Soft Magnetically Steerable Suction Device for Endoscopic Endonasal Brain Tumor Extraction

This paper introduces a soft, magnetically steerable suction (MSS) device for brain tumor extraction via the endoscopic endonasal approach. The device integrates a soft end-effector into a rigid, straight suction device, enhancing maneuverability and safety during minimally invasive neurosurgery. The soft tip’s design, made from Ecoflex 00-50 silicone with an embedded permanent magnet for magnetic actuation, was optimized through experimental testing of various geometries and materials and then fabricated using a four-part mold. Magnetic steering capabilities were tested using an electromagnet coil system with uniform magnetic fields ranging from -25 mT to 25 mT. A mechanical model was also developed based on constant curvature kinematics, which predicts the bending angle. The model’s accuracy was validated using image segmentation of the soft tip’s centerline against the experimental setup. Tensile tests were performed according to ISO-37 standards to determine the mechanical properties of Ecoflex 00-50, which were then used in non-linear FEA simulations. The FEA results are closely aligned with experimental data, validating the equivalent mechanical properties of the entire suction device and enabling future simulations of various loading conditions. The MSS device achieved over 90° of bending under applied magnetic fields of 25 mT, with an equivalent Young’s modulus of 0.273 MPa enabling controlled deformation. The device demonstrated suction capabilities of 80-90 kPa through its 1.8 mm diameter channel, providing approximately 0.23 N of suction force at the tip. The mechanical model predicted the bending behavior with a mean fit error of less than 1% (0.76 mm), validating its accuracy for surgical planning.

Authors

Institutions

Publication Details

Published
2025-04-22
DOI
https://doi.org/10.1109/robosoft63089.2025.11020933
Citations
1
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
0.67
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Soft Magnetically Steerable Suction Device for Endoscopic Endonasal Brain Tumor Extraction

James M. Drake, Changyan He, Eric Diller, Alex Zhang et al.
1 citations
Soft Robotics and Applications
0.67
article

Soft Magnetically Steerable Suction Device for Endoscopic Endonasal Brain Tumor Extraction

James M. Drake, Changyan He, Eric Diller, Alex Zhang, Majid Roshanfar, Thomas Looi, Amir Hooshiar
article en
1 citations

Abstract

This paper introduces a soft, magnetically steerable suction (MSS) device for brain tumor extraction via the endoscopic endonasal approach. The device integrates a soft end-effector into a rigid, straight suction device, enhancing maneuverability and safety during minimally invasive neurosurgery. The soft tip’s design, made from Ecoflex 00-50 silicone with an embedded permanent magnet for magnetic actuation, was optimized through experimental testing of various geometries and materials and then fabricated using a four-part mold. Magnetic steering capabilities were tested using an electromagnet coil system with uniform magnetic fields ranging from -25 mT to 25 mT. A mechanical model was also developed based on constant curvature kinematics, which predicts the bending angle. The model’s accuracy was validated using image segmentation of the soft tip’s centerline against the experimental setup. Tensile tests were performed according to ISO-37 standards to determine the mechanical properties of Ecoflex 00-50, which were then used in non-linear FEA simulations. The FEA results are closely aligned with experimental data, validating the equivalent mechanical properties of the entire suction device and enabling future simulations of various loading conditions. The MSS device achieved over 90° of bending under applied magnetic fields of 25 mT, with an equivalent Young’s modulus of 0.273 MPa enabling controlled deformation. The device demonstrated suction capabilities of 80-90 kPa through its 1.8 mm diameter channel, providing approximately 0.23 N of suction force at the tip. The mechanical model predicted the bending behavior with a mean fit error of less than 1% (0.76 mm), validating its accuracy for surgical planning.

University of Toronto (CA), Hospital for Sick Children (CA), SickKids Foundation (CA), McGill University (CA), University of Newcastle Australia (AU)
Openalex Percentile: Top 31%
Soft Robotics and Applications
0.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.