Utility of prepuncture ultrasound for localization of the thoracic epidural space.

BACKGROUND: Ultrasound has been shown to facilitate accurate identification of the intervertebral level and to predict skin-to-epidural depth in the lumbar epidural space with reliable precision. We hypothesized that we could accurately predict the skin-to-epidural depth and the intervertebral level in the thoracic spine with the use of ultrasound. METHODS: Twenty patients presenting for thoracic surgery were included in a feasibility study. The skin-to-epidural depth was measured using prepuncture ultrasound in the paramedian window, and the predicted depth was compared with the actual needle depth and the depth as measured by computed tomography. In addition, the intervertebral levels were identified by ultrasound using the "counting up" method, and the results were compared with the levels identified by anesthesiologists. RESULTS: The ultrasound-based depth measurements displayed a bias of 3.21 mm with 95% limits of agreement from -7.47 to 13.9 mm compared with the clinically determined needle depth. The intervertebral levels identified by the anesthesiologists and the sonographer matched in only 40% of cases. CONCLUSION: Ultrasound-based measurements of skin-to-epidural depth show acceptable agreement with the actual depth observed during epidural catheterization; however, the limits of agreement are wide, which restricts the predictive value of ultrasound-based measurements. Further study is required to delineate the role of ultrasound in thoracic epidural catheterizations.

Single-operator real-time ultrasound-guidance to aim and insert a lumbar epidural needle.

PURPOSE: In conventional practice of epidural needle placement, determining the interspinous level and choosing the puncture site are based on palpation of anatomical landmarks, which can be difficult with some subjects. Thereafter, the correct passage of the needle towards the epidural space is a blind "feel as you go" method. An aim-and-insert single-operator ultrasound-guided epidural needle placement is described and demonstrated. METHOD: Nineteen subjects undergoing elective Cesarean delivery consented to undergo both a pre-puncture ultrasound scan and real-time paramedian ultrasound-guidance for needle insertion. Following were the study objectives: to measure the success of a combined spinal-epidural needle insertion under real-time guidance, to compare the locations of the chosen interspinous levels as determined by both ultrasound and palpation, to measure the change in depth of the epidural space from the skin surface as pressure is applied to the ultrasound transducer, and to investigate the geometric limitations of using a fixed needle guide. RESULTS: One subject did not participate in the study because pre-puncture ultrasound examination showed unrecognizable bony landmarks. In 18 of 19 subjects, the epidural needle entered the epidural space successfully, as defined by a loss-of-resistance. In two subjects, entry into the epidural space was not achieved despite ultrasound guidance.Eighteen of the 19 interspinous spaces that were identified using palpation were consistent with those determined by ultrasound. The transducer pressure changed the depth of the epidural space by 2.8 mm. The measurements of the insertion lengths corresponded with the geometrical model of the needle guide, but the needle required a larger insertion angle than would be needed without the guide. CONCLUSION: This small study demonstrates the feasibility of the ultrasound-guidance technique. Areas for further development are identified for both ultrasound software and physical design.

Preinsertion paramedian ultrasound guidance for epidural anesthesia.

BACKGROUND: Ultrasound is receiving growing interest for improving the guidance of needle insertion in epidural anesthesia. Defining a paramedian ultrasound scanning technique would be helpful for correctly identifying the vertebral level. Finding surrogate measures of the depth of the epidural space may also improve the ease of scanning. METHODS: We examined 20 parturients with pre-epidural ultrasound in the paramedian plane, and the predicted depth was compared with the actual midline depth. The actual depth was also compared with subject biometrics, depth of transverse process, and thickness of lumbar fat. RESULTS: The scanning technique allowed the depth of the epidural space to be measured in all subjects. The depth measured in ultrasound was strongly correlated to the actual depth (R(2) = 0.8 and 95% limits of agreement of -14.8 to 5.2 mm), unlike patient biometrics (R(2) < 0.25), the depth of the neighboring transverse processes (R(2) = 0.35 and 95% limits of agreement of -13.8 to 19.1 mm), or the thickness of overlying fat (R(2) = 0.66). The duration of the ultrasound scan was 10 min at the beginning of the trial and 3 min for the last subjects. CONCLUSIONS: Paramedian ultrasound can be used to estimate the midline depth to the epidural space. The surrogate measures are not sufficiently correlated with the depth to the epidural space to recommend them as a replacement for the actual depth to the epidural space measurement.

