From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery

PURPOSE

Preventing positive margins is essential for ensuring favorable patient outcomes following breast-conserving surgery (BCS). Deep learning has the potential to enable this by automatically contouring the tumor and guiding resection in real time. However, evaluation of such models with respect to pathology outcomes is necessary for their successful translation into clinical practice.

METHODS

Sixteen deep learning models based on established architectures in the literature are trained on 7318 ultrasound images from 33 patients. Models are ranked by an expert based on their contours generated from images in our test set. Generated contours from each model are also analyzed using recorded cautery trajectories of five navigated BCS cases to predict margin status. Predicted margins are compared with pathology reports.

RESULTS

The best-performing model using both quantitative evaluation and our visual ranking framework achieved a mean Dice score of 0.959. Quantitative metrics are positively associated with expert visual rankings. However, the predictive value of generated contours was limited with a sensitivity of 0.750 and a specificity of 0.433 when tested against pathology reports.

CONCLUSION

We present a clinical evaluation of deep learning models trained for intraoperative tumor segmentation in breast-conserving surgery. We demonstrate that automatic contouring is limited in predicting pathology margins despite achieving high performance on quantitative metrics.

Real-time integration between Microsoft HoloLens 2 and 3D Slicer with demonstration in pedicle screw placement planning

PURPOSE

Up to date, there has been a lack of software infrastructure to connect 3D Slicer to any augmented reality (AR) device. This work describes a novel connection approach using Microsoft HoloLens 2 and OpenIGTLink, with a demonstration in pedicle screw placement planning.

METHODS

We developed an AR application in Unity that is wirelessly rendered onto Microsoft HoloLens 2 using Holographic Remoting. Simultaneously, Unity connects to 3D Slicer using the OpenIGTLink communication protocol. Geometrical transform and image messages are transferred between both platforms in real time. Through the AR glasses, a user visualizes a patient's computed tomography overlaid onto virtual 3D models showing anatomical structures. We technically evaluated the system by measuring message transference latency between the platforms. Its functionality was assessed in pedicle screw placement planning. Six volunteers planned pedicle screws' position and orientation with the AR system and on a 2D desktop planner. We compared the placement accuracy of each screw with both methods. Finally, we administered a questionnaire to all participants to assess their experience with the AR system.

RESULTS

The latency in message exchange is sufficiently low to enable real-time communication between the platforms. The AR method was non-inferior to the 2D desktop planner, with a mean error of 2.1 ± 1.4 mm. Moreover, 98% of the screw placements performed with the AR system were successful, according to the Gertzbein-Robbins scale. The average questionnaire outcomes were 4.5/5.

CONCLUSIONS

Real-time communication between Microsoft HoloLens 2 and 3D Slicer is feasible and supports accurate planning for pedicle screw placement.

The use of 3D digital anatomy model improves the communication with patients presenting with prostate disease: The first experience in Senegal

OBJECTIVES

We hypothesized that the use of an interactive 3D digital anatomy model can improve the quality of communication with patients about prostate disease.

METHODS

A 3D digital anatomy model of the prostate was created from an MRI scan, according to McNeal's zonal anatomy classification. During urological consultation, the physician presented the digital model on a computer and used it to explain the disease and available management options. The experience of patients and physicians was recorded in questionnaires.

RESULTS

The main findings were as follows: 308 patients and 47 physicians participated in the study. In the patient group, 96.8% reported an improved level of understanding of prostate disease and 90.6% reported an improved ability to ask questions during consultation. Among the physicians, 91.5% reported improved communication skills and 100% reported an improved ability to obtain patient consent for subsequent treatment. At the same time, 76.6% of physicians noted that using the computer model lengthened the consultation.

CONCLUSION

This exploratory study found that the use of a 3D digital anatomy model in urology consultations was received overwhelmingly favorably by both patients and physicians, and it was perceived to improve the quality of communication between patient and physician. A randomized study is needed to confirm the preliminary findings and further quantify the improvements in the quality of patient-physician communication.

Sensor-Based Automated Detection of Electrosurgical Cautery States

In computer-assisted surgery, it is typically required to detect when the tool comes into contact with the patient. In activated electrosurgery, this is known as the energy event. By continuously tracking the electrosurgical tools' location using a navigation system, energy events can help determine locations of sensor-classified tissues. Our objective was to detect the energy event and determine the settings of electrosurgical cautery-robustly and automatically based on sensor data. This study aims to demonstrate the feasibility of using the cautery state to detect surgical incisions, without disrupting the surgical workflow. We detected current changes in the wires of the cautery device and grounding pad using non-invasive current sensors and an oscilloscope. An open-source software was implemented to apply machine learning on sensor data to detect energy events and cautery settings. Our methods classified each cautery state at an average accuracy of 95.56% across different tissue types and energy level parameters altered by surgeons during an operation. Our results demonstrate the feasibility of automatically identifying energy events during surgical incisions, which could be an important safety feature in robotic and computer-integrated surgery. This study provides a key step towards locating tissue classifications during breast cancer operations and reducing the rate of positive margins.

Bridging 3D Slicer and ROS2 for Image-Guided Robotic Interventions

Developing image-guided robotic systems requires access to flexible, open-source software. For image guidance, the open-source medical imaging platform 3D Slicer is one of the most adopted tools that can be used for research and prototyping. Similarly, for robotics, the open-source middleware suite robot operating system (ROS) is the standard development framework. In the past, there have been several "ad hoc" attempts made to bridge both tools; however, they are all reliant on middleware and custom interfaces. Additionally, none of these attempts have been successful in bridging access to the full suite of tools provided by ROS or 3D Slicer. Therefore, in this paper, we present the SlicerROS2 module, which was designed for the direct use of ROS2 packages and libraries within 3D Slicer. The module was developed to enable real-time visualization of robots, accommodate different robot configurations, and facilitate data transfer in both directions (between ROS and Slicer). We demonstrate the system on multiple robots with different configurations, evaluate the system performance and discuss an image-guided robotic intervention that can be prototyped with this module. This module can serve as a starting point for clinical system development that reduces the need for custom interfaces and time-intensive platform setup.

Real-time automatic tumor segmentation for ultrasound-guided breast-conserving surgery navigation

PURPOSE

Ultrasound-based navigation is a promising method in breast-conserving surgery, but tumor contouring often requires a radiologist at the time of surgery. Our goal is to develop a real-time automatic neural network-based tumor contouring process for intraoperative guidance. Segmentation accuracy is evaluated by both pixel-based metrics and expert visual rating.

