Intraoperative Brain Shift Compensation Using a Hybrid Mixture Model

Bayer, Siming; Ravikumar, Nishant; Strumia, Maddalena; Tong, Xiaoguang; Gao, Ying; Ostermeier, Martin; Fahrig, Rebecca; Maier, Andreas

doi:10.1007/978-3-030-00937-3_14

Cited by 14 publications

(10 citation statements)

References 8 publications

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“…Although WM changes in the brain were considered in this study, the generic nature of the proposed framework permits its application to other organs exhibiting tissue anisotropy, such as cardiac diffusion data, and modelling bone micro-architecture. Additionally, it can be employed for a variety of other applications, such as vessel centerlines-based image registration, as demonstrated by our recent study (Bayer et al, 2018).…”

Section: Group Comparisonsmentioning

confidence: 96%

Generalised coherent point drift for group-wise multi-dimensional analysis of diffusion brain MRI data

Ravikumar

Gooya

Beltrachini

et al. 2019

Medical Image Analysis

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Section: Group Comparisonsmentioning

confidence: 96%

Generalised coherent point drift for group-wise multi-dimensional analysis of diffusion brain MRI data

Ravikumar

Gooya

Beltrachini

et al. 2019

Medical Image Analysis

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“…Moreover, the use of intraoperative CBCT has the potential to compensate for brain shift, addressing one of the major limitations of current navigation systems. 44,45…”

Section: Advantages Of the Arsn Setupmentioning

confidence: 99%

Augmented reality navigation for cranial biopsy and external ventricular drain insertion

Skyrman

Lai

Edström

et al. 2021

Neurosurgical Focus

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OBJECTIVE The aim of this study was to evaluate the accuracy (deviation from the target or intended path) and efficacy (insertion time) of an augmented reality surgical navigation (ARSN) system for insertion of biopsy needles and external ventricular drains (EVDs), two common neurosurgical procedures that require high precision. METHODS The hybrid operating room–based ARSN system, comprising a robotic C-arm with intraoperative cone-beam CT (CBCT) and integrated video tracking of the patient and instruments using nonobtrusive adhesive optical markers, was used. A 3D-printed skull phantom with a realistic gelatinous brain model containing air-filled ventricles and 2-mm spherical biopsy targets was obtained. After initial CBCT acquisition for target registration and planning, ARSN was used for 30 cranial biopsies and 10 EVD insertions. Needle positions were verified by CBCT. RESULTS The mean accuracy of the biopsy needle insertions (n = 30) was 0.8 mm ± 0.43 mm. The median path length was 39 mm (range 16–104 mm) and did not correlate to accuracy (p = 0.15). The median device insertion time was 149 seconds (range 87–233 seconds). The mean accuracy for the EVD insertions (n = 10) was 2.9 mm ± 0.8 mm at the tip with a 0.7° ± 0.5° angular deviation compared with the planned path, and the median insertion time was 188 seconds (range 135–400 seconds). CONCLUSIONS This study demonstrated that ARSN can be used for navigation of percutaneous cranial biopsies and EVDs with high accuracy and efficacy.

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“…Siming Bayer 1, * • Zhiwei Zhai 2 • Maddalena Strumia 3 • Xiaoguang Tong 4 • Ying Gao 5 • Marius Staring 2 • Berend Stoel 2 • Rebecca Fahrig 3 • Arya Nabavi 6 • Andreas Maier 1 • Nishant Ravikumar 1 Received: date / Accepted: date Abstract Purpose: Morphological changes to anatomy resulting from invasive surgical procedures or pathology, typically alter the surrounding vasculature. This makes it useful as a descriptor for feature-driven image registration in various clinical applications.…”

Section: Registration Of Vascular Structures Using a Hybrid Mixture Mmentioning

confidence: 99%

“…Consequently, in this study, we propose a novel and generalized framework for registering vessel centerlines. We improve on the HdMM-based vessel registration framework proposed in our recent study [2], through suitable algorithmic modifications, and provide a detailed description of the same. Furthermore, we evaluate the proposed approach comprehensively and compare it with the state-of-the-art, using vascular data from two different clinical applications, namely, intraoperative brain shift compensation, and quantification of pulmonary vascular changes caused by lung disease.…”

Section: Introductionmentioning

confidence: 99%