A Novel Suture Training System for Open Surgery Replicating Procedures Performed by Experts Using Augmented Reality.

The surgical education environment has been changing significantly due to restricted work hours, limited resources, and increasing public concern for safety and quality, leading to the evolution of simulation-based training in surgery. Of the various simulators, low-fidelity simulators are widely used to practice surgical skills such as sutures because they are portable, inexpensive, and easy to use without requiring complicated settings. However, since low-fidelity simulators do not offer any teaching information, trainees do self-practice with them, referring to textbooks or videos, which are insufficient to learn open surgical procedures. This study aimed to develop a new suture training system for open surgery that provides trainees with the three-dimensional information of exemplary procedures performed by experts and allows them to observe and imitate the procedures during self-practice. The proposed system consists of a motion capture system of surgical instruments and a three-dimensional replication system of captured procedures on the surgical field. Motion capture of surgical instruments was achieved inexpensively by using cylindrical augmented reality (AR) markers, and replication of captured procedures was realized by visualizing them three-dimensionally at the same position and orientation as captured, using an AR device. For subcuticular interrupted suture, it was confirmed that the proposed system enabled users to observe experts' procedures from any angle and imitate them by manipulating the actual surgical instruments during self-practice. We expect that this training system will contribute to developing a novel surgical training method that enables trainees to learn surgical skills by themselves in the absence of experts.

A comparison between 2- and 3-dimensional approaches to solid component measurement as radiological criteria for sublobar resection in lung adenocarcinoma ≤ 2 cm in size.

PURPOSE: We compared three-dimensional (3D) and two-dimensional (2D) measurements of the solid component to determine radiological criteria for sublobar resection of lung adenocarcinoma ≤ 2 cm in size. METHODS: We included 233 surgical cases. The maximum size of the solid component for 3D measurement was calculated by delineating the solid component on successive axial images and reconstructing the 3D surface model. RESULTS: The predictive performance for adenocarcinoma in situ (n = 43) and minimally invasive adenocarcinoma (n = 77) were equivalent to areas under the curve of 0.871 and 0.857 for 2D and 3D measurements (p = 0.229), respectively. A solid component of 5 mm had a prognostic impact on both measurements ( ≤ 5 mm versus > 5 mm; p = 0.003 for 2D and p = 0.002 for 3D, log-rank test). Survival rates at 5 years were 94.7-96.9% following lobectomy and sublobar resection among patients with a solid component ≤ 5 mm in size. Sublobar resection resulted in worse survival rates, with declines at 5 years of 15.8% on 2D and 11.5% on 3D measurements, than lobectomy in patients with a solid component > 5 mm in size. CONCLUSIONS: A solid component ≤ 5 mm in size is an appropriate criterion for sublobar resection for both measurements. In addition, 2D measurement is justified because of its simple implementation.

How can machine-learning methods assist in virtual screening for hyperuricemia? A healthcare machine-learning approach.

OBJECT: Our purpose was to develop a new machine-learning approach (a virtual health check-up) toward identification of those at high risk of hyperuricemia. Applying the system to general health check-ups is expected to reduce medical costs compared with administering an additional test. METHODS: Data were collected during annual health check-ups performed in Japan between 2011 and 2013 (inclusive). We prepared training and test datasets from the health check-up data to build prediction models; these were composed of 43,524 and 17,789 persons, respectively. Gradient-boosting decision tree (GBDT), random forest (RF), and logistic regression (LR) approaches were trained using the training dataset and were then used to predict hyperuricemia in the test dataset. Undersampling was applied to build the prediction models to deal with the imbalanced class dataset. RESULTS: The results showed that the RF and GBDT approaches afforded the best performances in terms of sensitivity and specificity, respectively. The area under the curve (AUC) values of the models, which reflected the total discriminative ability of the classification, were 0.796 [95% confidence interval (CI): 0.766-0.825] for the GBDT, 0.784 [95% CI: 0.752-0.815] for the RF, and 0.785 [95% CI: 0.752-0.819] for the LR approaches. No significant differences were observed between pairs of each approach. Small changes occurred in the AUCs after applying undersampling to build the models. CONCLUSIONS: We developed a virtual health check-up that predicted the development of hyperuricemia using machine-learning methods. The GBDT, RF, and LR methods had similar predictive capability. Undersampling did not remarkably improve predictive power.