METHODS

This retrospective study includes 7318 intraoperative ultrasound images acquired from 33 breast cancer patients, randomly split between 80:20 for training and testing. We implement a u-net architecture to label each pixel on ultrasound images as either tumor or healthy breast tissue. Quantitative metrics are calculated to evaluate the model's accuracy. Contour quality and usability are also assessed by fellowship-trained breast radiologists and surgical oncologists. Additionally, the viability of using our u-net model in an existing surgical navigation system is evaluated by measuring the segmentation frame rate.

RESULTS

The mean dice similarity coefficient of our u-net model is 0.78, with an area under the receiver-operating characteristics curve of 0.94, sensitivity of 0.95, and specificity of 0.67. Expert visual ratings are positive, with 93% of responses rating tumor contour quality at or above 7/10, and 75% of responses rating contour quality at or above 8/10. Real-time tumor segmentation achieved a frame rate of 16 frames-per-second, sufficient for clinical use.

CONCLUSION

Neural networks trained with intraoperative ultrasound images provide consistent tumor segmentations that are well received by clinicians. These findings suggest that neural networks are a promising adjunct to alleviate radiologist workload as well as improving efficiency in breast-conserving surgery navigation systems.

Training in soft tissue resection using real-time visual computer navigation feedback from the Surgery Tutor: A randomized controlled trial

BACKGROUND

In competency-based medical education, surgery trainees are often required to learn procedural skills in a simulated setting before proceeding to the clinical environment. The Surgery Tutor computer navigation platform allows for real-time proctor-less assessment of open soft tissue resection skills; however, the use of this platform as an aid in acquisition of procedural skills is yet to be explored.

METHODS

In this prospective randomized controlled trial, 20 final year medical students were randomized to receive either training with real-time computer navigation feedback (Intervention, n = 10) or simulation training without navigation feedback (Control, n = 10) during resection of simulated non-palpable soft tissue tumors. Real-time computer navigation feedback allowed participants to visualize the position of their scalpel relative to the tumor. Computer navigation feedback was removed for postintervention assessment. Primary outcome was positive margin rate. Secondary outcomes were procedure time, mass of tissue excised, number of scalpel motions, and distance traveled by the scalpel.

RESULTS

Training with real-time computer navigation resulted in a significantly lower positive margin rate as compared to training without navigation feedback (0% vs 40%, P = .025). All other performance metrics were not significantly different between the 2 groups. Participants in the intervention group displayed significant improvement in positive margin rate from baseline to final assessment (80% vs 0%, P < .01), whereas participants in the Control group did not.

CONCLUSION

Real-time visual computer navigation feedback from the Surgery Tutor resulted in superior acquisition of procedural skills as compared to training without navigation feedback.

System for central venous catheterization training using computer vision-based workflow feedback

OBJECTIVE

To develop a system for training central venous catheterization that does not require an expert observer. We propose a training system that uses video-based workflow recognition and electromagnetic tracking to provide trainees with real-time instruction and feedback.

METHODS

The system provides trainees with prompts about upcoming tasks and visual cues about workflow errors. Most tasks are recognized from a webcam video using a combination of a convolutional neural network and a recurrent neural network. We evaluate the systems ability to recognize tasks in the workflow by computing the percent of tasks that were recognized and the average signed transitional delay between the system and reviewers. We also evaluate the usability of the system using a participant questionnaire.

RESULTS

The system was able to recognize 86.2% of tasks in the workflow. The average signed transitional delay was -0.7 8.7s. The average score on the questionnaire was 4.7 out of 5 for the system overall. The participants found the interactive task list to be the most useful component of the system with an average score of 4.8 out of 5.

CONCLUSION

Overall, the participants were happy with the system and felt that it would improve central venous catheterization training. Our system provides trainees with meaningful instruction and feedback without needing an expert observer to be present.

SIGNIFICANCE

We are able to provide trainees with more opportunities to access instruction and meaningful feedback by using workflow recognition.

Ultrasound Probe Pose Classification for Task Recognition in Central Venous Catheterization

Central Line Tutor is a system that facilitates real-time feedback during training for central venous catheterization. One limitation of Central Line Tutor is its reliance on expensive, cumbersome electromagnetic tracking to facilitate various training aids, including ultrasound task identification and segmentation of neck vasculature. The purpose of this study is to validate deep learning methods for vessel segmentation and ultrasound pose classification in order to mitigate the system's reliance on electromagnetic tracking. A large dataset of segmented and classified ultrasound images was generated from participant data captured using Central Line Tutor. A U-Net architecture was used to perform vessel segmentation, while a shallow Convolutional Neural Network (CNN) architecture was designed to classify the pose of the ultrasound probe. A second classifier architecture was also tested that used the U-Net output as the CNN input. The mean testing set Intersect over Union score for U-Net cross-validation was 0.746 ± 0.052. The mean test set classification accuracy for the CNN was 92.0% ± 3.0, while the U-Net + CNN achieved 92.7% ± 2.1%. This study highlights the potential for deep learning on ultrasound images to replace the current electromagnetic tracking-based methods for vessel segmentation and ultrasound pose classification, and represents an important step towards removing the electromagnetic tracker altogether. Removing the need for an external tracking system would significantly reduce the cost of Central Line Tutor and make it far more accessible to the medical trainees that would benefit from it most.

Design of an Ultrasound-Navigated Prostate Cancer Biopsy System for Nationwide Implementation in Senegal

This paper presents the design of NaviPBx, an ultrasound-navigated prostate cancer biopsy system. NaviPBx is designed to support an affordable and sustainable national healthcare program in Senegal. It uses spatiotemporal navigation and multiparametric transrectal ultrasound to guide biopsies. NaviPBx integrates concepts and methods that have been independently validated previously in clinical feasibility studies and deploys them together in a practical prostate cancer biopsy system. NaviPBx is based entirely on free open-source software and will be shared as a free open-source program with no restriction on its use. NaviPBx is set to be deployed and sustained nationwide through the Senegalese Military Health Service. This paper reports on the results of the design process of NaviPBx. Our approach concentrates on "frugal technology", intended to be affordable for low-middle income (LMIC) countries. Our project promises the wide-scale application of prostate biopsy and will foster time-efficient development and programmatic implementation of ultrasound-guided diagnostic and therapeutic interventions in Senegal and beyond.

