Integrated multi-modality image-guided navigation for neurosurgery: open-source software platform using state-of-the-art clinical hardware

A comparison of ultrasound volume navigation, O-arm navigation, and X-ray guidance for screw placement in minimally invasive transforaminal lumbar interbody fusion: a randomized controlled trial

OBJECTIVE

To compare the differences between Ultrasound Volume Navigation (UVN), O-arm Navigation, and conventional X-ray fluoroscopy-guided screw placement in Minimally Invasive Transforaminal Lumbar Interbody Fusion (MIS-TLIF) surgeries.

METHODS

A total of 90 patients who underwent MIS-TLIF due to lumbar disc herniation from January 2022 to January 2023 were randomly assigned to the UVN group, O-arm group, and X-ray group. UVN, O-arm navigation, and X-ray guidance were used for screw placement in the respective groups, while the remaining surgical procedures followed routine MIS-TLIF protocols. Intraoperative data including average single screw placement time, total radiation dose, and average effective radiation dose per screw were recorded and calculated. On the 10th day after surgery, postoperative X-ray and CT examinations were conducted to assess screw placement accuracy and facet joint violation.

RESULTS

There were no significant differences in general characteristics among the three groups, ensuring comparability. Firstly, the average single screw placement time in the O-arm group was significantly shorter than that in the UVN group and X-ray group (P<0.05). Secondly, in terms of total radiation dose during surgery, for single-level MIS-TLIF, the O-arm group had a significantly higher radiation dose compared to the UVN group and X-ray group (P<0.05). However, for multi-level MIS-TLIF, the X-ray group had a significantly higher radiation dose than the O-arm group and UVN group (P<0.05). In terms of average single screw radiation dose, the O-arm group and X-ray group were similar (P>0.05), while the UVN group was significantly lower than the other two groups (P<0.05). Furthermore, no significant differences were found in screw placement assessment grades among the three groups (P>0.05). However, in terms of facet joint violation rate, the UVN group (10.3%) and O-arm group (10.7%) showed no significant difference (P>0.05), while the X-ray group (26.7%) was significantly higher than both groups (P<0.05). Moreover, in the UVN group, there were significant correlations between average single screw placement time and placement grade with BMI index (r = 0.637, P<0.05; r = 0.504, P<0.05), while no similar significant correlations were found in the O-arm and X-ray groups.

CONCLUSION

UVN-guided screw placement in MIS-TLIF surgeries demonstrates comparable efficiency, visualization, and accuracy to O-arm navigation, while significantly reducing radiation exposure compared to both O-arm navigation and X-ray guidance. However, UVN may be influenced by factors like obesity, limiting its application.

NeuroIGN: Explainable Multimodal Image-Guided System for Precise Brain Tumor Surgery

Precise neurosurgical guidance is critical for successful brain surgeries and plays a vital role in all phases of image-guided neurosurgery (IGN). Neuronavigation software enables real-time tracking of surgical tools, ensuring their presentation with high precision in relation to a virtual patient model. Therefore, this work focuses on the development of a novel multimodal IGN system, leveraging deep learning and explainable AI to enhance brain tumor surgery outcomes. The study establishes the clinical and technical requirements of the system for brain tumor surgeries. NeuroIGN adopts a modular architecture, including brain tumor segmentation, patient registration, and explainable output prediction, and integrates open-source packages into an interactive neuronavigational display. The NeuroIGN system components underwent validation and evaluation in both laboratory and simulated operating room (OR) settings. Experimental results demonstrated its accuracy in tumor segmentation and the success of ExplainAI in increasing the trust of medical professionals in deep learning. The proposed system was successfully assembled and set up within 11 min in a pre-clinical OR setting with a tracking accuracy of 0.5 (± 0.1) mm. NeuroIGN was also evaluated as highly useful, with a high frame rate (19 FPS) and real-time ultrasound imaging capabilities. In conclusion, this paper describes not only the development of an open-source multimodal IGN system but also demonstrates the innovative application of deep learning and explainable AI algorithms in enhancing neuronavigation for brain tumor surgeries. By seamlessly integrating pre- and intra-operative patient image data with cutting-edge interventional devices, our experiments underscore the potential for deep learning models to improve the surgical treatment of brain tumors and long-term post-operative outcomes.

Modern Image-Guided Surgery: A Narrative Review of Medical Image Processing and Visualization

Medical image analysis forms the basis of image-guided surgery (IGS) and many of its fundamental tasks. Driven by the growing number of medical imaging modalities, the research community of medical imaging has developed methods and achieved functionality breakthroughs. However, with the overwhelming pool of information in the literature, it has become increasingly challenging for researchers to extract context-relevant information for specific applications, especially when many widely used methods exist in a variety of versions optimized for their respective application domains. By being further equipped with sophisticated three-dimensional (3D) medical image visualization and digital reality technology, medical experts could enhance their performance capabilities in IGS by multiple folds. The goal of this narrative review is to organize the key components of IGS in the aspects of medical image processing and visualization with a new perspective and insights. The literature search was conducted using mainstream academic search engines with a combination of keywords relevant to the field up until mid-2022. This survey systemically summarizes the basic, mainstream, and state-of-the-art medical image processing methods as well as how visualization technology like augmented/mixed/virtual reality (AR/MR/VR) are enhancing performance in IGS. Further, we hope that this survey will shed some light on the future of IGS in the face of challenges and opportunities for the research directions of medical image processing and visualization.

