Mixed-Reality-Assisted Puncture of the Common Femoral Artery in a Phantom Model

Abstract

Percutaneous femoral arterial access is daily practice in a variety of medical specialties and enables physicians worldwide to perform endovascular interventions. The reported incidence of percutaneous femoral arterial access complications is 3–18% and often results from suboptimal puncture location due to insufficient visualization of the target vessel. The purpose of this proof-of-concept study was to evaluate the feasibility and the positional error of a mixed-reality (MR)-assisted puncture of the common femoral artery in a phantom model using a commercially available navigation system. In total, 15 MR-assisted punctures were performed. Cone-beam computed tomography angiography (CTA) was used following each puncture to allow quantification of positional error of needle placements in the axial and sagittal planes. Technical success was achieved in 14/15 cases (93.3%) with a median axial positional error of 1.0 mm (IQR 1.3) and a median sagittal positional error of 1.1 mm (IQR 1.6). The median duration of the registration process and needle insertion was 2 min (IQR 1.0). MR-assisted puncture of the common femoral artery is feasible with acceptable positional errors in a phantom model. Future studies should aim to measure and reduce the positional error resulting from MR registration.

Augmenting Performance: A Systematic Review of Optical See-Through Head-Mounted Displays in Surgery

“…Neurosurgery-related applications included incision planning [ 62 , 63 ], navigation [ 64 , 65 ], and complex craniotomies [ 66 ]. Vascular surgery related papers focused on use for percutaneous femoral artery access [ 67 ] and tumor puncture [ 68 ].…”

“…After preoperative imaging, Digital Imaging and Communications in Medicine (DICOM) formatted data are typically provided which can be read in an open source library, such as 3D Slicer ( , accessed on 23 March 2022) [ 46 , 65 , 74 , 87 ], or proprietary software, such as Mimics ( , accessed on 23 March 2022) [ 47 , 61 , 88 ] or Brainlab ( , accessed on 23 March 2022) [ 67 , 84 ]. Surface rendered models provide enormous utility due to their ease of creation, lightweight model representation, and additional modifiable visualization properties, such as color, transparency, wireframe representations, and heatmaps [ 89 ].…”

“…We have also indicated the measured accuracy of the surveyed papers in Table 6 . Overall, the accuracy provided by an OST-HMD guidance system which is integrated with an existing surgical navigation suite has been demonstrated to be on the order of 2–5 mm [ 67 , 68 , 82 , 93 , 98 , 102 ], which is sufficient for certain surgical interventions, such as neurosurgical burr hole placement (<10 mm) [ 104 ] or complex pelvic osteotomies (<10 mm) [ 45 ]. As previously mentioned, the most popular tracking strategy for OST-HMD-camera-led surgical navigation relied on square-marker fiducials, such as ArUco [ 31 ] or Vuforia and monocular RGB video.…”

“…The most frequent type of preprocessing of preoperative data was the creation of surface rendered models (shells). [47,61,88] or Brainlab (https://www.brainlab.com/digital-o-r/surgical-planning/, accessed on 23 March 2022) [67,84]. Surface rendered models provide enormous utility due to their ease of creation, lightweight model representation, and additional modifiable visualization properties, such as color, transparency, wireframe representations, and heatmaps [89].…”

Mixed Reality in der Gefäßchirurgie – ein Scoping Review

“…Aus den Volltexten wurde das Ziel der MR-Anwendung, eine möglichst detaillierte Beschreibung der Methodik, die Anzahl der Beobachter und Wiederholungen der durchgeführten Prozeduren, das angewandte HMD, ggf. Im Versuch von Uhl et al [25] erfolgte ebenfalls die Registrierung eines Phantommodells mit der entsprechenden CT-Angiografie und die folgende Darstellung in einer MR-Umgebung. Die Registrierung der CT-Angiografie mit dem Phantommodell erfolgte dabei mittels eines kommerziell erhältlichen Navigationssystems (Curve Navigation Platform, Brainlab AG, München, Deutschland) mit nachgewiesener Genauigkeit und einem Positionierungsfehler ≤ 2 mm in Verbindung mit einem Prototyp zur Darstellung der Navigation in einer MR-Umgebung (Brainlab AG, München, Deutschland) [29].…”