the application of robotics to keyhole transcranial ... · web viewrobotics in keyhole transcranial...

Robotics in Keyhole Neurosurgery

Robotics in Keyhole Transcranial Endoscope-assisted Microsurgery: A Critical Review of

Existing Systems and Proposed Specifications for New Robotic Platforms

Abstract (structured)

Background: Over the last decade advances in image guidance, endoscopy and tube-shaft

instruments have allowed for the development of keyhole transcranial endoscope-assisted

microsurgery; utilizing smaller craniotomies, and minimizing exposure and manipulation of

unaffected brain tissue. Although such approaches offer the possibility of shorter operating

times, reduced morbidity and mortality, and improved long-term outcomes, the technical skills

required to perform such surgery are inevitably greater than for traditional open surgical

techniques, and they have not been widely adopted by neurosurgeons. Surgical robotics, which

has the ability to improve visualization and increase dexterity, therefore has the potential to

enhance surgical performance.

Objective: To evaluate the role of surgical robots in keyhole transcranial endoscope-assisted

microsurgery.

Methods: The technical challenges faced by surgeons utilizing keyhole craniotomies were

reviewed, and a thorough appraisal of presently-available robotic systems was carried out.

Results: Surgical robotic systems have the potential to incorporate advances in augmented

reality, stereo-endoscopy, and jointed-wrist instruments, and therefore significantly impact on

the field of keyhole neurosurgery. To date, over 30 robotic systems have been applied to

neurosurgical procedures. The vast majority of these robots are best described as supervisory-

controlled, and are designed for stereotactic or image-guided surgery. Few telesurgical robots are

suitable for keyhole neurosurgical approaches, and none are in widespread clinical use in the

field.

Conclusion: New robotic platforms in minimally invasive neurosurgery must possess clear and

unambiguous advantages over conventional approaches if they are to achieve significant clinical

penetration.

1

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26


Abstract (unstructured)

Over the last decade advances in image guidance, endoscopy and tube-shaft instruments have

allowed for the development of keyhole transcranial endoscope-assisted microsurgery; utilizing

smaller craniotomies, and minimizing exposure and manipulation of unaffected brain tissue.

Although such approaches offer the possibility of shorter operating times, reduced morbidity and

mortality, and improved long-term outcomes, the technical skills required to perform such

surgery are inevitably greater than for traditional open surgical techniques, and they have not

been widely adopted by neurosurgeons. Surgical robotics, which has the ability to improve

visualization and increase dexterity, therefore has the potential to enhance surgical performance.

In this review we will: consider the evolution of cranial neurosurgery from historical extended

craniotomies to contemporary minimally invasive techniques; address the technical challenges

faced by surgeons utilizing keyhole craniotomies and the scope for robotics to assist in such

operations; thoroughly appraise presently-available robotic systems against these demands; and

propose broad specifications for our vision of new robotic platforms.

Key words

Image Guided Intervention; Minimally invasive surgery; Neurosurgery; Robotic Surgery

Running Title


2

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44


Introduction

Neurosurgery is inherently high risk. Pathologies within the brain invariably distort neighboring

anatomical landmarks making accurate and precise intra-operative localization challenging. In

addition, unaffected brain tissue is easily injured, frequently eloquent, and has limited scope for

regeneration. Over the last decade, neurosurgery has greatly benefited from advances in image

guidance allowing improved identification of target pathology and key brain structures. A natural

extension of these developments is the concept of keyhole transcranial endoscope-assisted

microsurgery; utilizing smaller craniotomies, and minimizing exposure and manipulation of

unaffected brain tissue. Although such approaches offer the possibility of shorter operating

times, reduced morbidity and mortality, and improved long-term outcomes, the technical skills

required to perform such surgery are inevitably greater than for traditional open surgical

techniques. Surgical robotics, which has the ability to improve visualization and increase

dexterity, therefore has the potential to enhance surgical performance.

In this review we will: consider the evolution of cranial neurosurgery from historical extended

craniotomies to contemporary minimally invasive techniques; address the technical challenges

faced by surgeons utilizing keyhole craniotomies and the scope for robotics to assist in such

operations; thoroughly appraise presently-available robotic systems against these demands; and

propose broad specifications for our vision of new robotic platforms.

The Evolution of Cranial Neurosurgery towards Keyhole Transcranial Endoscope-assisted

Microsurgical Approaches

Keyhole transcranial endoscope-assisted microsurgery is the product of over century of

technological progress in surgical approach, visualization and manipulation (see Fig. 1). Early

pioneers such as Sir Victor Horsley, who was appointed the world’s first neurological surgeon in

1886, habitually performed extended craniotomies to treat intracranial lesions1. Extended

craniotomies were needed for a number of reasons2, 3. In these early cases pathologies were

localized clinically and a large craniotomy was necessary to ensure the operating surgeon could

locate the lesion. Intra-operative visualization relied on ambient lighting in the operating theatre

and a large craniotomy was required to illuminate the surgical field. Additionally, instruments

3

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70

71

72


used at the time were designed for general surgery rather than neurosurgery, necessitating large

openings.

Several advances contributed to the replacement of extended craniotomies with mini-

craniotomies2, 3. The introduction of Computed Tomography (CT) in the early 1970s and

Magnetic Resonance Imaging (MRI) in the 1980s allowed brain pathologies such as tumors to be

directly visualized, permitting far more targeted surgical approaches. Intra-operative

visualization was also greatly enhanced with the introduction of the operating microscope in the

1960s, improving illumination and magnification of the surgical field. In parallel to these

developments, surgical instruments were adapted for use in microneurosurgery. Leonard Malis

and M. Gazi Yasargil described the use of bipolar coagulation and purpose-designed

microinstruments that allowed careful surgical dissection.

