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Figure 1.
Virtual Surgery Dashboard
Virtual Surgery Dashboard

Seven virtual surgery scenarios are available to choose from at the top right of the dashboard. Computed tomography (CT) imaging and computational fluid dynamics variable predictions change with the different surgical selections. For each virtual surgery procedure, surgeons can view a presurgery CT or simulated postsurgery CT at 3 different coronal sections (A, B, C) whose locations are displayed in the box on the left. The full presurgery coronal CT as well as a full virtual surgery coronal CT are also available to view. Computational fluid dynamics variable predictions are listed at the bottom of the screen with separate tabs for airflow, airflow partition, and mucosal cooling. Both right and left nasal cavity values are shown, with graphs showing the presurgery value and the predicted value based on the specific virtual procedure. A combined graph that lists all 3 variables in the left and right cavities for all surgical combinations is also available for review (eFigure 3 in the Supplement) by clicking the button at the center of the screen.

Figure 2.
The Technology Acceptance Model
The Technology Acceptance Model

Diagram of the interplay among factors influencing use of a new technology, adapted from Holden and Karsh.36

Table 1.  
Surgeon Feedback on the Strengths of the Computational Fluid Dynamics Models, the Virtual Surgery Dashboard, and the Influence on Surgical Decision Making
Surgeon Feedback on the Strengths of the Computational Fluid Dynamics Models, the Virtual Surgery Dashboard, and the Influence on Surgical Decision Making
Table 2.  
Surgeon Feedback on the Weaknesses of the Computational Fluid Dynamics Models, the Virtual Surgery Dashboard, and the Influence on Surgical Decision Making
Surgeon Feedback on the Weaknesses of the Computational Fluid Dynamics Models, the Virtual Surgery Dashboard, and the Influence on Surgical Decision Making
Table 3.  
Surgeon Feedback on Future Applications of Virtual Surgery Based on Computational Fluid Dynamics Simulations
Surgeon Feedback on Future Applications of Virtual Surgery Based on Computational Fluid Dynamics Simulations
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Original Investigation
Jan/Feb 2018

Virtual Surgery for the Nasal Airway: A Preliminary Report on Decision Support and Technology Acceptance

Author Affiliations
  • 1Department of Otolaryngology and Communication Sciences, Medical College of Wisconsin, Milwaukee
  • 2Department of Biomedical Engineering, Marquette University and the Medical College of Wisconsin, Milwaukee
  • 3Center for Patient Care and Outcomes Research, Department of Medicine, Medical College of Wisconsin, Milwaukee
  • 4Division of Head and Neck Surgery and Communication Sciences, Duke University Medical Center, Durham, North Carolina
  • 5Computational Biology & Bioinformatics Program, Duke University, Durham, North Carolina
  • 6Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina
  • 7Department of Otolaryngology/Head and Neck Surgery, University of North Carolina School of Medicine, Chapel Hill
JAMA Facial Plast Surg. 2018;20(1):63-69. doi:10.1001/jamafacial.2017.1554
Key Points

Question  What is surgeon feedback in regards to a virtual surgery planning tool using computational fluid dynamics (CFD) for nasal airway obstruction (NAO), and can this tool influence surgeon decision making?

Findings  In this cross-sectional study of 9 surgeons at a single academic institution, surgeons had overall positive feedback on the virtual surgery planning tool. Surgeon decision making was in some cases influenced by the tool, and potential applications of this tool in clinical care were examined.

Meaning  A virtual surgery planning tool for NAO using CFD was perceived positively by our pilot group of surgeons who see potential applications of this technology that would need further study.

Abstract

Importance  Nasal airway obstruction (NAO) is a common problem that affects patient quality of life. Surgical success for NAO correction is variable. Virtual surgery planning via computational fluid dynamics (CFD) has the potential to improve the success rates of NAO surgery.

Objective  To elicit surgeon feedback of a virtual surgery planning tool for NAO and to determine if this tool affects surgeon decision making.

Design, Setting, and Participants  For this cross-sectional study, 60-minute face-to-face interviews with board-certified otolaryngologists were conducted at a single academic otolaryngology department from September 16, 2016, through October 7, 2016. Virtual surgery methods were introduced, and surgeons were able to interact with the virtual surgery planning tool interface. Surgeons were provided with a patient case of NAO, and open feedback of the platform was obtained, with emphasis on surgical decision making.

Main Outcomes and Measures  Likert scale responses and qualitative feedback were collected for the virtual surgery planning tool and its influence on surgeon decision making.