Detection of an invisible needle in ultrasound using a probabilistic SVM and time-domain features.

We propose a novel learning-based approach to detect an imperceptible hand-held needle in ultrasound images using the natural tremor motion. The minute tremor induced on the needle however is also transferred to the tissue in contact with the needle, making the accurate needle detection a challenging task. The proposed learning-based framework is based on temporal analysis of the phase variations of pixels to classify them according to the motion characteristics. In addition to the classification, we also obtain a probability map of the segmented pixels by cross-validation. A Hough transform is then used on the probability map to localize the needle using the segmented needle and posterior probability estimate. The two-step probability-weighted localization on the segmented needle in a learning framework is the key innovation which results in localization improvement and adaptability to specific clinical applications. The method was tested in vivo for a standard 17 gauge needle inserted at 50-80° insertion angles and 40-60mm depths. The results showed an average accuracy of (2.12°, 1.69mm) and 81%±4% for localization and classification, respectively.

Ultrasound-Guided Spine Anesthesia: Feasibility Study of a Guidance System.

Spinal needle injections are guided by fluoroscopy or palpation, resulting in radiation exposure and/or multiple needle re-insertions. Consequently, guiding these procedures with live ultrasound has become more popular, but images are still challenging to interpret. We introduce a guidance system based on augmentation of ultrasound images with a patient-specific 3-D surface model of the lumbar spine. We assessed the feasibility of the system in a study on 12 patients. The system could accurately provide augmentations of the epidural space and the facet joint for all subjects. Following conventional, fluoroscopy-guided needle placement, augmentation accuracy was determined according to the electromagnetically tracked final position of the needle. In 9 of 12 cases, the accuracy was considered sufficient for successfully delivering anesthesia. The unsuccessful cases can be attributed to errors in the electromagnetic tracking reference, which can be avoided by a setup reducing the influence of the metal C-arm.

Registration of a statistical model to intraoperative ultrasound for scaphoid screw fixation.

PURPOSE: Volar percutaneous scaphoid fracture fixation is conventionally performed under fluoroscopy-based guidance, where surgeons need to mentally determine a trajectory for the insertion of the screw and its depth based on a series of 2D projection images. In addition to challenges associated with mapping 2D information to a 3D space, the process involves exposure to ionizing radiation. Three-dimensional ultrasound has been suggested as an alternative imaging tool for this procedure; however, it has not yet been integrated into clinical routine since ultrasound only provides a limited view of the scaphoid and its surrounding anatomy. METHODS: We propose a registration of a statistical wrist shape + scale + pose model to a preoperative CT and intraoperative ultrasound to derive a patient-specific 3D model for guiding scaphoid fracture fixation. The registered model is then used to determine clinically important intervention parameters, including the screw length and the trajectory of screw insertion in the scaphoid bone. RESULTS: Feasibility experiments are performed using 13 cadaver wrists. In 10 out of 13 cases, the trajectory of screw suggested by the registered model meets all clinically important intervention parameters. Overall, an average 94 % of maximum allowable screw length is obtained based on the measurements from gold standard CT. Also, we obtained an average 92 % successful volar accessibility, which indicates that the trajectory is not obstructed by the surrounding trapezium bone. CONCLUSIONS: These promising results indicate that determining clinically important screw insertion parameters for scaphoid fracture fixation is feasible using 3D ultrasound imaging. This suggests the potential of this technology in replacing fluoroscopic guidance for this procedure in future applications.

Panorama Ultrasound for Navigation and Guidance of Epidural Anesthesia.

Despite the common use of epidural anesthesia in obstetrics and surgery, the procedure can be challenging, especially for obese patients. We propose the use of an ultrasound guidance system employing a transducer-mounted camera to create 3-D panorama ultrasound volumes of the spine, thereby allowing identification of vertebrae and selection of puncture site, needle trajectory and depth of insertion. The camera achieves absolute position estimation of the transducer with respect to the patient using a specialized marker strip attached to the skin surface. The guidance system is validated first on a phantom against a commercial optical tracking system and then in vivo by comparing panorama images from human subjects against independent measurements by an experienced sonographer. The results for measuring depth to the epidural space, intervertebral spacing and registration of interspinous gaps to the skin prove the potential of the system for improving guidance of epidural anesthesia. The tracking and visualization are implemented in real time using the 3D Slicer software package.