Over the last decade, further technological progress has led to the development of keyhole

transcranial endoscope-assisted microsurgical techniques. Image guidance systems that combine

pre-operative imaging with live instrument tracking data to bring the real surgical field into

alignment have been widely adopted by neurosurgeons, and are associated with shorter operating

times, reduced blood loss and fewer major complications when compared with standard surgery4.

Endoscopes provide a method of further increasing illumination and magnification, while

extending the viewing angle, with keyhole approaches. Furthermore novel tube-shaft based

surgical instruments have been designed for keyhole surgery permitting improved surgical

manipulation through narrow surgical corridors compared with conventional microinstruments.

Axel Perneczky at the Johannes-Gutenberg University described a number of image-guided

endoscope-assisted keyhole techniques utilizing natural anatomical corridors within the brain to

reach surgical targets. One large case series reported the use of a short eyebrow incision, a

supraorbital keyhole craniotomy approximately 15mm x 25mm in diameter, and a subfrontal or

fronto-lateral approach to the anterior cranial fossa and suprasellar regions. Over a 10-year

period more than 450 patients underwent surgery to treat various pathologies including

intracranial aneurysms, meningiomas, craniopharyngiomas and pituitary adenomas, with the vast

majority making a good recovery (Glasgow Outcome Scale 5 in 86%, and 4 in 6.4%) in this

heterogeneous group5. Keyhole modifications of the subtemporal, retrosigmoid, suboccipital,

4

73

74

75

76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

100

101


supracerbellar and interhemispheric approaches have also been successfully utilized, providing a

number of routes to reach the deep intracranial cisterns2.

Technical Challenges of Keyhole Craniotomies and the Scope of Robotics to Assist Surgical

Performance

Despite the purported advantages of minimally invasive techniques over conventional

microsurgical techniques, they have not been widely embraced by neurosurgeons. Keyhole

craniotomies remain very technically challenging in spite of the aforementioned advances in

approach, visualization and manipulation. First, although image guidance systems are widely

used for planning surgery, their use intra-operatively generally requires neurosurgeons to

momentarily stop operating, apply a probe to the region of interest (potentially near critical

structures), and then take their eyes off the surgical field to view the image guidance monitors. In

minimally invasive neurosurgical procedures, the relative paucity of anatomical landmarks often

necessitates more frequent use of image guidance, which may considerably impact on surgical

performance. Second, while endoscopes do provide an extended viewing angle compared to

operating microscopes, some deliver lower quality imaging, and most lack stereoscopy, limiting

appreciation of complex spatial relationships within the brain. Third, the use of endoscopes

makes bimanual manipulation difficult or impossible. Within the brain, which is incompatible

with gas insufflation, debris quickly clouds the endoscopic field unless a sucker is concurrently

used; a single surgeon can therefore not easily view and manipulate tissue simultaneously.

Although an additional surgeon may assist, the use of a single anatomical corridor makes it

difficult to do so without the operating surgeons obstructing each other or their instruments

clashing. Instrument holders have recently been developed but can again lead to crowding of

instruments, and inevitably interrupt the operative workflow, as they must be repeatedly

repositioned. Moreover, even when using specially designed tube-shaft instruments,

manipulation through uniportal keyhole neurosurgical approaches is almost co-axial, to the major

detriment of surgical dexterity.

Future technological advances that overcome these technical barriers to keyhole neurosurgery

have the potential to greatly increase the adoption of such techniques by surgeons, and yield

significant improvements in patient outcomes. Augmented reality systems, which fuse virtual

5

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130


three-dimensional brain models and the actual operating field, may enhance the operating room

workflow and improve safety by eliminating the need for surgeons to repeatedly interrupt

operations and look away from the surgical field. Such systems are already commercially

available for use with surgical microscopes, but have not yet been widely applied to neuro-

endoscopy. The use of a single-shaft design with a stereo-endoscope and working channels for

instruments may allow for fully endoscopic approaches while preventing instrument clashing.

Although such single-shaft designs do exist, few compatible instruments are available and

control is entirely coaxial limiting their use to relatively straightforward operations such as

Endoscopic Third Ventriculostomy (that requires perforation through the floor of the third

ventricle, rather than tissue manipulation). Therefore, when implementing single-shaft designs,

the development of instruments with a jointed-wrist design would allow for greatly increased

surgical dexterity.

Surgical robotic systems have the potential to incorporate advances in augmented reality, stereo-

endoscopy, and jointed-wrist instruments, and therefore significantly impact on the field of

minimally invasive surgery. In addition, these systems offer the possibility of greater precision,

reduced physiological tremor, and motion scaling.

Appraisal of Existing Robotic Systems for Neurosurgery

Surgical robots can be broadly classified into three categories on the basis of how surgeons

interact with them6: supervisory-controlled robot systems in which the surgeon plans the

operation, and the robot then carries it out autonomously under the supervision of the surgeon;

telesurgical (master-slave) systems in which the surgeon (master) remotely controls the robots

actions (slave); and handheld shared-controlled systems in which the surgeon and robot share

control of the instrument.

To date, over 30 robotic systems have been applied to neurosurgical procedures (see Table 1;

robots performing endovascular or radiosurgical procedures were excluded). The vast majority of

these robots are best described as supervisory-controlled, and are designed for stereotactic or

image-guided surgery7-58. The first such robot, a modified Puma 560 industrial robot (Advance

Research & Robotics, Oxford, CT), was used in 1985 to define the trajectory of a frame-based

6

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158


brain biopsy7. In this system the surgeon entered the co-ordinates of a brain lesion, the effector

arm with the probe holder moved to the predefined location, and the surgeon then used the probe

as a guide for trephination and biopsy. Many other supervisory-controlled robots have since been

developed, with clinical studies illustrating their use in brain biopsy, and the implantation of

Deep Brain Stimulation electrodes. Perhaps the most widely used supervisory-controlled robots

within neurosurgery are the SpineAssist and Renaissance systems (Mazor Surgical Technologies,

Caesarea, Israel). Although principally developed for pedicle screw placement, they have also

received regulatory approval for use in the brain35-46. These robots offer a theoretical advantage

over conventional surgery because of their high precision and accuracy6, and may reduce

radiation exposure of the patient and surgical team59.