Feasibility of diffusion tensor tractography for preoperative prediction of the location of the facial and vestibulocochlear nerves in relation to vestibular schwannoma.

BACKGROUND: According to recent findings, diffusion tensor tractography (DTT) only allows prediction of facial nerve location in relation to vestibular schwannoma (VS) with high probability. However, previous studies have not mentioned why only the facial nerve was selectively visualized. Our previous report investigated the optimal conditions of DTT for normal facial and vestibulocochlear nerves. In the present study, we applied the optimal conditions of DTT to VS patients to assess the feasibility of DTT for the facial and vestibulocochlear nerves. METHODS: We investigated 11 patients with VS who underwent tumor resection. Visualized tracts were compared with locations of the facial and cochlear nerves as identified by intraoperative electrophysiological monitoring. RESULTS: With the proposed method, visualized tracts corresponded to pathway area of the facial or cochlear nerves in nine of 11 patients (81.8%); specifically, to the pathway area of the facial nerve in three of 11 patients (27.3%), and to the pathway area of the cochlear nerve in six of 11 patients (54.5%). CONCLUSIONS: We visualized facial or vestibulocochlear nerves in nine of 11 patients (81.8%). For the first time, DTT proved able to visualize not only the facial nerve but also the vestibulocochlear nerve in VS patients. Despite our findings, good methods for distinguishing whether a visualized nerve tract represents facial nerve, vestibulocochlear nerve, or only noise remain unavailable. Close attention should therefore be paid to the interpretation of visualized fibers.

Invention of an Online Interactive Virtual Neurosurgery Simulator With Audiovisual Capture for Tactile Feedback.

BACKGROUND: Present neurosurgical simulators are not portable. OBJECTIVE: To maximize portability of a virtual surgical simulator by providing online learning and to validate a unique psychometric method ("audiovisual capture") to provide tactile information without force feedback probes. METHODS: An online interactive neurosurgical simulator of a posterior petrosectomy was developed. The difference in the hardness of compact vs cancellous bone was presented with audiovisual effects as inclinations of the drilling speed and sound based on engineering perspectives. Three training methods (the developed simulator, lectures and review of slides, and dissection of a 3-dimensional printed temporal bone model [D3DPM]) were evaluated by 10 neurosurgical residents. They all first attended a lecture and were randomly allocated to 2 groups by the training D3DPM (A: simulator; B: review of slides, no simulator). In D3DPM, objective measures (required time, quality of completion, injury scores of important structures, and the number of instructions provided) were compared between groups. Finally, the residents answered questionnaires. RESULTS: The objective measures were not significantly different between groups despite a younger tendency in group A (graduate year -2.4 years, 95% confidence interval -5.3 to 0.5, P = .081). The mean perceived hardness of cancellous bone on the simulator was 70% of that of compact bone, matching the intended profile. The simulator was superior to lectures and review of slides in feedback and repeated practices and to D3DPM in adaptability to multiple learning environments. CONCLUSION: A novel online interactive neurosurgical simulator was developed, and satisfactory validity was shown. Audiovisual capture successfully transmitted the tactile information.

De-Identification Technique with Facial Deformation in Head CT Images.

Head CT, which includes the facial region, can visualize faces using 3D reconstruction, raising concern that individuals may be identified. We developed a new de-identification technique that distorts the faces of head CT images. Head CT images that were distorted were labeled as "original images" and the others as "reference images." Reconstructed face models of both were created, with 400 control points on the facial surfaces. All voxel positions in the original image were moved and deformed according to the deformation vectors required to move to corresponding control points on the reference image. Three face detection and identification programs were used to determine face detection rates and match confidence scores. Intracranial volume equivalence tests were performed before and after deformation, and correlation coefficients between intracranial pixel value histograms were calculated. Output accuracy of the deep learning model for intracranial segmentation was determined using Dice Similarity Coefficient before and after deformation. The face detection rate was 100%, and match confidence scores were < 90. Equivalence testing of the intracranial volume revealed statistical equivalence before and after deformation. The median correlation coefficient between intracranial pixel value histograms before and after deformation was 0.9965, indicating high similarity. Dice Similarity Coefficient values of original and deformed images were statistically equivalent. We developed a technique to de-identify head CT images while maintaining the accuracy of deep-learning models. The technique involves deforming images to prevent face identification, with minimal changes to the original information.