Needle Trajectory and Tip Localization in Real-Time 3-D Ultrasound Using a Moving Stylus.

Described here is a novel approach to needle localization in 3-D ultrasound based on automatic detection of small changes in appearance on movement of the needle stylus. By stylus oscillation, including its full insertion into the cannula to the tip, the image processing techniques can localize the needle trajectory and the tip in the 3-D ultrasound volume. The 3-D needle localization task is reduced to two 2-D localizations using orthogonal projections. To evaluate our method, we tested it on three different ex vivo tissue types, and the preliminary results indicated that the method accuracy lies within clinical acceptance, with average error ranges of 0.9°-1.4° in needle trajectory and 0.8-1.1 mm in needle tip. Results also indicate that method performance is independent of the echogenicity of the tissue. This technique is a safe way of producing ultrasonic intensity changes and appears to introduce negligible risk to the patient, as the outer cannula remains fixed.

Towards real-time, tracker-less 3D ultrasound guidance for spine anaesthesia.

PURPOSE: Epidural needle insertions and facet joint injections play an important role in spine anaesthesia. The main challenge of safe needle insertion is the deep location of the target, resulting in a narrow and small insertion channel close to sensitive anatomy. Recent approaches utilizing ultrasound (US) as a low-cost and widely available guiding modality are promising but have yet to become routinely used in clinical practice due to the difficulty in interpreting US images, their limited view of the internal anatomy of the spine, and/or inclusion of cost-intensive tracking hardware which impacts the clinical workflow. METHODS: We propose a novel guidance system for spine anaesthesia. An efficient implementation allows us to continuously align and overlay a statistical model of the lumbar spine on the live 3D US stream without making use of additional tracking hardware. The system is evaluated in vivo on 12 volunteers. RESULTS: The in vivo study showed that the anatomical features of the epidural space and the facet joints could be continuously located, at a volume rate of 0.5 Hz, within an accuracy of 3 and 7 mm, respectively. CONCLUSIONS: A novel guidance system for spine anaesthesia has been presented which augments a live 3D US stream with detailed anatomical information of the spine. Results from an in vivo study indicate that the proposed system has potential for assisting the physician in quickly finding the target structure and planning a safe insertion trajectory in the spine.

Real-time ultrasound image classification for spine anesthesia using local directional Hadamard features.

PURPOSE: Injection therapy is a commonly used solution for back pain management. This procedure typically involves percutaneous insertion of a needle between or around the vertebrae, to deliver anesthetics near nerve bundles. Most frequently, spinal injections are performed either blindly using palpation or under the guidance of fluoroscopy or computed tomography. Recently, due to the drawbacks of the ionizing radiation of such imaging modalities, there has been a growing interest in using ultrasound imaging as an alternative. However, the complex spinal anatomy with different wave-like structures, affected by speckle noise, makes the accurate identification of the appropriate injection plane difficult. The aim of this study was to propose an automated system that can identify the optimal plane for epidural steroid injections and facet joint injections. METHODS: A multi-scale and multi-directional feature extraction system to provide automated identification of the appropriate plane is proposed. Local Hadamard coefficients are obtained using the sequency-ordered Hadamard transform at multiple scales. Directional features are extracted from local coefficients which correspond to different regions in the ultrasound images. An artificial neural network is trained based on the local directional Hadamard features for classification. RESULTS: The proposed method yields distinctive features for classification which successfully classified 1032 images out of 1090 for epidural steroid injection and 990 images out of 1052 for facet joint injection. In order to validate the proposed method, a leave-one-out cross-validation was performed. The average classification accuracy for leave-one-out validation was 94 % for epidural and 90 % for facet joint targets. Also, the feature extraction time for the proposed method was 20 ms for a native 2D ultrasound image. CONCLUSION: A real-time machine learning system based on the local directional Hadamard features extracted by the sequency-ordered Hadamard transform for detecting the laminae and facet joints in ultrasound images has been proposed. The system has the potential to assist the anesthesiologists in quickly finding the target plane for epidural steroid injections and facet joint injections.

