from the received fibre-optic US transmissions, a recently-developed framework based on ResNet architecture, trained with a purely synthetic dataset, was employed. A preliminary evaluation of this framework was performed with data acquired from needle insertions in the heart of a fetal sheep in vivo. The axial and lateral spatial resolution of the tracking images were used as performance metrics of the trained network.

RESULTS

Application of the CNN yielded improvements in the spatial resolution of the tracking images. In three needle insertions, in which the tip depth ranged from 23.9 to 38.4 mm, the lateral resolution improved from 2.11 to 1.58 mm, and the axial resolution improved from 1.29 to 0.46 mm.

CONCLUSION

The results provide strong indications of the potential of CNNs to improve the spatial resolution of ultrasonic tracking images and thereby to increase the accuracy of needle tip localisation. These improvements could have broad applicability and impact across multiple clinical fields, which could lead to improvements in procedural efficiency and reductions in risk of complications.

Intraoperative Needle Tip Tracking with an Integrated Fibre-Optic Ultrasound Sensor

Ultrasound is an essential tool for guidance of many minimally-invasive surgical and interventional procedures, where accurate placement of the interventional device is critical to avoid adverse events. Needle insertion procedures for anaesthesia, fetal medicine and tumour biopsy are commonly ultrasound-guided, and misplacement of the needle may lead to complications such as nerve damage, organ injury or pregnancy loss. Clear visibility of the needle tip is therefore critical, but visibility is often precluded by tissue heterogeneities or specular reflections from the needle shaft. This paper presents the in vitro and ex vivo accuracy of a new, real-time, ultrasound needle tip tracking system for guidance of fetal interventions. A fibre-optic, Fabry-Pérot interferometer hydrophone is integrated into an intraoperative needle and used to localise the needle tip within a handheld ultrasound field. While previous, related work has been based on research ultrasound systems with bespoke transmission sequences, the new system-developed under the ISO 13485 Medical Devices quality standard-operates as an adjunct to a commercial ultrasound imaging system and therefore provides the image quality expected in the clinic, superimposing a cross-hair onto the ultrasound image at the needle tip position. Tracking accuracy was determined by translating the needle tip to 356 known positions in the ultrasound field of view in a tank of water, and by comparison to manual labelling of the the position of the needle in B-mode US images during an insertion into an ex vivo phantom. In water, the mean distance between tracked and true positions was 0.7 ± 0.4 mm with a mean repeatability of 0.3 ± 0.2 mm. In the tissue phantom, the mean distance between tracked and labelled positions was 1.1 ± 0.7 mm. Tracking performance was found to be independent of needle angle. The study demonstrates the performance and clinical compatibility of ultrasound needle tracking, an essential step towards a first-in-human study.

Medical instrument detection in ultrasound: a review

Medical instrument detection is essential for computer-assisted interventions, since it facilitates clinicians to find instruments efficiently with a better interpretation, thereby improving clinical outcomes. This article reviews image-based medical instrument detection methods for ultrasound-guided (US-guided) operations. Literature is selected based on an exhaustive search in different sources, including Google Scholar, PubMed, and Scopus. We first discuss the key clinical applications of medical instrument detection in the US, including delivering regional anesthesia, biopsy taking, prostate brachytherapy, and catheterization. Then, we present a comprehensive review of instrument detection methodologies, including non-machine-learning and machine-learning methods. The conventional non-machine-learning methods were extensively studied before the era of machine learning methods. The principal issues and potential research directions for future studies are summarized for the computer-assisted intervention community. In conclusion, although promising results have been obtained by the current (non-) machine learning methods for different clinical applications, thorough clinical validations are still required.

Enhanced Photoacoustic Visualisation of Clinical Needles by Combining Interstitial and Extracorporeal Illumination of Elastomeric Nanocomposite Coatings