A number of telesurgical robots have been utilized in neurosurgery60-85. One of the earliest

examples of such a system was the Robot Assisted Microsurgery (RAMS) robot (NASA,

Pasadena, California, USA)63. In a feasibility study, carotid arteriotomies were created and

closed using either RAMS or conventional microsurgical techniques in 10 rats; the precision and

technical quality, and error rate were comparable but the use of the RAMS robot was associated

with a twofold increase in the procedure length.

NeuroArm (University of Calgary, Calgary, Canada) is a robot purpose built for

microneurosurgery that is endowed with a number of distinct features64, 65. The console provides

visual, auditory and tactile feedback to the operating surgeon. The robot is MRI compatible,

allowing real-time imaging during procedures to account for brain shift. The manipulator

consists of two arms, each with 8 degrees of freedom (DOF), with end-effectors that mimic a

surgeon’s hand, and interface with microinstruments. Early reports from the NeuroArm case

series’ have been promising but its use at present is limited to microneurosurgery rather than

endoscope-assisted neurosurgery.

A team in Tokyo, Japan has also constructed a telesurgical robot to assist with

microneurosurgery. The MM-1 robot consists of a passive base with 6 DOF, and two robotic

arms each with 6 DOF66. In validation studies, closure of partial arteriotomies and end-to-end

anastomosis of the ICA was performed successfully in 20 rats. The frontotemporal transsylvian

approach, suboccipital retrosigmoid, and endonasal transphenoidal approaches were also

7

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187


performed in cadavers. Although a significant learning curve was demonstrated initially surgical

performance quickly reached a plateau, and the procedure durations were still unacceptably long.

Furthermore, the manipulators were felt to be too bulky to be used in the delicate operative field.

Recently, the same research group has developed a modified master-slave robot platform, with

two robotic arms each with 7 DOF, and either bent- or straight-forceps as end-effectors 85. In

feasibility studies the robot was able to perform a number of maneuvers including end-to-end

anastamoses of 0.3mm artificial vessels, which is very difficult to do manually, though with a

longer task completion time.

The da Vinci surgical system (Intuitive Surgical, Sunnyvale, California, USA) is the most

frequently used telesurgical robot worldwide but is not as yet widely used for neurosurgery.

Unlike the abovementioned robots, the da Vinci system is designed for endoscopic keyhole

surgery. A camera arm equipped with two lenses is used to generate a high-resolution

stereoscopic image display. Instruments are carried by two or three working arms, which include

articulated endo-wrists that increase surgical dexterity. In addition, the system allows for tremor

filtering and motion scaling, allowing more delicate tissue manipulation. A major advantage of

the da Vinci system is the ergonomic benefit provided by the anthropomorphic master console

that restores the motor-visual alignment of the camera and surgical instruments. The da Vinci

robot has been successfully used in a broad range of surgical procedures, particularly within the

field of urology. Several groups have demonstrated the feasibility of using the da Vinci system in

spinal surgery68-76. Unfortunately, the fact that the da Vinci system consists of several arms,

rather than possessing a single-shaft design, makes it ill suited to keyhole surgical procedures

within the brain. In a recent cadaveric study the da Vinci system was used during a supraorbital

approach and the issue of arm collisions within a narrow surgical corridor was cited as a key

drawback, which could interrupt operative workflow, and also raises safety concerns86.

NeuRobot (Shinshu University School of Medicine, Matsumoto, Japan) was the first telesurgical

robot designed specifically for keyhole neurosurgery77-82. The system has a single-shaft design

approximately 10mm in diameter containing a three-dimensional endoscope, and three sets of

micromanipulators, each with 3 DOF (rotation, neck swinging, and forward/backward motion).

Although the system was able to perform relatively simple surgical procedures in cadavers and

8

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

216


human studies, the authors report the system was limited by lack of maneuverability of the

micromanipulators and robot itself.

Another Japanese group have recently developed a similar Neurosurgical Robot for Brain Tumor

Removal (Nagoya Institute of Technology, Nagoya, Japan)83, 84. As with NeuRobot the robot has

a single-shaft design approximately 10mm in diameter, containing a three-dimensional

endoscope, an irrigation system, and a volume control suction tool, with 2 DOF at the instrument

tips. Although preliminary evaluation of the robot on a phantom demonstrated feasibility it is

likely that, as with NeuRobot, the restricted working space will limit its clinical use.

Only a handful of handheld shared-controlled systems have been described in the literature for

use in neurosurgery87-90. Shared-controlled systems exploit both the precision of a robot in the

control of the surgical instruments and the natural manipulation skill of the surgeon. In the

Steady Hand System (John Hopkins University, Baltimore, USA), for example, the surgical

instrument is held by both the robot and operator which allows finer, tremor-free motion control

of the instrument, and also lets surgeons to define critical ‘no-go’ areas to be avoided 87, 88.

Similarly, the Craniostar (University of Heidelberg, Heidelberg, Germany) and Safe

Trephination System (RWTH-Aachen, Aachen, Germany) allow surgeons to fashion

craniotomies along predefined paths, while reducing the risk of dural injury89, 90. Another

advantage of these hand-held systems is ease in which they can be integrated into the surgical

workflow compared to telesurgical systems that suffer from long setup times.

Proposed Specifications for New Robotic Platforms

Although a multitude of robots have been applied to neurosurgery, few are applicable to

minimally invasive techniques, and no robots are in widespread clinical use in the field. New

robotic platforms in minimally invasive neurosurgery must possess clear and unambiguous

advantages over conventional approaches if they are to achieve significant clinical penetration.

