Minimally invasive surgery is a widely used medical technique, one of the drawbacks of which is the loss of direct sense of touch during the operation. Palpation is the use of fingertips to explore and make fast assessments of tissue morphology. Although technologies are developed to equip minimally invasive surgery tools with haptic feedback capabilities, the majority focus on tissue stiffness profiling and tool–tissue interaction force measurement. For greatly increased diagnostic capability, a magnetic resonance imaging-compatible tactile sensor design is proposed, which allows minimally invasive surgery to be performed under image guidance, combining the strong capability of magnetic resonance imaging soft tissue and intuitive palpation. The sensing unit is based on a piezoelectric sensor methodology, which conforms to the stringent mechanical and electrical design requirements imposed by the magnetic resonance environment. The sensor mechanical design and the device integration to a 0.2 Tesla open magnetic resonance imaging scanner are described, together with the device’s magnetic resonance compatibility testing. Its design limitations and potential future improvements are also discussed. A tactile sensing unit based on a piezoelectric sensor principle is proposed, which is designed for magnetic resonance imaging guided interventions.
ChinzeiKMillerK. Towards MRI guided surgical manipulator. Med Sci Monit2001; 7: 11.
2.
SchneiderCM. A robotic system for transrectal needle insertion into the prostate with integrated ultrasound. In: IEEE international conference on robotics and automation, 2004, pp.365–370.
3.
MackMJ. Minimally invasive and robotic surgery. J Am Med Ass2001; 285: 568–572.
4.
DiMaioSPSalcudeanSE. Needle insertion modeling and simulation. IEEE Trans Robotics and Automation2003; 19: 864–875.
DargahiJNajarianSNajarianK. Development and three-dimensional modelling of a biological-tissue grasper tool equipped with a tactile sensor. Can J Elec Computer Engng2005; 30: 225–230.
7.
TholeyGDesaiJP. A compact and modular laparoscopic grasper with tridirectional force measurement capability. J Med Devices2008; 2: 031001.
8.
SedaghatiRDargahiJSinghH. Design and modeling of an endoscopic piezoelectric tactile sensor. Int J Solids Structures2005; 42: 5872–5886.
9.
BicchiACanepaGDe RossiD. A sensor-based minimally invasive surgery tool for detecting tissue elastic properties. In: Proceedings of IEEE international conference on robotics and automation, 1996, pp.884–888.
10.
TavakoliMPatelRVMoallemM. Haptic interaction in robot-assisted endoscopic surgery: a sensorized end-effector. Int J Med Robotics Computer Assisted Surg2005; 1: 53–63.
11.
TrejosALJayenderJPerriMT. Robot-assisted tactile sensing for minimally invasive tumor localization. Int J Robotics Res2009; 29: 1118–1133.
12.
OttermoMVStavdahlOJohansenTA. Palpation instrument for augmented minimally invasive surgery. In: IEEE/RSJ international conference on intelligent robots and systems, 2004, pp.3960–3964.
13.
PeineWJSonJSHoweRD. A palpation system for artery localization in laparoscopic surgery. In: 1st international symposium on medical robotics and computer assisted surgery, 1994.
14.
YipMCYuenSGHoweRD. A robust uniaxial force sensor for minimally invasive surgery. IEEE Trans Biomed Engng2010; 57: 1008–1011.
15.
YaoHYHaywardVEllisRE. A tactile enhancement instrument for minimally invasive surgery. Computer Aided Surg2005; 10: 233–239.
16.
OmataSMurayamaYConstantinouCE. Real time robotic tactile sensor system for the determination of physical properties of biomaterials. Sens Actuators2004; 112: 278–285.
ShikidaMShimizuTSatoK. Active tactile sensor for detecting contact force and hardness of an object. Sensors and Actuators A2003; 103: 213–218.
19.
ShimachiSHirunyanitiwatnaSFujiwaraY. Adapter for contact force sensing of the da Vinci® robot. Int J Med Robotics Computer Assisted Surg2008; 4: 121–130.
LeeMHNichollsHR. Tactile sensing for mechatronics—a state of the art survey. Mechatronics1999; 9: 1–31.
