3D intra-operative ultrasound and MR image guidance: pursuing an ultrasound-based management of brainshift to enhance neuronavigation

M Riva, C Hennersperger, F Milletari, A Katouzian, F Pessina, B Gutierrez-Becker, A Castellano, N Navab, L Bello

Research output: Contribution to journalArticle

Abstract

Background: Brainshift is still a major issue in neuronavigation. Incorporating intra-operative ultrasound (iUS) with advanced registration algorithms within the surgical workflow is regarded as a promising approach for a better understanding and management of brainshift. This work is intended to (1) provide three-dimensional (3D) ultrasound reconstructions specifically for brain imaging in order to detect brainshift observed intra-operatively, (2) evaluate a novel iterative intra-operative ultrasound-based deformation correction framework, and (3) validate the performance of the proposed image-registration-based deformation estimation in a clinical environment. Methods: Eight patients with brain tumors undergoing surgical resection are enrolled in this study. For each patient, a 3D freehand iUS system is employed in combination with an intra-operative navigation (iNav) system, and intra-operative ultrasound data are acquired at three timepoints during surgery. On this foundation, we present a novel resolution-preserving 3D ultrasound reconstruction, as well as a framework to detect brainshift through iterative registration of iUS images. To validate the system, the target registration error (TRE) is evaluated for each patient, and both rigid and elastic registration algorithms are analyzed. Results: The mean TRE based on 3D-iUS improves significantly using the proposed brainshift compensation compared to neuronavigation (iNav) before (2.7 vs. 5.9 mm; (Formula presented.)) and after dural opening (4.2 vs. 6.2 mm, (Formula presented.)), but not after resection (6.7 vs. 7.5 mm; (Formula presented.)). iUS depicts a significant ((Formula presented.)) dynamic spatial brainshift throughout the three timepoints. Accuracy of registration can be improved through rigid and elastic registrations by 29.2 and 33.3%, respectively, after dural opening, and by 5.2 and 0.4%, after resection. Conclusion: 3D-iUS systems can improve the detection of brainshift and significantly increase the accuracy of the navigation in a real scenario. 3D-iUS can thus be regarded as a robust, reliable, and feasible technology to enhance neuronavigation. © 2017 CARS
Original languageEnglish
Pages (from-to)1711-1725
Number of pages15
JournalInternational journal of computer assisted radiology and surgery
Volume12
Issue number10
DOIs
Publication statusPublished - 2017

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Neuronavigation
Ultrasonics
Workflow
Neuroimaging
Brain Neoplasms
Technology
Brain
Navigation
Image registration
Navigation systems
Surgery
Tumors

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3D intra-operative ultrasound and MR image guidance: pursuing an ultrasound-based management of brainshift to enhance neuronavigation. / Riva, M; Hennersperger, C; Milletari, F; Katouzian, A; Pessina, F; Gutierrez-Becker, B; Castellano, A; Navab, N; Bello, L.

In: International journal of computer assisted radiology and surgery, Vol. 12, No. 10, 2017, p. 1711-1725.

Research output: Contribution to journalArticle

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title = "3D intra-operative ultrasound and MR image guidance: pursuing an ultrasound-based management of brainshift to enhance neuronavigation",
abstract = "Background: Brainshift is still a major issue in neuronavigation. Incorporating intra-operative ultrasound (iUS) with advanced registration algorithms within the surgical workflow is regarded as a promising approach for a better understanding and management of brainshift. This work is intended to (1) provide three-dimensional (3D) ultrasound reconstructions specifically for brain imaging in order to detect brainshift observed intra-operatively, (2) evaluate a novel iterative intra-operative ultrasound-based deformation correction framework, and (3) validate the performance of the proposed image-registration-based deformation estimation in a clinical environment. Methods: Eight patients with brain tumors undergoing surgical resection are enrolled in this study. For each patient, a 3D freehand iUS system is employed in combination with an intra-operative navigation (iNav) system, and intra-operative ultrasound data are acquired at three timepoints during surgery. On this foundation, we present a novel resolution-preserving 3D ultrasound reconstruction, as well as a framework to detect brainshift through iterative registration of iUS images. To validate the system, the target registration error (TRE) is evaluated for each patient, and both rigid and elastic registration algorithms are analyzed. Results: The mean TRE based on 3D-iUS improves significantly using the proposed brainshift compensation compared to neuronavigation (iNav) before (2.7 vs. 5.9 mm; (Formula presented.)) and after dural opening (4.2 vs. 6.2 mm, (Formula presented.)), but not after resection (6.7 vs. 7.5 mm; (Formula presented.)). iUS depicts a significant ((Formula presented.)) dynamic spatial brainshift throughout the three timepoints. Accuracy of registration can be improved through rigid and elastic registrations by 29.2 and 33.3{\%}, respectively, after dural opening, and by 5.2 and 0.4{\%}, after resection. Conclusion: 3D-iUS systems can improve the detection of brainshift and significantly increase the accuracy of the navigation in a real scenario. 3D-iUS can thus be regarded as a robust, reliable, and feasible technology to enhance neuronavigation. {\circledC} 2017 CARS",
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AU - Riva, M