Three-dimensional ultrasound for knee osteophyte depiction: a comparative study to computed tomography

Purpose

Osteophytes are common radiographic markers of osteoarthritis. However, they are not accurately depicted using conventional imaging, thus hampering surgical interventions that rely on pre-operative images. Studies have shown that ultrasound (US) is promising at detecting osteophytes and monitoring the progression of osteoarthritis. Furthermore, three-dimensional (3D) ultrasound reconstructions may offer a means to quantify osteophytes. The purpose of this study was to compare the accuracy of osteophyte depiction in the knee joint between 3D US and conventional computed tomography (CT).

Methods

Eleven human cadaveric knees were pre-screened for the presence of osteophytes. Three osteoarthritic knees were selected, and then, 3D US and CT images were obtained, segmented, and digitally reconstructed in 3D. After dissection, high-resolution structured light scanner (SLS) images of the joint surfaces were obtained. Surface matching and root mean square (RMS) error analyses of surface distances were performed to assess the accuracy of each modality in capturing osteophytes. The RMS errors were compared between 3D US, CT and SLS models.

Results

Average RMS error comparisons for 3D US versus SLS and CT versus SLS models were 0.87 mm ± 0.33 mm (average ± standard deviation) and 0.95 mm ± 0.32 mm, respectively. No statistical difference was found between 3D US and CT. Comparative observations of imaging modalities suggested that 3D US better depicted osteophytes with cartilage and fibrocartilage tissue characteristics compared to CT.

Conclusion

Using 3D US can improve the depiction of osteophytes with a cartilaginous portion compared to CT. It can also provide useful information about the presence and extent of osteophytes. Whilst algorithm improvements for automatic segmentation and registration of US are needed to provide a more robust investigation of osteophyte depiction accuracy, this investigation puts forward the potential application for 3D US in routine diagnostic evaluations and pre-operative planning of osteoarthritis.

An End-to-End Solution for Automatic Contouring of Tumor Region in Intraoperative Images of Breast Lumpectomy

Breast-conserving surgery, also known as lumpectomy, is an early stage breast cancer treatment that aims to spare as much healthy breast tissue as possible. A risk associated with lumpectomy is the presence of cancer positive margins post operation. Surgical navigation has been shown to reduce cancer positive margins but requires manual segmentation of the tumor intraoperatively. In this paper, we propose an end-to-end solution for automatic contouring of breast tumor from intraoperative ultrasound images using two convolutional neural network architectures, the U-Net and residual U-Net. The networks are trained on annotated intraoperative breast ultrasound images and evaluated on the quality of predicted segmentations. This work brings us one step closer to providing surgeons with an automated surgical navigation system that helps reduce cancer-positive margins during lumpectomy.

Navigated tissue characterization during skin cancer surgery

PURPOSE

Basal cell carcinoma (BCC) is the most commonly diagnosed skin cancer and is treated by surgical resection. Incomplete tumor removal requires surgical revision, leading to significant healthcare costs and impaired cosmesis. We investigated the clinical feasibility of a surgical navigation system for BCC surgery, based on molecular tissue characterization using rapid evaporative ionization mass spectrometry (REIMS).

METHODS

REIMS enables direct tissue characterization by analysis of cell-specific molecules present within surgical smoke, produced during electrocautery tissue resection. A tissue characterization model was built by acquiring REIMS spectra of BCC, healthy skin and fat from ex vivo skin cancer specimens. This model was used for tissue characterization during navigated skin cancer surgery. Navigation was enabled by optical tracking and real-time visualization of the cautery relative to a contoured resection volume. The surgical smoke was aspirated into a mass spectrometer and directly analyzed with REIMS. Classified BCC was annotated at the real-time position of the cautery. Feasibility of the navigation system, and tissue classification accuracy for ex vivo and intraoperative surgery were evaluated.

RESULTS

Fifty-four fresh excision specimens were used to build the ex vivo model of BCC, normal skin and fat, with 92% accuracy. While 3 surgeries were successfully navigated without breach of sterility, the intraoperative performance of the ex vivo model was low (< 50%). Hypotheses are: (1) the model was trained on heterogeneous mass spectra that did not originate from a single tissue type, (2) during surgery mixed tissue types were resected and thus presented to the model, and (3) the mass spectra were not validated by pathology.

CONCLUSION

REIMS-navigated skin cancer surgery has the potential to detect and localize remaining tumor intraoperatively. Future work will be focused on improving our model by using a precise pencil cautery tip for burning localized tissue types, and having pathology-validated mass spectra.

Automatic Spine Ultrasound Segmentation for Scoliosis Visualization and Measurement

OBJECTIVE

Integrate tracked ultrasound and AI methods to provide a safer and more accessible alternative to X-ray for scoliosis measurement. We propose automatic ultrasound segmentation for 3-dimensional spine visualization and scoliosis measurement to address difficulties in using ultrasound for spine imaging.

METHODS

We trained a convolutional neural network for spine segmentation on ultrasound scans using data from eight healthy adult volunteers. We tested the trained network on eight pediatric patients. We evaluated image segmentation and 3-dimensional volume reconstruction for scoliosis measurement.

RESULTS

As expected, fuzzy segmentation metrics reduced when trained networks were translated from healthy volunteers to patients. Recall decreased from 0.72 to 0.64 (8.2% decrease), and precision from 0.31 to 0.27 (3.7% decrease). However, after finding optimal thresholds for prediction maps, binary segmentation metrics performed better on patient data. Recall decreased from 0.98 to 0.97 (1.6% decrease), and precision from 0.10 to 0.06 (4.5% decrease). Segmentation prediction maps were reconstructed to 3-dimensional volumes and scoliosis was measured in all patients. Measurement in these reconstructions took less than 1 minute and had a maximum error of 2.2° compared to X-ray.

CONCLUSION

automatic spine segmentation makes scoliosis measurement both efficient and accurate in tracked ultrasound scans.

SIGNIFICANCE

Automatic segmentation may overcome the limitations of tracked ultrasound that so far prevented its use as an alternative of X-ray in scoliosis measurement.

