Simulation of surgery for supratentorial gliomas in virtual reality using a 3D volume rendering technique: a poor man's neuronavigation

Setting Up a Department of Neurosurgery in a Government Hospital in an LMIC: Jodhpur, India

BACKGROUND

The number of government institutes offering affordable super specialty and tertiary healthcare in India has traditionally not been able to keep pace with the growth in population, most of whom are too poor to be able to afford private healthcare services. To meet this mandate, 6 new institutes built on the template of the premier institute of the country-the All India Institute of Medical Sciences, New Delhi-were founded and began operations in 2012. Using the progress of our department as an example, the aim of this report is to outline the principles that were followed to set up the department of neurosurgery.

METHODS

The Department of Neurosurgery at All India Institute of Medical Sciences, Jodhpur, began providing services in August 2017. Data related to the inception and development of the department were collected.

RESULTS

The department has grown during the past 5 years from 400 outpatients and 79 inpatients in 2017 to 11,144 outpatients and 1624 inpatients in 2022. Only 59 surgeries were performed in 2017 compared with 597 routine and 311 emergency procedures performed in 2022. Currently, the department has 7 faculty members performing all forms of complex skull base, craniovertebral junction, vascular, endovascular, epilepsy, and functional surgeries. A total of 134 studies have been reported in national and international journals, and 8 patents have been granted.

CONCLUSIONS

We report the unique experiences of one department that could be useful as a template and as guidelines for the establishment process of a new department.

How to Omit the Potential Pitfalls in Distal Radial Access: Lessons From Cadaveric and CTA Analysis

OBJECTIVES

To verify the anatomical basis, ideal puncture sites, and potential pitfalls of the distal radial artery (dRA) in the anatomical snuffbox region for distal radial access (dTRA).

MATERIALS AND METHODS

Overall, 26 formalin-fixed upper limbs and computed tomography angiography (CTA) of the upper limbs of 168 consecutive patients were studied. Cadaveric dissection and dRA 3D reconstruction were used to evaluate the dRA route for dTRA. The puncture sites, dRA diameter, and angle of the dRA and tendons of the extensor pollicis brevis were also measured in the patients and cadavers.

RESULTS

The cadaver dissection provided more insights than did the dRA 3D reconstruction. However, preoperative evaluation had better diagnostic accuracy (p=0.024). Puncture sites 1 and 3 had a high success rate (63.2% possible success rate, 191/302). The DISFAVOR theory was put forward, in which 8 types of potential pitfalls that may interrupt puncture procedure or lead to a surgical failure were observed, including occlusion, stenosis, tortuosity, arteriovenous fistula, angioma, different radial artery (RA) ramifications, radial veins, and cephalic veins. The mean diameter of dRA based on cadaver dissection and CTA was 2.53 (SD=0.73) and 2.63 (SD=0.69) mm, respectively. Furthermore, the minimum distance from the outer layer of dRA to the skin was 5.71 (SD=2.0) mm based on CTA. The angle between the dRA and tendons of extensor pollicis brevis (TEPB) based on cadaver dissection and CTA was 58.0° (SD=21.5°) and 51.8° (SD=16.6°), respectively.

CONCLUSIONS

Puncture sites 1 and 3 were more suitable for the dTRA, and we put forward the DISFAVOR theory to summarize the 8 types of potential pitfalls during the use of dTRA.

Automated, fast, robust brain extraction on contrast-enhanced T1-weighted MRI in presence of brain tumors: an optimized model based on multi-center datasets

OBJECTIVES

Existing brain extraction models should be further optimized to provide more information for oncological analysis. We aimed to develop an nnU-Net-based deep learning model for automated brain extraction on contrast-enhanced T1-weighted (T1CE) images in presence of brain tumors.

METHODS

This is a multi-center, retrospective study involving 920 patients. A total of 720 cases with four types of intracranial tumors from private institutions were collected and set as the training group and the internal test group. Mann-Whitney U test (U test) was used to investigate if the model performance was associated with pathological types and tumor characteristics. Then, the generalization of model was independently tested on public datasets consisting of 100 glioma and 100 vestibular schwannoma cases.

RESULTS

In the internal test, the model achieved promising performance with median Dice similarity coefficient (DSC) of 0.989 (interquartile range (IQR), 0.988-0.991), and Hausdorff distance (HD) of 6.403 mm (IQR, 5.099-8.426 mm). U test suggested a slightly descending performance in meningioma and vestibular schwannoma group. The results of U test also suggested that there was a significant difference in peritumoral edema group, with median DSC of 0.990 (IQR, 0.989-0.991, p = 0.002), and median HD of 5.916 mm (IQR, 5.000-8.000 mm, p = 0.049). In the external test, our model also showed to be robust performance, with median DSC of 0.991 (IQR, 0.983-0.998) and HD of 8.972 mm (IQR, 6.164-13.710 mm).

