1. Johns Hopkins Receives NIH Grant for Enabling Technology for Image-Guided Robot-Assisted Sub-Retinal Injections.

    Johns Hopkins Receives NIH Grant for Enabling Technology for Image-Guided Robot-Assisted Sub-Retinal Injections.

    Johns Hopkins Receives a 2020 NIH Grant for $504,023 for Enabling Technology for Image-Guided Robot-Assisted Sub-Retinal Injections. The principal investigator is Iulian Iordachita. Below is a summary of the proposed work.

    The goal of this proposal is to design, develop and evaluate a novel clinically compatible surgical platform for enhancing the retina surgeon's ability to provide therapy to the subretinal domain. Efficient, safe, reproducible delivery methods would enable safe and precise delivery of stem cell, nanoparticle and gene therapies for prevalent ocular diseases including but not limited to Age-related Macular Degeneration (AMD). The proposed cooperative surgical robot utilizes force-sensing instruments that are guided by 4D intraoperative Optical Coherence Tomography (4D-iOCT) imaging for intuitive surgeon-robot-patient interfaces. It is recognized that precise surgical access to the subretinal and intraretinal spaces would provide novel treatment options for a number of prevalent ocular diseases; the fact that AMD remains the leading cause of blindness in the elderly as well as its extraordinary cost of care makes it a strategic prototype condition for advances in therapy. During the last decade, stem cells and gene therapy have been extensively explored as treatments for AMD. Preliminary results indicate a promising safety profile, and suggest potential efficacy for both. However, translation of these methods into a clinical standard of care has in part, been limited by lack of a method to easily, safely, reproducibly and effectively deliver fully viable agents to the subretinal space. By advancing robotic technology, we seek to safely and reliably enhance access to the subretinal space to allow for the targeted delivery of novel therapeutic agents in the setting of prevalent retinal diseases, such as AMD. Our aims are: (1) Develop and evaluate a clinically compatible cooperative-controlled robotic assistant to enable precise tool manipulation. The enhanced functionality will allow for precise targeted delivery, proper orientation of cells and genetic cargo in the subretinal space, and enhanced survival of therapeutic biological agents; (2) Develop and integrate a novel path planning function to the workstation that will facilitate robot- assisted subretinal injections: utilizing real-time intraoperative 3D OCT images we will detect and track previously invisible subretinal microstructure, optimize approach trajectories to achieve safe, controlled and precise subretinal injections into the target space. Virtual fixtures will be incorporated into the design to avoid dangerous motions; (3) System integration and preclinical evaluation: we will develop assistive control schemes and workflow that fuse the tool-tissue interactions captured by the force-sensing instruments and the visual information provided by the OCT system. In addition, comparison of the new technology against current surgical techniques, in vivo, will be conducted to demonstrate the feasibility of our approach. This highly innovative system will enable surgeons to perform complex maneuvers in a tremor free environment with a higher level of precision than previously possible and with the ability to sense tool-to-tissue interactions that have been previously imperceptible. We envision this development as a logical next step in the integration of man, machine and computer for the performance of unprecedented microsurgical maneuvers.

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