A158 LACK OF DIFFERENCE OF COLONIC CURVATURE IN SUPINE VERSUS PRONE PATIENT POSITIONS, IN NORMAL AND HIGH BMI INDIVIDUALS, AS ASSESSED BY QUANTITATIVE ASSESSMENT OF COMPUTED TOMOGRAPHY COLONOGRAPHY

Background

Dynamic positional changes during colonoscopy are commonly used in clinical practice, in particular moving from side to side. It has been shown to improve both adenoma detection rates as well as cecal intubation times. However, perhaps due to an additional level of inconvenience, there have been few studies comparing the anatomy and changes in colonic curvature when patients are in the prone position, which may help to prevent anterior bowing of the scope, particularly in patients with high body mass index (BMI).

Aims

To compare both the number of colonic curves and degree of change in curves with patients in supine versus prone positioning during computed tomography colonography (CTC).

Methods

75 CTC studies, obtained between January and April 2017 at Hotel Dieu Hospital in Kingston, Ontario, were screened and included based on image quality and adequacy of distention. Per standardized protocol, all patients undergoing CTC are imaged both in supine and prone positioning. Using an automated computer algorithm process developed for this study, curves were identified and measured via centerline points placed digitally through the colonic lumen, and compared between supine and prone patient positioning.

Results

75 colonographies were examined. The mean age was 68 years and 37/75 were male. BMI data was available for 56 patients, with mean BMI 29.4 (SD 5.7). There were no significant differences in total mean degrees of curvature between supine and prone positions [75.3 (SD 13.5) vs. 77.3 (SD 15.3), p=0.07], nor a significantly higher total number of curves &gt;100 degrees [4.0 (SD 2.0) vs. 4.5 (SD 2.3), p=0.14]. No significant correlation was seen between BMI and change in position (correlation factor 0.2, p=0.13).

Conclusions

No significant differences were found between the two positions during CT colonography. This certainly calls into question the strategy of starting in prone position, even in higher BMI patients. However, CT colonography doesn’t account for changes that can occur during colonoscopy, as the scope itself can dynamically affect angulations within the colon.

Funding Agencies

None

Real-time electromagnetic navigation for breast-conserving surgery using NaviKnife technology: A matched case-control study

Breast-conserving surgery (BCS) is a mainstay in breast cancer treatment. For nonpalpable breast cancers, current strategies have limited accuracy, contributing to high positive margin rates. We developed NaviKnife, a surgical navigation system based on real-time electromagnetic (EM) tracking. The goal of this study was to confirm the feasibility of intraoperative EM navigation in patients with nonpalpable breast cancer and to assess the potential value of surgical navigation. We recruited 40 patients with ultrasound visible, single, nonpalpable lesions, undergoing BCS. Feasibility was assessed by equipment functionality and sterility, acceptable duration of the operation, and surgeon feedback. Secondary outcomes included specimen volume, positive margin rate, and reoperation outcomes. Study patients were compared to a control group by a matched case-control analysis. There was no equipment failure or breach of sterility. The median operative time was 66 (44-119) minutes with NaviKnife vs 65 (34-158) minutes for the control (P = .64). NaviKnife contouring time was 3.2 (1.6-9) minutes. Surgeons rated navigation as easy to setup, easy to use, and useful in guiding nonpalpable tumor excision. The mean specimen volume was 95.4 ± 73.5 cm³ with NaviKnife and 140.7 ± 100.3 cm³ for the control (P = .01). The positive margin rate was 22.5% with NaviKnife and 28.7% for the control (P = .52). The re-excision specimen contained residual disease in 14.3% for NaviKnife and 50% for the control (P = .28). Our results demonstrate that real-time EM navigation is feasible in the operating room for BCS. Excisions performed with navigation result in the removal of less breast tissue without compromising postive margin rates.

Surgery Tutor for Computational Assessment of Technical Proficiency in Soft-Tissue Tumor Resection in a Simulated Setting

BACKGROUND

In competency-based medical education, progression between milestones requires reliable and valid methods of assessment. Surgery Tutor is an open-source motion tracking platform developed to objectively assess technical proficiency during open soft-tissue tumor resections in a simulated setting. The objective of our study was to provide evidence in support of construct validity of the scores obtained by Surgery Tutor. We hypothesized that Surgery Tutor would discriminate between novice, intermediate, and experienced operators.

METHODS

Thirty participants were assigned to novice, intermediate, or experienced groups, based on the number of prior soft-tissue resections performed. Each participant resected 2 palpable and 2 nonpalpable lesions from a soft-tissue phantom. Surgery Tutor was used to track hand and instrument motions, number of tumor breaches, and time to perform each resection. Mass of excised specimens and margin status were also recorded.

RESULTS

Surgery Tutor scores demonstrated "moderate" to "good" internal structure (test-retest reliability) for novice, intermediate, and experienced groups (interclass correlation coefficient = 0.596, 0.569, 0.737; p < 0.001). Evidence in support of construct validity (consequences) was demonstrated by comparing scores of novice, intermediate, and experienced participantsfor number of hand and instrument motions (690 ± 190, 597 ± 169, 469 ± 110; p < 0.001), number of tumor breaches (29 ± 34, 16 ± 11, 9 ± 6; p < 0.001), time per resection (677 ± 331 seconds, 561 ± 210 seconds, 449 ± 148 seconds; p < 0.001), mass of completely excised specimens (22 ± 7g, 21 ± 11g, 17 ± 6 g; p = 0.035), and rate of positive margin (68%, 50%, 28%; p < 0.001). There was "strong" and "moderate" relationships between motion scores and Objective Structured Assessment of Technical Skill scores, and time per resection and Objective Structured Assessment of Technical Skill scores respectively (r = -0.60, p < 0.001; r = -0.54, p < 0.001).

CONCLUSION

Surgery Tutor scores demonstrate evidenceof construct validity with regards to good internal structure, consequences, and relationship to other variables in the assessment of technical proficiency duringopen soft-tissue tumor resections in a simulated setting. Utilization of Surgery Tutor can provide formative feedback and objective assessment of surgical proficiency in a simulated setting.

Machine learning methods for automated technical skills assessment with instructional feedback in ultrasound-guided interventions

OBJECTIVE

Currently, there is a worldwide shift toward competency-based medical education. This necessitates the use of automated skills assessment methods during self-guided interventions training. Making assessment methods that are transparent and configurable will allow assessment to be interpreted into instructional feedback. The purpose of this work is to develop and validate skills assessment methods in ultrasound-guided interventions that are transparent and configurable.

METHODS

We implemented a method based upon decision trees and a method based upon fuzzy inference systems for technical skills assessment. Subsequently, we validated these methods for their ability to predict scores of operators on a 25-point global rating scale in ultrasound-guided needle insertions and their ability to provide useful feedback for training.