CONCLUSIONS

For automated processing of MRI neuroimaging data presence of brain tumors, the proposed model can perform brain extraction including important superficial structures for oncological analysis.

CLINICAL RELEVANCE STATEMENT

The proposed model serves as a radiological tool for image preprocessing in tumor cases, focusing on superficial brain structures, which could streamline the workflow and enhance the efficiency of subsequent radiological assessments.

KEY POINTS

• The nnU-Net-based model is capable of segmenting significant superficial structures in brain extraction. • The proposed model showed feasible performance, regardless of pathological types or tumor characteristics. • The model showed generalization in the public datasets.

Virtual Reality in Preoperative Planning of Complex Cranial Surgery

OBJECTIVE

Changing paradigms of neurosurgical training and limited operative exposure during the residency period have made it necessary to evaluate newer technologies for training. Virtual reality (VR) technology provides three-dimensional reconstruction of routine imaging, along with the ability to see as well as interact. The application of VR technology in operative planning, which is an important part of neurosurgical training, has been incompletely studied so far.

METHODS

Sixteen final-year residents, post-M.Ch. (magister chirurgiae) residents, and fellows were included as study participants. They were divided into 2 groups based on their seniority for further analysis. Five complex cranial cases were selected and a multiple-choice question-based test was prepared by the authors, with 5 questions for each of the cases. The pretest score was determined based on performance on the test after participants accessed routine preoperative imaging. The posttest score was calculated after use of the VR system (ImmersiveTouch VR System, ImmersiveTouch Inc.). Analysis was performed by the investigators, who were blinded to the identity of the participant. Subanalysis based on the type of case and type of question was performed. Feedback was obtained from each participant regarding VR use.

RESULTS

There was an overall improvement in scores from pretest to posttest, which was also noted in the analysis based on the participants' seniority. This improvement was noted to be more for the vascular cases (15.89%) compared with the tumor cases (7.84%). Participants also fared better in questions related to surgical anatomy and surgical approach, compared with questions based on the diagnosis. There was overall positive feedback from participants regarding VR use, and most participants wanted VR to become a routine part of operative planning.

CONCLUSIONS

Our study shows that there is improvement in understanding of surgical aspects after use of this VR system.

Enhancing the Reliability of Intraoperative Ultrasound in Pediatric Space-Occupying Brain Lesions

INTRODUCTION

Intraoperative ultrasound (IOUS) may aid the resection of space-occupying brain lesions, though technical limits may hinder its reliability.

METHODS

IOUS (MyLabTwice^®, Esaote, Italy) with a microconvex probe was utilized in 45 consecutive cases of children with supratentorial space-occupying lesions aiming to localize the lesion (pre-IOUS) and evaluate the extent of resection (EOR, post-IOUS). Technical limits were carefully assessed, and strategies to enhance the reliability of real-time imaging were accordingly proposed.

RESULTS

Pre-IOUS allowed us to localize the lesion accurately in all of the cases (16 low-grade gliomas, 12 high-grade gliomas, eight gangliogliomas, seven dysembryoplastic neuroepithelial tumors, five cavernomas, and five other lesions, namely two focal cortical dysplasias, one meningioma, one subependymal giant cell astrocytoma, and one histiocytosis). In 10 deeply located lesions, IOUS with hyperechoic marker, eventually coupled with neuronavigation, was useful to plan the surgical route. In seven cases, the administration of contrast ensured a better definition of the vascular pattern of the tumor. Post-IOUS allowed the evaluation of EOR reliably in small lesions (<2 cm). In large lesions (>2 cm) assessing EOR is hindered by the collapsed surgical cavity, especially when the ventricular system is opened, and by artifacts that may simulate or hide residual tumors. The main strategies to overcome the former limit are inflation of the surgical cavity through pressure irrigation while insonating, and closure of the ventricular opening with Gelfoam before insonating. The strategies to overcome the latter are avoiding the use of hemostatic agents before IOUS and insonating through normal adjacent brain instead of corticotomy. These technical nuances enhanced the reliability of post-IOUS, with a total concordance to postoperative MRI. Indeed, the surgical plan was changed in about 30% of cases, as IOUS showed a residual tumor that was left behind.

CONCLUSION

IOUS ensures reliable real-time imaging in the surgery of space-occupying brain lesions. Limits may be overcome with technical nuances and proper training.