The force pyramid: a spatial analysis of force application during virtual reality brain tumor resection

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  • 1 Neurosurgical Simulation Research and Training Centre, Department of Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada;
  • 2 Department of Biomedical Engineering, AmirKabir University of Technology (Tehran Polytechnic), Tehran, Iran;
  • 3 National Neuroscience Institute, Department of Neurosurgery, King Fahad Medical City, Riyadh;
  • 4 Department of Surgery, Faculty of Medicine, Umm Al-Qura University, Makkah Almukarramah;
  • 5 Division of Neurosurgery, Faculty of Medicine, University of Jeddah; and
  • 6 Division of Neurosurgery, Department of Surgery, Faculty of Medicine and
  • 7 Clinical Skill and Simulation Center, King Abdulaziz University, Jeddah, Saudi Arabia
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OBJECTIVE

Virtual reality simulators allow development of novel methods to analyze neurosurgical performance. The concept of a force pyramid is introduced as a Tier 3 metric with the ability to provide visual and spatial analysis of 3D force application by any instrument used during simulated tumor resection. This study was designed to answer 3 questions: 1) Do study groups have distinct force pyramids? 2) Do handedness and ergonomics influence force pyramid structure? 3) Are force pyramids dependent on the visual and haptic characteristics of simulated tumors?

METHODS

Using a virtual reality simulator, NeuroVR (formerly NeuroTouch), ultrasonic aspirator force application was continually assessed during resection of simulated brain tumors by neurosurgeons, residents, and medical students. The participants performed simulated resections of 18 simulated brain tumors with different visual and haptic characteristics. The raw data, namely, coordinates of the instrument tip as well as contact force values, were collected by the simulator. To provide a visual and qualitative spatial analysis of forces, the authors created a graph, called a force pyramid, representing force sum along the z-coordinate for different xy coordinates of the tool tip.

RESULTS

Sixteen neurosurgeons, 15 residents, and 84 medical students participated in the study. Neurosurgeon, resident and medical student groups displayed easily distinguishable 3D “force pyramid fingerprints.” Neurosurgeons had the lowest force pyramids, indicating application of the lowest forces, followed by resident and medical student groups. Handedness, ergonomics, and visual and haptic tumor characteristics resulted in distinct well-defined 3D force pyramid patterns.

CONCLUSIONS

Force pyramid fingerprints provide 3D spatial assessment displays of instrument force application during simulated tumor resection. Neurosurgeon force utilization and ergonomic data form a basis for understanding and modulating resident force application and improving patient safety during tumor resection.

OBJECTIVE

Virtual reality simulators allow development of novel methods to analyze neurosurgical performance. The concept of a force pyramid is introduced as a Tier 3 metric with the ability to provide visual and spatial analysis of 3D force application by any instrument used during simulated tumor resection. This study was designed to answer 3 questions: 1) Do study groups have distinct force pyramids? 2) Do handedness and ergonomics influence force pyramid structure? 3) Are force pyramids dependent on the visual and haptic characteristics of simulated tumors?

METHODS

Using a virtual reality simulator, NeuroVR (formerly NeuroTouch), ultrasonic aspirator force application was continually assessed during resection of simulated brain tumors by neurosurgeons, residents, and medical students. The participants performed simulated resections of 18 simulated brain tumors with different visual and haptic characteristics. The raw data, namely, coordinates of the instrument tip as well as contact force values, were collected by the simulator. To provide a visual and qualitative spatial analysis of forces, the authors created a graph, called a force pyramid, representing force sum along the z-coordinate for different xy coordinates of the tool tip.

RESULTS

Sixteen neurosurgeons, 15 residents, and 84 medical students participated in the study. Neurosurgeon, resident and medical student groups displayed easily distinguishable 3D “force pyramid fingerprints.” Neurosurgeons had the lowest force pyramids, indicating application of the lowest forces, followed by resident and medical student groups. Handedness, ergonomics, and visual and haptic tumor characteristics resulted in distinct well-defined 3D force pyramid patterns.

CONCLUSIONS

Force pyramid fingerprints provide 3D spatial assessment displays of instrument force application during simulated tumor resection. Neurosurgeon force utilization and ergonomic data form a basis for understanding and modulating resident force application and improving patient safety during tumor resection.

A neurosurgeon has no means of continuously assessing the forces he or she, or a resident being supervised, is applying with surgical instruments while removing a patient's tumor. The improper application of excessive force and/or the utilization of too much force over long time periods can result in brain injury, bleeding, and other complications.1–7 In a previous study, utilizing the NeuroTouch/NeuroVR simulator, our group has outlined Tier 1, Tier 2, and Tier 3 metrics in the assessment of neurosurgical performance during the removal of a series of simulated tumors with distinct haptic and color characteristics.6 A series of proficiency performance benchmarks for these procedures was also developed.1,2 Tier 1, Tier 2, and advanced Tier 2 metrics have been used in a series of studies to demonstrate face, content, and construct validity of the NeuroTouch/NeuroVR platform.1–7,14 The concept of the force pyramid was introduced as one of the Tier 3 metrics with the ability to display and assess the forces applied by any virtual instrument in any tumor region during the resection of 3D tumors.6 A number of studies have equipped neurosurgery tools with force sensors or used robotic tools to make force measurements.13,17–19,21–23 None of these studies provide a 3D spatial representation of the forces applied in all tumor regions. Force pyramids provide visual and spatial analysis of all these force values and insights into how hand position ergonomics modulate instrument force application. Comparing force pyramids between groups sheds light on the differences and geometry of force application between “expert” and “novice” operators. The results could be useful in validation and further development of neurosurgical simulators, in surgical education, and in robotic surgery.