Ultrasound (US) image guidance is widely used for minimally invasive procedures, but the invasive medical devices (such as metallic needles), especially their tips, can be poorly visualised in US images, leading to significant complications. Photoacoustic (PA) imaging is promising for visualising invasive devices and peripheral tissue targets. Light-emitting diodes (LEDs) acting as PA excitation sources facilitate the clinical translation of PA imaging, but the image quality is degraded due to the low pulse energy leading to insufficient contrast with needles at deep locations. In this paper, photoacoustic visualisation of clinical needles was enhanced by elastomeric nanocomposite coatings with superficial and interstitial illumination. Candle soot nanoparticle-polydimethylsiloxane (CSNP-PDMS) composites with high optical absorption and large thermal expansion coefficients were applied onto the needle exterior and the end-face of an optical fibre placed in the needle lumen. The excitation light was delivered at the surface by LED arrays and through the embedded optical fibre by a pulsed diode laser to improve the visibility of the needle tip. The performance was validated using an ex-vivo tissue model. An LED-based PA/US imaging system was used for imaging the needle out-of-plane and in-plane insertions over approach angles of 20 deg to 55 deg. The CSNP-PDMS composite conferred substantial visual enhancements on both the needle shaft and the tip, with an average of 1.7- and 1.6-fold improvements in signal-to-noise ratios (SNRs), respectively. With the extended light field involving extracorporeal and interstitial illumination and the highly absorbing coatings, enhanced visualisation of the needle shaft and needle tip was achieved with PA imaging, which could be helpful in current US-guided minimally invasive surgeries.

Improving needle visibility in LED-based photoacoustic imaging using deep learning with semi-synthetic datasets

Photoacoustic imaging has shown great potential for guiding minimally invasive procedures by accurate identification of critical tissue targets and invasive medical devices (such as metallic needles). The use of light emitting diodes (LEDs) as the excitation light sources accelerates its clinical translation owing to its high affordability and portability. However, needle visibility in LED-based photoacoustic imaging is compromised primarily due to its low optical fluence. In this work, we propose a deep learning framework based on U-Net to improve the visibility of clinical metallic needles with a LED-based photoacoustic and ultrasound imaging system. To address the complexity of capturing ground truth for real data and the poor realism of purely simulated data, this framework included the generation of semi-synthetic training datasets combining both simulated data to represent features from the needles and in vivo measurements for tissue background. Evaluation of the trained neural network was performed with needle insertions into blood-vessel-mimicking phantoms, pork joint tissue ex vivo and measurements on human volunteers. This deep learning-based framework substantially improved the needle visibility in photoacoustic imaging in vivo compared to conventional reconstruction by suppressing background noise and image artefacts, achieving 5.8 and 4.5 times improvements in terms of signal-to-noise ratio and the modified Hausdorff distance, respectively. Thus, the proposed framework could be helpful for reducing complications during percutaneous needle insertions by accurate identification of clinical needles in photoacoustic imaging.

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.

Neural Network Kalman Filtering for 3-D Object Tracking From Linear Array Ultrasound Data

Many interventional surgical procedures rely on medical imaging to visualize and track instruments. Such imaging methods not only need to be real time capable but also provide accurate and robust positional information. In ultrasound (US) applications, typically, only 2-D data from a linear array are available, and as such, obtaining accurate positional estimation in three dimensions is nontrivial. In this work, we first train a neural network, using realistic synthetic training data, to estimate the out-of-plane offset of an object with the associated axial aberration in the reconstructed US image. The obtained estimate is then combined with a Kalman filtering approach that utilizes positioning estimates obtained in previous time frames to improve localization robustness and reduce the impact of measurement noise. The accuracy of the proposed method is evaluated using simulations, and its practical applicability is demonstrated on experimental data obtained using a novel optical US imaging setup. Accurate and robust positional information is provided in real time. Axial and lateral coordinates for out-of-plane objects are estimated with a mean error of 0.1 mm for simulated data and a mean error of 0.2 mm for experimental data. The 3-D localization is most accurate for elevational distances larger than 1 mm, with a maximum distance of 6 mm considered for a 25-mm aperture.

Ultrasonic Needle Tracking with Dynamic Electronic Focusing

Accurate identification of the needle tip is a key challenge with ultrasound-guided percutaneous interventions in regional anaesthesia, foetal surgery and cardiovascular medicine. In this study, we developed an ultrasonic needle tracking system in which the measured needle tip location was used to set the electronic focus of the external ultrasound imaging probe. In this system, needle tip tracking was enabled with a fibre-optic ultrasound sensor that was integrated into a needle stylet, and the A-lines recorded by the sensor were processed to generate tracking images of the needle tip. The needle tip position was estimated from the tracking images. The dependency of the tracking image on the electronic focal depth of the external ultrasound imaging probe was studied in a water bath and with needle insertions into a clinical training phantom. The variability in the estimated tracked position of the needle tip, with the needle tip at fixed depths in the imaging plane across a depth range from 0.5 to 7.5 cm, was studied. When the electronic focus was fixed, the variability of tracked position was found to increase with distance from that focus. The variability with the fixed focus was found to depend on the the relative distance between the needle tip and focal depth. It was found that with dynamic focusing, the maximum variability of tracked position was below 0.31 mm, as compared with 3.97 mm for a fixed focus.

