Adaptive ultrasound imaging of the lumbar spine for guidance of epidural anesthesia
Introduction
In obstetrics, a patient may require the use of epidural anesthesia to ease the pain of labour and delivery. For these patients, the anesthesia is administered into the epidural space near the spine as seen in Fig. 1, at a depth of 20–90 mm from the skin surface [1]. A failed epidural procedure in which the epidural needle goes beyond the epidural space and perforates the dura mater may cause the patient to experience headaches and, in more severe cases, paralysis or death [2].
Considerable research has been done previously on computer aided needle guidance. For the problem of epidural anesthesia, a computer-controlled infusion pump has been proposed as a way to provide feedback of the different tissues encountered at the needle tip (CompuFlo, Medgadget, El Granada, CA). There have also been efforts to use computer-based localization systems to track the needle trajectory [3]. Sophisticated systems have also been constructed to perform robot-assisted needle insertion [4], [5]. None of these systems addresses the problem of the difficulty in visually identifying the epidural target reliably and accurately.
Ultrasound guidance has been proposed for similar anesthesia needle insertion procedures. In [6], Grau presents several peripheral and neuroaxial blocks being performed with ultrasound pre-puncture information or with real-time ultrasound guidance. In the case of epidural anesthesia, it has been observed that the use of pre-puncture ultrasound to view the patient's lumbar anatomy facilitates the localization of the epidural space [2], [7]. Ultrasound images were also used as real-time feedback for epidural procedures on young infants [8] and on parturient subjects [9], [10]. However, ultrasound of the lumbar spine shows an image filled with speckle and artifacts that can impede visualization of important and hard to detect features such as the ligamentum flavum and epidural space. Many post-processing methods employ filters to reduce speckle but all suffer to some degree from loss of fine details as they tend to reject content with high spatial frequency [11].
There are many other techniques for improving ultrasound appearance [12], but the spatial compounding technique is chosen here since it can be implemented on standard commercial machines and is well-suited for the epidural detection problem. Spatial compounding involves imaging at various angles and the interface between the ligamentum flavum and epidural space is usually only visible at certain angles depicted as a short horizontal line pair or “doublet” and is the target for needle insertion. The goal of this research is to improve visibility of the epidural anatomy with a new adaptive spatial compounding technique. Preliminary results on a spine phantom [13] and lumbar anatomy of human subjects [14] were reported previously. This paper starts with a description of the key concepts, followed by extensions to the technique and more performance evaluation and validation.
Section snippets
Methods
Spatial compounding uses beam steering [15], [16], [17], to capture several images of the same region by sending the ultrasound pulses at different angles of incidence. Since speckle noise is dependent on the distribution of reflectors along the ultrasound path [18], changing the beam angle will also change the speckle noise pattern. Given different noise patterns but similar anatomical features, averaging these images will reduce the noise and enhance features.
Spatial compounding has been
Results
In the spine phantom, it is observed that a block size of 48 × 48 and a search range of ±4 × ±4 gives the highest NCC and Laplacian of the ligamentum flavum value between blocks of the reference image and blocks of the warped beam-steered images. This translates to a block size of 9.6 mm and a maximum warping of 0.8 mm vertically and horizontally. These parameters are used for the rest of the spine phantom tests.
Fig. 3 shows different compounding methods using this search region and block size. The
Discussion
The reference images Fig. 3, Fig. 5, Fig. 6 show a high quality ligamentum flavum and bone surface. This is because the reference image in this case was deliberately chosen to have maximum clarity of these structures for the purpose of comparison. However, the beneficial effect of spatial compounding with warping is even more apparent when comparing with frames that are not the reference frame and thus represent more typical images captured without such careful alignment of the reference beam
Conclusions
Spatial compounding is shown to improve the key aspects of image quality in this application of spinal imaging. This is especially apparent in human subjects. The reason is that the epidural space is only visible from some angles, and perception of the characteristic doublet is limited by noise. The reference image in comparison, although having a high gradient and Laplacian for the features, has a low SNR which impedes detection of the features, the doublet may look like speckle. Adding the
Acknowledgements
This work is supported by a Collaborative Health Research Project grant funded by the Natural Sciences and Engineering Research Council and the Canadian Institute of Health Research. Fig. 1 was created by Vicky Earle of the Media Group at the University of British Columbia.
Denis Tran received the B. Eng. degree in computer engineering (2003) and the M.Eng. degree in electrical engineering (2005) from the McGill University (Montreal, Quebec, Canada). He is currently a Ph.D. candidate at the University of British Columbia. His interest is ultrasonography for epidural anesthesiology.
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Denis Tran received the B. Eng. degree in computer engineering (2003) and the M.Eng. degree in electrical engineering (2005) from the McGill University (Montreal, Quebec, Canada). He is currently a Ph.D. candidate at the University of British Columbia. His interest is ultrasonography for epidural anesthesiology.
King Wei Hor received the B.A.Sc. degree in electrical engineering and the M.A.Sc. degree in electrical engineering from the University of British Columbia (Vancouver, British Columbia, Canada). He is currently working at Microsoft Corporation (Redmond, Washington, USA).
Victoria A. Lessoway, RT(R), RDMS, RDCS has held positions as Chief Sonographer, Manager of Education and Research, and Senior Clinical Analyst for a major Picture Archiving and Communication (PACS) company. She has been an invited speaker at medical ultrasound conferences in the USA and Canada and has been the principal or associate author of several papers on various ultrasound research topics, including research involving NASA astronauts on shuttle missions IML-1 and IML-2. Her fetal biometric research resulted in the development of fetal growth charts that currently serve as the British Columbia standard. Ms. Lessoway chaired the founding committee of the Canadian Society of Diagnostic Medical Sonographers (CSDMS) and has held executive positions in local, provincial, and national professional organizations. She was awarded a lifetime membership in the CSDMS in recognition of her significant contribution to medical sonography in Canada.
Allaudin A. Kamani, FRCPC, received the M.D. degree from the University of Manitoba (Winnipeg, Manitoba, Canada). He is currently an Associate Professor in Medicine at the University of British Columbia (Vancouver, British Columbia, Canada). He is also a practicing anesthesiologist at the BC Women's Hospital (Vancouver, BC, Canada).
Robert N. Rohling (M’00) received the B.A.Sc. degree in engineering physics from the University of British Columbia (Vancouver, British Columbia, Canada), the M.Eng. degree in biomedical engineering from McGill University (Montreal, Quebec, Canada), and the PhD degree in information engineering from the University of Cambridge (Cambridge, UK). He worked as the project manager of 3D medical imaging at ALI Technologies from 1999–2000, before joining the University of British Columbia where he is now Associate Professor. Dr. Rohling is a working member of DICOM on multidimensional interchange. He is a member of Precarn Inc. as part of a Network of Centres of Excellence. He is also the coordinator of the Biomedical Engineering Option and co-coordinator of the Mechatronics program at UBC. In 2002, he was awarded a New Opportunities Fund Award from the Canada Foundation for Innovation to establish a research laboratory called the Ultrasound Innovation Laboratory. His current research areas include adaptive ultrasound, 3D ultrasound, elastography and image-guided surgery.