This study was designed to answer 3 questions: 1) Do study groups have distinct force pyramids? 2) Do handedness and ergonomics influence force pyramid structure? 3) Are force pyramids dependent on the visual and haptic characteristics of simulated tumors?

Methods

Subjects

Eighty-four medical students and 15 residents (9 junior residents [PGY 1–3] and 6 senior residents [PGY 4–6]), all from McGill University, along with 16 board-certified neurosurgeons from 3 institutions participated in the study. There was no financial or other compensation offered for participation in the study. All participants in the study signed an approved McGill University Health Centre Research Ethics Board consent form.

NeuroVR Simulator

The previously described NeuroTouch (now known as NeuroVR) platform was used to conduct this study.1–7,10,11,14,16,20,26 Tumor removal was accomplished with a simulated virtual ultrasonic aspirator held in the participant's dominant hand (Fig. 1A).1,2,6

FIG. 1.
FIG. 1.

A: Operator hand position holding haptic instrument for simulated ultrasonic aspirator. B: Six simulated tumor scenarios with tumor color and sequence. In Scenarios 1–3, the 3 tumors in each scenario represent 3 different degrees of stiffness, while the visual appearance of the tumor varies by scenario. In Scenarios 4–6, all 3 tumor appearances are represented in each scenario, and the stiffness varies by scenario. In Scenarios 4–6 each scenario includes 3 tumors with different appearances by the same stiffness, soft in Scenario 4, medium stiffness in Scenario 5, and hard in Scenario 6. (For details see Simulation Scenarios in Methods.) C: Lateral view of the brain tumor geometry and elliptical shape used in each scenario demonstrating the 3 identical tumors, tumor buried underneath simulated “normal' tissue and the top views of the R1, R2, and R3 regions. D: Top view of the regions of tumors divided into Quadrants Q1–Q4. Figure is available in color online only.

Simulation Scenarios

To address the study questions, a series of 6 simulated brain tumor scenarios were employed (Fig. 1B and C). These scenarios were developed by our group in previous studies,1,2,6 and each scenario involved 3 tumors of identical ellipsoidal shape with different color and stiffness cues. In Scenarios 1 through 3, the 3 tumors within each individual scenario had the same visual color appearance, black in Scenario 1, glioma-like in Scenario 2, and white in Scenario 3. However, in each of these scenarios the 3 tumors had different stiffness, namely “soft” (Young's modulus: 3 kPa), “medium” (Young's modulus: 9 kPa), and “hard” (Young's modulus: 15 kPa). Scenarios 4 through 6 each contained 3 tumors with the same stiffness, soft in Scenario 4, medium stiffness in Scenario 5, and hard in Scenario 6. Each of these 3 scenarios contained a black, a glioma-like, and a white tumor as can be seen in Fig. 1B. The stiffness of the background tissue in all tumor scenarios (simulated white matter) was similar to that of a soft tumor (Young's modulus: 3 kPa).

Each participant was specifically instructed verbally and in written instructions that the goal of the simulation was to remove each tumor utilizing the simulated ultrasonic aspirator with minimal removal of the background tissue, which represented “normal” brain tissue. In each scenario, the operator used the simulated ultrasonic aspirator in the dominant hand to remove the tumors, in a predefined sequence, one at a time (Fig. 1B and 1C).1,2,6 For left-handed participants, the left tool and haptic device were activated on the simulator. The aspirator intensity was fixed at a constant value to standardize this component of the study. A practice scenario familiarized the participants with the task. Data from this scenario were excluded from the analysis. Each participant was given 3 minutes to remove each tumor with a 1-minute mandatory rest period between the tasks.

Spatial Analysis of Force

Figure 1C demonstrates the 3D geometry of each tumor in each scenario.6 The ellipsoidal tumor shape extended underneath the “normal” brain tissue surface, creating a challenge for the operator to resect the lesion in this tumor–normal tissue interface.1,2,6 The projection of the visible segment of the tumor on the “normal” tissue plane is denoted as Region R1 and contains the bulk of the tumor tissue, as outlined previously.6 The projection of the tumor segments that extend underneath the normal brain tissue is denoted as Region R2, and the operator must remove this tumor component, resulting in deformation of both tumor and surrounding tissue similar to that seen during human brain tumor operations. The projection of the “normal” brain tissue surrounding the brain tumor is denoted as Region R3.