Results  Our 9 study participants were all male, board-certified otolaryngologists with a mean (range) 15 (4-28) number of years in practice and a mean (range) number of nasal surgeries per month at 2.2 (0.0-6.0). When examined on a scale of 1 (not at all) to 5 (completely), surgeon mean (SD) score was 3.4 (0.5) for how realistic the virtual models were compared with actual surgery. On the same scale, when asked how much the virtual surgery planning tool changed surgeon decision making, mean (SD) score was 2.6 (1.6). On a scale of 1 (strongly disagree) to 7 (strongly agree), surgeon scores for perceived usefulness of the technology and attitude toward using it were 5.1 (1.1) and 5.7 (0.9), respectively.

Conclusions and Relevance  Our study shows positive surgeon experience with a virtual surgery planning tool for NAO based on CFD simulations. Surgeons felt that future applications and areas of study of the virtual surgery planning tool include its potential role for patient counseling, selecting appropriate surgical candidates, and identifying which anatomical structures should be targeted for surgical correction.

Level of Evidence  NA.

Introduction

Nasal airway obstruction (NAO) is a common reason for referral to an otolaryngology or facial plastic surgery clinic,1 affects quality of life in all age groups,2 and has an estimated economic burden upwards of $5 billion annually.3 More than half of sinonasal procedures in 2006 were for septoplasty and/or turbinate surgery.4 Despite surgical correction for NAO, short-term studies report failure rates as high as 20% to 37%,5-9 with long-term studies reporting even higher failure over time.10-14 Treating patients with NAO is a challenge because there is a lack of reliable objective measures that correlate with patient symptoms.14-21 Currently, the decision to proceed with surgery for correction of NAO and the targets for anatomic correction are based on surgeon experience and intuition. Objective methods are needed to guide preoperative decision making to improve the success rates of NAO surgery.11,22

Owing to the complex nature of the nasal airway, analysis with computational modeling tools can aid surgeons in decision making. Recent literature using 3-dimensional (3-D) nasal airway modeling and computational fluid dynamics (CFD) have been able to identify CFD-derived physiologic variables such as airflow and mucosal cooling that correlate with subjective nasal patency scores.23-26 These 3-D nasal airway models combined with CFD provide a promising future for use in virtual surgery planning where specific anatomic areas can be targeted to demonstrate changes to the CFD-derived physiologic variables.

Virtual reality training has been used in otolaryngology with most of the applications related to endoscopic surgery or temporal bone surgery.27 Virtual surgery is also used for plate design in mandibular reconstruction.28,29 However, there are very few virtual surgery planning applications within the field of otolaryngology. At present, there is no virtual surgery tool for patients with NAO.

Establishing this novel method will only be beneficial if the technology is accepted by the practicing surgeons who will actually use the technology. While health technologies have become more commonplace and have potential benefits, their value ultimately depends on health care providers perceiving the technology favorably, accepting it, and appropriately using it for patient care.30,31 Thus, the purpose of this study was 3-fold. Our first goal was to provide practicing otolaryngologists an opportunity to interact with a prototype CFD virtual surgery planning tool and elicit their feedback in regards to the tool’s usefulness and potential applications. Second, we wanted to determine if the planning tool would have any influence on surgeons’ choice of surgery for an actual case of a patient with NAO. The third goal was to obtain feedback from practicing surgeons on the prototype design of the technology interface, so that the technology interface can be refined to effectively communicate virtual surgery predictions to surgeons.

Methods
Study Participants

The institutional review board at the Medical College of Wisconsin approved this study with informed consent obtained from each participant. In this pilot study, we aimed to collect feedback on a prototype virtual surgery dashboard from board-certified surgeons at our institution who have varying levels of experience with nasal surgery and included both surgeons who perform several cases per month and surgeons who perform a few cases per year.

Patient Case

An actual patient case was presented to surgeons and included a preoperative computed tomography (CT) scan for review (eFigure 1 in the Supplement). This patient case was part of a previous study23,24 and institutional review board approval and informed consent was obtained prior to enrollment. No patient identifiers were presented to surgeons. The patient described was a 27-year-old woman with long-standing right-sided nasal obstruction. Her preoperative Nasal Obstruction Symptom Evaluation (NOSE) score32,33 was 80. She had a C-shaped septal deformity with convexity on the right side causing obstruction on that side with contralateral inferior turbinate enlargement (eFigure 1 in the Supplement).