Deep Learning for Instrumented Ultrasonic Tracking: From Synthetic Training Data to In Vivo Application

Instrumented ultrasonic tracking is used to improve needle localization during ultrasound guidance of minimally invasive percutaneous procedures. Here, it is implemented with transmitted ultrasound pulses from a clinical ultrasound imaging probe, which is detected by a fiber-optic hydrophone integrated into a needle. The detected transmissions are then reconstructed to form the tracking image. Two challenges are considered with the current implementation of ultrasonic tracking. First, tracking transmissions are interleaved with the acquisition of B-mode images, and thus, the effective B-mode frame rate is reduced. Second, it is challenging to achieve an accurate localization of the needle tip when the signal-to-noise ratio is low. To address these challenges, we present a framework based on a convolutional neural network (CNN) to maintain spatial resolution with fewer tracking transmissions and enhance signal quality. A major component of the framework included the generation of realistic synthetic training data. The trained network was applied to unseen synthetic data and experimental in vivo tracking data. The performance of needle localization was investigated when reconstruction was performed with fewer (up to eightfold) tracking transmissions. CNN-based processing of conventional reconstructions showed that the axial and lateral spatial resolutions could be improved even with an eightfold reduction in tracking transmissions. The framework presented in this study will significantly improve the performance of ultrasonic tracking, leading to faster image acquisition rates and increased localization accuracy.

Time-aware deep neural networks for needle tip localization in 2D ultrasound

PURPOSE

Accurate placement of the needle is critical in interventions like biopsies and regional anesthesia, during which incorrect needle insertion can lead to procedure failure and complications. Therefore, ultrasound guidance is widely used to improve needle placement accuracy. However, at steep and deep insertions, the visibility of the needle is lost. Computational methods for automatic needle tip localization could improve the clinical success rate in these scenarios.

METHODS

We propose a novel algorithm for needle tip localization during challenging ultrasound-guided insertions when the shaft may be invisible, and the tip has a low intensity. There are two key steps in our approach. First, we enhance the needle tip features in consecutive ultrasound frames using a detection scheme which recognizes subtle intensity variations caused by needle tip movement. We then employ a hybrid deep neural network comprising a convolutional neural network and long short-term memory recurrent units. The input to the network is a consecutive plurality of fused enhanced frames and the corresponding original B-mode frames, and this spatiotemporal information is used to predict the needle tip location.

RESULTS

We evaluate our approach on an ex vivo dataset collected with in-plane and out-of-plane insertion of 17G and 22G needles in bovine, porcine, and chicken tissue, acquired using two different ultrasound systems. We train the model with 5000 frames from 42 video sequences. Evaluation on 600 frames from 30 sequences yields a tip localization error of [Formula: see text] mm and an overall inference time of 0.064 s (15 fps). Comparison against prior art on challenging datasets reveals a 30% improvement in tip localization accuracy.

CONCLUSION

The proposed method automatically models temporal dynamics associated with needle tip motion and is more accurate than state-of-the-art methods. Therefore, it has the potential for improving needle tip localization in challenging ultrasound-guided interventions.

Efficient Medical Instrument Detection in 3D Volumetric Ultrasound Data

Ultrasound-guided procedures have been applied in many clinical therapies, such as cardiac catheterization and regional anesthesia. Medical instrument detection in 3D Ultrasound (US) is highly desired, but the existing approaches are far from real-time performance. Our objective is to investigate an efficient instrument detection method in 3D US for practical clinical use. We propose a novel Multi-dimensional Mixed Network for efficient instrument detection in 3D US, which extracts the discriminating features at 3D full-image level by a 3D encoder, and then applies a specially designed dimension reduction block to reduce the spatial complexity of the feature maps by projecting from 3D space into 2D space. A 2D decoder is adopted to detect the instrument along the specified axes. By projecting the predicted 2D outputs, the instrument is detected or visualized in the 3D volume. Furthermore, to enable the network to better learn the discriminative information, we propose a multi-level loss function to capture both pixel- and image-level differences. We carried out extensive experiments on two datasets for two tasks: (1) catheter detection for cardiac RF-ablation and (2) needle detection for regional anesthesia. Our experiments show that our proposed method achieves a detection error of 2-3 voxels with an efficiency of about 0.12 sec per 3D US volume. The proposed method is 3-8 times faster than the state-of-the-art methods, leading to real-time performance. The results show that our proposed method has significant clinical value for real-time 3D US-guided intervention.