To provide a visual and qualitative spatial analysis of forces, one can create a graph representing force sum along the z-coordinate for different xy coordinates of the tool tip. Normally, recording the position of the tool tip at various instances of time creates a cloud of data points that are distributed in space in a nonuniform fashion. Therefore, to create the above-mentioned graph, a 3D interpolation is performed to assign force values to different grid points in the xyz space. Then the force sum is calculated along the z-axis to generate a force sum for various xy coordinates on the xy plane. To analyze the performance of a participating group as a whole, a force average was calculated for all the individuals in the group. Since the generated force graphs generally resemble pyramids, we called them force pyramids.6

To extract the zones where high forces are applied we assessed a number of thresholds above 50% of the highest force applied for each group. Since all of these applied force thresholds were qualitatively similar we report only those above each group's 70% threshold. However, the 70% thresholds were always lowest for the neurosurgeon group, followed by the resident group and then the medical student group. All zones in which forces exceed this 70% threshold were segmented out. Since all tumors are round from the top view, this vantage point was used to compare the 70% threshold of high force application for all 3 groups.

Results

Figure 2 demonstrates examples of force pyramids for a medical student, a resident, and a neurosurgeon, obtained after resecting a black hard tumor. Each pyramid is coupled with a top view to provide a color-coded visualization of the applied force values in all tumor regions. In the top view, Region R1, R2, and R3 (as defined in Fig. 1C) can be identified by the area within the smaller dashed circle, the area between the 2 dashed circles, and the area outside the larger dashed circle, respectively. In these examples, the medical student has applied higher forces more frequently and in all 3 regions in comparison with the resident and neurosurgeon. The resident applied higher forces than the neurosurgeon, predominately in the R1 and R2 regions.

FIG. 2.
FIG. 2.

Examples of force pyramids (3D and top views) for a medical student, resident, and neurosurgeon obtained for the resection of a black hard tumor, demonstrating applied forces in Newtons (N) in the xy and xz coordinates. The color map on the right outlines the colors corresponding to different forces in Newtons. Figure is available in color online only.

The 2 left columns of Fig. 3 provide a comparison of the force pyramids and their top views for the 3 participating groups. Each pyramid represents, collectively, the performance of all individuals in each group and for all 18 tumors. These pyramids have a smoother appearance in comparison with those in Fig. 2, since they contain average forces for all individuals and all tumors. Medical students used higher forces than the other groups, and they had multiple force peak regions. Residents used higher forces than neurosurgeons, and their dominate peak force regions were localized to the right lower quadrant. To further assess the intratumor spatial distribution (regionality) of maximum force application, the force pyramids from the top view were divided into 4 quadrants (Q1–4) moving counterclockwise (Fig. 1D). When we applied the 70% threshold of the pyramid maximum and extracted all zones with higher maximum force application, we obtained the crescent-like maximum force application regions outlined in the third column of Fig. 3. All group maximum force application crescent regions were predominately localized in the Q4 quadrant (3 to 6 o'clock), with smaller crescents in the lower Q3 quadrant of the tumor (6 to 8 o'clock).

FIG. 3.
FIG. 3.

Force pyramids (3D and top views) for the medical student (n = 84), resident (n = 15), and neurosurgeon (n = 16) groups for all 18 tumors. Each pyramid represents, collectively, the applied forces in Newtons in the xy and xz coordinates of all individuals in each group for all of the tumors. The color map on the right outlines the colors corresponding to different forces in Newtons. Figure is available in color online only.

Our hypothesis for the appearance of the maximum force application crescents observed was related to the ergonomic human factor of operator hand position during tumor resection. The majority of participants were right handed and needed to continually adjust their right hand holding the aspirator by beginning to flex their wrist to remove tumor in the Q3 quadrant and then further flexing and internally rotating the wrist to resect tumor from the rim region of the Q4 quadrant (Fig. 4B). Alternately, left-handed individuals flexed their wrist to remove tumor in the Q4 quadrant and then further flexed their wrist in the Q3 quadrant to accomplish tumor resection (Fig. 4A). This ergonomically constrained hand position results in the inability of the dominant hand to control applied forces and/or receive appropriate force application sensory feedback to modulate force application in the Q4 quadrant for right-handed and in the Q3 quadrant for left-handed operators. To test this hypothesis, we separated the groups into right-and left-handed participants and generated their respective pyramids. If our hypothesis is correct, right-handed operators will have their maximum applied force crescents predominately in the Q4 quadrant and left-handed operators in the Q3 quadrants. Figure 5 (upper) demonstrates the pyramids for all right-handed (n = 107) and left-handed (n = 8) individuals from all groups. The maximum applied force crescent for the right-handed participants remains in the Q4 quadrant, whereas for the left-handed group the crescent lies predominately in the Q3 quadrant, consistent with our hypothesis. To further refine our data set we outlined the pyramids utilizing right-handed (n = 30) and left-handed (n = 3) neurosurgeon and resident groups (Fig. 5 lower). Although the numbers were small, the pyramids and crescents for these groups were consistent with our hypothesis.

FIG. 4.
FIG. 4.

A: Ergonomic hand positions of a left-handed operator resecting simulated tumor in the Q1–Q4 quadrants. B: Ergonomic hand positions of a right-handed operator resecting simulated tumor in the Q1–Q4 quadrants. Figure is available in color online only.

FIG. 5.
FIG. 5.