Virtual Surgery Models

A 3-D model of the nasal cavity anatomy was created based on the presurgery CT scan in Mimics (Materialise Inc) (magnetic resonance imaging can also be used to create the 3-D model, but in this study a CT scan was used). Virtual surgery models were created representing the following 7 possible surgical procedures: septoplasty alone, inferior turbinate reduction alone (left side only, right side only, or bilateral), and all possible combinations of septoplasty and inferior turbinate reduction(s) (eFigure 2 in the Supplement). Computational fluid dynamics simulations were run to quantify nasal airflow variables in the presurgery model and in all virtual surgery models using methods described in the Supplement.23,24,34

Virtual Surgery Dashboard

To provide surgeons with a technology interface, we created a virtual surgery dashboard as a web browser application using the NW.js platform (Figure 1). The dashboard allowed surgeons to select from the 7 different surgical procedures described above and view both the presurgery CT scan and simulated postsurgery CT scans for each virtual surgery scenario (eFigure 2 in the Supplement). Computational fluid dynamics measures of nasal airflow for each virtual surgery procedure were displayed both numerically and with bar plots (Figure 1). The following measures of nasal airflow were reported in the dashboard: unilateral airflow rate, airflow partition between nostrils, and unilateral surface area stimulated by mucosal cooling. These CFD variables were selected based on previous work suggesting that these 3 variables have the strongest correlation with subjective nasal patency.23,24 The dashboard included the normative range for each CFD variable based a cohort of 47 healthy subjects (Figure 1) (eFigure 3 in the Supplement).26,35

Because several surgical scenarios predicted airflow variables within the normal range, a criterion was needed to select the CFD-recommended surgery. We reasoned that performing less surgery would have lower morbidity, require less time in the operating room (OR), and reduce costs. We also estimated that unilateral inferior turbinate reduction alone would require less time in the OR than septoplasty alone (approximately 15 minutes vs 30 minutes, respectively). Thus, the CFD-recommended surgery was defined as the procedure that normalized all airflow variables close to the 50th percentile, while minimizing surgical time. Based on these criteria, our virtual surgery models and CFD simulations predicted that septoplasty would be the “best” procedure for our patient case.

Questionnaire and Interview

Our survey questionnaire was developed based on the Technology Acceptance Model36 (Figure 2). This model was developed in the 1980s to understand why workers were not using information technology available to them. To increase use of a technology, the technology must first be accepted, and the factors that affect its acceptance must be evaluated. Based on this model (Figure 2), external factors affect both perceived usefulness and perceived ease of use, which, in turn, affect attitude toward use. An improved attitude toward use will lead to behavioral intention to use. Once the technology has been accepted, this will then lead to actual use.36,37

Surgeons participated in a 60-minute face-to-face interview with the same member of our research team (D.L.V.) who was the only person who had access to surgeon identifiers. This information was blinded from Drs Rhee and Pawar, who are cofaculty of these surgeons at our institution. Surgeons were provided with a brief presentation on CFD technology and a summary of previous studies on the correlation of CFD variables with subjective nasal patency. Then, we explained to surgeons how the virtual surgery models were created and the 7 possible surgical combinations. The patient case was presented to surgeons, and they were given the opportunity to rank their surgical choices for this patient among the 7 possible options. The virtual surgery dashboard was then presented. After surgeons were given time to review the virtual surgery predictions, surgeons were asked to reevaluate their rank of surgical choices. Surgeon feedback was recorded throughout this interview process via a structured questionnaire.

Data Analysis

This pilot study focused on obtaining feedback from practicing surgeons to refine the virtual surgery dashboard. Based on the Technology Acceptance Model,36 our questionnaire asked open-ended questions and Likert scale questions, as is standard in Technology Acceptance Model research.36,37 The Cronbach α, a measure of internal consistency, was calculated where applicable (Cronbach α > 0.70 indicates internal consistency).38 Based on methods of qualitative data analysis,39,40 we used both inductive and deductive approaches to identify strengths and weaknesses of the technology and also to identify general concepts and overall categories from the specific feedback.41 Our conventional approach evaluated text data to establish categories42 focusing solely on manifest content.43 Quantitative data, including the Likert scale data, were collected where applicable and were represented by descriptive analysis.

Results
Demographics

Our 9 study participants were all male, board-certified otolaryngologists at our academic institution, and 7 white and 2 Asian. Mean (SD) years in practice was 15 (8) years with a range of 4 to 28 years. Mean (SD) nasal surgeries performed in a month (septoplasty, inferior turbinate reduction, nasal valve repair, and functional rhinoplasty) was 2.2 (2.4) with range of 0 to 6 surgeries a month (with some surgeons performing only a few a year).

