Design of a synthetic simulator for pediatric lumbar spine pathologies

Laboratory investigation

Restricted access

Object

Simulation has become an important tool in neurosurgical education as part of the complex process of improving residents' technical expertise while preserving patient safety. Although different simulators have already been designed for a variety of neurosurgical procedures, spine simulators are still in their infancy and, at present, there is no available simulator for lumbar spine pathologies in pediatric neurosurgery. In this paper the authors describe the peculiarities and challenges involved in developing a synthetic simulator for pediatric lumbar spine pathologies, including tethered spinal cord syndrome and open neural tube defects.

Methods

The Department of Neurosurgery of the University of Illinois at Peoria, in a joint program with the Mechanical Engineering Department of Bradley University, designed and developed a general synthetic model for simulating pediatric neurosurgical interventions on the lumbar spine. The model was designed to be composed of several sequential layers, so that each layer might closely mimic the tensile properties of the natural tissues under simulation. Additionally, a system for pressure monitoring was developed to enable precise measurements of the degree of manipulation of the spinal cord.

Results

The designed prototype successfully simulated several scenarios commonly found in pediatric neurosurgery, such as tethered spinal cord, retethered spinal cord, and fatty terminal filum, as well as meningocele, myelomeningocele, and lipomyelomeningocele. Additionally, the formulated grading system was able to account for several variables involved in the qualitative evaluation of the technical performance during the training sessions and, in association with an expert qualitative analysis of the recorded sessions, proved to be a useful feedback tool for the trainees.

Conclusions

Designing and building a synthetic simulator for pediatric lumbar spine pathologies poses a wide variety of unique challenges. According to the authors' experience, a modular system composed of separable layers that can be independently replaced significantly enhances the applicability of such a model, enabling its individualization to distinctive but interrelated pathologies. Moreover, the design of a system for pressure monitoring (as well as a general score that may be able to account for the overall technical quality of the trainee's performance) may further enhance the educational applications of a simulator of this kind so that it can be further incorporated into the neurosurgical residency curriculum for training and evaluation purposes.

Abbreviation used in this paper:PGY = Postgraduate Year.

Article Information

Address correspondence to: Tobias A. Mattei, M.D., Department of Neurosurgery, University of Illinois at Peoria, 530 NE Glen Oak, #7430, Peoria, Illinois 61637. email: tobias.a.mattei@osfhealthcare.org.

Please include this information when citing this paper: published online May 24, 2013; DOI: 10.3171/2013.4.PEDS12540.

© AANS, except where prohibited by US copyright law.

Headings

Figures

  • View in gallery

    A–C: Three-dimensional reconstructions of the anatomical structures of a pediatric lumbar spine based on the morphometric data obtained from patient-specific CT scans in DICOM format. The morphometric structure of such a virtual model was exported to a rapid prototyper that, by using an elastomeric powder, printed the 3D models. D and E: These models were further treated with 2 coats of Easy Cast resin to increase their strength and durability (D) and were finally assembled together to form the general bony and discoligamentous structures of the lumbar spine (E).

  • View in gallery

    The general structure of the torso was first computationally modeled (A and B) and, in the sequence, built into a custom retail mannequin (C), which, by possessing a range of possible size adjustments, enabled the adaption of inner structures of different sizes according to tissue modeling based on DICOM images from children of different ages. To provide prompt access to the region inside the simulator for maintenance and replacement of the modular components, a coronal cut was made in the mannequin, and hinges were placed to allow opening and closure of the simulator (D).

  • View in gallery

    Upper: Illustration of the pressure-monitoring system that was used to measure and record the pressure applied to the spinal cord, thereby reflecting its degree of manipulation. Lower: The pressure transducer was connected to a DataScope Passport, which was able to record and display the pressure values exerted on the surface of the spinal cord.

  • View in gallery

    A and B: Simulating open neural tube defects required a new paradigm in which several sequential concentric layers of different tissues (skin, subcutaneous tissue, dura mater, and neural structures) were modeled in the surface of a 3D semicircumferential space. C and D: Representation of the computational modeling of neural tube defects in a multilayer fashion. E and F: Similar to the final prototype for tethered spinal cord, the final system was planned to be connected to an inner chamber capable of detecting and measuring the pressure exerted upon its surface by transmission of forces through a water column.

  • View in gallery

    Left: Graphic representation of pressure analysis during trials performed by 2 trainees with different levels of surgical expertise (junior resident/PGY-2 [upper] and spine fellow/PGY-7 [lower]). Right: Final score according to the proposed grading system for these 2 specific training sessions.