RESULTS

Decision tree and fuzzy rule-based assessment performed comparably to state-of-the-art assessment methods. They produced median errors (on a 25-point scale) of 1.7 and 1.8 for in-plane insertions and 1.5 and 3.0 for out-of-plane insertions, respectively. In addition, these methods provided feedback that was useful for trainee learning. Decision tree assessment produced feedback with median usefulness 7 out of 7; fuzzy rule-based assessment produced feedback with median usefulness 6 out of 7.

CONCLUSION

Transparent and configurable assessment methods are comparable to the state of the art and, in addition, can provide useful feedback. This demonstrates their value in self-guided interventions training curricula.

Utility of 3D Reconstruction of 2D Liver Computed Tomography/Magnetic Resonance Images as a Surgical Planning Tool for Residents in Liver Resection Surgery

OBJECTIVE

A fundamental aspect of surgical planning in liver resections is the identification of key vessel tributaries to preserve healthy liver tissue while fully resecting the tumor(s). Current surgical planning relies primarily on the surgeon's ability to mentally reconstruct 2D computed tomography/magnetic resonance (CT/MR) images into 3D and plan resection margins. This creates significant cognitive load, especially for trainees, as it relies on image interpretation, anatomical and surgical knowledge, experience, and spatial sense. The purpose of this study is to determine if 3D reconstruction of preoperative CT/MR images will assist resident-level trainees in making appropriate operative plans for liver resection surgery.

DESIGN

Ten preoperative patient CT/MR images were selected. Images were case-matched, 5 to 2D planning and 5 to 3D planning. Images from the 3D group were segmented to create interactive digital models that the resident can manipulate to view the tumor(s) in relation to landmark hepatic structures. Residents were asked to evaluate the images and devise a surgical resection plan for each image. The resident alternated between 2D and 3D planning, in a randomly generated order. The primary outcome was the accuracy of resident's plan compared to expert opinion. Time to devise each surgical plan was the secondary outcome. Residents completed a prestudy and poststudy questionnaire regarding their experience with liver surgery and the 3D planning software.

SETTING AND PARTICIPANTS

Senior level surgical residents from the Queen's University General Surgery residency program were recruited to participate.

RESULTS

A total of 14 residents participated in the study. The median correct response rate was 2 of 5 (40%; range: 0-4) for the 2D group, and 3 of 5 (60%; range: 1-5) for the 3D group (p < 0.01). The average time to complete each plan was 156 ± 107 seconds for the 2D group, and 84 ± 73 seconds for the 3D group (p < 0.01). A total 13 of 14 residents found the 3D model easier to use than the 2D. Most residents noticed a difference between the 2 modalities and found that the 3D model improved their confidence with the surgical plan proposed.

CONCLUSIONS

The results of this study show that 3D reconstruction for liver surgery planning increases accuracy of resident surgical planning and decreases amount of time required. 3D reconstruction would be a useful model for improving trainee understanding of liver anatomy and surgical resection, and would serve as an adjunct to current 2D planning methods. This has the potential to be developed into a module for teaching liver surgery in a competency-based medical curriculum.

1.5 T augmented reality navigated interventional MRI: paravertebral sympathetic plexus injections

PURPOSE

The high contrast resolution and absent ionizing radiation of interventional magnetic resonance imaging (MRI) can be advantageous for paravertebral sympathetic nerve plexus injections. We assessed the feasibility and technical performance of MRI-guided paravertebral sympathetic injections utilizing augmented reality navigation and 1.5 T MRI scanner.

METHODS

A total of 23 bilateral injections of the thoracic (8/23, 35%), lumbar (8/23, 35%), and hypogastric (7/23, 30%) paravertebral sympathetic plexus were prospectively planned in twelve human cadavers using a 1.5 Tesla (T) MRI scanner and augmented reality navigation system. MRI-conditional needles were used. Gadolinium-DTPA-enhanced saline was injected. Outcome variables included the number of control magnetic resonance images, target error of the needle tip, punctures of critical nontarget structures, distribution of the injected fluid, and procedure length.

RESULTS

Augmented-reality navigated MRI guidance at 1.5 T provided detailed anatomical visualization for successful targeting of the paravertebral space, needle placement, and perineural paravertebral injections in 46 of 46 targets (100%). A mean of 2 images (range, 1-5 images) were required to control needle placement. Changes of the needle trajectory occurred in 9 of 46 targets (20%) and changes of needle advancement occurred in 6 of 46 targets (13%), which were statistically not related to spinal regions (P = 0.728 and P = 0.86, respectively) and cadaver sizes (P = 0.893 and P = 0.859, respectively). The mean error of the needle tip was 3.9±1.7 mm. There were no punctures of critical nontarget structures. The mean procedure length was 33±12 min.

CONCLUSION

1.5 T augmented reality-navigated interventional MRI can provide accurate imaging guidance for perineural injections of the thoracic, lumbar, and hypogastric sympathetic plexus.

Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience

The National Alliance for Medical Image Computing (NA-MIC) was launched in 2004 with the goal of investigating and developing an open source software infrastructure for the extraction of information and knowledge from medical images using computational methods. Several leading research and engineering groups participated in this effort that was funded by the US National Institutes of Health through a variety of infrastructure grants. This effort transformed 3D Slicer from an internal, Boston-based, academic research software application into a professionally maintained, robust, open source platform with an international leadership and developer and user communities. Critical improvements to the widely used underlying open source libraries and tools-VTK, ITK, CMake, CDash, DCMTK-were an additional consequence of this effort. This project has contributed to close to a thousand peer-reviewed publications and a growing portfolio of US and international funded efforts expanding the use of these tools in new medical computing applications every year. In this editorial, we discuss what we believe are gaps in the way medical image computing is pursued today; how a well-executed research platform can enable discovery, innovation and reproducible science ("Open Science"); and how our quest to build such a software platform has evolved into a productive and rewarding social engineering exercise in building an open-access community with a shared vision.

MR-guided perineural injection of the ganglion impar: technical considerations and feasibility

OBJECTIVE

Perineural ganglion impar injections are used in the management of pelvic pain syndromes; however, there is no consensus regarding the optimal image guidance. Magnetic resonance imaging (MRI) provides high soft tissue contrast and the potential to directly visualize and target the ganglion. The purpose of this study was to assess the feasibility of MR-guided percutaneous perineural ganglion impar injections.