Here we outline broad specifications for our vision of new robotic platforms designed to assist

with keyhole transcranial endoscope-assisted microsurgical approaches (see Fig. 2).

It is likely that most systems in the near future will adopt a master-slave arrangement with the

surgeon sitting comfortably at a console controlling the robots actions. This will restore

9

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

238

239

240

241

242

243

244


visuomotor alignment and provide considerable ergonomic benefits, particularly in cases in

which the patient is placed in a seated position, such as those utilizing the supracerebellar

infratentorial approach, that presently require the operator to stand hunched over with their arms

outstretched for several hours.

In order to safely approach pathology, new surgical robots must be fully integrated with image

guidance systems, and augmented reality displays utilized at the surgical console to improve the

operating room workflow. The use of intra-operative imaging such as ultrasound, CT or MRI to

compensate for brain shift is also desirable to ensure accuracy of the system is maintained

throughout the course of an operation.

The overall design of robots themselves should be a single shaft with visualization and

manipulation features located at their ‘head’. The length of the shaft should be approximately

300mm, long enough to access deep-sited lesions using the keyhole concept. The diameter of the

shaft should be as small as possible to minimize trauma. In animal studies brain retraction

pressures of 20mmHg or less do not appear to be associated with cortical damage91, and

subsequent case series’ using cylindrical retractors up to 20mm in diameter have recorded

surrounding intracranial pressures of less than 10 mmHg92 with no approach-related neurological

deficits observed post-operatively. Nonetheless, it is suggested that robots be no more than

12mm in diameter to reduce the risk of brain injury.

Visualization in new robotic systems will be achieved through cameras providing uninterrupted

illumination, magnification and wide-angle images of the operative field. High-definition and

three-dimensional neuro-endoscopes have recently been developed, and the incorporation of

such devices into surgical robots would allow for unparalleled views within the brain. In

addition, endoscopes may be used in conjunction with photosensitizing agents such as 5-

aminolevulinic acid (5-ALA) for fluorescence guided tumor resection. In a randomized

controlled multicentre trial of patients undergoing surgery for malignant glioma, resection was

achieved in 65% with the use of 5-ALA versus 36% using white light alone93. A number of

emerging technologies may ultimately allow real-time in-vivo visualization of tumor tissue, with

the promise of even greater identification of tumor cells. In confocal microendoscopy, for

example, the principles of confocal microscopy and fiber-optic endoscopy are combined to

10

245

246

247

248

249

250

251

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

267

268

269

270

271

272

273


reveal cellular morphology and micro-architecture in a similar manner to cytological and

histological analysis respectively94, 95.

Bimanual manipulation of delicate tissue will require at least two working channels for

instruments in putative robotic systems. Robotic end-effectors should be miniaturized to a size

comparable with conventional microinstruments, with the smallest tips measuring approximately

1-2mm. Perhaps most importantly these instruments must have sufficient degrees of freedom to

operate within the small working spaces used in keyhole approaches; jointed-wrist designs will

almost certainly be invaluable in this context (see Fig. 3). In the first instance, a range of

standard microinstruments such as bayonet forceps, bipolar coagulation, scissors, dissectors,

needle-holders, and suction tubes would likely be used. Additional instruments such as waterjet

dissection, which may allow for more rapid dissection around delicate neurovascular structures,

may also be developed in subsequent iterations.

Control of slave-micromanipulators will rely on intuitive human-machine interfaces at the

master-console. The development of systems that provide haptic-feedback has proved

challenging for researchers within surgical robotics. However, surgical robots such as NeuroArm

demonstrate the technological feasibility of incorporating force-feedback, and such robots will

undoubtedly provide a more immersive environment.

Conclusions

The keyhole concept holds arguably greater potential to improve patient outcomes in

neurosurgery than in other surgical fields because, in addition to reducing the length of scalp

incisions and size of craniotomies, minimally invasive techniques entail reduced exposure and

manipulation of unaffected brain tissue, which may reduce the risk of serious approach-related

complications such as stroke or death. Although keyhole approaches utilizing image-guidance,

endoscopy and tube-shaft instruments have been developed as alternatives to most conventional

open microsurgical techniques, they remain highly challenging and have not been widely

accepted into neurosurgical practice. The development of master-slave robots encompassing

improvements such augmented-reality, stereo-endoscopy, and jointed-wrist instruments, may

herald a paradigm shift in neurosurgery towards minimally invasive neurosurgical techniques

11

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

296

297

298

299

300

301


that most neurosurgeons find almost impossible to perform safely using presently available

surgical tools.

In the long-term, technological progress may see robots becoming smaller, more powerful and

less costly, in a way comparable to the growth of digital computing over the last 50 years.

Perhaps the world’s first digital computers were the Colossus machines developed for

cryptanalysis during World War 2, each of which weighed approximately a ton and occupied an

entire room. Over the proceeding decades personal computers such as desktops and laptops were

popularized. More recently, further miniaturization has led to the integration of digital computing

into everyday ‘smart’ devices such as mobile phones or wristwatches. The result, paradoxically,

has been the regression of digital computing into the background of people’s lives. There is some

evidence that robotic may be evolving along a similar path, and it is possible that the large and

cumbersome robots of today will eventually be replaced with a range of ‘smart’ handheld

instruments each encompassing robotic qualities, and performing a different task96.

12

302

303

304

305

306

307

308

309

310

311

312

313

314


References

1. Uff C, Frith D, Harrison C, Powell M, Kitchen N. Sir Victor Horsley's 19th century

operations at the National Hospital for Neurology and Neurosurgery, Queen Square. J

Neurosurg. Feb 2011;114(2):534-542.

2. Perneczky A, Reisch R. Keyhole approaches in neurosurgery. Volume 1: Concept and

surgical technique. 1 ed: Springer; 2008.

3. Reisch R, Stadie A, Kockro RA, Hopf N. The Keyhole Concept in Neurosurgery. World

Neurosurg. Feb 10 2012.