References

1

Aggarwal RDarzi A: Innovation in surgical education—a driver for change. Surgeon 9:1 Suppl 1S30S312011

2

Agus MGiachetti AGobbetti EZanetti GZorcolo AJohn NW: Mastoidectomy simulation with combined visual and haptic feedback. Stud Health Technol Inform 85:17232002

3

Alaraj ALemole MGFinkle JHYudkowsky RWallace ALuciano C: Virtual reality training in neurosurgery: review of current status and future applications. Surg Neurol Int 2:522011

4

Almeida DBHunhevicz SBordignon KBarros EMehl AABurak Mehl AC: A model for foramen ovale puncture training: technical note. Acta Neurochir (Wien) 148:8818832006

5

Arulesan VSrimathveeravalli GKesavadas TNagathan PBaier RE: Data acquisition and development of a trocar insertion simulator using synthetic tissue models. Stud Health Technol Inform 125:25272007

6

Aubin CELabelle HChevrefils CDesroches GClin JEng AB: Preoperative planning simulator for spinal deformity surgeries. Spine (Phila Pa 1976) 33:214321522008

7

Banerjee PPLuciano CJLemole GM JrCharbel FTOh MY: Accuracy of ventriculostomy catheter placement using a head- and hand-tracked high-resolution virtual reality simulator with haptic feedback. J Neurosurg 107:5155212007

8

Beier FSismanidis EStadie ASchmieder KMänner R: An aneurysm clipping training module for the neurosurgical training simulator NeuroSim. Stud Health Technol Inform 173:42472012

9

Bernardo APreul MCZabramski JMSpetzler RF: A three-dimensional interactive virtual dissection model to simulate transpetrous surgical avenues. Neurosurgery 52:4995052003

10

Botden SMBuzink SNSchijven MPJakimowicz JJ: Augmented versus virtual reality laparoscopic simulation: what is the difference? A comparison of the ProMIS augmented reality laparoscopic simulator versus LapSim virtual reality laparoscopic simulator. World J Surg 31:7647722007

11

Browd SRZauberman JKarandikar MOjemann JGAvellino AMEllenbogen RG: A new fiber-mediated carbon dioxide laser facilitates pediatric spinal cord detethering. Technical note. J Neurosurg Pediatr 4:2802842009

12

Chou BHanda VL: Simulators and virtual reality in surgical education. Obstet Gynecol Clin North Am 33:283296viiiix2006

13

Clark JSodergren MNoonan DDarzi AYang GZ: The natural orifice simulated surgical environment (NOSsE): exploring the challenges of NOTES without the animal model. J Laparoendosc Adv Surg Tech A 19:2112142009

14

Condino SCarbone MFerrari VFaggioni LPeri AFerrari M: How to build patient-specific synthetic abdominal anatomies. An innovative approach from physical toward hybrid surgical simulators. Int J Med Robot 7:2022132011

15

De Paolis LTDe Mauro ARaczkowsky JAloisio G: Virtual model of the human brain for neurosurgical simulation. Stud Health Technol Inform 150:8118152009

16

Debes AJAggarwal RBalasundaram IJacobsen MB: Construction of an evidence-based, graduated training curriculum for D-box, a webcam-based laparoscopic basic skills trainer box. Am J Surg 203:7687752012

17

Delorme SLaroche DDiraddo RDel Maestro RF: Neuro-Touch: a physics-based virtual simulator for cranial microneurosurgery training. Neurosurgery 71:1 Suppl Operativeons32ons422012

18

Ferroli PTrignali GAcerbi FAquino DFranzini ABroggi G: Brain surgery in a stereoscopic virtual reality environment: a single institution's experience with 100 cases. Neurosurgery 67:3 Suppl Operativeons79ons842010

19

Filho FVCoelho GCavalheiro SLyra MZymberg ST: Quality assessment of a new surgical simulator for neuroendoscopic training. Neurosurg Focus 30:4E172011

20

Ganju AKahol KLee PSimonian NQuinn SJFerrara JJ: The effect of call on neurosurgery residents' skills: implications for policy regarding resident call periods. Clinical article. J Neurosurg 116:4784822012

21

González Sánchez JJEnseñat Nora JCandela Canto SRumià Arboix JCaral Pons LAOliver D: New stereoscopic virtual reality system application to cranial nerve microvascular decompression. Acta Neurochir (Wien) 152:3553602010

22

Halic TKockara SBayrak CRowe R: Mixed reality simulation of rasping procedure in artificial cervical disc replacement (ACDR) surgery. BMC Bioinformatics 11:Suppl 6S112010