MATERIALS AND METHODS

Six MR-guided ganglion impar injections were performed in six human cadavers. Procedures were performed with a clinical 1.5-Tesla MRI system through a far lateral transgluteus approach. Ganglion impar visibility, distance from the sacrococcygeal joint, number of intermittent MRI control steps required to place the needle, target error between the intended and final needle tip location, inadvertent punctures of non-targeted vulnerable structures, injectant distribution, and procedure time were determined.

RESULTS

The ganglion impar was seen on MRI in 4/6 (66 %) of cases and located 0.8 mm cephalad to 16.3 mm caudad (average 1.2 mm caudad) to the midpoint of the sacrococcygeal joint. Needle placement required an average of three MRI control steps (range, 2-6). The average target error was 2.2 ± 2.1 mm. In 6/6 cases (100 %), there was appropriate periganglionic distribution and filling of the presacrococcygeal space. No punctures of non-targeted structures occurred. The median procedure time was 20 min (range, 12-29 min).

CONCLUSION

Interventional MRI can visualize and directly target the ganglion impar for accurate needle placement and successful periganglionic injection with the additional benefit of no ionizing radiation exposure to patient and staff. Our results support clinical evaluation.

Registration of a statistical model to intraoperative ultrasound for scaphoid screw fixation

PURPOSE

Volar percutaneous scaphoid fracture fixation is conventionally performed under fluoroscopy-based guidance, where surgeons need to mentally determine a trajectory for the insertion of the screw and its depth based on a series of 2D projection images. In addition to challenges associated with mapping 2D information to a 3D space, the process involves exposure to ionizing radiation. Three-dimensional ultrasound has been suggested as an alternative imaging tool for this procedure; however, it has not yet been integrated into clinical routine since ultrasound only provides a limited view of the scaphoid and its surrounding anatomy.

METHODS

We propose a registration of a statistical wrist shape + scale + pose model to a preoperative CT and intraoperative ultrasound to derive a patient-specific 3D model for guiding scaphoid fracture fixation. The registered model is then used to determine clinically important intervention parameters, including the screw length and the trajectory of screw insertion in the scaphoid bone.

RESULTS

Feasibility experiments are performed using 13 cadaver wrists. In 10 out of 13 cases, the trajectory of screw suggested by the registered model meets all clinically important intervention parameters. Overall, an average 94 % of maximum allowable screw length is obtained based on the measurements from gold standard CT. Also, we obtained an average 92 % successful volar accessibility, which indicates that the trajectory is not obstructed by the surrounding trapezium bone.

CONCLUSIONS

These promising results indicate that determining clinically important screw insertion parameters for scaphoid fracture fixation is feasible using 3D ultrasound imaging. This suggests the potential of this technology in replacing fluoroscopic guidance for this procedure in future applications.

Design and development of a mobile image overlay system for needle interventions

Previously, a static and adjustable image overlay systems were proposed for aiding needle interventions. The system was either fixed to a scanner or mounted over a large articulated counterbalanced arm. Certain drawbacks associated with these systems limited the clinical translation. In order to minimize these limitations, we present the mobile image overlay system with the objective of reduced system weight, smaller dimension, and increased tracking accuracy. The design study includes optimal workspace definition, selection of display device, mirror, and laser source. The laser plane alignment, phantom design, image overlay plane calibration, and system accuracy validation methods are discussed. The virtual image is generated by a tablet device and projected into the patient by using a beamsplitter mirror. The viewbox weight (1.0 kg) was reduced by 8.2 times and image overlay plane tracking precision (0.21 mm, STD = 0.05) was improved by 5 times compared to previous system. The automatic self-calibration of the image overlay plane was achieved in two simple steps and can be done away from patient table. The fiducial registration error of the physical phantom to scanned image volume registration was 1.35 mm (STD = 0.11). The reduced system weight and increased accuracy of optical tracking should enable the system to be hand held by the physician and explore the image volume over the patient for needle interventions.

Examination of Learning Trajectories for Simulated Lumbar Puncture Training Using Hand Motion Analysis

OBJECTIVES

A prospective cohort study was conducted using hand motion analysis (HMA) to assess the acquisition and retention of technical proficiency among first-year medical students learning the lumbar puncture (LP) skill in a simulated setting.

METHODS

Twenty-five subjects attended three or four simulation sessions at 6-week intervals. The initial session consisted of an introduction to the procedure and a baseline HMA assessment. This was followed by a session involving deliberate practice and evaluation using HMA. Subject HMA metrics were followed over time and compared to performance benchmarks to determine the volume of practice required to achieve and maintain technical proficiency in the simulated setting. Performance benchmarks were derived from the assessment of experts using HMA.

RESULTS

Subject baseline metrics were significantly different from expert (p < 0.01). At the outset of session 2, none of the subjects achieved the performance benchmarks. At the outset of sessions 3 and 4, 40 and 60% of subjects, respectively, demonstrated retention of technical proficiency. However, there was evidence of significant skill erosion between sessions (p < 0.01). The mean number of practice attempts required to achieve technical proficiency declined between sessions. Regression analysis indicated that there was a significant training effect for all students (overall negative slopes) over time. When examining the group as a whole, the speed at which students reached the expert benchmark was not significantly associated with number of practices in the first three sessions, although for some individuals these factors did appear associated. A total of 76% of subjects retained technical proficiency by session 4 and required a mean of 14 practices (range = 5 to 19).

CONCLUSIONS

These results show that the majority of students require three to four sessions of deliberate practice to achieve a sustainable level of proficiency in the LP procedure. There is considerable variation in learning progression and retention of technical proficiency. These results have important implications for the design and resource requirements of a competency-based medical education program targeting LP training.

Hole filling with oriented sticks in ultrasound volume reconstruction

Volumes reconstructed from tracked planar ultrasound images often contain regions where no information was recorded. Existing interpolation methods introduce image artifacts and tend to be slow in filling large missing regions. Our goal was to develop a computationally efficient method that fills missing regions while adequately preserving image features. We use directional sticks to interpolate between pairs of known opposing voxels in nearby images. We tested our method on 30 volumetric ultrasound scans acquired from human subjects, and compared its performance to that of other published hole-filling methods. Reconstruction accuracy, fidelity, and time were improved compared with other methods.

