NeuroOCT

Robotic Needle Positioning with realtime OCT imaging

Patient-Mounted Neuro Optical Coherence Tomography for Targeted Minimally Invasive Micro-Resolution Volumetric Imaging in Brain In Vivo.

Advanced Intelligent System, IROS 2024, SPIE 2024

Abstract

Targeted neuroimaging plays a vital role in evaluating pathologies and guiding interventions in deep brain regions, such as biopsy, laser ablation, and deep brain stimulation. However, current neuroimaging techniques face several challenges when it comes to imaging the deep brain. These challenges include limited imaging depth, a narrow field of view, low resolution, and a lack of real-time imaging and stereotactic deployment capabilities.
To address these challenges, a patient-mounted neuro optical coherence tomography (neuroOCT) system that combines a lightweight 5 degrees-of-freedom skull-mounted robot (Skullbot) with a neuroendoscope measuring ≈0.6 mm in diameter is introduced. This innovative system enables targeted and minimally invasive neuroimaging with an axial resolution of ≈2.4 μm and a transverse resolution of around 4.5 μm. The Skullbot can be securely attached to the head and precisely deploys the neuroendoscope with an accuracy of ±1.5 mm in the transverse direction and ±0.25 mm in the longitudinal direction. This allows for motion-insensitive stereotactic imaging within the brain. By utilizing the neuroOCT system, targeted imaging of a tumor in a brain phantom is successfully demonstrated. Furthermore, the system's capability for in vivo micro-resolution volumetric neuroimaging of fine structures within a mouse brain is validated.

Results on Phantom Targeting

Citation

@article{xuPatientMountedNeuroOptical,
              title = {Patient-Mounted Neuro Optical Coherence Tomography for Targeted Minimally Invasive Micro-Resolution Volumetric Imaging in Brain In Vivo},
              author = {Xu, Chao and Fang, Zhiwei and Gao, Huxin and Zhang, Tinghua and Zhang, Tao and Liu, Peng and Ren, Hongliang and Yuan, Wu},
              journal = {Advanced Intelligent Systems},
              volume = {n/a},
              number = {n/a},
              issn = {2640-4567},
              doi = {10.1002/aisy.202400488},
              copyright = {{\copyright} 2024 The Author(s). Advanced Intelligent Systems published by Wiley-VCH GmbH},
              langid = {english}
            }