Literature DB >> 25964065

Panorama Ultrasound for Navigation and Guidance of Epidural Anesthesia.

Hedyeh Rafii-Tari1, Victoria A Lessoway2, Allaudin A Kamani3, Purang Abolmaesumi4, Robert Rohling5.   

Abstract

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.
Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  3-D panorama ultrasound; Epidural anesthesia; Optical tracking; Ultrasound guidance

Mesh:

Year:  2015        PMID: 25964065     DOI: 10.1016/j.ultrasmedbio.2015.03.012

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  2 in total

1.  Discrimination of thoracic spine from muscle based on their difference in ultrasound reflection and scattering characteristics.

Authors:  Tomohiro Yokoyama; Shohei Mori; Mototaka Arakawa; Eiko Onishi; Masanori Yamauchi; Hiroshi Kanai
Journal:  J Med Ultrason (2001)       Date:  2019-08-21       Impact factor: 1.314

2.  SLIDE: automatic spine level identification system using a deep convolutional neural network.

Authors:  Jorden Hetherington; Victoria Lessoway; Vit Gunka; Purang Abolmaesumi; Robert Rohling
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-03-30       Impact factor: 2.924

  2 in total

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