Upper: Force pyramids (3D and top views) for all right-handed (n = 107) and left-handed (n = 8) individuals from all groups. Each pyramid represents, collectively, the applied forces in Newtons (N) in the xy and xz planes. The maximum applied force crescent for the right-handed participants is in the Q4 quadrant, whereas for the left-handed group the corresponding crescent is predominately in the Q3 quadrant. Lower: The pyramid data set utilizing right-handed (n = 30) and left-handed (n = 3) neurosurgeons and residents. The color map on the right outlines the colors corresponding to different forces in Newtons. Figure is available in color online only.

Figure 6 demonstrates the pyramids and their top views for groups resecting black, glioma-like, and white tumors. All groups applied higher forces to remove black tumors, followed by glioma-like and then white tumors. The reason(s) black tumors are more difficult to remove are unclear but these findings are consistent with our previous studies.4,6 One hypothesis for this result is that operators may have had difficulty estimating tool tip to tumor surface spacing due to the similar coloration of the black aspirator tool tip and black tumor, and this may result in application of higher tumor forces to locate the tumor in our virtual reality environment. The location of the maximum applied force crescents and intratumor 3D regionality were consistent with our previous findings (Fig. 3).

FIG. 6.
FIG. 6.

Force pyramids (3D and top views) for medical student, resident, and neurosurgeon groups for resection of simulated tumors of varying appearance. Each pyramid represents, collectively, the applied forces in Newtons (N) in the xy and xz coordinates of all individuals in each group for the 6 black, glioma-like, and white tumors. The color map on the right outlines the colors corresponding to different forces in Newtons. Figure is available in color online only.

Figure 7 demonstrates the pyramids and their top views for groups resecting the tumors of the different degrees of stiffness—soft, medium, and hard. As expected, each group applied higher forces to remove hard tumors and smaller forces to remove medium and soft tumors, as seen in our previous studies.4,6 In each stiffness category, the tallest and shortest pyramids correspond to the medical students and the staff, respectively, and maximum applied force crescents and intratumor 3D regionality were similar to our previous results.

FIG. 7.
FIG. 7.

Force pyramids (3D view and top views) for medical student, resident, and neurosurgeon groups for resection of simulated tumors of varying stiffness. Each pyramid represents, collectively, the applied forces in Newtons (N) in the xy and xz coordinates of all individuals in each group for the 6 soft, medium, and hard tumors. The color map on the right outlines the colors corresponding to different forces in Newtons. Figure is available in color online only.

Discussion

In this study we investigated whether a novel Tier 3 metric called force pyramids would outline differences among the groups assessed, whether participant handedness and ergonomics influenced force pyramid shape, and whether the force pyramids could be modulated by the visual and tactile characteristics of simulated tumors. The data set selected for this study has previously been used by our group to develop novel metrics and proficiency-based benchmarks for the resection of simulated tumors.1,2,6 We have now employed this same data set for a separate purpose: to explore the concept of force pyramids during virtual tumor resection. This investigation is unique in utilizing force pyramids, derived from the NeuroVR virtual reality platform, to assess “expert” and “novice” performance during the resection of a wide variety of different simulated tumors.

Variability of Force Pyramids Among Participant Groups

Figure 2 outlines some of the variations in the force pyramids when individual participants are compared. Differences can be characterized into 4 major groups.6 These include maximum applied force used, in which tumor region forces are applied, the specific forces applied at the tumor–normal tissue interface, and whether forces are applied outside of the tumor in the “normal” simulated area. In totality each person's force information can be considered as that operator's “force pyramid fingerprint,” characterizing that individual's force utilization during the resection of a specific simulated tumor. Whether this specific force pyramid fingerprint is reproduced during the repeated resection of the same simulated tumor is presently being investigated.

Neurosurgeon, resident, and medical students groups displayed easily distinguishable 3D force pyramid fingerprints. The medical student force pyramid had a major central peak of force application with multiple other peaks in the right and left lower quadrant areas (Q4 and Q3, respectively) of the simulated tumors. The resident and neurosurgeon peaks were predominately located in the Q4 quadrant, outlining a crescent-like shape. Performance in these study cohorts segregated into low, middle, and high force pyramids related to neurosurgeon, resident, and medical student groups, respectively. In a previous study involving the same cohorts, the mean value (± SD) of the maximum force applied was 0.15 ± 0.05 N (range 0.09–0.28 N) for neurosurgeons, 0.17 ± 0.08 N (range 0.10–0.42 N) for residents, and 0.27 ± 0.12 (range 0.07–0.83 N) for medical students.1,2 In a brain cadaveric study utilizing vibrotactile feedback, a maximum force of 0.3 N was set as a warning alert that too much force was being applied.19 These results reported by Payne et al.19 and others by Bergin et al.8 are similar to those seen in our studies.1,2, Employing bipolar forceps to perform blunt nondamaging dissection around the circle of Willis in robot-assisted surgery, the maximum force found was 2.04 N.18 A lower peak force of 1.35 N was measured in another study when bipolar forceps were used to do cadaveric brain dissections.13 In a subsequent study by this group involving robot-assisted surgery, the maximum forces used by 2 surgical instruments, bipolar forceps and a suction device, during the resection of 4 human tumors by a single surgeon was 1.86 N.21 The majority of the forces measured in the neurosurgeon group in our study, irrespective of the visual and tactile characteristics of the simulated tumors, were below the values reported in the studies from Sutherland's group13,17,18,21 and were more consistent with findings reported by other groups.9,19 The differences in these results may relate to different platforms (simulation versus robot assisted), instruments tested, (bipolar forceps versus aspirator), measurement techniques, and the impact of cadaveric and human tissues (i.e., meningiomas) on force application. Our previous simulation studies and present studies have demonstrated that increasing tumor stiffness significantly increases maximum applied forces, suggesting that when a neurosurgical procedure involves stiffer tumors, increased forces are employed, whether the procedure is performed with robot assistance or not, and this may be one reason for the differences measured.