Prediction of myocardial tissue loss by quantitative densitometric myocardial blush parameters following ST-elevation myocardial infarction

Tissue level myocardial perfusion is one of the most important prognostic factors after successful recanalisation of the occluded coronary artery in patients suffering acute ST elevation myocardial infarction (STEMI). The primary objective of the present study was to examine the relationship between videodensitometric myocardial perfusion parameters as assessed on coronary angiograms directly following successful recanalization therapy and magnetic resonance imaging (MRI)-derived myocardial tissue loss late after STEMI. The study comprised 29 STEMI patients. Videodensitometric parameter G(max)/T(max) was calculated to characterize myocardial perfusion, derived from the plateau of grey-level intensity (G(max)), divided by the time-to-peak intensity (Tmax). Myocardial loss index (MLI) was assessed by cardiac MRI following 376 ± 254 days after PCI.

RESULTS

Significant correlations could be demonstrated between MLI and G(max) (r = 0.36, p = 0.05) and G(max)/T(max) (r = 0.40, p = 0.03) using vessel masking. Using receiver operating characteristic curve analysis, G(max)/T(max) < 2.17 predicted best MLI = 0.3, 0.4, 0.5 and 0.6 with good sensitivity and specificity data, while G(max)/T(max) < 3.25 proved to have a prognostic role in the prediction of MLI = 0.7.

CONCLUSIONS

Selective myocardial tissue level perfusion quantitative measurement method is feasible and can serve as a good predictor of myocardial tissue loss following STEMI and revascularization therapy.

Feasibility of real-time workflow segmentation for tracked needle interventions

Computer-assisted training systems promote both training efficacy and patient health. An important component for providing automatic feedback in computer-assisted training systems is workflow segmentation: the determination of what task in the workflow is being performed. Our objective was to develop a workflow segmentation algorithm for needle interventions using needle tracking data. Needle tracking data were collected from ultrasound-guided epidural injections and lumbar punctures, performed by medical personnel. The workflow segmentation algorithm was tested in a simulated real-time scenario: the algorithm was only allowed access to data recorded at, or prior to, the time being segmented. Segmentation output was compared to the ground-truth segmentations produced by independent blinded observers. Overall, the algorithm was 93% accurate. It automatically segmented the ultrasound-guided epidural procedures with 81% accuracy and the lumbar punctures with 82% accuracy. Given that the manual segmentation consistency was only 84%, the algorithm's accuracy was 93%. Using Cohen's d statistic, a medium effect size (0.5) was calculated. Because the algorithm segments needle-based procedures with such high accuracy, expert observers can be augmented by this algorithm without a large decrease in ability to follow trainees in a workflow. The proposed algorithm is feasible for use in a computer-assisted needle placement training system.

Live ultrasound volume reconstruction using scout scanning

INTRODUCTION

Ultrasound-guided interventions often necessitate scanning of deep-seated anatomical structures that may be hard to visualize. Visualization can be improved using reconstructed 3D ultrasound volumes. High-resolution 3D reconstruction of a large area during clinical interventions is challenging if the region of interest is unknown. We propose a two-stage scanning method allowing the user to perform quick low-resolution scouting followed by high-resolution live volume reconstruction.

METHODS

Scout scanning is accomplished by stacking 2D tracked ultrasound images into a low-resolution volume. Then, within a region of interest defined in the scout scan, live volume reconstruction can be performed by continuous scanning until sufficient image density is achieved. We implemented the workflow as a module of the open-source 3D Slicer application, within the SlicerIGT extension and building on the PLUS toolkit.

RESULTS

Scout scanning is performed in a few seconds using 3 mm spacing to allow region of interest definition. Live reconstruction parameters are set to provide good image quality (0.5 mm spacing, hole filling enabled) and feedback is given during live scanning by regularly updated display of the reconstructed volume.

DISCUSSION

Use of scout scanning may allow the physician to identify anatomical structures. Subsequent live volume reconstruction in a region of interest may assist in procedures such as targeting needle interventions or estimating brain shift during surgery.

The development and validation of hand motion analysis to evaluate competency in central line catheterization

OBJECTIVES

Traditionally, technical skills proficiency has been assessed by direct observation. While direct observation and feedback are essential components in technical skills learning, they demand considerable investment of faculty time, and as an assessment tool, direct observation is inherently subjective and has been criticized as unreliable. The purpose of this study was to determine if quantitative electromagnetic motion tracking is feasible and can discriminate between experts and nonexperts during simulated ultrasound (US)-guided insertion of a central venous catheter (CVC) guidewire.

METHODS

Ten nonexperts (junior emergency medicine residents) and 10 experts (critical care fellows or attending physicians) were recruited. Electromagnetic sensor probes were used to capture hand motion during an US-guided internal jugular cannulation on a standardized manikin. Hand, US, and needle motion were analyzed for the following metrics: total path length, total time, translational movements, and rotational movements. Subjects were also videotaped and evaluated using a modified, validated global rating scale (GRS) by a blinded expert.

RESULTS

There was a significant difference in almost all examined motion parameters between experts and nonexperts. Experts took 66% less time (50.2 seconds vs. 148.7 seconds, p < 0.001) and had significantly less right-hand and US motion (total path length and translational and rotational movements). Left-hand total path length was the only parameter that was not significantly different between groups. Concurrent validity of motion parameters was established by strong correlations (r2 > 0.74) to a previously published, modified GRS.

CONCLUSIONS

Electromagnetic hand and instrument motion analysis is technically feasible for assessing competence in US-guided insertion of a CVC guidewire in a simulation setting. In showing that it discriminates between the performances of nonexperts and experts, this study has provided evidence for construct validity. It also shows excellent correlation with a modified version of a previously validated GRS, providing evidence of concurrent validity.

Assessment of lumbar puncture skill in experts and nonexperts using checklists and quantitative tracking of needle trajectories: implications for competency-based medical education

CONSTRUCT: With the current shift toward competency-based education, rigorous assessment tools are needed for procedurally based tasks.

BACKGROUND

Multiple tools exist to evaluate procedural skills, each with specific weaknesses.

APPROACH

We sought to determine if quantitative needle tracking could be used as a measure of lumbar puncture (LP) performance and added discriminatory value to a dichotomous checklist. Thirty-two medical students were divided into 2 groups. One group was asked to practice an LP once (single practice [SP]) and the other 5 times (multiple practice [MP]). Experts (attending ER physicians, senior ER residents, and a junior anesthesia resident) were used as comparators. Medical students were assessed again at 1 month to assess skill retention. Groups were assessed performing an LP with an electromagnetic tracking device that allows the needle's 3-dimensional movements to be captured and analyzed, and a dichotomous checklist.