Enhancement of needle visualization and localization in ultrasound

PURPOSE

This scoping review covers needle visualization and localization techniques in ultrasound, where localization-based approaches mostly aim to compute the needle shaft (and tip) location while potentially enhancing its visibility too.

METHODS

A literature review is conducted on the state-of-the-art techniques, which could be divided into five categories: (1) signal and image processing-based techniques to augment the needle, (2) modifications to the needle and insertion to help with needle-transducer alignment and visibility, (3) changes to ultrasound image formation, (4) motion-based analysis and (5) machine learning.

RESULTS

Advantages, limitations and challenges of representative examples in each of the categories are discussed. Evaluation techniques performed in ex vivo, phantom and in vivo studies are discussed and summarized.

CONCLUSION

Greatest limitation of the majority of the literature is that they rely on original visibility of the needle in the static image. Need for additional/improved apparatus is the greatest limitation toward clinical utility in practice.

SIGNIFICANCE

Ultrasound-guided needle placement is performed in many clinical applications, including biopsies, treatment injections and anesthesia. Despite the wide range and long history of this technique, an ongoing challenge is needle visibility in ultrasound. A robust technique to enhance ultrasonic needle visibility, especially for steeply inserted hand-held needles, and while maintaining clinical utility requirements is needed.

Ultrasonographic needle tip tracking for in-plane infraclavicular brachialis plexus blocks: a randomized controlled volunteer study

BACKGROUND

Onvision is a new technology for needle tip detection and tracking in ultrasound-guided regional anesthesia. The system consists of a piezoelectric sensor close to the needle tip and an electronic console integrated in the ultrasound system. The needle tip is visualized by a green circle on the ultrasound screen. The aim of the study was to investigate the effect of the new needle tip tracking technology on in-plane infraclavicular plexus blocks.

METHODS

The study was a randomized, controlled, observer blinded cross-over trial in 26 healthy volunteers. Two specialists in anesthesiology performed an ultrasound-guided infraclavicular lateral sagittal brachial plexus block with and without needle tip tracking. Primary outcome was procedure time, measured from insertion of the needle until local anesthesia injection was completed. Secondary outcome measures included the number of hand movements and path lengths (assessed by hand motion analysis), block success rate, onset time and duration, discomfort experienced by the volunteers, and the anesthesiologists' confidence as to whether their block would be successful or not.

RESULTS

Mean (SD) procedure time was 183.0 (56.1) s with and 206.8 (56.2) s without needle tip tracking (p=0.16). There were no significant differences in any of the secondary outcomes. Two volunteers' experienced Horner syndrome after blocks without needle tip tracking. No other adverse events occurred during the study.

CONCLUSION

Our study on needle tip tracking for infraclavicular blocks did not reveal any significant differences between active needle tip tracking and the control procedures, neither for primary outcome nor secondary outcome measurements.

TRIAL REGISTRATION NUMBER

NCT03631914.

A Novel Smart Assistance System for Blood Vessel Approaching: A Technical Report Based on Oximetry

In clinical practice, the catheter has to be placed at an accurate position during anesthesia administration. However, effectively guiding the catheter to the accurate position in deeper tissues can be difficult for an inexperienced practitioner. We aimed to address the current issues associated with catheter placement using a novel smart assistance system for blood vessel catheter placement. We used a hollow introducer needle embedded with dual wavelength (690 and 850 nm) optical fibers to advance the tip into the subclavian vessels in anesthetized piglets. The results showed average optical density changes, and the difference between the absorption spectra and hemoglobin concentrations of different tissue components effectively identified different tissues (p < 0.05). The radial basis function neural network (RBFNN) technique was applied to distinguish tissue components (the F-measure value and accuracy were 93.02% and 94%, respectively). Finally, animal experiments were designed to validate the performance of the proposed system. Using this system based on oximetry, we easily navigated the needle tip to the target vessel. Based on the experimental results, the proposed system could effectively distinguish different tissue layers of the animals.