4. Paleologos TS, Wadley JP, Kitchen ND, Thomas DG. Clinical utility and cost-

effectiveness of interactive image-guided craniotomy: clinical comparison between

conventional and image-guided meningioma surgery. Neurosurgery. Jul 2000;47(1):40-

47; discussion 47-48.

5. Reisch R, Perneczky A. Ten-year experience with the supraorbital subfrontal approach

through an eyebrow skin incision. Neurosurgery. Oct 2005;57(4 Suppl):242-255;

discussion 242-255.

6. Nathoo N, Cavusoglu MC, Vogelbaum MA, Barnett GH. In touch with robotics:

neurosurgery for the future. Neurosurgery. Mar 2005;56(3):421-433; discussion 421-433.

7. Kwoh YS, Hou J, Jonckheere EA, Hayati S. A robot with improved absolute positioning

accuracy for CT guided stereotactic brain surgery. IEEE Trans Biomed Eng. Feb

1988;35(2):153-160.

8. Drake JM, Joy M, Goldenberg A, Kreindler D. Computer- and robot-assisted resection of

thalamic astrocytomas in children. Neurosurgery. Jul 1991;29(1):27-33.

9. Benabid AL, Cinquin P, Lavalle S, Le Bas JF, Demongeot J, de Rougemont J. Computer-

driven robot for stereotactic surgery connected to CT scan and magnetic resonance

imaging. Technological design and preliminary results. Appl Neurophysiol. 1987;50(1-

6):153-154.

10. Benabid AL, Hoffmann D, Ashraf A, Koudsie A, Esteve F, Le Bas JF. [Robotics in

neurosurgery: current status and future prospects]. Chirurgie. Feb 1998;123(1):25-31.

13

315

316

317

318

319

320

321

322

323

324

325

326

327

328

329

330

331

332

333

334

335

336

337

338

339

340

341

342


11. Li QH, Zamorano L, Pandya A, Perez R, Gong J, Diaz F. The application accuracy of the

NeuroMate robot--A quantitative comparison with frameless and frame-based surgical

localization systems. Comput Aided Surg. 2002;7(2):90-98.

12. Varma TR, Eldridge PR, Forster A, et al. Use of the NeuroMate stereotactic robot in a

frameless mode for movement disorder surgery. Stereotact Funct Neurosurg. 2003;80(1-

4):132-135.

13. Varma TR, Eldridge P. Use of the NeuroMate stereotactic robot in a frameless mode for

functional neurosurgery. Int J Med Robot. Jun 2006;2(2):107-113.

14. Xia T, Baird C, Jallo G, et al. An integrated system for planning, navigation and robotic

assistance for skull base surgery. Int J Med Robot. Dec 2008;4(4):321-330.

15. Haegelen C, Touzet G, Reyns N, Maurage CA, Ayachi M, Blond S. Stereotactic robot-

guided biopsies of brain stem lesions: Experience with 15 cases. Neurochirurgie. Oct

2010;56(5):363-367.

16. Koyama H, Uchida T, Funakubo H, Takakura K, Fankhauser H. Development of a new

microsurgical robot for stereotactic neurosurgery. Stereotact Funct Neurosurg. 1990;54-

55:462-467.

17. Glauser D, Flury P, Durr P, et al. Configuration of a robot dedicated to stereotactic

surgery. Stereotact Funct Neurosurg. 1990;54-55:468-470.

18. Fankhauser H, Glauser D, Flury P, et al. Robot for CT-guided stereotactic neurosurgery.

Stereotact Funct Neurosurg. 1994;63(1-4):93-98.

19. Glauser D, Fankhauser H, Epitaux M, Hefti JL, Jaccottet A. Neurosurgical robot

Minerva: first results and current developments. J Image Guid Surg. 1995;1(5):266-272.

20. Hefti JL, Epitaux M, Glauser D, Fankhauser H. Robotic three-dimensional positioning of

a stimulation electrode in the brain. Comput Aided Surg. 1998;3(1):1-10.

21. Giorgi C, Eisenberg H, Costi G, Gallo E, Garibotto G, Casolino DS. Robot-assisted

microscope for neurosurgery. J Image Guid Surg. 1995;1(3):158-163.

22. DiMaio SP, Pieper S, Chinzei K, et al. Robot-assisted needle placement in open-MRI:

system architecture, integration and validation. Stud Health Technol Inform.

2006;119:126-131.

23. Levesque MF, Parker F. MKM-guided resection of diffuse brainstem neoplasms.

Stereotact Funct Neurosurg. 1999;73(1-4):15-18.

14

343

344

345

346

347

348

349

350

351

352

353

354

355

356

357

358

359

360

361

362

363

364

365

366

367

368

369

370

371

372

373


24. Willems PW, Noordmans HJ, Berkelbach van der Sprenkel JW, Viergever MA, Tulleken

CA. An MKM-mounted instrument holder for frameless point-stereotactic procedures: a

phantom-based accuracy evaluation. J Neurosurg. Dec 2001;95(6):1067-1074.

25. Willems PW, Noordmans HJ, Ramos LM, et al. Clinical evaluation of stereotactic brain

biopsies with an MKM-mounted instrument holder. Acta Neurochir (Wien). Oct

2003;145(10):889-897; discussion 897.

26. Cleary K, Stoianovici D, Patriciu A, Mazilu D, Lindisch D, Watson V. Robotically

assisted nerve and facet blocks: a cadaveric study. Acad Radiol. Jul 2002;9(7):821-825.

27. Koseki Y, Washio T, Chinzei K, Iseki H. Endoscope Manipulator for Trans-nasal

Neurosurgery, Optimized for and Compatible to Vertical Field Open MRI. Medical

Image Computing and Computer-Assisted Intervention — MICCAI 2002. In: Dohi T,

Kikinis R, eds. Vol 2488: Springer Berlin / Heidelberg; 2002:114-121.