22.
ManducaAOliphantTEDresnerMA. Magnetic resonance elastography: non-invasive mapping of tissue elasticity. Med Image Analysis2001; 5: 237–254.
23.
LiuHNoonanDPZweiriYH. The development of nonlinear viscoelastic model for the application of soft tissue identification. In: IEEE/RSJ international conference on intelligent robots and systems, San Diego, CA, 2007.
24.
SamaniALuginbuhlCPlewesDB. Magnetic resonance elastography technique for breast tissue in-vitro elasticity measurement. In: IEEE international biomedical imaging symposium, 2002, pp.931–934.
25.
ShostekSHoCKalanovicD. Artificial tactile sensing in minimally invasive surgery – a new technical approach. Minimally Invasive Therapy and Allied Technologies2006; 15: 296–304.
26.
ElhawaryHTseZTHHamedA. The case for MR-compatible robotics: a review of the state of the art. Int J Med Robotics Computer Assisted Surg2008; 4: 105–113.
27.
LiuJZDaiTHElsterTH. Simultaneous measurement of human joint force, surface electromyograms, and functional MRI-measured brain activation. J Neurosci Meth2000; 101: 49–57.
28.
KhanichehAMutoATriantafyllouC. fMRI-compatible rehabilitation hand device. J NeuroEngng Rehabilitation2006; 3.
HidlerJMbwanaJZeffiroT. MRI compatible force sensing system for real-time monitoring of wrist moments during fMRI testing. In: 9th international conference on rehabilitation robotics, ICORR, 2005, pp.212–214.
31.
ZbyszewskiDPolygerinosPSeneviratneLD. A novel MRI compatible air-cushion tactile sensor for minimally invasive surgery. In: IEEE/RSJ international conference on intelligent robots and systems, 2009, pp.2647–2652.
32.
TokunoTTadaMUmedaK. High-precision MRI-compatible force sensor with parallel plate structure. In: 2nd IEEE RAS & EMBS international conference on biomedical robotics and biomechatronics, BioRob, 2008, pp.33–38.
33.
Hao Sand FischerGS. A 3-axis optical force/torque sensor for prostate needle placement in Magnetic resonance imaging environments. In: IEEE international conference on technologies for practical robot applications, TePRA, 2009, pp.5–9.
34.
TanUXBoYGullapalliR. Design and development of a 3-axis MRI-compatible force sensor. In: IEEE international conference on robotics and automation, ICRA, 2010, pp.2586–2591.
35.
SutherlandGRMcBethPBLouwDF, NeuroArm: an mr compatible robot for microsurgery. Computer Assisted Radiology Surg2003; 1256: 504–508.
36.
KriegerASusilRCMenardC. Design of a novel MRI compatible manipulator for image guided prostate interventions. IEEE Trans Biomed Engng2005; 52: 306–313.
37.
FichtingerGKriegerASusilRC. Transrectal prostate biopsy inside closed mri scanner with remote actuation, under real-time image guidance. In: Proceedings of the 5th medical image computing and computer-assisted intervention, Tokyo, Japan, 2002, pp.91–98.
38.
StoianoviciD. A new type of motor: pneumatic step motor. IEEE/ASME Trans Mechatronics2007; 12: 98–107.
39.
TseZTHElhawaryHZivanovicA. A 3 degree of freedom MR compatible device for magic angle related in vivo experiments. ASME/IEEE Trans Mechatronics2008; 13: 316–324.
40.
GassertRMBurdetEBleulerH. MRI/fMRI-compatible robotic system with force feedback for interaction with human motion. IEEE/ASME Trans Mechatronics2006; 11: 216–224.
41.
GaneshGGassertRBurdetE. Dynamics and control of an MRI compatible master-slave system with hydrostatic transmission. In: IEEE international conference on robotics and automation, New Orleans, LA, USA, 2004, pp.1288–1294.
42.
ChinzeiKHataNJoleszFA. Surgical assist robot for the active navigation in the intraoperative MRI: hardware design issues. In: Proceedings of IEEE/RSJ international conference of intelligent robots and systems, Maui, HI, USA, 2000, pp.727–732.
43.