23

Halvorsen FHFosse EMjåland O: Unsupervised virtual reality training may not increase laparoscopic suturing skills. Surg Laparosc Endosc Percutan Tech 21:4584612011

24

Jain MTantia OKhanna SSen BSasmal PK: Hernia endotrainer: results of training on self-designed hernia trainer box. J Laparoendosc Adv Surg Tech A 19:5355402009

25

Kahol KLeyba MJDeka MDeka VMayes SSmith M: Effect of fatigue on psychomotor and cognitive skills. Am J Surg 195:1952042008

26

Khine MLeung EMorran CMuthukumarasamy G: Homemade laparoscopic simulators for surgical trainees. Clin Teach 8:1181212011

27

Klein SWhyne CMRush RGinsberg HJ: CT-based patient-specific simulation software for pedicle screw insertion. J Spinal Disord Tech 22:5025062009

28

Larsen OVHaase JØstergaard LRHansen KVNielsen H: The Virtual Brain Project—development of a neurosurgical simulator. Stud Health Technol Inform 81:2562622001

29

Lathan CCleary KGreco R: Development and evaluation of a spine biopsy simulator. Stud Health Technol Inform 50:3753761998

30

Lee RAvan Zundert TCvan Koesveld JJvan Zundert AAStolker RJWieringa PA: Evaluation of the Mediseus epidural simulator. Anaesth Intensive Care 40:3113182012

31

Lehmann KSRitz JPMaass HCakmak HKKuehnapfel UGGermer CT: A prospective randomized study to test the transfer of basic psychomotor skills from virtual reality to physical reality in a comparable training setting. Ann Surg 241:4424492005

32

Lemole GM JrBanerjee PPLuciano CNeckrysh SCharbel FT: Virtual reality in neurosurgical education: part-task ventriculostomy simulation with dynamic visual and haptic feedback. Neurosurgery 61:1421492007

33

Luciano CJBanerjee PPBellotte BOh GMLemole M JrCharbel FT: Learning retention of thoracic pedicle screw placement using a high-resolution augmented reality simulator with haptic feedback. Neurosurgery 69:1 Suppl Operativeons14ons192011

34

Malone HRSyed ONDownes MSD'Ambrosio ALQuest DOKaiser MG: Simulation in neurosurgery: a review of computer-based simulation environments and their surgical applications. Neurosurgery 67:110511162010

35

Menovsky T: A human skull cast model for training of intracranial microneurosurgical skills. Microsurgery 20:3113132000

36

Mora VJiang DBrooks RDelorme S: A computer model of soft tissue interaction with a surgical aspirator. Med Image Comput Comput Assist Interv 12:51582009

37

Nauck ET: [On the anatomical, surgical and obstetrical schools excluding universities from the 16th to the 19th century. 2nd part of review study.]. Anat Anz 116:2022161965. (Ger)

38

Nogueira JFStamm ACLyra MBalieiro FOLeão FS: Building a real endoscopic sinus and skull-base surgery simulator. Otolaryngol Head Neck Surg 139:7277282008

39

Oishi MFukuda MHiraishi TYajima NSato YFujii Y: Interactive virtual simulation using a 3D computer graphics model for microvascular decompression surgery. Clinical article. J Neurosurg 117:5555652012

40

Okada DMde Sousa AMde Andrade Huertas RSuzuki FA: Surgical simulator for temporal bone dissection training. Braz J Otorhinolaryngol 76:5755782010

41

Palter VNGrantcharov THarvey AMacrae HM: Ex vivo technical skills training transfers to the operating room and enhances cognitive learning: a randomized controlled trial. Ann Surg 253:8868892011

42

Panait LAkkary EBell RLRoberts KEDudrick SJDuffy AJ: The role of haptic feedback in laparoscopic simulation training. J Surg Res 156:3123162009

43

Phillips NIJohn NW: Web-based surgical simulation for ventricular catheterization. Neurosurgery 46:9339372000

44

Pohlemann TCulemann UHolstein JH: Initial experience using a pelvic emergency simulator to train reduction in blood loss. Clin Orthop Relat Res 470:209821032012

45

Price JNaik VBoodhwani MBrandys THendry PLam BK: A randomized evaluation of simulation training on performance of vascular anastomosis on a high-fidelity in vivo model: the role of deliberate practice. J Thorac Cardiovasc Surg 142:4965032011

46

Ra JBKwon SMKim JKYi JKim KHPark HW: Spine needle biopsy simulator using visual and force feedback. Comput Aided Surg 7:3533632002