28. Zimmermann M, Krishnan R, Raabe A, Seifert V. Robot-assisted navigated

neuroendoscopy. Neurosurgery. Dec 2002;51(6):1446-1451; discussion 1451-1442.

29. Zimmermann M, Krishnan R, Raabe A, Seifert V. Robot-assisted navigated endoscopic

ventriculostomy: implementation of a new technology and first clinical results. Acta

Neurochir (Wien). Jul 2004;146(7):697-704.

30. Nimsky C, Rachinger J, Iro H, Fahlbusch R. Adaptation of a hexapod-based robotic

system for extended endoscope-assisted transsphenoidal skull base surgery. Minim

Invasive Neurosurg. Feb 2004;47(1):41-46.

31. Bumm K, Wurm J, Rachinger J, et al. An automated robotic approach with redundant

navigation for minimal invasive extended transsphenoidal skull base surgery. Minim

Invasive Neurosurg. Jun 2005;48(3):159-164.

32. Korb W, Engel D, Boesecke R, et al. Development and first patient trial of a surgical

robot for complex trajectory milling. Comput Aided Surg. 2003;8(5):247-256.

33. Eggers G, Wirtz C, Korb W, et al. Robot-assisted craniotomy. Minim Invasive

Neurosurg. Jun 2005;48(3):154-158.

34. Junchuan L, Yuru Z, Tianmiao W, Hongguang X, Zengmin T. Neuromaster: a robot

system for neurosurgery. Paper presented at: Robotics and Automation, 2004.

Proceedings. ICRA '04. 2004 IEEE International Conference on; 26 April-1 May 2004,

2004.

15

374

375

376

377

378

379

380

381

382

383

384

385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404


35. Shamir R, Freiman M, Joskowicz L, Shoham M, Zehavi E, Shoshan Y. Robot-assisted

image-guided targeting for minimally invasive neurosurgery: planning, registration, and

in-vitro experiment. Med Image Comput Comput Assist Interv. 2005;8(Pt 2):131-138.

36. Lieberman IH, Togawa D, Kayanja MM, et al. Bone-mounted miniature robotic guidance

for pedicle screw and translaminar facet screw placement: Part I--Technical development

and a test case result. Neurosurgery. Sep 2006;59(3):641-650; discussion 641-650.

37. Barzilay Y, Liebergall M, Fridlander A, Knoller N. Miniature robotic guidance for spine

surgery--introduction of a novel system and analysis of challenges encountered during

the clinical development phase at two spine centres. Int J Med Robot. Jun 2006;2(2):146-

153.

38. Sukovich W, Brink-Danan S, Hardenbrook M. Miniature robotic guidance for pedicle

screw placement in posterior spinal fusion: early clinical experience with the SpineAssist.

Int J Med Robot. Jun 2006;2(2):114-122.

39. Joskowicz L, Shamir R, Freiman M, et al. Image-guided system with miniature robot for

precise positioning and targeting in keyhole neurosurgery. Comput Aided Surg. Jul

2006;11(4):181-193.

40. Shoham M, Lieberman IH, Benzel EC, et al. Robotic assisted spinal surgery--from

concept to clinical practice. Comput Aided Surg. Mar 2007;12(2):105-115.

41. Togawa D, Kayanja MM, Reinhardt MK, et al. Bone-mounted miniature robotic

guidance for pedicle screw and translaminar facet screw placement: part 2--Evaluation of

system accuracy. Neurosurgery. Feb 2007;60(2 Suppl 1):ONS129-139; discussion

ONS139.

42. Pechlivanis I, Kiriyanthan G, Engelhardt M, et al. Percutaneous placement of pedicle

screws in the lumbar spine using a bone mounted miniature robotic system: first

experiences and accuracy of screw placement. Spine (Phila Pa 1976). Feb 15

2009;34(4):392-398.

43. Devito DP, Kaplan L, Dietl R, et al. Clinical acceptance and accuracy assessment of

spinal implants guided with SpineAssist surgical robot: retrospective study. Spine (Phila

Pa 1976). Nov 15 2010;35(24):2109-2115.

44. Kantelhardt SR, Martinez R, Baerwinkel S, Burger R, Giese A, Rohde V. Perioperative

course and accuracy of screw positioning in conventional, open robotic-guided and

16

405

406

407

408

409

410

411

412

413

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

429

430

431

432

433

434

435


percutaneous robotic-guided, pedicle screw placement. Eur Spine J. Jun 2011;20(6):860-

868.

45. Hu X, Ohnmeiss DD, Lieberman IH. Robotic-assisted pedicle screw placement: lessons

learned from the first 102 patients. Eur Spine J. Sep 14 2012.

46. Ringel F, Stuer C, Reinke A, et al. Accuracy of robot-assisted placement of lumbar and

sacral pedicle screws: a prospective randomized comparison to conventional freehand

screw implantation. Spine (Phila Pa 1976). Apr 15 2012;37(8):E496-501.

47. Heinig M, Hofmann UG, Schlaefer A. Calibration of the motor-assisted robotic

stereotaxy system: MARS. Int J Comput Assist Radiol Surg. Mar 14 2012.

48. Brodie J, Eljamel S. Evaluation of a neurosurgical robotic system to make accurate burr

holes. Int J Med Robot. Jan 11 2011.

49. Eljamel MS. Robotic application in epilepsy surgery. Int J Med Robot. Sep

2006;2(3):233-237.

50. Eljamel MS. Robotic neurological surgery applications: accuracy and consistency or pure

fantasy? Stereotact Funct Neurosurg. 2009;87(2):88-93.

51. Deacon G, Harwood A, Holdback J, et al. The Pathfinder image-guided surgical robot.

Proc Inst Mech Eng H. 2010;224(5):691-713.

52. Ortmaier T, Weiss H, Dobele S, Schreiber U. Experiments on robot-assisted navigated

drilling and milling of bones for pedicle screw placement. Int J Med Robot. Dec

2006;2(4):350-363.