Acceptability of Virtual Surgery Models

When surgeons were asked how well does the virtual surgery model replicate what could be performed in the operating room, on a scale of 1 (not at all) to 5 (completely), the mean (SD) score was 3.4 (0.5). In regards to how accurately the virtual surgery models replicate what would be a realistic outcome after healing on the same scale, the mean (SD) score was also 3.4 (0.5) (eTable 1 in the Supplement). Strengths and weaknesses of the model noted by the surgeons are listed in Table 1 and Table 2, respectively. There were many different opinions regarding the accuracy of the virtual inferior turbinate reduction model.

Virtual Surgery Influence on Surgeon’s Decision

When asked to rank which surgical procedure the surgeon was most likely to perform based on the case presentation alone, 6 chose septoplasty with bilateral inferior turbinate reduction, 2 chose septoplasty with left inferior turbinate reduction, and 1 chose septoplasty alone. When asked if surgeons would reconsider their initial surgical choice after being presented with the virtual surgery prediction that septoplasty alone was the “best” option, on a scale of 1 (not at all) to 5 (completely), mean (SD) score was 2.6 (1.6) with 4 surgeons who stated “not at all;” 2,“somewhat;” 2, “quite a lot;” and 1, “completely” (eTable 1 in the Supplement). Surgeons who had some consideration for changing their rankings mentioned the need for objective data to inform surgical decisions as a motivation to reconsider (Table 1). Contrary to our assumption that minimizing OR time was an important criterion to select the “best surgery,” some surgeons felt that the additional time, cost, and risk of a turbinate reduction was minimal and hence stated that they would still perform turbinate reduction to maximize the benefit of surgery (Table 2).

Ease of Use of the Virtual Surgery Dashboard

As the interface between surgeons and the CFD-based virtual surgery technology, our virtual surgery dashboard represents the ease of use portion of the Technology Acceptance Model with the strengths listed in Table 1 and the weaknesses listed in Table 2. The dashboard strengths include the organization and visual aspect of the presentation. Weaknesses include the inability to modify the models in real time and the desire for additional information.

Perceived Usefulness and Attitude Toward Using

Surgeons were asked Likert-scale questions (scale 1 [strongly disagree]-7 [strongly agree]) regarding the perceived usefulness of virtual surgery with CFD and their attitude toward using the technology. Mean (SD) for the 4 questions on perceived usefulness was 5.1 (1.1) with a Cronbach α of 0.9 (eTable 2 in the Supplement). Qualitative feedback from the questions regarding the perceived usefulness revealed categories that the CFD virtual surgery technology would provide a better tool for patient counseling, help make objective decisions, and select the surgical procedure with greatest benefit (Table 1). The major disadvantages of the technology were the time involved to both create the models and use them, the radiation exposure for the CT scan, and costs involved (Table 2).

Overall, surgeons had a positive attitude toward using virtual surgery planning for NAO, as demonstrated by a mean (SD) score of 5.7 (0.9) for the 3 questions probing their attitude toward using the technology (eTable 2 in the Supplement). The Cronbach α of 0.8 revealed internal consistency for questions in the “Attitude Towards Using” category. Specific surgeon feedback is listed in Table 1 and Table 2.

Applications of Virtual Surgery Technology

Examination of feedback from surgeons in regards to future applications of this virtual surgery technology led to 4 broad categories: patient counseling, determining appropriate surgical candidates, determining the anatomic site to target when operating, and other uses of this technology in otolaryngology (Table 3).

Discussion

Virtual surgery planning based on CFD simulations of nasal airflow has the potential to improve surgical outcomes for NAO patients.44-50 However, this technology needs to be accepted and implemented by practicing surgeons to have a real-world effect in health care.36 To our knowledge, this study represents the first time that practicing surgeons have had an opportunity to interact with a prototype CFD virtual surgery tool for NAO with the goal of soliciting open feedback and discussion to refine the virtual surgery dashboard. Qualitative research is a well-established method in other areas of medicine39,40 but with relatively few studies within the field of otolaryngology.51-55 We used many of the concepts and ideas of qualitative research to gain important insights that could not have been obtained with numeric data alone.

Only 1 of the 9 surgeons selected septoplasty alone (the CFD-predicted “best surgical procedure”) for this patient before being presented with the virtual surgery predictions. The CFD simulations predicted slightly better values in regards to airflow, airflow partition, and mucosal cooling for septoplasty plus any combination of turbinate reduction as compared with septoplasty alone. However, the “best surgical procedure” was chosen based also on decreased operative time and thus decreased risk and cost. While 4 surgeons chose “not at all” when asked if the CFD predictions would make them reconsider their original decision, all 4 felt validated in their choices because CFD predicted a greater change in airflow variables with septoplasty combined with inferior turbinate reduction.

