MOTIVATION: Spinal needle injections are technically demanding procedures. The use of ultrasound image guidance without prior CT and MR imagery promises to improve the efficacy and safety of these procedures in an affordable manner. METHODOLOGY: We propose to create a statistical shape model of the lumbar spine and warp this atlas to patient-specific ultrasound images during the needle placement procedure. From CT image volumes of 35 patients, statistical shape model of the L3 vertebra is built, including mean shape and main modes of variation. This shape model is registered to the ultrasound data by simultaneously optimizing the parameters of the model and its relative pose. Ground-truth data was established by printing 3D anatomical models of 3 patients using a rapid prototyping. CT and ultrasound data of these models were registered using fiducial markers. RESULTS: Pairwise registration of the statistical shape model and 3D ultrasound images led to a mean target registration error of 3.4 mm, while 81% of all cases yielded clinically acceptable accuracy below the 3.5 mm threshold.
MOTIVATION: Spinal needle injections are technically demanding procedures. The use of ultrasound image guidance without prior CT and MR imagery promises to improve the efficacy and safety of these procedures in an affordable manner. METHODOLOGY: We propose to create a statistical shape model of the lumbar spine and warp this atlas to patient-specific ultrasound images during the needle placement procedure. From CT image volumes of 35 patients, statistical shape model of the L3 vertebra is built, including mean shape and main modes of variation. This shape model is registered to the ultrasound data by simultaneously optimizing the parameters of the model and its relative pose. Ground-truth data was established by printing 3D anatomical models of 3 patients using a rapid prototyping. CT and ultrasound data of these models were registered using fiducial markers. RESULTS: Pairwise registration of the statistical shape model and 3D ultrasound images led to a mean target registration error of 3.4 mm, while 81% of all cases yielded clinically acceptable accuracy below the 3.5 mm threshold.
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: Emran Mohammad Abu Anas; Alexander Seitel; Abtin Rasoulian; Paul St John; David Pichora; Kathryn Darras; David Wilson; Victoria A Lessoway; Ilker Hacihaliloglu; Parvin Mousavi; Robert Rohling; Purang Abolmaesumi Journal: Int J Comput Assist Radiol Surg Date: 2015-04-07 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: Javier Esteban; Walter Simson; Sebastian Requena Witzig; Anna Rienmüller; Salvatore Virga; Benjamin Frisch; Oliver Zettinig; Drazen Sakara; Yu-Mi Ryang; Nassir Navab; Christoph Hennersperger Journal: Int J Comput Assist Radiol Surg Date: 2018-04-18 Impact factor: 2.924
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