Reproducibility of Facial Information in Three-Dimensional Reconstructed Head Images: An Exploratory Study.

BACKGROUND: Facial information acquired via three-dimensional reconstruction of head computed tomography (CT) data may be considered personal information, which can be problematic for neuroimaging studies. However, no study has verified the relationship between slice thickness and face reproducibility. This study determined the relationship and match rate between image slice thickness and face detection accuracy of face-recognition software in facial reconstructed models. METHODS: Head CT data of 60 cases comprising entire faces obtained under conditions of non-contrast and 1-mm slice thickness were resampled to obtain 2-10-mm slice-thickness data. Facial models, reconstructed by image thresholding, were acquired from the data. We performed face detection tests per slice thickness on the models and calculated the face detection rate. The reconstructed facial models created from 1-mm slice-thickness data and other slice thicknesses were used as training and test data, respectively. Match confidence scores were obtained via three programs, match rates were calculated per slice thickness, and generalized estimating equations were used to evaluate the match rate trend. RESULTS: In general, the face detection rates for the 1-10-mm slice thicknesses were 100, 100, 98.3, 98.3, 95.0, 91.7, 86.7, 78.3, 68.3, and 61.7 %, respectively. The match rates for the 2-10-mm slice thicknesses were 100, 98.3, 98.3, 95.0, 85.0, 71.7, 53.3, 28.3, and 16.7 %, respectively. CONCLUSION: The reconstructed models tended to have higher match rates as the slice thickness decreased. Thus, thin-slice head CT imaging data may increase the possibility of the information becoming personally identifiable health information.

Augmented reality self-training system for suturing in open surgery: A randomized controlled trial.

BACKGROUND: Existing self-training materials are insufficient to learn open surgical procedures, and a new self-training system that provides three-dimensional procedural information is needed. The effectiveness and usability of a self-training system providing three-dimensional information by augmented reality (AR) were compared to those of an existing self-training system, instructional video, in self-learning of suturing in open surgery. MATERIALS AND METHODS: This was a prospective, evaluator-blinded, randomized, controlled study. Medical students who were suturing novices were randomized into 2 groups: practice with the AR training system (AR group) or an instructional video (video group). Participants were instructed in subcuticular interrupted suture and each training system and watched the instructional video once. They then completed a pretest performing the suture on a skin pad. Participants in each group practiced the procedure 10 times using each training system, followed by a posttest. The pretest and posttest were video-recorded and graded by blinded evaluators using a validated scoring form composed of global rating (GR) and task-specific (TS) subscales. Students completed a post-study questionnaire assessing system usability, each system's usefulness, and their confidence and interest in surgery. RESULTS: Nineteen participants in each group completed the trial. No significant difference was found between the AR and video groups on the improvement of the scores from pretest to posttest (GR: p = 0.54, TS: p = 0.91). The posttest scores of both GR and TS improved significantly from pretest in both groups (GR: both p < 0.001, TS: both p < 0.001). There was no significant difference between the groups in the system usability scale scores (p = 0.38). The motion provided in the AR system was more helpful for manipulating surgical instruments than the video (p = 0.02). CONCLUSION: The AR system was considered as understandable and easy to use as the instructional video in learning suture technique in open surgery for novices.

Threshold field painting saves the time for segmentation of minute arteries.

PURPOSE: It is often time-consuming to segment fine structures, such as the cerebral arteries from magnetic resonance imaging (MRI). Moreover, extracting anatomically abnormal structures is generally difficult. The segmentation workflow called threshold field painting was tested for its feasibility in morbid minute artery segmentation with special emphasis on time efficiency. METHODS: Seven patients with meningioma with ten-sided feeding arteries (n = 10) originating from middle meningeal arteries (MMA) were investigated by three experts of the conventional method for segmentation. The MRI time-of-flight sequence was utilized for the segmentation of each procedure. The tasks were accomplished using both the conventional method and the proposed method in random order. The task completion time and usability score were analyzed using the Wilcoxon signed-rank test. RESULTS: Except for one examinee (P = 0.06), the completion time significantly decreased (both P < 0.01) with the use of the proposed method. The average task completion time among the three examinees for the conventional method was 2.8 times longer than that for the proposed method. The usability score was generally in favor of the proposed method. CONCLUSION: The normally nonexistent minute arteries, such as the MMA feeders, were deemed more efficiently segmented with the proposed method than with the conventional method. While automatic segmentation might be the ultimate solution, our semiautomatic method incorporating expert knowledge is expected to work as the practical solution.