Influence of Participant Handedness and Ergonomics on Force Pyramid Structure

In our initial assessment of force pyramids, the majority of the instances of maximum force application by residents and consultants utilizing a simulated ultrasonic aspirator involved the Q4 tumor quadrant in a crescent-like shape adjacent to the tumor–normal tissue interface. We tested the concept that participant handedness and hand ergonomics were responsible for these results. The results support the concept that right-handed residents and neurosurgeons apply maximum forces in the Q4 quadrant, whereas left-handed residents and neurosurgeons apply these forces in the Q3 quadrant. Medical students have a much higher maximum force application and larger Q3 and Q4 regionality of force application, which suggests that force modulation is a learned behavior that undergoes refinement during residency, as we have shown previously.1 If these results can be extrapolated to resident education during human operations, care should be taken when instruments like the ultrasonic aspirator are first being used by students. It may also be important for operators to be aware that—because of their hand-position ergonomics—the Q4 and Q3 quadrants of tumor-brain interspace may be particularly at risk during procedures performed by right- and left-handed individuals, respectively. Further studies are necessary to define the best ergonomic hand positions, body dynamics, and other human and machine factors for safe tumor resection. How these data can be incorporated into other surgical procedures, such as aneurysm clipping and vascular anastomosis as well as future robot development, should be explored.

Force Pyramids are Dependent on Tumor Visual and Haptic Characteristics

In previous studies, our group has demonstrated how changes in the visual and tactile characteristics of simulated tumors influence bimanual psychomotor performance.3,4,6 In the present study, altering the visual and tactile components of tumors resulted in well-defined 3D force pyramid patterns consistent with these results. The appearance of maximum force application crescents in the Q4 and Q3 quadrants was consistent in all tumors assessed, confirming the importance of the ergonomics of hand position during tumor resection.

Strengths and Limitations of the Study

NeuroVR technology has allowed us to address the 3 questions proposed by this study and provided insights into how experts (neurosurgeons) and novices (residents) actually perform simulated brain tumor operations with different visual and tactile characteristics. Our results are consistent with the concept that the novel Tier 3 metric force pyramid provides information on expert surgical performance and may be useful in defining a neurosurgeon's force pyramid fingerprint. Further studies are ongoing to assess whether this force pyramid fingerprint is a characteristic of an individual neurosurgeon's expert bimanual psychomotor behavior in tumor resection and how this fingerprint is modulated during residency training.

One should be knowledgeable about the underlying issues, problems, and challenges in virtual reality simulation studies in interpreting our results. First, for tumor resection, operators used only a simulated ultrasonic aspirator in the dominant hand, which is not representative of the multiple interactive bimanual psychomotor skills used during actual tumor resections in patients.12 We are currently assessing whether the individual force pyramids of instruments held in the dominant (aspirator, bipolar forceps) and the nondominant hand (suction device) can be overlapped and combined, providing a 3D total force map outlining all forces applied by the used instruments in all tumor-related geometries. These more accurate force data should provide an improved 3D representation of all forces applied during simulated tumor resection. The ability to examine these overlapping force pyramids should not only allow a comparison of expert and novice operator performance but also provide insights into the ergonomic geometry of force application between right- and left-handed participants. The relationship of force application as outlined by the force pyramids and surrounding simulated white matter preservation and removal (tissue injury) is also being examined by our group. The correlation between these pyramid data sets relating increased force application in the tumor cavity by instruments used by a surgeon with clinical injury to surrounding tissues should provide further information pertaining to the force application–tissue injury relationship. Second, the short task duration, color, ellipsoidal shape, and stiffness of the simulated tumors may not discriminate performance among participants. Although individuals resected 18 tumors, this included 9 sets of 2, each with different characteristics, limiting the ability of this study to assess the impact of repetition learning on force pyramid structure. A more realistic tumor scenario involving repeated resections of a complex 3D mass with simulated bleeding adjacent to the motor strip is being used to address these issues. Third, the utilization of medical students and residents from a single institution may limit the application of these results to other centers. However, this study involved 16 neurosurgeons from 3 different institutions with different areas of expertise, which should be more representative of the general neurosurgical population.1 We are presently serially tracking and videotaping residents during training until and after graduation to further understand the sequence of development and modulation of their individual force pyramids.9 The assessment of force pyramid usefulness in other simulated neurosurgical operations and by other surgical specialties may increase the range of application of this type of analysis.20,24,25 A number of publications have reviewed how virtual reality simulators may be used to augment neurosurgical training and resident selection.3,15,26 Although this study focused on only one metric, the force pyramid, without the ability to use the information that simulators such as NeuroVR can provide to enhance resident operating room performance, their use will be limited. As with any other training and/or assessment tool, rigorous efforts are necessary to provide evidence for validation and effectiveness of a virtual reality system over traditional educational methods.3,14,15

Conclusions

Force pyramids derived from virtual reality simulators such as NeuroVR can assess and display a spatial assessment of applied forces during simulated brain tumor resections. Such information provides insights into individual neurosurgeon and resident force pyramid fingerprints and may begin to form the basis for modulating resident performance and improving patient safety during tumor resection.