Reliable and accurate needle localization in curvilinear ultrasound images using signature-based analysis of ultrasound beamformed radio frequency signals

PURPOSE

Ultrasound imaging is used in many minimally invasive needle insertion procedures to track the advancing needle, but localizing the needle in ultrasound images can be challenging, particularly at steep insertion angles. Previous methods have been introduced to localize the needle in ultrasound images, but the majority of these methods are based on ultrasound B-mode image analysis that is affected by the needle visibility. To address this limitation, we propose a two-phase, signature-based method to achieve reliable and accurate needle localization in curvilinear ultrasound images based on the beamformed radio frequency (RF) signals that are acquired using conventional ultrasound imaging systems.

METHODS

In the first phase of our proposed method, the beamformed RF signals are divided into overlapping segments and these segments are processed to extract needle-specific features to identify the needle echoes. The features are analyzed using a support vector machine classifier to synthesize a quantitative image that highlights the needle. The quantitative image is processed using the Radon transform to achieve a reliable and accurate signature-based estimation of the needle axis. In the second phase, the accuracy of the needle axis estimation is improved by processing the RF samples located around the signature-based estimation of the needle axis using local phase analysis combined with the Radon transform. Moreover, a probabilistic approach is employed to identify the needle tip. The proposed method is used to localize needles with two different sizes inserted in ex vivo animal tissue specimens at various insertion angles.

RESULTS

Our proposed method achieved reliable and accurate needle localization for an extended range of needle insertion angles with failure rates of 0% and mean angle, axis, and tip errors smaller than or equal to 0 . 7 ∘ , 0.6 mm, and 0.7 mm, respectively. Moreover, our proposed method outperformed a recently introduced needle localization method that is based on B-mode image analysis.

CONCLUSIONS

These results suggest the potential of employing our signature-based method to achieve reliable and accurate needle localization during ultrasound-guided needle insertion procedures.

Minimally invasive photoacoustic imaging: Current status and future perspectives

Photoacoustic imaging (PAI) is an emerging biomedical imaging modality that is based on optical absorption contrast, capable of revealing distinct spectroscopic signatures of tissue at high spatial resolution and large imaging depths. However, clinical applications of conventional non-invasive PAI systems have been restricted to examinations of tissues at depths less than a few cm due to strong light attenuation. Minimally invasive photoacoustic imaging (miPAI) has greatly extended the landscape of PAI by delivering excitation light within tissue through miniature fibre-optic probes. In the past decade, various miPAI systems have been developed with demonstrated applicability in several clinical fields. In this article, we present an overview of the current status of miPAI and our thoughts on future perspectives.

Needle tip tracking for ultrasound-guided peripheral nerve block procedures-An observer blinded, randomised, controlled, crossover study on a phantom model

BACKGROUND

The Onvision needle tip tracking (NTT) is a new technology consisting of a needle with an ultrasound sensor close to the needle tip and a console for computerised signal processing. The aim of the study was to evaluate NTT technology during ultrasound-guided simulated peripheral nerve block procedures in a porcine phantom model.

METHODS

Forty anaesthesiologists performed in-plane and out-of-plane simulated nerve blocks with and without NTT guidance. The primary outcome measure was procedure time. Secondary outcomes were hand movements and the path length travelled by the hands measured by motion analysis, precision of the needle tip related to the target structure, success rates and violations of the target structure, and the participants confidence whether their procedure would be successful or not.

RESULTS

Procedure time was reduced from 66.7 (SD = 47.5) seconds to 43.8 (SD = 29.2) seconds when NTT was used for out-of-plane procedures (P = 0.002). The number of hand movements of the probe hand was 13.9 (SD = 30.2) with NTT and 22.8 (SD = 30.0) without NTT (P = 0.019). No significant differences were registered during the performance of in-plane procedures. The participants confidence in a presumed block success was increased with both in-plane procedures (8.50 (SD = 1.18) with NTT vs 7.65 (SD = 1.96), P = 0.004) and out-of-plane procedures (8.50 (SD = 1.09) vs 7.10 (SD = 1.89), P = 0.0001).