Effect of a Virtual Reality Contact-Based Educational Intervention on the Public Stigma of Depression: Randomized Controlled Pilot Study.

BACKGROUND: Public stigma against depression contributes to low employment rates among individuals with depression. Contact-based educational (CBE) interventions have been shown to reduce this public stigma. OBJECTIVE: We investigated the ability of our Virtual Reality Antistigma (VRAS) app developed for CBE interventions to reduce the stigma of depression. METHODS: Sixteen medical students were recruited and randomized 1:1 to the intervention group, who used the VRAS app (VRAS group), and the control group, who watched a video on depression. The depression stigma score was assessed using the Depression Stigma Scale (DSS) and Attitudinal Social Distance (ASD) questionnaire at pre- and postintervention. Feasibility was assessed in both groups and usability was assessed only in the VRAS group after the intervention. A qualitative study was performed on the acquisition of knowledge about stigma in both groups based on participants' answers to open-ended questions and interviews after the intervention. RESULTS: The feasibility score was significantly higher in the VRAS group (mean 5.63, SD 0.74) than in the control group (mean 3.88, SD 1.73; P=.03). However, no significant differences were apparent between the VRAS and control groups for the DSS (VRAS: mean 35.13, SD 5.30; control: mean 35.38, SD 4.50; P=.92) or ASD (VRAS: mean 12.25, SD 3.33; control: mean 11.25, SD 1.91; P=.92). Stigma scores tended to decrease; however, the stigma-reducing effects of the VRAS app were not significant for the DSS (pre: mean 33.00, SD 4.44; post: mean 35.13, SD 5.30; P=.12) or ASD (pre: mean 13.25, SD 3.92; post: mean 12.25, SD 3.33; P=.12). Qualitative analysis suggested that the VRAS app facilitated perspective-taking and promoted empathy toward the patient. CONCLUSIONS: The CBE intervention using virtual reality technology (VRAS app) was as effective as the video intervention. The results of the qualitative study suggested that the virtual reality intervention was able to promote perspective-taking and empathy toward patients. TRIAL REGISTRATION: University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR) UMIN000043020; https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000049109.

Accurate Preoperative Identification of Motor Speech Area as Termination of Arcuate Fasciculus Depicted by Q-Ball Imaging Tractography.

BACKGROUND: Tractography is one way to predict the distribution of cortical functional domains preoperatively. Diffusion tensor tractography (DTT) is commonly used in clinical practice, but is known to have limitations in delineating crossed fibers, which can be overcome by Q-ball imaging tractography (QBT). We aimed to compare the reliability of these 2 methods based on the spatial correlation between the arcuate fasciculus depicted by tractography and direct cortical stimulation during awake surgery. METHODS: In this study, 15 patients with glioma underwent awake surgery with direct cortical stimulation. Tractography was depicted in a three-dimensional computer graphic model preoperatively, which was integrated with a photograph of the actual brain cortex using our novel mixed-reality technology. The termination of the arcuate fasciculus depicted by either DTT or QBT and the results of direct cortical stimulation were compared, and sensitivity and specificity were calculated in speech-associated brain gyri: pars triangularis, pars opercularis, ventral precentral gyrus, and middle frontal gyrus. RESULTS: QBT had significantly better sensitivity and lower false-positive rate than DTT in the pars opercularis. The same trend was noted for the other gyri. CONCLUSIONS: QBT is more reliable than DTT in identification of the motor speech area and may be clinically useful in brain tumor surgery.

Development of Innovative Neurosurgical Operation Support Method Using Mixed-Reality Computer Graphics.