47

Robison RALiu CYApuzzo ML: Man, mind, and machine: the past and future of virtual reality simulation in neurologic surgery. World Neurosurg 76:4194302011

48

Rochkind SOuaknine GE: New trend in neuroscience: low-power laser effect on peripheral and central nervous system (basic science, preclinical and clinical studies). Neurol Res 14:2111992

49

Sadideen HHamaoui KSaadeddin MKneebone R: Simulators and the simulation environment: getting the balance right in simulation-based surgical education. Int J Surg 10:4584622012

50

Salkini MWDoarn CRKiehl NBroderick TJDonovan JFGaitonde K: The role of haptic feedback in laparoscopic training using the LapMentor II. J Endourol 24:991022010

51

Schebesta KHüpfl MRössler BRingl HMüller MPKimberger O: Degrees of reality: airway anatomy of high-fidelity human patient simulators and airway trainers. Anesthesiology 116:120412092012

52

Selden NROrigitano TCBurchiel KJGetch CCAnderson VCMcCartney S: A national fundamentals curriculum for neurosurgery PGY1 residents: the 2010 Society of Neurological Surgeons boot camp courses. Neurosurgery 70:9719812012

53

Sewell CMorris DBlevins NHDutta SAgrawal SBarbagli F: Providing metrics and performance feedback in a surgical simulator. Comput Aided Surg 13:63812008

54

Shamim Khan MAhmed KGavazzi AGohil RThomas LPoulsen J: Development and implementation of centralized simulation training: evaluation of feasibility, acceptability and construct validity. BJU Int 111:5185232012

55

Shen YDevarajan VEberhart RWatson MButala J: Selective tessellation algorithm for modeling interactions between surgical instruments and tissues. Stud Health Technol Inform 119:5065112006

56

Spiotta AMRasmussen PAMasaryk TJBenzel ECSchlenk R: Simulated diagnostic cerebral angiography in neurosurgical training: a pilot program. J Neurointerv Surg [epub ahead of print]2012

57

Suk PCundrle I JrHruda JVocilková LKonecny ZVlasin M: Porcine model of ruptured abdominal aortic aneurysm repair. Eur J Vasc Endovasc Surg 43:6987042012

58

Tofil NMBenner KWZinkan LAlten JVarisco BMWhite ML: Pediatric intensive care simulation course: a new paradigm in teaching. J Grad Med Educ 3:81872011

59

van Empel PJvan Rijssen LBCommandeur JPVerdam MGHuirne JAScheele F: Validation of a new box trainer-related tracking device: the TrEndo. Surg Endosc 26:234623522012

60

Van Sickle KRRitter EMMcClusky DA IIILederman ABaghai MGallagher AG: Attempted establishment of proficiency levels for laparoscopic performance on a national scale using simulation: the results from the 2004 SAGES Minimally Invasive Surgical Trainer-Virtual Reality (MISTVR) learning center study. Surg Endosc 21:5102007

61

Walker JBPerkins EHarkey HL: A novel simulation model for minimally invasive spine surgery. Neurosurgery 65:6 Suppl1881952009

62

Wang PBecker AAJones IAGlover ATBenford SDGreenhalgh CM: A virtual reality surgery simulation of cutting and retraction in neurosurgery with force-feedback. Comput Methods Programs Biomed 84:11182006

63

Wang SSXue LJing JJWang RM: Virtual reality surgical anatomy of the sphenoid sinus and adjacent structures by the transnasal approach. J Craniomaxillofac Surg 40:4944992012

64

Wanibuchi MOhtaki MFukushima TFriedman AHHoukin K: Skull base training and education using an artificial skull model created by selective laser sintering. Acta Neurochir (Wien) 152:105510602010

65

Webster RHarris MShenk RBlumenstock JGerber JBillman C: Using an approximation to the euclidean skeleton for efficient collision detection and tissue deformations in surgical simulators. Stud Health Technol Inform 111:5965982005

66

Wignall GRDenstedt JDPreminger GMCadeddu JAPearle MSSweet RM: Surgical simulation: a urological perspective. J Urol 179:169016992008

67

Zevin BAggarwal RGrantcharov TP: Simulation-based training and learning curves in laparoscopic Roux-en-Y gastric bypass. Br J Surg 99:8878952012

68

Zhou MTse SDerevianko AJones DBSchwaitzberg SDCao CG: Effect of haptic feedback in laparoscopic surgery skill acquisition. Surg Endosc 26:112811342012

69

Zymberg SVaz-Guimarães Filho FLyra ML: Neuroendoscopic training: presentation of a new real simulator. Minim Invasive Neurosurg 53:44462010

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