53. Lollis SS, Roberts DW. Robotic placement of a CNS ventricular reservoir for

administration of chemotherapy. Br J Neurosurg. 2009;23(5):516-520.

54. Bekelis K, Radwan TA, Desai A, Roberts DW. Frameless robotically targeted

stereotactic brain biopsy: feasibility, diagnostic yield, and safety. J Neurosurg. May

2012;116(5):1002-1006.

55. Chan F, Kassim I, Lo C, et al. Image-guided robotic neurosurgery--an in vitro and in vivo

point accuracy evaluation experimental study. Surg Neurol. Jun 2009;71(6):640-647,

discussion 647-648.

56. Frasson L, Ko SY, Turner A, Parittotokkaporn T, Vincent JF, Rodriguez y Baena F.

STING: a soft-tissue intervention and neurosurgical guide to access deep brain lesions

through curved trajectories. Proc Inst Mech Eng H. 2010;224(6):775-788.

17

436

437

438

439

440

441

442

443

444

445

446

447

448

449

450

451

452

453

454

455

456

457

458

459

460

461

462

463

464

465

466


57. Wei J, Wang T, Liu D. A vision guided hybrid robotic prototype system for stereotactic

surgery. Int J Med Robot. Dec 2011;7(4):475-481.

58. Lefranc M, Touzet G, Caron S, Maurage CA, Assaker R, Blond S. Are stereotactic

sample biopsies still of value in the modern management of pineal region tumours?

Lessons from a single-department, retrospective series. Acta Neurochir (Wien). May

2011;153(5):1111-1121; discussion 1121-1112.

59. Roser F, Tatagiba M, Maier G. Spinal robotics: current applications and future

perspectives. Neurosurgery. Jan 2013;72 Suppl 1:12-18.

60. Bast P, Popovic A, Wu T, et al. Robot- and computer-assisted craniotomy: resection

planning, implant modelling and robot safety. Int J Med Robot. Jun 2006;2(2):168-178.

61. Engelhardt M, Bast P, Jeblink N, et al. Analysis of surgical management of calvarial

tumours and first results of a newly designed robotic trepanation system. Minim Invasive

Neurosurg. Apr 2006;49(2):98-103.

62. Cunha-Cruz V, Follmann A, Popovic A, et al. Robot- and computer-assisted craniotomy

(CRANIO): from active systems to synergistic man-machine interaction. Proc Inst Mech

Eng H. 2010;224(3):441-452.

63. Le Roux PD, Das H, Esquenazi S, Kelly PJ. Robot-assisted microsurgery: a feasibility

study in the rat. Neurosurgery. Mar 2001;48(3):584-589.

64. Louw DF, Fielding T, McBeth PB, Gregoris D, Newhook P, Sutherland GR. Surgical

robotics: a review and neurosurgical prototype development. Neurosurgery. Mar

2004;54(3):525-536; discussion 536-527.

65. Pandya S, Motkoski JW, Serrano-Almeida C, Greer AD, Latour I, Sutherland GR.

Advancing neurosurgery with image-guided robotics. J Neurosurg. Dec

2009;111(6):1141-1149.

66. Morita A, Sora S, Mitsuishi M, et al. Microsurgical robotic system for the deep surgical

field: development of a prototype and feasibility studies in animal and cadaveric models.

J Neurosurg. Aug 2005;103(2):320-327.

67. Raoufi C, Goldenberg AA, Kucharczyk W. A New Hydraulically/Pneumatically

Actuated MR-Compatible Robot for MRI-Guided Neurosurgery. Paper presented at:

Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International

Conference on; 16-18 May 2008, 2008.

18

467

468

469

470

471

472

473

474

475

476

477

478

479

480

481

482

483

484

485

486

487

488

489

490

491

492

493

494

495

496

497


68. Aaronson OS, Tulipan NB, Cywes R, et al. Robot-assisted endoscopic intrauterine

myelomeningocele repair: a feasibility study. Pediatr Neurosurg. Feb 2002;36(2):85-89.

69. Ponnusamy K, Chewning S, Mohr C. Robotic approaches to the posterior spine. Spine

(Phila Pa 1976). Sep 1 2009;34(19):2104-2109.

70. Lee JY, Lega B, Bhowmick D, et al. Da Vinci Robot-assisted transoral odontoidectomy

for basilar invagination. ORL J Otorhinolaryngol Relat Spec. 2010;72(2):91-95.

71. Kim MJ, Ha Y, Yang MS, et al. Robot-assisted anterior lumbar interbody fusion (ALIF)

using retroperitoneal approach. Acta Neurochir (Wien). Apr 2010;152(4):675-679.

72. Yang MS, Kim KN, Yoon do H, Pennant W, Ha Y. Robot-assisted resection of

paraspinal Schwannoma. J Korean Med Sci. Jan 2011;26(1):150-153.

73. Yang MS, Yoon do H, Kim KN, et al. Robot-assisted anterior lumbar interbody fusion in

a Swine model in vivo test of the da vinci surgical-assisted spinal surgery system. Spine

(Phila Pa 1976). Jan 15 2011;36(2):E139-143.

74. Yang MS, Yoon TH, Yoon do H, Kim KN, Pennant W, Ha Y. Robot-assisted transoral

odontoidectomy : experiment in new minimally invasive technology, a cadaveric study. J

Korean Neurosurg Soc. Apr 2011;49(4):248-251.

75. Deboudt C, Labat JJ, Riant T, Bouchot O, Robert R, Rigaud J. Pelvic Schwannoma:

Robotic Laparoscopic Resection. Neurosurgery. Aug 15 2012.

76. Perez-Cruet MJ, Welsh RJ, Hussain NS, Begun EM, Lin J, Park P. Use of the da vinci

minimally invasive robotic system for resection of a complicated paraspinal schwannoma

with thoracic extension: case report. Neurosurgery. Sep 2012;71(1 Suppl

Operative):onsE209-eE214.