BACKGROUND: In neurosurgery, it is important to inspect the spatial correspondence between the preoperative medical image (virtual space), and the intraoperative findings (real space) to improve the safety of the surgery. Navigation systems and related modalities have been reported as methods for matching this correspondence. However, because of the influence of the brain shift accompanying craniotomy, registration accuracy is reduced. In the present study, to overcome these issues, we developed a spatially accurate registration method of medical fusion 3-dimensional computer graphics and the intraoperative brain surface photograph, and its registration accuracy was measured. METHODS: The subjects included 16 patients with glioma. Nonrigid registration using the landmarks and thin-plate spline methods was performed for the fusion 3-dimensional computer graphics and the intraoperative brain surface photograph, termed mixed-reality computer graphics. Regarding the registration accuracy measurement, the target registration error was measured by two neurosurgeons, with 10 points for each case at the midpoint of the landmarks. RESULTS: The number of target registration error measurement points was 160 in the 16 cases. The target registration error was 0.72 ± 0.04 mm. Aligning the intraoperative brain surface photograph and the fusion 3-dimensional computer graphics required ∼10 minutes on average. The average number of landmarks used for alignment was 24.6. CONCLUSIONS: Mixed-reality computer graphics enabled highly precise spatial alignment between the real space and virtual space. Mixed-reality computer graphics have the potential to improve the safety of the surgery by allowing complementary observation of brain surface photographs and fusion 3-dimensional computer graphics.

Development of a New Image-Guided Neuronavigation System: Mixed-Reality Projection Mapping Is Accurate and Feasible.

BACKGROUND: Image-guided systems improve the safety, functional outcome, and overall survival of neurosurgery but require extensive equipment. OBJECTIVE: To develop an image-guided surgery system that combines the brain surface photographic texture (BSP-T) captured during surgery with 3-dimensional computer graphics (3DCG) using projection mapping. METHODS: Patients who underwent initial surgery with brain tumors were prospectively enrolled. The texture of the 3DCG (3DCG-T) was obtained from 3DCG under similar conditions as those when capturing the brain surface photographs. The position and orientation at the time of 3DCG-T acquisition were used as the reference. The correct position and orientation of the BSP-T were obtained by aligning the BSP-T with the 3DCG-T using normalized mutual information. The BSP-T was combined with and displayed on the 3DCG using projection mapping. This mixed-reality projection mapping (MRPM) was used prospectively in 15 patients (mean age 46.6 yr, 6 males). The difference between the centerlines of surface blood vessels on the BSP-T and 3DCG constituted the target registration error (TRE) and was measured in 16 fields of the craniotomy area. We also measured the time required for image processing. RESULTS: The TRE was measured at 158 locations in the 15 patients, with an average of 1.19 ± 0.14 mm (mean ± standard error). The average image processing time was 16.58 min. CONCLUSION: Our MRPM method does not require extensive equipment while presenting information of patients' anatomy together with medical images in the same coordinate system. It has the potential to improve patient safety.

Mice lacking a functional NMDA receptor exhibit social subordination in a group-housed environment.

Social dominance, in which an individual asserts control over others or benefits most after social conflict, has an influence on social behaviour. However, the mechanisms mediating social dominance remain unclear. Social dominance within social groups determines the distribution of rewards such as food and access to mating partners, which can act as reinforcers. In this study, we used the water competition test to determine whether mice were dominant or subordinate. It has been previously reported that mice heterozygous for a missense mutation in Grin1 (Grin1Rgsc174 ) showed altered social behaviour, with increased locomotor activity, novelty seeking and anxiety. However, social dominance in these mice has not been previously investigated. We subjected Grin1Rgsc174/+ mice to the water competition test using IntelliCage and observed that Grin1 influences competitive dominance. We found that Grin1Rgsc174/+ mice exhibited social subordination characterised by decreased corner visit frequency and occupancy time at the beginning of the task. However, Grin1Rgsc174/+ mice retained increased basal activity and exploring behaviour under a group-housed environment. Our findings suggested that Grin1 plays an important role in determining social dominance.

Microsurgery Simulator of Cerebral Aneurysm Clipping with Interactive Cerebral Deformation Featuring a Virtual Arachnoid.