MasamuneKKobayashiEMasutaniY. Development of an MRI-compatible needle insertion manipulator for stereotactic neurosurgery. J Image Guided Surg1995; 1: 242–248.
44.
FlueckigerMBulloMChapuisD. fMRI compatible haptic interface actuated with traveling wave ultrasonic motor. In: Proceedings of the 40th industry applications annual conference, Provo, UT, USA, 2005, pp.2075–2082.
45.
FischerGKriegerAIordachitaI. MRI compatibility of robot actuation techniques – a comparative study medical image computing and computer-assisted intervention – MICCAI, MetaxasD. eds. Berlin/Heidelberg: Springer, 2008, pp.509–517.
46.
GassertRYamamotoAChapuisD. Actuation methods for applications in MR environments. Concepts in Magnetic Resonance Part B: Magnetic Resonance Engng2006; 29: 191–209.
47.
ShellockFG. Metallic surgical instruments for interventional MRI procedures: evaluation of MR safety. J MRI2001; 13: 152–157.
48.
ASTM, Standard test method for measurement of magnetically induced displacement force on medical devices in the magnetic resonance environment. ASTM F2052-02, 2004.
49.
ASTM-F2119, Standard Test method for evaluation of MR image artifacts from passive implants. ASTM F2119, 2007.
50.
ChinzeiKKikinisRJoleszF. MR compatibility of mechatronic devices: design criteria. In: Proceedings of 2nd international conference on medical image computing and computer-assisted interventions, Cambridge, UK, 1999, pp.1020–1031.
51.
PuangmaliPAlthoeferKSeneviratneLD. State-of-the-art in force and tactile sensing for minimally invasive surgery. IEEE Sensors J2008; 8: 371–381.
52.
PapakostasTVLimaJLoweM. A large area force sensor for smart skin applications. In: Proceedings of the 1st IEEE international conference on sensors, Florida, USA, 2002, pp.1620–1624.
53.
GassertRChapuisDBleulerH. Sensors for applications in magnetic resonance environments. IEEE/ASME Trans Mechatronics2008; 13: 335–344.
54.
HamedAMTseZTHYoungI. Applying tactile sensing with piezoelectric materials for minimally invasive surgery and magnetic-resonance-guided interventions. Proc IMechE, Part H: J Engineering in Medicine2009; 223; 99–110.
55.
BurdeaGC. Haptic feedback for virtual reality. In: Virtual reality and prototyping workshop, 1999.
56.
SrinivasanMABeauregardGLBrockDL. The impact of visual information on the haptic perception of stiffness in virtual environments. In: Proceedings of the ASME dynamics systems and control division, Georgia, USA, 1996, pp.555–559.
57.
DarioPBergamascoM. An advanced robot system for automated diagnostic tasks through palpation. IEEE Trans Biomed Engng1988; 35: 118–126.
58.
DargahiJParameswaranMPayandehS. A micromachined piezoelectric tactile sensor for an endoscopic grasper-theory, fabrication and experiments. J Microelectromech Sys2000; 9: 329–335.
59.
TseZTHJanssenHHamedA. Magnetic resonance elastography hardware design: a survey. Proc IMechE, Part H: J Engineering in Medicine2009; 223: 497–514.
60.
ElhawaryHZivanovicADaviesB. A review of magnetic resonance imaging compatible manipulators in surgery. Proc IMechE, Part H: J Engineering in Medicine2006; 220: 413–424.
61.
BurdetEGassertRGowrishankarG. fMRI compatible hapticinterfaces to investigate human motor control. In: 9th international symposium on experimental robotics, Berlin, 2006, pp.25–34.
62.
BottomleyPAKumarAEdelsteinWA. Designing passive MRI-safe implantable conducting leads with electrodes. Med Physics2010; 37: 3828–3843.
63.
TholeyGDesaiJPCastellanosAE. Force feedback plays a significant role in minimally invasive surgery. Ann Surg2005; 241: 102–109.
64.
OttermoMVOvstedalMLangoT. The role of tactile feedback in laparoscopic surgery. Surg Laparosc Endosc Percutan Tech2006; 16: 390–400.
