Challenges and Opportunities of Intraoperative 3D Ultrasound With Neuronavigation in Relation to Intraoperative MRI.

3D iMRI = intraoperative MRI neurosurgery tumor ultrasound

Journal

Frontiers in oncology
ISSN: 2234-943X
Titre abrégé: Front Oncol
Pays: Switzerland
ID NLM: 101568867

Informations de publication

Date de publication:
2021
Historique:
received: 20 01 2021
accepted: 09 04 2021
entrez: 24 5 2021
pubmed: 25 5 2021
medline: 25 5 2021
Statut: epublish

Résumé

Neuronavigation greatly improves the surgeons ability to approach, assess and operate on brain tumors, but tends to lose its accuracy as the surgery progresses and substantial brain shift and deformation occurs. Intraoperative MRI (iMRI) can partially address this problem but is resource intensive and workflow disruptive. Intraoperative ultrasound (iUS) provides real-time information that can be used to update neuronavigation and provide real-time information regarding the resection progress. We describe the intraoperative use of 3D iUS in relation to iMRI, and discuss the challenges and opportunities in its use in neurosurgical practice. We performed a retrospective evaluation of patients who underwent image-guided brain tumor resection in which both 3D iUS and iMRI were used. The study was conducted between June 2020 and December 2020 when an extension of a commercially available navigation software was introduced in our practice enabling 3D iUS volumes to be reconstructed from tracked 2D iUS images. For each patient, three or more 3D iUS images were acquired during the procedure, and one iMRI was acquired towards the end. The iUS images included an extradural ultrasound sweep acquired before dural incision (iUS-1), a post-dural opening iUS (iUS-2), and a third iUS acquired immediately before the iMRI acquisition (iUS-3). iUS-1 and preoperative MRI were compared to evaluate the ability of iUS to visualize tumor boundaries and critical anatomic landmarks; iUS-3 and iMRI were compared to evaluate the ability of iUS for predicting residual tumor. Twenty-three patients were included in this study. Fifteen patients had tumors located in eloquent or near eloquent brain regions, the majority of patients had low grade gliomas (11), gross total resection was achieved in 12 patients, postoperative temporary deficits were observed in five patients. In twenty-two iUS was able to define tumor location, tumor margins, and was able to indicate relevant landmarks for orientation and guidance. In sixteen cases, white matter fiber tracts computed from preoperative dMRI were overlaid on the iUS images. In nineteen patients, the EOR (GTR or STR) was predicted by iUS and confirmed by iMRI. The remaining four patients where iUS was not able to evaluate the presence or absence of residual tumor were recurrent cases with a previous surgical cavity that hindered good contact between the US probe and the brainsurface. This recent experience at our institution illustrates the practical benefits, challenges, and opportunities of 3D iUS in relation to iMRI.

Identifiants

pubmed: 34026631
doi: 10.3389/fonc.2021.656519
pmc: PMC8139191
doi:

Types de publication

Journal Article

Langues

eng

Pagination

656519

Subventions

Organisme : NIBIB NIH HHS
ID : P41 EB028741
Pays : United States
Organisme : NIBIB NIH HHS
ID : P41 EB015902
Pays : United States
Organisme : NCI NIH HHS
ID : R21 CA198740
Pays : United States
Organisme : NIBIB NIH HHS
ID : P41 EB015898
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB027134
Pays : United States

Informations de copyright

Copyright 2021 Bastos, Juvekar, Tie, Jowkar, Pieper, Wells, Bi, Golby, Frisken and Kapur.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Dhiego Chaves De Almeida Bastos (DCA)

Department of Neurosurgery, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, United States.

Parikshit Juvekar (P)

Department of Neurosurgery, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, United States.

Yanmei Tie (Y)

Department of Neurosurgery, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, United States.

Nick Jowkar (N)

Department of Neurosurgery, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, United States.

Steve Pieper (S)

Department of Neurosurgery, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, United States.

Willam M Wells (WM)

Department of Neurosurgery, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, United States.

Wenya Linda Bi (WL)

Department of Neurosurgery, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, United States.

Alexandra Golby (A)

Department of Neurosurgery, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, United States.

Sarah Frisken (S)

Department of Neurosurgery, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, United States.

Tina Kapur (T)

Department of Neurosurgery, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, United States.

Classifications MeSH