BACKGROUND: A virtual reality simulator for aneurysmal clipping surgery is an attractive research target for neurosurgeons. Brain deformation is one of the most important functionalities necessary for an accurate clipping simulator and is vastly affected by the status of the supporting tissue, such as the arachnoid membrane. However, no virtual reality simulator implementing the supporting tissue of the brain has yet been developed. OBJECTIVE: To develop a virtual reality clipping simulator possessing interactive brain deforming capability closely dependent on arachnoid dissection and apply it to clinical cases. METHODS: Three-dimensional computer graphics models of cerebral tissue and surrounding structures were extracted from medical images. We developed a new method for modifiable cerebral tissue complex deformation by incorporating a nonmedical image-derived virtual arachnoid/trabecula in a process called multitissue integrated interactive deformation (MTIID). MTIID made it possible for cerebral tissue complexes to selectively deform at the site of dissection. Simulations for 8 cases of actual clipping surgery were performed before surgery and evaluated for their usefulness in surgical approach planning. RESULTS: Preoperatively, each operative field was precisely reproduced and visualized with the virtual brain retraction defined by users. The clear visualization of the optimal approach to treating the aneurysm via an appropriate arachnoid incision was possible with MTIID. CONCLUSION: A virtual clipping simulator mainly focusing on supporting tissues and less on physical properties seemed to be useful in the surgical simulation of cerebral aneurysm clipping. To our knowledge, this article is the first to report brain deformation based on supporting tissues.

Impact of predicting health-guidance candidates using massive health check-up data: A data-driven analysis.

INTRODUCTION: Starting in 2008, specific health checkups and health guidance to prevent non-communicable diseases have been provided in Japan, which has the highest proportion of elderly citizens in the world. The attendance rate for health guidance appointments is 17.7%, which is far from the national goal of the system (45%). To improve the attendance rate, we present a model for predicting whether an examinee is a candidate for health guidance; this model was based on a machine learning method and a restricted but massive amount of health checkup information. MATERIALS AND METHODS: Using machine learning methods, we developed the following five prediction models for identifying health-guidance candidates: baseline: this model included sex and age; model 1: this model included variables that can be measured in person+information on whether the examinee was a candidate in the past year; model 2: model 1+systolic blood pressure+diastolic blood pressure; model 3: model 2+all health checkup results from the past year; and model 4: model 3 using the training dataset excluding cases with missing data. RESULTS: The performance levels of the five prediction models (the AUC values of the models for the test dataset) were as follows: 0.592 [95% CI: 0.586-0.596] for the baseline model, 0.855 [95% CI: 0.851-0.858] for model 1, 0.985 [95% CI: 0.984-0.985] for model 2, 0.993 [95% CI: 0.993-0.993] for model 3, and 0.943 [95% CI: 0.941-0.945] for model 4. CONCLUSIONS: We studied five models for identifying health-guidance candidates. The model that used all health checkup results from the past year had the highest predictive power. Application of the prediction model developed in the present study to the selection of health-guidance candidates could reduce the cost of guidance.

Neurosurgical Virtual Reality Simulation for Brain Tumor Using High-definition Computer Graphics: A Review of the Literature.

Simulation and planning of surgery using a virtual reality model is becoming common with advances in computer technology. In this study, we conducted a literature search to find trends in virtual simulation of surgery for brain tumors. A MEDLINE search for "neurosurgery AND (simulation OR virtual reality)" retrieved a total of 1,298 articles published in the past 10 years. After eliminating studies designed solely for education and training purposes, 28 articles about the clinical application remained. The finding that the vast majority of the articles were about education and training rather than clinical applications suggests that several issues need be addressed for clinical application of surgical simulation. In addition, 10 of the 28 articles were from Japanese groups. In general, the 28 articles demonstrated clinical benefits of virtual surgical simulation. Simulation was particularly useful in better understanding complicated spatial relations of anatomical landmarks and in examining surgical approaches. In some studies, Virtual reality models were used on either surgical navigation system or augmented reality technology, which projects virtual reality images onto the operating field. Reported problems were difficulties in standardized, objective evaluation of surgical simulation systems; inability to respond to tissue deformation caused by surgical maneuvers; absence of the system functionality to reflect features of tissue (e.g., hardness and adhesion); and many problems with image processing. The amount of description about image processing tended to be insufficient, indicating that the level of evidence, risk of bias, precision, and reproducibility need to be addressed for further advances and ultimately for full clinical application.

Usefulness of high-resolution 3D multifusion medical imaging for preoperative planning in patients with posterior fossa hemangioblastoma: technical note.

