Quantifying workspace and forces of surgical dissection during robot‐assisted neurosurgery

Maddahi, Yaser; Gan, Liu Shi; Zareinia, Kourosh; Lama, Sanju; Sepehri, Nariman; Sutherland, Garnette R.

doi:10.1002/rcs.1679

Cited by 35 publications

(44 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The resulting force ranges were from 0.32 to 1.61 N and 0.51 to 2.48 N, for olfactory bulb and cortex insertion, respectively (fourth row of Table 1b). All four works [29,30,31,32] presented procedures similar to our. Nevertheless, they did not consider the haptic perception at the surgeon's fingertip, focusing only on forces applied to cadaver [29], mouse brain [31], and in vivo tissue [30,32].…”

Section: Discussionmentioning

confidence: 99%

“…All four works [29,30,31,32] presented procedures similar to our. Nevertheless, they did not consider the haptic perception at the surgeon's fingertip, focusing only on forces applied to cadaver [29], mouse brain [31], and in vivo tissue [30,32]. Eventually, the interaction force values presented by these works are in-line with our acquisition, especially when considering median values (see red dashes in Figure 5(b)).…”

Section: Discussionmentioning

confidence: 99%

“…The authors used a six DoFs force/torque sensor, but we assume that the reported force values are computed as the Euclidean norm of the solely force components. Maddahi et al, [30], measured the interaction forces during four robot-assisted neurosurgical operations. The authors employed a bipolar forces and a suction tool, linked to the robot end-effector via two six DoFs force/torque sensors.…”

Section: Discussionmentioning

confidence: 99%

“…Measured forces exerted during carrying incision or tissue retraction were approximately 0.2 N, with low variability. Another interesting study has been proposed by Maddahi et al [30], where the authors have conducted four operations in which the neuroArm surgical system [27] was employed to surgically remove brain tumors. The authors employed a bipolar forces and a suction tool, linked to the robot end-effector via two six DoFs force/torque sensors.…”

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

Hand–tool–tissue interaction forces in neurosurgery for haptic rendering

Aggravi

Momi

DiMeco³

et al. 2015

Med Biol Eng Comput

View full text Add to dashboard Cite

Abstract:Haptics provides sensory stimuli that represent the interaction with a virtual or telemanipulated object, and it is considered a valuable navigation and manipulation tool during tele-operated surgical procedures. Haptic feedback can be provided to the user via cutaneous information and kinesthetic feedback. Sensory subtraction removes the kinesthetic component of the haptic feedback, having only the cutaneous component provided to the user. Such a technique guarantees a stable haptic feedback loop, while it keeps the transparency of the tele-operation system high, which means that the system faithfully replicates and render back the user's directives. This work focuses on checking whether the interaction forces during a bench model neurosurgery operation can lie in the solely cutaneous perception of the human finger pads. If this assumption is found true, it would be possible to exploit sensory subtraction techniques for providing surgeons with feedback from neurosurgery. We measured the forces exerted to surgical tools by three neurosurgeons performing typical actions on a brain phantom, using contact force sensors, whilst the forces exerted by the tools to the phantom tissue were recorded using a load cell placed under the brain phantom box. The measured surgeon-tool contact forces were 0.01 -3.49 N for the thumb and 0.01 -6.6 N for index and middle finger, whereas the measured tool-tissue interaction forces were from six to eleven times smaller than the contact forces, i.e., 0.01 -0.59 N. The measurements for the contact forces fit the range of the cutaneous sensitivity for the Powered by Edit orial Manager® and ProduXion Manager® from Aries Syst em s Corporat ionhuman finger pad, thus, we can say that, in a tele-operated robotic neurosurgery scenario, it would possible to render forces at the fingertip level by conveying haptic cues solely through the cutaneous channel of the surgeon's finger pads. This approach would allow high transparency and high stability of the haptic feedback loop in a teleoperation systemResponse to Reviewers: REVIEWER 1 Comment no. 1: The methodology of the submitted work is good and, since it is a bench model, it might allow to replace other similar systems presented in previous works. However, the authors should make an extra effort to increase the clarity of the text. The added section 2 is a good help to put the work in context. However, section 1 appears as too long and lacks focus. I would recommend to severely shorten section 1 and merge it with section 2. Our answer:We thank the reviewer for the positive opinion on our work. To improve the clarity of the introductory part, we have removed an example of sensory substitution reference and an example of sensory subtraction application reference. Moreover, we have merged Section 2 Related Works with Section 1 Introduction, which now comprises the related works as a subsection.Comment no. 2: Also section 5 could be reorganized to strengthen the papers conclusion. Our answer:We have modified Section 4 Discussion as follow...

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Hand–tool–tissue interaction forces in neurosurgery for haptic rendering

Aggravi

Momi

DiMeco³

et al. 2015

Med Biol Eng Comput

View full text Add to dashboard Cite

show abstract

“…With the development of medical technology and robotics, brain surgery robots have been increasingly used in the planning, navigation, and orientation of cerebral surgery. And the computer vision has been applied in neurosurgery 1,2 and robotic brain surgery. [3][4][5] Brain surgery robot uses embedded computer vision module to collect brain image data, and then accurately segment, detect, and locate brain tissue.…”

Section: Introductionmentioning

confidence: 99%

An active contour model for brain magnetic resonance image segmentation based on multiple descriptors

Chen

et al. 2018

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

With the increasing use of surgical robots, robust and accurate segmentation techniques for brain tissue in the brain magnetic resonance image are needed to be embedded in the robot vision module. However, the brain magnetic resonance image segmentation results are often unsatisfactory because of noise and intensity inhomogeneity. To obtain accurate segmentation of brain tissue, one new multiphase active contour model, which is based on multiple descriptors mean, variance, and the local entropy, is proposed in this study. The model can bring about a more full description of local intensity distribution. Also, the entropy is introduced to improve the performance of robustness to noise of the algorithm. The segmentation and bias correction for brain magnetic resonance image can be simultaneously incorporated by introducing the bias factor in the proposed approach. At last, three experiments are carried out to test the performance of the method. The results in the experiments show that method proposed in this study performed better than most current methods in regard to accuracy and robustness. In addition, the bias-corrected images obtained by proposed method have better visual effect.

show abstract

Research of the master–slave robot surgical system with the function of force feedback

Shi¹,

Zhou²,

Xie

et al. 2017

Robotics Computer Surgery

View full text Add to dashboard Cite

show abstract

Quantifying workspace and forces of surgical dissection during robot‐assisted neurosurgery

Abstract: This data provides important information specific to neurosurgery that can be used to select among commercially available, or further design a customized, haptic hand-controller for robot-assisted neurosurgical systems. Copyright © 2015 John Wiley & Sons, Ltd.

Cited by 35 publications

References 31 publications

Hand–tool–tissue interaction forces in neurosurgery for haptic rendering

Hand–tool–tissue interaction forces in neurosurgery for haptic rendering

An active contour model for brain magnetic resonance image segmentation based on multiple descriptors

Research of the master–slave robot surgical system with the function of force feedback

Contact Info

Product

Resources

About