AU - Hennersperger, C

AU - Milletari, F

AU - Katouzian, A

AU - Pessina, F

AU - Gutierrez-Becker, B

AU - Castellano, A

AU - Navab, N

AU - Bello, L

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N2 - Background: Brainshift is still a major issue in neuronavigation. Incorporating intra-operative ultrasound (iUS) with advanced registration algorithms within the surgical workflow is regarded as a promising approach for a better understanding and management of brainshift. This work is intended to (1) provide three-dimensional (3D) ultrasound reconstructions specifically for brain imaging in order to detect brainshift observed intra-operatively, (2) evaluate a novel iterative intra-operative ultrasound-based deformation correction framework, and (3) validate the performance of the proposed image-registration-based deformation estimation in a clinical environment. Methods: Eight patients with brain tumors undergoing surgical resection are enrolled in this study. For each patient, a 3D freehand iUS system is employed in combination with an intra-operative navigation (iNav) system, and intra-operative ultrasound data are acquired at three timepoints during surgery. On this foundation, we present a novel resolution-preserving 3D ultrasound reconstruction, as well as a framework to detect brainshift through iterative registration of iUS images. To validate the system, the target registration error (TRE) is evaluated for each patient, and both rigid and elastic registration algorithms are analyzed. Results: The mean TRE based on 3D-iUS improves significantly using the proposed brainshift compensation compared to neuronavigation (iNav) before (2.7 vs. 5.9 mm; (Formula presented.)) and after dural opening (4.2 vs. 6.2 mm, (Formula presented.)), but not after resection (6.7 vs. 7.5 mm; (Formula presented.)). iUS depicts a significant ((Formula presented.)) dynamic spatial brainshift throughout the three timepoints. Accuracy of registration can be improved through rigid and elastic registrations by 29.2 and 33.3%, respectively, after dural opening, and by 5.2 and 0.4%, after resection. Conclusion: 3D-iUS systems can improve the detection of brainshift and significantly increase the accuracy of the navigation in a real scenario. 3D-iUS can thus be regarded as a robust, reliable, and feasible technology to enhance neuronavigation. © 2017 CARS

AB - Background: Brainshift is still a major issue in neuronavigation. Incorporating intra-operative ultrasound (iUS) with advanced registration algorithms within the surgical workflow is regarded as a promising approach for a better understanding and management of brainshift. This work is intended to (1) provide three-dimensional (3D) ultrasound reconstructions specifically for brain imaging in order to detect brainshift observed intra-operatively, (2) evaluate a novel iterative intra-operative ultrasound-based deformation correction framework, and (3) validate the performance of the proposed image-registration-based deformation estimation in a clinical environment. Methods: Eight patients with brain tumors undergoing surgical resection are enrolled in this study. For each patient, a 3D freehand iUS system is employed in combination with an intra-operative navigation (iNav) system, and intra-operative ultrasound data are acquired at three timepoints during surgery. On this foundation, we present a novel resolution-preserving 3D ultrasound reconstruction, as well as a framework to detect brainshift through iterative registration of iUS images. To validate the system, the target registration error (TRE) is evaluated for each patient, and both rigid and elastic registration algorithms are analyzed. Results: The mean TRE based on 3D-iUS improves significantly using the proposed brainshift compensation compared to neuronavigation (iNav) before (2.7 vs. 5.9 mm; (Formula presented.)) and after dural opening (4.2 vs. 6.2 mm, (Formula presented.)), but not after resection (6.7 vs. 7.5 mm; (Formula presented.)). iUS depicts a significant ((Formula presented.)) dynamic spatial brainshift throughout the three timepoints. Accuracy of registration can be improved through rigid and elastic registrations by 29.2 and 33.3%, respectively, after dural opening, and by 5.2 and 0.4%, after resection. Conclusion: 3D-iUS systems can improve the detection of brainshift and significantly increase the accuracy of the navigation in a real scenario. 3D-iUS can thus be regarded as a robust, reliable, and feasible technology to enhance neuronavigation. © 2017 CARS

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