Successful resection of hemangioblastoma depends on preoperative assessment of the precise locations of feeding arteries and draining veins. Simultaneous 3D visualization of feeding arteries, draining veins, and surrounding structures is needed. The present study evaluated the usefulness of high-resolution 3D multifusion medical imaging (hr-3DMMI) for preoperative planning of hemangioblastoma. The hr-3DMMI combined MRI, MR angiography, thin-slice CT, and 3D rotated angiography. Surface rendering was mainly used for the creation of hr-3DMMI using multiple thresholds to create 3D models, and processing took approximately 3-5 hours. This hr-3DMMI technique was used in 5 patients for preoperative planning and the imaging findings were compared with the operative findings. Hr-3DMMI could simulate the whole 3D tumor as a unique sphere and show the precise penetration points of both feeding arteries and draining veins with the same spatial relationships as the original tumor. All feeding arteries and draining veins were found intraoperatively at the same position as estimated preoperatively, and were occluded as planned preoperatively. This hr-3DMMI technique could demonstrate the precise locations of feeding arteries and draining veins preoperatively and estimate the appropriate route for resection of the tumor. Hr-3DMMI is expected to be a very useful support tool for surgery of hemangioblastoma.

Marker-less tracking of brain surface deformations by non-rigid registration integrating surface and vessel/sulci features.

PURPOSE: To compensate for brain shift in image-guided neurosurgery, we propose a new non-rigid registration method that integrates surface and vessel/sulci feature to noninvasively track the brain surface. METHOD: Textured brain surfaces were acquired using phase-shift three-dimensional (3D) shape measurement, which offers 2D image pixels and their corresponding 3D points directly. Measured brain surfaces were noninvasively tracked using the proposed method by minimizing a new energy function, which is a weighted combination of 3D point corresponding estimation and surface deformation constraints. Initially, the measured surfaces were divided into featured and non-featured parts using a Frangi filter. The corresponding feature/non-feature points between intraoperative brain surfaces were estimated using the closest point algorithm. Subsequently, smoothness and rigidity constraints were introduced in the energy function for a smooth surface deformation and local surface detail conservation, respectively. Our 3D shape measurement accuracy was evaluated using 20 spheres for bias and precision errors. In addition, the proposed method was evaluated based on root mean square error (RMSE) and target registration error (TRE) with five porcine brains for which deformations were produced by gravity and pushing with different displacements in both the vertical and horizontal directions. RESULTS: The minimum and maximum bias errors were 0.32 and 0.61 mm, respectively. The minimum and maximum precision errors were 0.025 and 0.30 mm, respectively. Quantitative validation with porcine brains showed that the average RMSE and TRE were 0.1 and 0.9 mm, respectively. CONCLUSION: The proposed method appeared to be advantageous in integrating vessels/sulci feature, robust to changes in deformation magnitude and integrated feature numbers, and feasible in compensating for brain shift deformation in surgeries.

Wall-to-lumen ratio of intracranial arteries measured by indocyanine green angiography.

BACKGROUND: The wall-to-lumen ratio (WLR) is an important parameter in vascular medicine because it indicates the character of vascular wall as well as the degree of stenosis. Despite the advances in medical imaging technologies, it is still difficult to measure the thin-walled normal intracranial arteries, and the reports on the WLR of normal intracranial artery are limited. It might be possible to calculate the WLR using the indocyanine green (ICG) angiography, which is used to observe intracranial vessels during microsurgery. PURPOSE: To evaluate the WLR of normal intracranial arteries using ICG angiography. MATERIALS AND METHODS: From the three cases in which ICG angiography was recorded with a ruler during microsurgery, 20 measurement points were chosen for the analysis. The ICG was injected intravenously with a dose of 0.2 mg/kg, and the vessels were inspected at high magnification using an operating microscope equipped with near-infrared illumination system. The vessel outer diameter and the luminal diameter were measured using the images before and after the ICG arrival based on the pixel ratio method using a ruler as reference, respectively. The WLR was calculated as 0.5 × (vessel outer diameter - vessel luminal diameter). RESULTS: The WLR (mean ± standard deviation) of normal intracranial arteries was 0.086 ± 0.022. The WLR tended to be high in small arteries. CONCLUSION: The WLR of normal intracranial arteries calculated using ICG angiography was consistent with the WLR reported in the previous reports based on human autopsy.