Acknowledgments

We thank all the medical students, residents, and neurosurgeons from multiple institutions who participated in these studies. We would like to particularly thank Jawad Fares, Marta Baggiani, Amy Haddlesey, Sara Venturini, and Aysha Alsahlawi for their help with this study. We would also like to thank Dr. Robert DiRaddo, Group Leader, Simulation, Life Sciences Division, National Research Council of Canada at Boucherville and his team, including Denis Laroche, Valérie Pazos, Nusrat Choudhury, Patricia Debergue, and Linda Pecora for their support in the development of the scenarios used in these studies and all the members of the Simulation, Life Sciences Division, National Research Council of Canada.

Disclosures

This work was supported by the Di Giovanni Foundation, the Montreal English School Board, the B-Strong Foundation, the Colannini Foundation, and the Montreal Neurological Institute and Hospital.

Author Contributions

Conception and design: Azarnoush, Al Zhrani, Winkler-Schwartz, Alotaibi, Del Maestro. Acquisition of data: Azarnoush, Sawaya, Al Zhrani, Winkler-Schwartz, Alotaibi, Bajunaid, Del Maestro. Analysis and interpretation of data: Azarnoush, Siar, Sawaya, Al Zhrani, Winkler-Schwartz, Alotaibi, Bajunaid, Marwa, Sabbagh, Del Maestro. Drafting the article: Azarnoush, Sawaya, Del Maestro. Critically revising the article: Azarnoush, Sawaya, Bugdadi, Bajunaid, Marwa, Sabbagh, Del Maestro. Reviewed submitted version of manuscript: Azarnoush, Sawaya, Al Zhrani, Winkler-Schwartz, Alotaibi, Bugdadi, Bajunaid, Marwa, Sabbagh, Del Maestro. Approved the final version of the manuscript on behalf of all authors: Azarnoush. Administrative/technical/material support: Del Maestro. Study supervision: Del Maestro.

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  • 14

    Gélinas-Phaneuf N, Choudhury N, Al-Habib AR, Cabral A, Nadeau E, Mora V, : Assessing performance in brain tumor resection using a novel virtual reality simulator. Int J CARS 9:19, 2014

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15

    Gélinas-Phaneuf N, Del Maestro RF: Surgical expertise in neurosurgery: integrating theory into practice. Neurosurgery 73:Suppl 1 3038, 2013

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16

    Holloway T, Lorsch ZS, Chary MA, Sobotka S, Moore MM, Costa AB, : Operator experience determines performance in a simulated computer-based brain tumor resection task. Int J CARS 10:18531862, 2015

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17

    Maddahi Y, Gan LS, Zareinia K, Lama S, Sepehri N, Sutherland GR: Quantifying workspace and forces of surgical dissection during robot-assisted neurosurgery. Int J Med Robot [epub ahead of print] 2015

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18

    Marcus HJ, Zareinia K, Gan LS, Yang FW, Lama S, Yang GZ, : Forces exerted during microneurosurgery: a cadaver study. Int J Med Robot 10:251256, 2014

  • 19

    Payne CJ, Marcus HJ, Yang GZ: A smart haptic hand-held device for neurosurgical microdissection. Ann Biomed Eng 43:21852195, 2015

  • 20

    Rosseau G, Bailes J, del Maestro R, Cabral A, Choudhury N, Comas O, : The development of a virtual simulator for training neurosurgeons to perform and perfect endoscopic endonasal transsphenoidal surgery. Neurosurgery 73:Suppl 1 8593, 2013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Sutherland GR, Maddahi Y, Gan LS, Lama S, Zareinia K: Robotics in the neurosurgical treatment of glioma. Surg Neurol Int 6:1 Suppl 1 S1S8, 2015

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22

    Trejos AL, Jayaraman S, Patel RV, Naish MD, Schlachta CM: Force sensing in natural orifice transluminal endoscopic surgery. Surg Endosc 25:186192, 2011

  • 23

    Trejos AL, Patel RV, Naish MD: Force sensing and its application in minimally invasive surgery and therapy: a survey. Proc Inst Mech Eng C J Mech Eng Sci 224:14351454, 2010

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 24

    Varshney R, Frenkiel S, Nguyen LH, Young M, Del Maestro R, Zeitouni A, : Development of the McGill simulator for endoscopic sinus surgery: a new high-fidelity virtual reality simulator for endoscopic sinus surgery. Am J Rhinol Allergy 28:330334, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25

    Varshney R, Frenkiel S, Nguyen LH, Young M, Del Maestro R, Zeitouni A, : The McGill simulator for endoscopic sinus surgery (MSESS): a validation study. J Otolaryngol Head Neck Surg 43:40, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26

    Winkler-Schwartz A, Bajunaid K, Mullah MAS, Marwa I, Alotaibi FE, Fares J, : Bimanual psychomotor performance in neurosurgical resident applicants assessed using NeuroTouch, a virtual reality simulator. J Surg Educ [epub ahead of print] 2016

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation

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Contributor Notes

Correspondence Hamed Azarnoush, Neurosurgical Simulation Research and Training Centre, Department of Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, 3801 University, Rm. W201, Montreal, Quebec, H3A 2B4, Canada. email: hamed.azarnoush@mail.mcgill.ca.