CONCLUSIONS

The new NTT technology significantly reduced the procedure time and the number of hand movements for ultrasound-guided out-of-plane PNB procedures. No significant differences were found for the in-plane procedures.

3D Ultrasonic Needle Tracking with a 1.5D Transducer Array for Guidance of Fetal Interventions

Ultrasound image guidance is widely used in minimally invasive procedures, including fetal surgery. In this context, maintaining visibility of medical devices is a significant challenge. Needles and catheters can readily deviate from the ultrasound imaging plane as they are inserted. When the medical device tips are not visible, they can damage critical structures, with potentially profound consequences including loss of pregnancy. In this study, we performed 3D ultrasonic tracking of a needle using a novel probe with a 1.5D array of transducer elements that was driven by a commercial ultrasound system. A fiber-optic hydrophone integrated into the needle received transmissions from the probe, and data from this sensor was processed to estimate the position of the hydrophone tip in the coordinate space of the probe. Golay coding was used to increase the signal-to-noise (SNR). The relative tracking accuracy was better than 0.4 mm in all dimensions, as evaluated using a water phantom. To obtain a preliminary indication of the clinical potential of 3D ultrasonic needle tracking, an intravascular needle insertion was performed in an in vivo pregnant sheep model. The SNR values ranged from 12 to 16 at depths of 20 to 31 mm and at an insertion angle of 49° relative to the probe surface normal. The results of this study demonstrate that 3D ultrasonic needle tracking with a fiber-optic hydrophone sensor and a 1.5D array is feasible in clinically realistic environments.

Three-Dimensional Ultrasonic Needle Tip Tracking with a Fiber-Optic Ultrasound Receiver

Ultrasound is frequently used for guiding minimally invasive procedures, but visualizing medical devices is often challenging with this imaging modality. When visualization is lost, the medical device can cause trauma to critical tissue structures. Here, a method to track the needle tip during ultrasound image-guided procedures is presented. This method involves the use of a fiber-optic ultrasound receiver that is affixed within the cannula of a medical needle to communicate ultrasonically with the external ultrasound probe. This custom probe comprises a central transducer element array and side element arrays. In addition to conventional two-dimensional (2D) B-mode ultrasound imaging provided by the central array, three-dimensional (3D) needle tip tracking is provided by the side arrays. For B-mode ultrasound imaging, a standard transmit-receive sequence with electronic beamforming is performed. For ultrasonic tracking, Golay-coded ultrasound transmissions from the 4 side arrays are received by the hydrophone sensor, and subsequently the received signals are decoded to identify the needle tip's spatial location with respect to the ultrasound imaging probe. As a preliminary validation of this method, insertions of the needle/hydrophone pair were performed in clinically realistic contexts. This novel ultrasound imaging/tracking method is compatible with current clinical workflow, and it provides reliable device tracking during in-plane and out-of-plane needle insertions.

Handheld Real-Time LED-Based Photoacoustic and Ultrasound Imaging System for Accurate Visualization of Clinical Metal Needles and Superficial Vasculature to Guide Minimally Invasive Procedures

Ultrasound imaging is widely used to guide minimally invasive procedures, but the visualization of the invasive medical device and the procedure’s target is often challenging. Photoacoustic imaging has shown great promise for guiding minimally invasive procedures, but clinical translation of this technology has often been limited by bulky and expensive excitation sources. In this work, we demonstrate the feasibility of guiding minimally invasive procedures using a dual-mode photoacoustic and ultrasound imaging system with excitation from compact arrays of light-emitting diodes (LEDs) at 850 nm. Three validation experiments were performed. First, clinical metal needles inserted into biological tissue were imaged. Second, the imaging depth of the system was characterized using a blood-vessel-mimicking phantom. Third, the superficial vasculature in human volunteers was imaged. It was found that photoacoustic imaging enabled needle visualization with signal-to-noise ratios that were 1.2 to 2.2 times higher than those obtained with ultrasound imaging, over insertion angles of 26 to 51 degrees. With the blood vessel mimicking phantom, the maximum imaging depth was 38 mm. The superficial vasculature of a human middle finger and a human wrist were clearly visualized in real-time. We conclude that the LED-based system is promising for guiding minimally invasive procedures with peripheral tissue targets.

