Delaram Behnami1, Alexander Seitel2, Abtin Rasoulian2, Emran Mohammad Abu Anas2, Victoria Lessoway3, Jill Osborn4, Robert Rohling2,5, Purang Abolmaesumi2. 1. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada. delaramb@ece.ubc.ca. 2. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada. 3. Department of Ultrasound, Women's Hospital, Vancouver, BC, Canada. 4. Department of Anesthesia, St. Paul's Hospital, Vancouver, BC, Canada. 5. Department of Mechanical Engineering, University of British Columbia, Vancouver, BC, Canada.
Abstract
PURPOSE: Facet joint injections and epidural needle insertions are widely used for spine anesthesia. Accurate needle placement is important for effective therapy delivery and avoiding complications arising from damage of soft tissue and nerves. Needle guidance is usually performed by fluoroscopy or palpation, resulting in radiation exposure and multiple needle re-insertions. Several ultrasound (US)-based approaches have been proposed but have not found wide acceptance in clinical routine. This is mainly due to difficulties in interpretation of the complex spinal anatomy in US, which leads to clinicians' lack of confidence in relying only on information derived from US for needle guidance. METHODS: We introduce a multimodal joint registration technique that takes advantage of easy-to-interpret preprocedure computed topography (CT) scans of the lumbar spine to concurrently register a shape+pose model to the intraprocedure 3D US. Common shape coefficients are assumed between two modalities, while pose coefficients are specific to each modality. RESULTS: The joint method was evaluated on patient data consisting of ten pairs of US and CT scans of the lumbar spine. It was successfully applied in all cases and yielded an RMS shape error of 2.1 mm compared to the CT ground truth. The joint registration technique was compared to a previously proposed method of statistical model to US registration Rasoulian et al. (Information processing in computer-assisted interventions. Springer, Berlin, pp 51-60, 2013). The joint framework improved registration accuracy to US in 7 out of 17 visible vertebrae, belonging to four patients. In the remaining cases, the two methods were equally accurate. CONCLUSION: The joint registration allows visualization and augmentation of important anatomy in both the US and CT domain and improves the registration accuracy in both modalities. Observing the patient-specific model in the CT domain allows the clinicians to assess the local registration accuracy qualitatively, which is likely to increase their confidence in using the US model for deriving needle guidance decisions.
PURPOSE: Facet joint injections and epidural needle insertions are widely used for spine anesthesia. Accurate needle placement is important for effective therapy delivery and avoiding complications arising from damage of soft tissue and nerves. Needle guidance is usually performed by fluoroscopy or palpation, resulting in radiation exposure and multiple needle re-insertions. Several ultrasound (US)-based approaches have been proposed but have not found wide acceptance in clinical routine. This is mainly due to difficulties in interpretation of the complex spinal anatomy in US, which leads to clinicians' lack of confidence in relying only on information derived from US for needle guidance. METHODS: We introduce a multimodal joint registration technique that takes advantage of easy-to-interpret preprocedure computed topography (CT) scans of the lumbar spine to concurrently register a shape+pose model to the intraprocedure 3D US. Common shape coefficients are assumed between two modalities, while pose coefficients are specific to each modality. RESULTS: The joint method was evaluated on patient data consisting of ten pairs of US and CT scans of the lumbar spine. It was successfully applied in all cases and yielded an RMS shape error of 2.1 mm compared to the CT ground truth. The joint registration technique was compared to a previously proposed method of statistical model to US registration Rasoulian et al. (Information processing in computer-assisted interventions. Springer, Berlin, pp 51-60, 2013). The joint framework improved registration accuracy to US in 7 out of 17 visible vertebrae, belonging to four patients. In the remaining cases, the two methods were equally accurate. CONCLUSION: The joint registration allows visualization and augmentation of important anatomy in both the US and CT domain and improves the registration accuracy in both modalities. Observing the patient-specific model in the CT domain allows the clinicians to assess the local registration accuracy qualitatively, which is likely to increase their confidence in using the US model for deriving needle guidance decisions.
Authors: Denis Tran; Allaudin A Kamani; Elias Al-Attas; Victoria A Lessoway; Simon Massey; Robert N Rohling Journal: Can J Anaesth Date: 2010-04 Impact factor: 5.063
Authors: Mikael Brudfors; Alexander Seitel; Abtin Rasoulian; Andras Lasso; Victoria A Lessoway; Jill Osborn; Atsuto Maki; Robert N Rohling; Purang Abolmaesumi Journal: Int J Comput Assist Radiol Surg Date: 2015-04-18 Impact factor: 2.924
Authors: Abtin Rasoulian; Alexander Seitel; Jill Osborn; Samira Sojoudi; Saman Nouranian; Victoria A Lessoway; Robert N Rohling; Purang Abolmaesumi Journal: Int J Comput Assist Radiol Surg Date: 2015-06-03 Impact factor: 2.924
Authors: Fouad H Ebrahim; Antonio C O Ruellas; Beatriz Paniagua; Erika Benavides; Karl Jepsen; Larry Wolford; Joao Roberto Goncalves; Lucia H S Cevidanes Journal: Oral Surg Oral Med Oral Pathol Oral Radiol Date: 2017-08-24
Authors: Yunliang Cai; Shaoju Wu; Xiaoyao Fan; Jonathan Olson; Linton Evans; Scott Lollis; Sohail K Mirza; Keith D Paulsen; Songbai Ji Journal: Int J Comput Assist Radiol Surg Date: 2021-05-10 Impact factor: 3.421