Some of the most interesting feedback was based on questions related to strengths of this technology and situations where this technology would be most helpful. Review of answers to these questions led to the 4 broad categories listed in Table 3. This technology could be a useful tool for patient counseling, especially in the scenario where surgery is not likely to improve patient outcomes. As stated in Table 3, the use of virtual surgery with CFD could provide an objective measure for surgeons to counsel patients with “symptoms out of proportion to their physical examination.” The use of virtual surgery with CFD could also be beneficial when deciding whether or not to operate on a patient with NAO. This tool would be useful in situations where the benefit of surgery may be minimal compared with medical management, or the benefit may be small compared with surgical risk. An example of this would be patients who are anticoagulated or who may have other comorbidities that put them at a higher surgical risk. Virtual surgery with CFD could also help predict which surgical procedure or anatomic targets may give patients the most benefit, which would be very beneficial if you could get acceptable results with the less morbid procedure of turbinate reduction alone vs also needing to perform a septoplasty. Furthermore, the virtual surgery tool could be used to test different versions of a surgical procedure (ie, targeting different areas of the septum or performing different variations of turbinectomy techniques).

Limitations

Our study is limited by the fact that this was a pilot study, conducted within a single academic institution with surgeons who have varying levels of experience with surgery for nasal airway obstruction. Also the surgeons at our institution with the most experience and most referrals for nasal airway obstruction (J.S.R. and S.S.P.) are members of our research team and were not interviewed for the study. Also, surgery for NAO is not limited to septoplasty and inferior turbinate reduction, but our virtual surgery dashboard did not include procedures for addressing the lateral nasal wall or for functional rhinoplasty. In addition, turbinate surgery is performed in a variety of ways and surgeons interviewed felt that this variability was not well reflected in the technique chosen for virtual inferior turbinate reduction (for example, it did not replicate turbinate outfracture). Finally, given our small sample size and focus on qualitative feedback, our study was not designed to produce quantitative conclusions based on a large sample size.

Conclusions

Our study is the first that we know of to introduce virtual surgery planning with CFD to surgeons in a real patient scenario and to evaluate if this virtual model had any effect on surgeon decision making. We focused on ease of use, perceived usefulness, and attitude toward using based on the Technology Acceptance Model36 (Figure 2) as a means to identify how to best implement this technology with practicing surgeons. Incorporation of the feedback obtained in this pilot study will allow for further refinement of this technology as a possible tool for surgeon decision making for patients with NAO. Future studies should focus on creating a more efficient dashboard as the surgeon-technology interface, including the ability to modify the nasal geometry in real time and update the corresponding airflow variables, so that the virtual surgery tool can be implemented in clinical practice.

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Article Information

Corresponding Author: Guilherme J. M. Garcia, PhD, Assistant Professor, Department of Biomedical Engineering, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI 53226 (ggarcia@mcw.edu).

Accepted for Publication: July 25, 2017.

Published Online: October 12, 2017. doi:10.1001/jamafacial.2017.1554

Author Contributions: Dr Garcia had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Vanhille and Garcia contributed equally to this work.

Study concept and design: Vanhille, Garcia, Asan, Frank-Ito, Pawar, Rhee.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Vanhille, Garcia, Asan, Rhee.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Vanhille, A.T. Borojeni.

Obtained funding: Garcia, Kimbell, Rhee.

Administrative, technical, or material support: Vanhille, Garcia, A.T. Borojeni, Frank-Ito, Kimbell, Pawar, Rhee.

Study supervision: Garcia, Asan, Pawar, Rhee.

Conflict of Interest Disclosures: None reported.

Funding/Support: This research was funded by the National Institutes of Health National Institute of Biomedical Imaging and Bioengineering (grant No. R01EB009557).

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Meeting Presentation: This work was presented as an abstract at the American Academy of Facial Plastic and Reconstructive Surgery meeting at the Combined Otolaryngology Spring Meetings 2017; San Diego, California; April 26-30, 2017.

Additional Contributions: The authors wish to thank Andrew Vallejos, MS, for the implementation of the virtual surgery dashboard in the NW.js platform. We are grateful to Chris Larkee, BFA; John Venn, MS; and John LaDisa, PhD (Department of Biomedical Engineering, Marquette University and The Medical College of Wisconsin) for creating a 3-dimensional visualization of the virtual surgery models used during the surgeon interviews.

Disclaimer: Dr Rhee is Deputy Editor of JAMA Facial Plastic Surgery, but he was not involved in any of the decisions regarding review of the manuscript or its acceptance.

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