Laser Generated Leaky Acoustic Waves for Needle Visualization

Ultrasound (US)-guided needle operation is usually used to visualize both tissue and needle position such as tissue biopsy and localized drug delivery. However, the transducer-needle orientation is limited due to reflection of the acoustic waves. We proposed a leaky acoustic wave method to visualize the needle position and orientation. Laser pulses are emitted on top of the needle to generate acoustic waves; then, these acoustic waves propagate along the needle surface. Leaky wave signals are detected by the US array transducer. The needle position can be calculated by phase velocities of two different wave modes and their corresponding emission angles. In our experiments, a series of needles was inserted into a tissue mimicking phantom and porcine tissue to evaluate the accuracy of the proposed method. The results show that the detection depth is up to 51 mm and the insertion angle is up to 40° with needles of different diameters. It is demonstrated that the proposed approach outperforms the conventional B-mode US-guided needle operation in terms of the detection range while achieving similar accuracy. The proposed method reveals the potentials for further clinical applications.

Through-needle all-optical ultrasound imaging in vivo: a preclinical swine study

High-frequency ultrasound imaging can provide exquisite visualizations of tissue to guide minimally invasive procedures. Here, we demonstrate that an all-optical ultrasound transducer, through which light guided by optical fibers is used to generate and receive ultrasound, is suitable for real-time invasive medical imaging in vivo. Broad-bandwidth ultrasound generation was achieved through the photoacoustic excitation of a multiwalled carbon nanotube-polydimethylsiloxane composite coating on the distal end of a 300-μm multi-mode optical fiber by a pulsed laser. The interrogation of a high-finesse Fabry-Pérot cavity on a single-mode optical fiber by a wavelength-tunable continuous-wave laser was applied for ultrasound reception. This transducer was integrated within a custom inner transseptal needle (diameter 1.08 mm; length 78 cm) that included a metallic septum to acoustically isolate the two optical fibers. The use of this needle within the beating heart of a pig provided unprecedented real-time views (50 Hz scan rate) of cardiac tissue (depth: 2.5 cm; axial resolution: 64 μm) and revealed the critical anatomical structures required to safely perform a transseptal crossing: the right and left atrial walls, the right atrial appendage, and the limbus fossae ovalis. This new paradigm will allow ultrasound imaging to be integrated into a broad range of minimally invasive devices in different clinical contexts.

Ultrasonic Needle Tracking with a Fibre-Optic Ultrasound Transmitter for Guidance of Minimally Invasive Fetal Surgery

Ultrasound imaging is widely used for guiding minimally invasive procedures, including fetal surgery. Visualisation of medical devices such as medical needles is critically important and it remains challenging in many clinical contexts. During in-plane insertions, a needle can have poor visibility at steep insertion angles and at large insertion depths. During out-of-plane insertions, the needle tip can have a similar ultrasonic appearance to the needle shaft when it intersects with the ultrasound imaging plane. When the needle tip is not accurately identified, it can damage critical structures, with potentially severe consequences, including loss of pregnancy. In this paper, we present a tracking system to directly visualise the needle tip with an ultrasonic beacon. The waves transmitted by the beacon were received by an external ultrasound imaging probe. Pairs of co-registered images were acquired in rapid succession with this probe: a photoacoustic image obtained with the system in receive-only mode, and a conventional B-mode ultrasound image. The beacon comprised a custom elastomeric nanocomposite coating at the distal end of an optical fibre, which was positioned within the lumen of a commercial 22 gauge needle. Delivery of pulsed light to the coating resulted in the photoacoustic generation of ultrasonic waves. The measured tracking accuracies in water in the axial and lateral dimensions were 0.39±0.19 mm and 1.85±0.29 mm, respectively. To obtain a preliminary indication of the clinical potential of this ultrasonic needle tracking system, needle insertions were performed in an in vivo fetal sheep model. The results demonstrate that ultrasonic needle tracking with a fibre-optic transmitter is feasible in a clinically realistic fetal surgery environment, and that it could be useful to guide minimally invasive procedures by providing accurate visualisation of the medical device tip.

Micro-cantilever-based fiber optic hydrophone fabricated by a femtosecond laser

We report an open cavity, cantilever-based fiber optic Fabry-Perot interferometer hydrophone. The hydrophone is made of fused silica material, and its micro-cantilever beam is directly fabricated by femtosecond (fs) laser micromachining. The theoretical analyses and experimental verifications of the frequency response of the sensor are presented.