INCLUDE WHEN CITING Published online September 30, 2016; DOI: 10.3171/2016.7.JNS16322.

Disclosures This work was supported by the Di Giovanni Foundation, the Montreal English School Board, the B-Strong Foundation, the Colannini Foundation, and the Montreal Neurological Institute and Hospital.

  • View in gallery

    A: Operator hand position holding haptic instrument for simulated ultrasonic aspirator. B: Six simulated tumor scenarios with tumor color and sequence. In Scenarios 1–3, the 3 tumors in each scenario represent 3 different degrees of stiffness, while the visual appearance of the tumor varies by scenario. In Scenarios 4–6, all 3 tumor appearances are represented in each scenario, and the stiffness varies by scenario. In Scenarios 4–6 each scenario includes 3 tumors with different appearances by the same stiffness, soft in Scenario 4, medium stiffness in Scenario 5, and hard in Scenario 6. (For details see Simulation Scenarios in Methods.) C: Lateral view of the brain tumor geometry and elliptical shape used in each scenario demonstrating the 3 identical tumors, tumor buried underneath simulated “normal' tissue and the top views of the R1, R2, and R3 regions. D: Top view of the regions of tumors divided into Quadrants Q1–Q4. Figure is available in color online only.

  • View in gallery

    Examples of force pyramids (3D and top views) for a medical student, resident, and neurosurgeon obtained for the resection of a black hard tumor, demonstrating applied forces in Newtons (N) in the xy and xz coordinates. The color map on the right outlines the colors corresponding to different forces in Newtons. Figure is available in color online only.

  • View in gallery

    Force pyramids (3D and top views) for the medical student (n = 84), resident (n = 15), and neurosurgeon (n = 16) groups for all 18 tumors. Each pyramid represents, collectively, the applied forces in Newtons in the xy and xz coordinates of all individuals in each group for all of the tumors. The color map on the right outlines the colors corresponding to different forces in Newtons. Figure is available in color online only.

  • View in gallery

    A: Ergonomic hand positions of a left-handed operator resecting simulated tumor in the Q1–Q4 quadrants. B: Ergonomic hand positions of a right-handed operator resecting simulated tumor in the Q1–Q4 quadrants. Figure is available in color online only.

  • View in gallery

    Upper: Force pyramids (3D and top views) for all right-handed (n = 107) and left-handed (n = 8) individuals from all groups. Each pyramid represents, collectively, the applied forces in Newtons (N) in the xy and xz planes. The maximum applied force crescent for the right-handed participants is in the Q4 quadrant, whereas for the left-handed group the corresponding crescent is predominately in the Q3 quadrant. Lower: The pyramid data set utilizing right-handed (n = 30) and left-handed (n = 3) neurosurgeons and residents. The color map on the right outlines the colors corresponding to different forces in Newtons. Figure is available in color online only.

  • View in gallery

    Force pyramids (3D and top views) for medical student, resident, and neurosurgeon groups for resection of simulated tumors of varying appearance. Each pyramid represents, collectively, the applied forces in Newtons (N) in the xy and xz coordinates of all individuals in each group for the 6 black, glioma-like, and white tumors. The color map on the right outlines the colors corresponding to different forces in Newtons. Figure is available in color online only.

  • View in gallery

    Force pyramids (3D view and top views) for medical student, resident, and neurosurgeon groups for resection of simulated tumors of varying stiffness. Each pyramid represents, collectively, the applied forces in Newtons (N) in the xy and xz coordinates of all individuals in each group for the 6 soft, medium, and hard tumors. The color map on the right outlines the colors corresponding to different forces in Newtons. Figure is available in color online only.

  • 1

    Al Zhrani G, Alotaibi F, Azarnoush H, Winkler-Schwartz A, Sabbagh A, Bajunaid K, : Proficiency performance benchmarks for removal of simulated brain tumors using a virtual reality simulator NeuroTouch. J Surg Educ 72:685696, 2015

    • Crossref
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  • 2

    Al Zhrani GA, Lajoie SP, Del Maestro RF: A Validation Study of NeuroTouch in Neurosurgical Training Saarbrücken, Germany, Lambert Academic Publishing, 2014

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  • 3

    Alotaibi F, Al Zhrani G, Bajunaid K, Winkler-Schwartz A, Azarnoush H, Mullah AS, : Assessing neurosurgical psychomotor performance: role of virtual reality simulators, current and future potential. SOJ Neurol 2:17, 2015

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  • 4

    Alotaibi FE, Al Zhrani GA, Mullah MA, Sabbagh AJ, Azarnoush H, Winkler-Schwartz A, : Assessing bimanual performance in brain tumor resection with NeuroTouch, a virtual reality simulator. Neurosurgery 11:Suppl 2 8998, 2015

