Accuracy analysis of line-based registration for image guided neurosurgery at different operating areas – a phantom study

Abstract

Space registration is the primary function of neuronavigation systems. According to the stage of the operation, the registration could be classified as rigid and non-rigid methods. Scientists have proposed three types of rigid registration methods: point-based registration (PBR), line-based registration (LBR), and surface-based registration (SBR). PBR has been widely used in clinical applications. Recently, LBR was proposed as a new spacing registration method. However, the range and accuracy of LBR are still not defined for clinical applications. In this paper, LBR has been evaluated directly with target registration error (TRE) in different operating areas: sphenoid-frontal, parietal-temporal, and occipital areas. We used two head phantoms: elastic and rigid phantoms. After scanning with computerized tomography (CT), the difference between the TRE of the elastic and rigid phantom had been evaluated based on LBR method. Then, LBR had been employed at the rigid phantom using different line patterns: single (100 points), double (200 points), triple (300 points), and quartic lines (400 points). TRE were directly measured on the phantom. Then, t-tests were applied to evaluate the difference between the TRE of LBR of both the phantoms and line patterns. Results indicate that there is no statistical difference in TRE between the phantoms. TRE were reduced to less than 3 mm after the use of double lines which was significantly less than those after the use of single lines. Except for sphenoid tumor, the other operating areas showed statistical differences in TRE between double and triple lines. Except for temporal tumor, the differences between the TRE of triple and quartic lines are not significant.

Automated machine learning (AutoML)‐based surface registration methodology for image‐guided surgical navigation system

“…To consider the locations of various lesions located in the sinus space and nasal cavity, we placed the target points densely, as shown in Figure 4a (a total of 90 targets in a 10 × 3 × 3 format). However, this number of targets was too dense compared to the numbers of targets (5, 42 11, 43 and 72% below 10 targets 44 ) of previous studies considered to verify the registration accuracy. Therefore, among these 90 targets, 10 targets were randomly selected and grouped, which can be expected to achieve a similar effect as considering nine lesions in the corresponding area.…”

How precise are oral splints for frameless stereotaxy in guided ear, nose, throat, and maxillofacial surgery: a cadaver study

“…, periorbital or temporal regions), additional techniques such as surface matching or fiducial markers with a maximum of 4 or 5 markers are also recommended [ 30 ]. Some authors advocate extensions to oral splint to minimise errors [ 13 ]. The use of dental splints or the combination of oral splints with other navigational methods could improve the accuracy and the validation of surgical interventions and would be even a simple instrument for quality management after radiotherapy or surgery.…”

“…Scanning 15 to 40 defined or coincidental surface points is necessary. The overlay of the current video and the patient data three-dimensional reconstruction to pursue the patient's head's exact position was described by Ji et al [ 13 ]. Inaccuracies occur when soft tissue is oedematous or traumatised, and operational intervention is delayed [ 14 ].…”

Fusion of multimodality image and point cloud for spatial surface registration for knee arthroplasty

“…Generally, the preoperative image is defined as the image space, and the intraoperative patient is defined as the patient space 10 . Mapping the patient space to the image space is called as spatial registration, which is the essence of surgical navigation 11–13 . Its precision is directly related to the accuracy of intraoperative osteotomy, the alignment of biological axis and the reconstruction of anterior cruciate ligament.…”

“…10 Mapping the patient space to the image space is called as spatial registration, which is the essence of surgical navigation. [11][12][13] Its precision is directly related to the accuracy of intraoperative osteotomy, the alignment of biological axis and the reconstruction of anterior cruciate ligament. This is also the main factor restricting the effectiveness of clinical treatment.…”