Looking beyond the imaging plane: 3D needle tracking with a linear array ultrasound probe

Ultrasound is well suited for guiding many minimally invasive procedures, but its use is often precluded by the poor visibility of medical devices. When devices are not visible, they can damage critical structures, with life-threatening complications. Here, we developed the first ultrasound probe that comprises both focused and unfocused transducer elements to provide both 2D B-mode ultrasound imaging and 3D ultrasonic needle tracking. A fibre-optic hydrophone was integrated into a needle to receive Golay-coded transmissions from the probe and these data were processed to obtain tracking images of the needle tip. The measured tracking accuracy in water was better than 0.4 mm in all dimensions. To demonstrate the clinical potential of this system, insertions were performed into the spine and the uterine cavity, in swine and pregnant ovine models in vivo. In both models, the SNR ranged from 13 to 38 at depths of 22 to 38 mm, at out-of-plane distances of 1 to 15 mm, and at insertion angles of 33 to 42 degrees relative to the probe surface normal. This novel ultrasound imaging/tracking probe has strong potential to improve procedural outcomes by providing 3D needle tip locations that are co-registered to ultrasound images, while maintaining compatibility with current clinical workflow.

Coded excitation ultrasonic needle tracking: An in vivo study

PURPOSE

Accurate and efficient guidance of medical devices to procedural targets lies at the heart of interventional procedures. Ultrasound imaging is commonly used for device guidance, but determining the location of the device tip can be challenging. Various methods have been proposed to track medical devices during ultrasound-guided procedures, but widespread clinical adoption has remained elusive. With ultrasonic tracking, the location of a medical device is determined by ultrasonic communication between the ultrasound imaging probe and a transducer integrated into the medical device. The signal-to-noise ratio (SNR) of the transducer data is an important determinant of the depth in tissue at which tracking can be performed. In this paper, the authors present a new generation of ultrasonic tracking in which coded excitation is used to improve the SNR without spatial averaging.

METHODS

A fiber optic hydrophone was integrated into the cannula of a 20 gauge insertion needle. This transducer received transmissions from the ultrasound imaging probe, and the data were processed to obtain a tracking image of the needle tip. Excitation using Barker or Golay codes was performed to improve the SNR, and conventional bipolar excitation was performed for comparison. The performance of the coded excitation ultrasonic tracking system was evaluated in an in vivo ovine model with insertions to the brachial plexus and the uterine cavity.

RESULTS

Coded excitation significantly increased the SNRs of the tracking images, as compared with bipolar excitation. During an insertion to the brachial plexus, the SNR was increased by factors of 3.5 for Barker coding and 7.1 for Golay coding. During insertions into the uterine cavity, these factors ranged from 2.9 to 4.2 for Barker coding and 5.4 to 8.5 for Golay coding. The maximum SNR was 670, which was obtained with Golay coding during needle withdrawal from the brachial plexus. Range sidelobe artifacts were observed in tracking images obtained with Barker coded excitation, and they were visually absent with Golay coded excitation. The spatial tracking accuracy was unaffected by coded excitation.

CONCLUSIONS

Coded excitation is a viable method for improving the SNR in ultrasonic tracking without compromising spatial accuracy. This method provided SNR increases that are consistent with theoretical expectations, even in the presence of physiological motion. With the ultrasonic tracking system in this study, the SNR increases will have direct clinical implications in a broad range of interventional procedures by improving visibility of medical devices at large depths.

Injectable biomaterials: a perspective on the next wave of injectable therapeutics

We are experiencing a new wave of injectable therapeutics (namely/injectable biomaterials) to complement injectable drugs and injectable biologics, and to serve as the basis for injectable combinatorial therapeutics. Injectable biomaterials contribute to the treatment of the fluid-filled defects which often result from disease and injury, by providing the missing physical framework (i.e. the stroma). However, while injectable matrices may be necessary for the successful treatment of certain lesions, they will not likely be sufficient. Chemoattractants for select endogenous cells, or cells themselves, may need to be incorporated into the matrix prior to its injection to ensure the necessary cellular repopulation of the cavitary defect. These agents and others (drugs and biologics) delivered by the matrix represent the new category of injectable combinatorial therapeutics.