    • PubMed
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  • 5

    Alotaibi FE, Al Zhrani GA, Sabbagh AJ, Azarnoush H, Winkler-Schwartz A, Del Maestro RF: Neurosurgical assessment of metrics including judgment and dexterity using the virtual reality simulator NeuroTouch (NAJD Metrics). Surg Innov 22:636642, 2015

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  • 6

    Azarnoush H, Alzhrani G, Winkler-Schwartz A, Alotaibi F, Gelinas-Phaneuf N, Pazos V, : Neurosurgical virtual reality simulation metrics to assess psychomotor skills during brain tumor resection. Int J CARS 10:603618, 2015

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  • 7

    Bajunaid K, Mullah MAS, Winkler-Schwartz A, Alotaibi FE, Fares J, Baggiani M, : Impact of acute stress on psychomotor bimanual performance during a simulated tumor resection task. J Neurosurg [epub ahead of print March 11, 2016. DOI:, 2016

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    Bergin M, Sheedy M, Ross P, Wylie G, Bird P: Measuring the forces of middle ear surgery; evaluating a novel force-detection instrument. Otol Neurotol 35:e77e83, 2014

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  • 9

    Birkmeyer JD, Finks JF, O'Reilly A, Oerline M, Carlin AM, Nunn AR, : Surgical skill and complication rates after bariatric surgery. N Engl J Med 369:14341442, 2013

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  • 10

    Choudhury N, Gélinas-Phaneuf N, Delorme S, Del Maestro R: Fundamentals of neurosurgery: virtual reality tasks for training and evaluation of technical skills. World Neurosurg 80:e9e19, 2013

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  • 11

    Delorme S, Laroche D, DiRaddo R, Del Maestro RF: NeuroTouch: a physics-based virtual simulator for cranial microneurosurgery training. Neurosurgery 71:1 Suppl Operative 3242, 2012

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  • 12

    Ericsson KA, Krampe RT, Tesch-Römer C: The role of deliberate practice in the acquisition of expert performance. Psychol Rev 100:363406, 1993

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  • 13

    Gan LS, Zareinia K, Lama S, Maddahi Y, Yang FW, Sutherland GR: Quantification of forces during a neurosurgical procedure: A pilot study. World Neurosurg 84:537548, 2015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14

    Gélinas-Phaneuf N, Choudhury N, Al-Habib AR, Cabral A, Nadeau E, Mora V, : Assessing performance in brain tumor resection using a novel virtual reality simulator. Int J CARS 9:19, 2014

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15

    Gélinas-Phaneuf N, Del Maestro RF: Surgical expertise in neurosurgery: integrating theory into practice. Neurosurgery 73:Suppl 1 3038, 2013

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16

    Holloway T, Lorsch ZS, Chary MA, Sobotka S, Moore MM, Costa AB, : Operator experience determines performance in a simulated computer-based brain tumor resection task. Int J CARS 10:18531862, 2015

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17

    Maddahi Y, Gan LS, Zareinia K, Lama S, Sepehri N, Sutherland GR: Quantifying workspace and forces of surgical dissection during robot-assisted neurosurgery. Int J Med Robot [epub ahead of print] 2015

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18

    Marcus HJ, Zareinia K, Gan LS, Yang FW, Lama S, Yang GZ, : Forces exerted during microneurosurgery: a cadaver study. Int J Med Robot 10:251256, 2014

  • 19

    Payne CJ, Marcus HJ, Yang GZ: A smart haptic hand-held device for neurosurgical microdissection. Ann Biomed Eng 43:21852195, 2015

  • 20

    Rosseau G, Bailes J, del Maestro R, Cabral A, Choudhury N, Comas O, : The development of a virtual simulator for training neurosurgeons to perform and perfect endoscopic endonasal transsphenoidal surgery. Neurosurgery 73:Suppl 1 8593, 2013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Sutherland GR, Maddahi Y, Gan LS, Lama S, Zareinia K: Robotics in the neurosurgical treatment of glioma. Surg Neurol Int 6:1 Suppl 1 S1S8, 2015

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22

    Trejos AL, Jayaraman S, Patel RV, Naish MD, Schlachta CM: Force sensing in natural orifice transluminal endoscopic surgery. Surg Endosc 25:186192, 2011

  • 23

    Trejos AL, Patel RV, Naish MD: Force sensing and its application in minimally invasive surgery and therapy: a survey. Proc Inst Mech Eng C J Mech Eng Sci 224:14351454, 2010

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 24

    Varshney R, Frenkiel S, Nguyen LH, Young M, Del Maestro R, Zeitouni A, : Development of the McGill simulator for endoscopic sinus surgery: a new high-fidelity virtual reality simulator for endoscopic sinus surgery. Am J Rhinol Allergy 28:330334, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25

    Varshney R, Frenkiel S, Nguyen LH, Young M, Del Maestro R, Zeitouni A, : The McGill simulator for endoscopic sinus surgery (MSESS): a validation study. J Otolaryngol Head Neck Surg 43:40, 2014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26

    Winkler-Schwartz A, Bajunaid K, Mullah MAS, Marwa I, Alotaibi FE, Fares J, : Bimanual psychomotor performance in neurosurgical resident applicants assessed using NeuroTouch, a virtual reality simulator. J Surg Educ [epub ahead of print] 2016

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation

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