Imperial College London

DrStefanoGalvan

Faculty of EngineeringDepartment of Mechanical Engineering

Advanced Research Fellow
 
 
 
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Contact

 

s.galvan

 
 
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Location

 

564City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

9 results found

Jamal A, Yuan T, Galvan S, Castellano A, Riva M, Secoli R, Falini A, Bello L, Rodriguez y Baena F, Dini Det al., 2022, Insights into infusion-based targeted drug delivery in brain: perspectives, challenges and opportunities, International Journal of Molecular Sciences, Vol: 23, Pages: 3139-3139, ISSN: 1422-0067

Targeted drug delivery in the brain is instrumental in the treatment of lethal brain diseases, such as glioblastoma multiforme, the most aggressive primary central nervous system tumour in adults. Infusion-based drug delivery techniques, which directly administer to the tissue for local treatment, as in convection-enhanced delivery (CED), provide an important opportunity; however, poor understanding of the pressure-driven drug transport mechanisms in the brain has hindered its ultimate success in clinical applications. In this review, we focus on the biomechanical and biochemical aspects of infusion-based targeted drug delivery in the brain and look into the underlying molecular level mechanisms. We discuss recent advances and challenges in the complementary field of medical robotics and its use in targeted drug delivery in the brain. A critical overview of current research in these areas and their clinical implications is provided. This review delivers new ideas and perspectives for further studies of targeted drug delivery in the brain.

Journal article

Segato A, Vece CD, Zucchelli S, Di Marzo M, Wendler T, Azampour MF, Galvan S, Secoli R, De Momi Eet al., 2021, Position-Based Dynamics Simulator of Brain Deformations for Path Planning and Intra-Operative Control in Keyhole Neurosurgery, IEEE ROBOTICS AND AUTOMATION LETTERS, Vol: 6, Pages: 6061-6067, ISSN: 2377-3766

Journal article

Pinzi M, Watts T, Secoli R, Galvan S, Baena FRYet al., 2021, Path replanning for orientation-constrained needle steering, IEEE Transactions on Biomedical Engineering, Vol: 68, Pages: 1459-1466, ISSN: 0018-9294

Introduction: Needle-based neurosurgical procedures require high accuracy in catheter positioning to achieve high clinical efficacy. Significant challenges for achieving accurate targeting are (i) tissue deformation (ii) clinical obstacles along the insertion path (iii) catheter control. Objective: We propose a novel path-replanner able to generate an obstacle-free and curvature bounded three-dimensional (3D) path at each time step during insertion, accounting for a constrained target pose and intraoperative anatomical deformation. Additionally, our solution is sufficiently fast to be used in a closed-loop system: needle tip tracking via electromagnetic sensors is used by the path-replanner to automatically guide the programmable bevel-tip needle (PBN) while surgical constraints on sensitive structures avoidance are met. Methods: The generated path is achieved by combining the ”Bubble Bending” method for online path deformation and a 3D extension of a convex optimisation method for path smoothing. Results: Simulation results performed on a realistic dataset show that our replanning method can guide a PBN with bounded curvature to a predefined target pose with an average targeting error of 0.65 ± 0.46 mm in position and 3.25 ± 5.23 degrees in orientation under a deformable simulated environment. The proposed algorithm was also assessed in-vitro on a brain-like gelatin phantom, achieving a target error of 1.81 ± 0.51 mm in position and 5.9 ± 1.42 degrees in orientation. Conclusion: The presented work assessed the performance of a new online steerable needle path-planner able to avoid anatomical obstacles while optimizing surgical criteria. Significance: This method is particularly suited for surgical procedures demanding high accuracy on the desired goal pose under tissue deformations and real-world inaccuracies.

Journal article

Tan Z, Bernardini A, Konstantinou I, Forte AE, Galvan S, Van Wachem B, Dini D, Rodriguez Y Baena Fet al., 2017, Diffusion Measurement and Modelling, European Robotics Forum 2017

Conference paper

Tan Z, Forte AE, Galvan S, Dini D, Rodriguez Y Baena Fet al., 2016, Composite Hydrogel: a New Tool for Reproducing the Mechanical Behaviour of Soft Human Tissues, Biotribology 2016

Conference paper

Forte AE, galvan S, manieri F, Dini Det al., 2014, A Novel Composite Phantom for Brain Tissue, EMBC 2014

Conference paper

Cattilino M, Secoli R, Galvan S, Forte AE, Dini D, rodriguez y Baena Fet al., 2014, Development of a Dynamic Soft Tissue Phantom for Cooperative Control Testing in Robotic Surgery, Hamlyn Symposium

Conference paper

Rasin I, Pekar Z, Sadowsky O, Forte AE, Galvan S, Dini D, Shoham M, Joskowicz Let al., 2014, Real-Time Modelling of Intra-operative Brain Shift Based on Video Tracking, The Hamlyn Symposium on Medical Robotics 2014

Conference paper

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