RESULTS

Quantitative needle metrics as assessed by electromagnetic tracking showed a decreasing trend in needle movement distance with practice and with experience. The SP group made significantly more checklist mistakes initially as compared to the MP group (1.2 vs. 0.3, p <.05). At 1 month, there was a significant increase in both groups' mistakes (SP 3.4 vs. MP 1.3, p =.01). No correlation existed between individuals' needle motion and checklist mistakes.

CONCLUSIONS

These findings suggest that quantitative needle tracking identifies students who struggle with needle insertion but are successful at completing the dichotomous checklist.

Tracked ultrasonography snapshots enhance needle guidance for percutaneous renal access: a pilot study

BACKGROUND AND PURPOSE

Although ultrasonography-guided percutaneous nephrostomy is relatively safe, a number of factors make it challenging for inexperienced operators. A computerized needle navigation technique using tracked ultrasonography snapshots was investigated to determine whether performance of percutaneous nephrostomy by inexperienced users could be improved.

METHODS

Ten operators performed the procedure on a phantom model with alternating needle guidance between conventional ultrasonography and tracked ultrasonography snapshots. The needle was reinserted until fluid backflow confirmed calyceal access. Needle trajectories were recorded using the real time needle navigation system for offline evaluation of operator performance. Recorded needle trajectories were used to measure needle motion path length inside the phantom tissue, number of reinsertions, total procedure time, and needle insertion time as end points of this study.

RESULTS

Needle path length measured inside the phantom tissue was significantly lower with ultrasonography snapshots guidance (295.0±23.1 mm, average±standard error of the mean) compared with control procedures (977.9±144.4 mm, P<0.01). This was associated with a significantly lower number of needle insertion attempts with ultrasonography snapshots (average 1.27±0.10 vs 2.83±0.31, P<0.01). The total procedure time and the needle insertion time were also significantly lower with ultrasonography snapshots guidance.

CONCLUSION

Tracked ultrasonography snapshots appear to improve the performance of percutaneous nephrostomy in these preliminary investigations, justifying further validation studies. The presented navigation system is reproducible because of commercially available hardware and open-source software components, facilitating its potential role in clinical practice.

PLUS: open-source toolkit for ultrasound-guided intervention systems

A variety of advanced image analysis methods have been under the development for ultrasound-guided interventions. Unfortunately, the transition from an image analysis algorithm to clinical feasibility trials as part of an intervention system requires integration of many components, such as imaging and tracking devices, data processing algorithms, and visualization software. The objective of our paper is to provide a freely available open-source software platform-PLUS: Public software Library for Ultrasound-to facilitate rapid prototyping of ultrasound-guided intervention systems for translational clinical research. PLUS provides a variety of methods for interventional tool pose and ultrasound image acquisition from a wide range of tracking and imaging devices, spatial and temporal calibration, volume reconstruction, simulated image generation, and recording and live streaming of the acquired data. This paper introduces PLUS, explains its functionality and architecture, and presents typical uses and performance in ultrasound-guided intervention systems. PLUS fulfills the essential requirements for the development of ultrasound-guided intervention systems and it aspires to become a widely used translational research prototyping platform. PLUS is freely available as open source software under BSD license and can be downloaded from http://www.plustoolkit.org.

Spinal curvature measurement by tracked ultrasound snapshots

Monitoring spinal curvature in adolescent kyphoscoliosis requires regular radiographic examinations; however, the applied ionizing radiation increases the risk of cancer. Ultrasound imaging is favored over radiography because it does not emit ionizing radiation. Therefore, we tested an ultrasound system for spinal curvature measurement, with the help of spatial tracking of the ultrasound transducer. Tracked ultrasound was used to localize vertebral transverse processes as landmarks along the spine to measure curvature angles. The method was tested in two scoliotic spine models by localizing the same landmarks using both ultrasound and radiographic imaging and comparing the angles obtained. A close correlation was found between tracked ultrasound and radiographic curvature measurements. Differences between results of the two methods were 1.27 ± 0.84° (average ± SD) in an adult model and 0.96 ± 0.87° in a pediatric model. Our results suggest that tracked ultrasound may become a more tolerable and more accessible alternative to radiographic spine monitoring in adolescent kyphoscoliosis.

Tracked ultrasound snapshots in percutaneous pedicle screw placement navigation: a feasibility study

BACKGROUND

Computerized navigation improves the accuracy of minimally invasive pedicle screw placement during spine surgery. Such navigation, however, exposes both the patient and the staff to radiation during surgery. To avoid intraoperative exposure to radiation, tracked ultrasound snapshots-ultrasound image frames coupled with corresponding spatial positions-could be used to map preoperatively defined screw plans into the intraoperative coordinate frame. The feasibility of such an approach, however, has not yet been investigated.

QUESTIONS/PURPOSES

Are there vertebral landmarks that can be identified using tracked ultrasound snapshots? Can tracked ultrasound snapshots allow preoperative pedicle screw plans to be accurately mapped--compared with CT-derived pedicle screw plans--into the intraoperative coordinate frame in a simulated setting?

METHODS

Ultrasound visibility of registration landmarks was checked on volunteers and phantoms. An ultrasound machine with integrated electromagnetic tracking was used for tracked ultrasound acquisition. Registration was performed using 3D Slicer open-source software (www.slicer.org). Two artificial lumbar spine phantoms were used to evaluate registration accuracy of pedicle screw plans using tracked ultrasound snapshots. Registration accuracy was determined by comparing the ultrasound-derived plans with the CT-derived plans.

RESULTS

The four articular processes proved to be identifiable using tracked ultrasound snapshots. Pedicle screw plans were registered to the intraoperative coordinate system using landmarks. The registrations were sufficiently accurate in that none of the registered screw plans intersected the pedicle walls. Registered screw plan positions had an error less than 1.28 ± 1.37 mm (average ± SD) in each direction and an angle difference less than 1.92° ± 1.95° around each axis relative to the CT-derived positions.

CONCLUSIONS

Registration landmarks could be located using tracked ultrasound snapshots and permitted accurate mapping of pedicle screw plans to the intraoperative coordinate frame in a simulated setting.

CLINICAL RELEVANCE

Tracked ultrasound may allow accurate computer-navigated pedicle screw placement while avoiding ionizing radiation in the operating room; however, further studies that compare this approach with other navigation techniques are needed to confirm the practical use of this new approach.