77. Hongo K, Goto T, Miyahara T, Kakizawa Y, Koyama J, Tanaka Y. Telecontrolled

micromanipulator system (NeuRobot) for minimally invasive neurosurgery. Acta

Neurochir Suppl. 2006;98:63-66.

78. Hongo K, Kobayashi S, Kakizawa Y, et al. NeuRobot: telecontrolled micromanipulator

system for minimally invasive microneurosurgery-preliminary results. Neurosurgery. Oct

2002;51(4):985-988; discussion 988.

79. Takasuna H, Goto T, Kakizawa Y, et al. Use of a micromanipulator system (NeuRobot)

in endoscopic neurosurgery. J Clin Neurosci. Nov 2012;19(11):1553-1557.

19

498

499

500

501

502

503

504

505

506

507

508

509

510

511

512

513

514

515

516

517

518

519

520

521

522

523

524

525

526

527


80. Goto T, Hongo K, Kakizawa Y, et al. Clinical application of robotic telemanipulation

system in neurosurgery. Case report. J Neurosurg. Dec 2003;99(6):1082-1084.

81. Miyata N, Kobayashi E, Kim D, et al. Micro-grasping Forceps Manipulator for MR-

Guided Neurosurgery. Proceedings of the 5th International Conference on Medical

Image Computing and Computer-Assisted Intervention-Part I: Springer-Verlag;

2002:107-113.

82. Koyama J, Hongo K, Kakizawa Y, Goto T, Kobayashi S. Endoscopic telerobotics for

neurosurgery: preliminary study for optimal distance between an object lens and a target.

Neurol Res. Jun 2002;24(4):373-376.

83. Arata J, Kenmotsu H, Takagi M, et al. Surgical bedside master console for neurosurgical

robotic system. Int J Comput Assist Radiol Surg. May 15 2012.

84. Arata J, Tada Y, Kozuka H, et al. Neurosurgical robotic system for brain tumor removal.

Int J Comput Assist Radiol Surg. May 2011;6(3):375-385.

85. Mitsuishi M, Morita A, Sugita N, et al. Master-slave robotic platform and its feasibility

study for micro-neurosurgery. Int J Med Robot. May 16 2012.

86. Hong WC, Tsai JC, Chang SD, Sorger JM. Robotic skull base surgery via supraorbital

keyhole approach: a cadaveric study. Neurosurgery. Jan 2013;72 Suppl 1:33-38.

87. Matinfar M, Baird C, Batouli A, Clatterbuck R, Kazanzides P. Robot-assisted skull base

surgery. Paper presented at: Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ

International Conference on; Oct. 29 2007-Nov. 2 2007, 2007.

88. Kazanzides P, Xia T, Baird C, et al. A cooperatively-controlled image guided robot

system for skull base surgery. Stud Health Technol Inform. 2008;132:198-203.

89. Kane G, Eggers G, Boesecke R, et al. System design of a hand-held mobile robot for

craniotomy. Med Image Comput Comput Assist Interv. 2009;12(Pt 1):402-409.

90. Follmann A, Korff A, Fuertjes T, Kunze SC, Schmieder K, Radermacher K. A novel

concept for smart trepanation. J Craniofac Surg. Jan 2012;23(1):309-314.

91. Rosenorn J, Diemer N. The risk of cerebral damage during graded brain retractor

pressure in the rat. J Neurosurg. Oct 1985;63(4):608-611.

92. Ogura K, Tachibana E, Aoshima C, Sumitomo M. New microsurgical technique for

intraparenchymal lesions of the brain: transcylinder approach. Acta Neurochir (Wien). Jul

2006;148(7):779-785; discussion 785.

20

528

529

530

531

532

533

534

535

536

537

538

539

540

541

542

543

544

545

546

547

548

549

550

551

552

553

554

555

556

557

558


93. Stummer W, Pichlmeier U, Meinel T, et al. Fluorescence-guided surgery with 5-

aminolevulinic acid for resection of malignant glioma: a randomised controlled

multicentre phase III trial. Lancet Oncol. May 2006;7(5):392-401.

94. Foersch S, Heimann A, Ayyad A, et al. Confocal laser endomicroscopy for diagnosis and

histomorphologic imaging of brain tumors in vivo. PLoS One. 2012;7(7):e41760.

95. Martirosyan NL, Cavalcanti DD, Eschbacher JM, et al. Use of in vivo near-infrared laser

confocal endomicroscopy with indocyanine green to detect the boundary of infiltrative

tumor. J Neurosurg. Dec 2011;115(6):1131-1138.

96. Marcus H, Nandi D, Darzi A, Yang GZ. Surgical Robotics Through a Keyhole: From

Today's Translational Barriers to Tomorrow's "Disappearing" Robots. IEEE Trans

Biomed Eng. Mar 2013;60(3):674-681.

21

559

560

561

562

563

564

565

566

567

568

569

570

571


Figures

Fig. 1. Evolution of cranial neurosurgery towards keyhole transcranial endoscope-assisted

microsurgical approaches. CT = Computed Tomography; MRI = Magnetic Resonance

Imaging

Fig. 2. Proposed working specifications of new robotic platforms. HD = High Definition

Fig. 3. Comparison of visualization and manipulation in present-day and proposed robot-assisted

keyhole approaches. (A) At present bimanual dissection occurs under a microscope with

a narrow field of view, using rigid instruments with limited dexterity, making

triangulation difficult. (B) In the future robotic platforms with integrated endoscopy will

allow a wider field of view, and joint-wristed instruments will improve dexterity, and

facilitate triangulation.

22

572

573

574

575

576

577

578

579

580

581

582

the application of robotics to keyhole transcranial ... · web viewrobotics in keyhole transcranial...

Documents