Ultrasound-guided spinal injections: a feasibility study of a guidance system.

PURPOSE: Facet joint injections of analgesic agents are widely used to treat patients with lower back pain. The current standard-of-care for guiding the injection is fluoroscopy, which exposes the patient and physician to significant radiation. As an alternative, several ultrasound guidance systems have been proposed, but have not become the standard-of-care, mainly because of the difficulty in image interpretation by the anesthesiologist unfamiliar with the complex spinal sonography. METHODS: We introduce an ultrasound-based navigation system that allows for live 2D ultrasound images augmented with a patient-specific statistical model of the spine and relating this information to the position of the tracked injection needle. The model registration accuracy is assessed on ultrasound data obtained from nine subjects who had prior CT images as the gold standard for the statistical model. The clinical validity of our method is evaluated on four subjects (of an ongoing in vivo study) which underwent facet joint injections. RESULTS: The statistical model could be registered to the bone structures in the ultrasound volume with an average RMS accuracy of 2.3±0.4 mm. The shape of the individual vertebrae could be estimated from the US volume with an average RMS surface distance error of 1.5±0.4 mm. The facet joints could be identified by the statistical model with an average accuracy of 5.1 ± 1.5 mm. CONCLUSIONS: The results of this initial feasibility assessment suggest that this ultrasound-based system is capable of providing information sufficient to guide facet joint injections. Further clinical studies are warranted.

Bone enhancement in ultrasound using local spectrum variations for guiding percutaneous scaphoid fracture fixation procedures.

PURPOSE: The scaphoid bone is the most frequently fractured bone in the wrist. When fracture fixation is indicated, a screw is inserted into the bone either in an open surgical procedure or percutaneously under fluoroscopic guidance. Due to the complex geometry of the wrist, fracture fixation is a challenging task. Fluoroscopic guidance exposes both the patient and the physician to ionizing radiation. Ultrasound-based guidance has been suggested as a real-time, radiation-free alternative. The main challenge of using ultrasound is the difficulty in interpreting the images due to the low contrast and noisy nature of the data. METHODS: We propose a bone enhancement method that exploits local spectrum features of the ultrasound image. These features are utilized to design a set of quadrature band-pass filters and subsequently estimate the local phase symmetry, where high symmetry is expected at the bone locations. We incorporate the shadow information below the bone surfaces to further enhance the bone responses. The extracted bone surfaces are then used to register a statistical wrist model to ultrasound volumes, allowing the localization and interpretation of the scaphoid bone in the volumes. RESULTS: Feasibility experiments were performed using phantom and in vivo data. For phantoms, we obtain a surface distance error 1.08 mm and an angular deviation from the main axis of the scaphoid bone smaller than 5°, which are better compared to previously presented approaches. CONCLUSION: The results are promising for further development of a surgical guidance system to enable accurate anatomy localization for guiding percutaneous scaphoid fracture fixations.

A multi-vertebrae CT to US registration of the lumbar spine in clinical data.

PURPOSE: Spinal needle injections are widely applied to alleviate back pain and for anesthesia. Current treatment is performed either blindly with palpation or using fluoroscopy or computed tomography (CT). Both fluoroscopy and CT guidance expose patients to ionizing radiation. Ultrasound (US) guidance for spinal needle procedures is becoming more prevalent as an alternative. It is challenging to use US as the sole imaging modality for intraoperative guidance of spine needle injections due to the acoustic shadows created by the bony structures of the vertebra that limit visibility of the target areas for injection. We propose registration of CT and the US images to augment anatomical visualization for the clinician during spinal interventions guided by US. METHODS: The proposed method involves automatic global and multi-vertebrae registration to find the closest alignment between CT and US data. This is performed by maximizing the similarity between the two modalities using voxel intensity information as well as features extracted from the input volumes. In our method, the lumbar spine is first globally aligned between the CT and US data using intensity-based registration followed by point-based registration. To account for possible curvature change of the spine between the CT and US volumes, a multi-vertebrae registration step is also performed. Springs are used to constrain the movement of the individually transformed vertebrae to ensure the optimal alignment is a pose of the lumbar spine that is physically possible. RESULTS: Evaluation of the algorithm is performed on 10 clinical patient datasets. The registration approach was able to align CT and US datasets from initial misalignments of up to 25 mm, with a mean TRE of 1.37 mm. These results suggest that the proposed approach has the potential to offer a sufficiently accurate registration between clinical CT and US data.

