Initial Experience with Using a Structured Light 3D Scanner and Image Registration to Plan Bedside Subdural Evacuating Port System Placement.
3D printing
3D scanning
Chronic subdural hematoma
Image registration
SEPS
Journal
World neurosurgery
ISSN: 1878-8769
Titre abrégé: World Neurosurg
Pays: United States
ID NLM: 101528275
Informations de publication
Date de publication:
05 2020
05 2020
Historique:
received:
01
11
2019
revised:
26
01
2020
accepted:
27
01
2020
pubmed:
8
2
2020
medline:
29
7
2020
entrez:
8
2
2020
Statut:
ppublish
Résumé
Chronic subdural hematoma evacuation can be achieved in select patients through bedside placement of the Subdural Evacuation Port System (SEPS; Medtronic, Inc., Dublin, Ireland). This procedure involves drilling a burr hole at the thickest part of the hematoma. Identifying this location is often difficult, given the variable tilt of available imaging and distant anatomic landmarks. This paper evaluates the feasibility and accuracy of a bedside navigation system that relies on visible light-based 3-dimensional (3D) scanning and image registration to a pre-procedure computed tomography scan. The information provided by this system may increase accuracy of the burr hole location. In Part 1, the accuracy of this system was evaluated using a rigid 3D printed phantom head with implanted fiducials. In Part 2, the navigation system was tested on 3 patients who underwent SEPS placement. The error in registration of this system was less than 2.5 mm when tested on a rigid 3D printed phantom head. Fiducials located in the posterior aspect of the head were difficult to reliably capture. For the 3 patients who underwent 5 SEPS placements, the distance between anticipated SEPS burr hole location based on registration and actual burr hole location was less than 1cm. A bedside cranial navigation system based on 3D scanning and image registration has been introduced. Such a system may increase the success rate of bedside procedures, such as SEPS placement. However, technical challenges such as the ability to scan hair and practical challenges such as minimization of patient movement during scans must be overcome.
Sections du résumé
BACKGROUND
Chronic subdural hematoma evacuation can be achieved in select patients through bedside placement of the Subdural Evacuation Port System (SEPS; Medtronic, Inc., Dublin, Ireland). This procedure involves drilling a burr hole at the thickest part of the hematoma. Identifying this location is often difficult, given the variable tilt of available imaging and distant anatomic landmarks. This paper evaluates the feasibility and accuracy of a bedside navigation system that relies on visible light-based 3-dimensional (3D) scanning and image registration to a pre-procedure computed tomography scan. The information provided by this system may increase accuracy of the burr hole location.
METHODS
In Part 1, the accuracy of this system was evaluated using a rigid 3D printed phantom head with implanted fiducials. In Part 2, the navigation system was tested on 3 patients who underwent SEPS placement.
RESULTS
The error in registration of this system was less than 2.5 mm when tested on a rigid 3D printed phantom head. Fiducials located in the posterior aspect of the head were difficult to reliably capture. For the 3 patients who underwent 5 SEPS placements, the distance between anticipated SEPS burr hole location based on registration and actual burr hole location was less than 1cm.
CONCLUSIONS
A bedside cranial navigation system based on 3D scanning and image registration has been introduced. Such a system may increase the success rate of bedside procedures, such as SEPS placement. However, technical challenges such as the ability to scan hair and practical challenges such as minimization of patient movement during scans must be overcome.
Identifiants
pubmed: 32032785
pii: S1878-8750(20)30221-7
doi: 10.1016/j.wneu.2020.01.203
pmc: PMC7354700
mid: NIHMS1576020
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
350-356Subventions
Organisme : NINDS NIH HHS
ID : R01 NS049251
Pays : United States
Informations de copyright
Copyright © 2020 Elsevier Inc. All rights reserved.
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