Abstract:PurposeTest the feasibility of the novel Single Landmark image-to-patient registration method for use in the operating room for future clinical trials. The algorithm is implemented in the open-source platform CustusX, a computer-aided intervention research platform dedicated to intraoperative navigation and ultrasound, with an interface for laparoscopic ultrasound probes.
MethodsThe Single Landmark method is compared to fiducial landmark on an IOUSFAN (Kyoto Kagaku Co., Ltd., Japan) soft tissue abdominal phant… Show more
“…In this study, the image space is represented by a on rails Siemens SOMATOM CT scanner and the position of the patient is on the operation table prepared for surgery or in the biomechanical diagnostics laboratory. The most common approaches in the literature for image-to-patient registration is rigid transformations based on landmarks [ 3 , 8 , 9 ].…”
Purpose
This study presents a novel surgical navigation tool developed in mixed reality environment for orthopaedic surgery. Joint and skeletal deformities affect all age groups and greatly reduce the range of motion of the joints. These deformities are notoriously difficult to diagnose and to correct through surgery.
Method
We have developed a surgical tool which integrates surgical instrument tracking and augmented reality through a head mounted display. This allows the surgeon to visualise bones with the illusion of possessing “X-ray” vision. The studies presented below aim to assess the accuracy of the surgical navigation tool in tracking a location at the tip of the surgical instrument in holographic space.
Results
Results show that the average accuracy provided by the navigation tool is around 8 mm, and qualitative assessment by the orthopaedic surgeons provided positive feedback in terms of the capabilities for diagnostic use.
Conclusions
More improvements are necessary for the navigation tool to be accurate enough for surgical applications, however, this new tool has the potential to improve diagnostic accuracy and allow for safer and more precise surgeries, as well as provide for better learning conditions for orthopaedic surgeons in training.
“…In this study, the image space is represented by a on rails Siemens SOMATOM CT scanner and the position of the patient is on the operation table prepared for surgery or in the biomechanical diagnostics laboratory. The most common approaches in the literature for image-to-patient registration is rigid transformations based on landmarks [ 3 , 8 , 9 ].…”
Purpose
This study presents a novel surgical navigation tool developed in mixed reality environment for orthopaedic surgery. Joint and skeletal deformities affect all age groups and greatly reduce the range of motion of the joints. These deformities are notoriously difficult to diagnose and to correct through surgery.
Method
We have developed a surgical tool which integrates surgical instrument tracking and augmented reality through a head mounted display. This allows the surgeon to visualise bones with the illusion of possessing “X-ray” vision. The studies presented below aim to assess the accuracy of the surgical navigation tool in tracking a location at the tip of the surgical instrument in holographic space.
Results
Results show that the average accuracy provided by the navigation tool is around 8 mm, and qualitative assessment by the orthopaedic surgeons provided positive feedback in terms of the capabilities for diagnostic use.
Conclusions
More improvements are necessary for the navigation tool to be accurate enough for surgical applications, however, this new tool has the potential to improve diagnostic accuracy and allow for safer and more precise surgeries, as well as provide for better learning conditions for orthopaedic surgeons in training.
“…8 is represented by transformation matrix . Most approaches in the literature 13,25 compute rigid transformations. The same was performed throughout this study.…”
Section: Methodsmentioning
confidence: 99%
“…Through in vivo assessment of AR accuracy attained with state-of-the art algorithms for IGS, this study aims to test if intraoperative imaging is necessary for accurate surgical navigation for LLR. Moreover, since liver navigation systems make use of input from clinicians 12,13 , this study assesses how user annotations effect accuracy of IGS navigation. This study analyses the following hypotheses:Intraoperative imaging allows AR surgical navigation to be more accurate compared to preoperative imaging.Annotations performed by medical doctors can cause statistically significant differences in terms of accuracy in the surgical navigation.Fiducials remove user-induced error and significantly increase the accuracy of surgical navigation.A higher number of fiducials can increase the accuracy of surgical navigation, up to a certain point.Figure 1Laparoscopic liver frames from in-vivo study.…”
Conventional surgical navigation systems rely on preoperative imaging to provide guidance. In laparoscopic liver surgery, insufflation of the abdomen (pneumoperitoneum) can cause deformations on the liver, introducing inaccuracies in the correspondence between the preoperative images and the intraoperative reality. This study evaluates the improvements provided by intraoperative imaging for laparoscopic liver surgical navigation, when displayed as augmented reality (AR). Significant differences were found in terms of accuracy of the AR, in favor of intraoperative imaging. In addition, results showed an effect of user-induced error: image-to-patient registration based on annotations performed by clinicians caused 33% more inaccuracy as compared to image-to-patient registration algorithms that do not depend on user annotations. Hence, to achieve accurate surgical navigation for laparoscopic liver surgery, intraoperative imaging is recommendable to compensate for deformation. Moreover, user annotation errors may lead to inaccuracies in registration processes.
“…The alignment between volumetric CT/MRI images (and segmented models) to the liver configuration when the patient is on the operating table is a field of image registration known as image-to-patient or image-to-physical registration. Two solutions are most commonly in use in the literature to perform image-to-patient registration: PBR [16] and the single landmark registration method [17]. Both algorithms work by sampling and matching a set of correspondent positions between coordinate systems.…”
Purpose: This study aims to evaluate the accuracy of point-based registration (PBR) when used for augmented reality (AR) in laparoscopic liver resection surgery. Material and methods: The study was conducted in three different scenarios in which the accuracy of sampling targets for PBR decreases: using an assessment phantom with machined divot holes, a patient-specific liver phantom with markers visible in computed tomography (CT) scans and in vivo, relying on the surgeon's anatomical understanding to perform annotations. Target registration error (TRE) and fiducial registration error (FRE) were computed using five randomly selected positions for image-to-patient registration. Results: AR with intra-operative CT scanning showed a mean TRE of 6.9 mm for the machined phantom, 7.9 mm for the patient-specific phantom and 13.4 mm in the in vivo study. Conclusions: AR showed an increase in both TRE and FRE throughout the experimental studies, proving that AR is not robust to the sampling accuracy of the targets used to compute imageto-patient registration. Moreover, an influence of the size of the volume to be register was observed. Hence, it is advisable to reduce both errors due to annotations and the size of registration volumes, which can cause large errors in AR systems.
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