An augmented reality system for epidural anesthesia (AREA): prepuncture identification of vertebrae.

We propose an augmented reality system to identify lumbar vertebral levels to assist in spinal needle insertion for epidural anesthesia. These procedures require careful placement of a needle to ensure effective delivery of anesthetics and to avoid damaging sensitive tissue such as nerves. In this system, a trinocular camera tracks an ultrasound transducer during the acquisition of a sequence of B-mode images. The system generates an ultrasound panorama image of the lumbar spine, automatically identifies the lumbar levels in the panorama image, and overlays the identified levels on a live camera view of the patient's back. Validation is performed to test the accuracy of panorama generation, lumbar level identification, overall system accuracy, and the effect of changes in the curvature of the spine during the examination. The results from 17 subjects demonstrate the feasibility and capability of achieving an error within clinically acceptable range for epidural anaesthesia.

AREA: an augmented reality system for epidural anaesthesia.

PURPOSE: Spinal needle injection procedures are used for anesthesia and analgesia, such as lumbar epidurals. These procedures require careful placement of a needle, both to ensure effective therapy delivery and to avoid damaging sensitive tissue such as the spinal cord. An important step in such procedures is the accurate identification of the vertebral levels, which is currently performed using manual palpation with a reported 30% success rate for correct identification. METHODS: An augmented reality system was developed to help identify the lumbar vertebral levels. The system consists of an ultrasound transducer tracked in real time by a trinocular camera system, an automatic ultrasound panorama generation module that provides an extended view of the lumbar vertebrae, an image processing technique that automatically identifies the vertebral levels in the panorama image, and a graphical interface that overlays the identified levels on a live camera view of the patient's back. RESULTS: Validation was performed on ultrasound data obtained from 10 subjects with different spine arching. The average success rate for segmentation of the vertebrae was 85%. The automatic level identification had an average accuracy of 6.6 mm. CONCLUSION: The prototype system demonstrates better accuracy for identifying the vertebrae than traditional manual methods.

Instrumentation of the loss-of-resistance technique for epidural needle insertion.

Epidural anesthesia is the most common form of anesthesia in obstetrics. The loss-of-resistance to saline injection is used to confirm when the needle tip enters the epidural space. This procedure is highly dependent on skill and expertise, so it is useful to quantify the tissue resistance during insertion. Sensors are used to measure the force and displacement of the plunger of the syringe and the pressure at the needle tip. A model is also developed to estimate the pressure from the force and displacement. Tests are first performed on porcine tissue to compare the continuous-pressure and intermittent-pressure versions of the technique and to compare the paramedian and midline needle approaches. The accuracy of the pressure model is 12% of peak pressure for the continuous technique and 20% for the intermittent technique. Significant differences in injection flow rate were also found for the muscle, interspinous ligament, and ligamentum flavum encountered in the two approaches. A small clinical study on human subjects was performed and again significant differences were found in flow rate for different tissues. These quantitative results improve the understanding of small differences in feel that have been previously known qualitatively and may help in the development of simulators.

Adaptive ultrasound imaging of the lumbar spine for guidance of epidural anesthesia.

Ultrasound imaging can help in choosing the needle trajectory for epidural anesthesia but anatomical features are not always clear. Spatial compounding can emphasize structures; however, features in the beam-steered images are not aligned due to varying speeds of sound. A non-rigid registration method, called warping, shifts pixels of the beam-steered images to best match the reference image. Linear prediction is used to find the warping vectors and decrease computational cost. An adaptive median-based combination technique for compounding is also investigated. The algorithms are tested on a spine phantom and human subjects. The results show a significant improvement in quality when using warping with adaptive median-based compounding.