[Comparison of screw placement guided by O-arm navigation and ultrasound volume navigation in minimally invasive transforaminal lumbar interbody fusion]

Objective

To compare the effectiveness of O-arm navigation and ultrasound volume navigation (UVN) in guiding screw placement during minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) surgery.

Methods

Sixty patients who underwent MIS-TLIF surgery for lumbar disc herniation between June 2022 and June 2023 and met the selection criteria were included in the study. They were randomly assigned to group A (screw placement guided by UVN during MIS-TLIF) or group B (screw placement guided by O-arm navigation during MIS-TLIF), with 30 cases in each group. There was no significant difference in baseline data, including gender, age, body mass index, and surgical segment, between the two groups ( P>0.05). Intraoperative data, including average single screw placement time, total radiation dose, and average single screw effective radiation dose, were recorded and calculated. Postoperatively, X-ray film and CT scans were performed at 10 days to evaluate screw placement accuracy and assess facet joint violation. Pearson correlation and Spearman correlation analyses were used to observe the relationship between the studied parameters (average single screw placement time and screw placement accuracy grading) and BMI.

Results

The average single screw placement time in group B was significantly shorter than that in group A, and the total radiation dose of single segment and multi-segment and the average single screw effective radiation dose in group B were significantly higher than those in group A ( P<0.05). There was no significant difference in the total radiation dose between single segment and multiple segments in group B ( P>0.05), while the total radiation dose of multiple segments was significantly higher than that of single segment in group A ( P<0.05). No significant difference was found in the accuracy of screw implantation between the two groups ( P>0.05). In both groups, the grade 1 and grade 2 screws broke through the outer wall of the pedicle, and no screw broke through the inner wall of the pedicle. There was no significant difference in the rate of facet joint violation between the two groups ( P>0.05). In group A, both the average single screw placement time and screw placement accuracy grading were positively correlated with BMI ( r=0.677, P<0.001; r=0.222, P=0.012), while in group B, neither of them was correlated with BMI ( r=0.224, P=0.233; r=0.034, P=0.697).

Conclusion

UVN-guided screw placement in MIS-TLIF surgery demonstrates comparable efficiency, visualization, and accuracy to O-arm navigation, while significantly reducing radiation exposure. However, it may be influenced by factors such as obesity, which poses certain limitations.

[Clinical application of percutaneous pedicle screw placement guided by ultrasound volume navigation combined with X-ray fluoroscopy: a prospective randomized controlled study]

Objective

To explore the feasibility and accuracy of ultrasound volume navigation (UVN) combined with X-ray fluoroscopy-guided percutaneous pedicle screw implantation through a prospective randomized controlled study.

Methods

Patients with thoracic and lumbar vertebral fractures scheduled for percutaneous pedicle screw fixation between January 2022 and January 2023 were enrolled. Among them, 60 patients met the selection criteria and were included in the study. There were 28 males and 32 females, with an average age of 49.5 years (range, 29-60 years). The cause of injury included 20 cases of traffic accidents, 21 cases of falls, 17 cases of slips, and 2 cases of heavy object impact. The interval from injury to hospital admission ranged from 1 to 5 days (mean, 1.57 days). The fracture located at T 12 in 15 cases, L 1 in 20 cases, L 2 in 19 cases, and L 3 in 6 cases. The study used each patient as their own control, randomly guiding pedicle screw implantation using UVN combined with X-ray fluoroscopy on one side of the vertebral body and the adjacent segment (trial group), while the other side was implanted under X-ray fluoroscopy (control group). A total of 4 screws and 2 rods were implanted in each patient. The implantation time and fluoroscopy frequency during implantation of each screw, angle deviation and distance deviation between actual and preoperative planned trajectory by imaging examination, and the occurrence of zygapophysial joint invasion were recorded.

Results

In terms of screw implantation time, fluoroscopy frequency, angle deviation, distance deviation, and incidence of zygapophysial joint invasion, the trial group showed superior results compared to the control group, and the differences were significant ( P<0.05).

Conclusion

UVN combined with X-ray fluoroscopy-guided percutaneous pedicle screw implantation can yreduce screw implantation time, adjust dynamically, reduce operational difficulty, and reduce radiation damage.

SciKit-SurgeryGlenoid, an Open Source Toolkit for Glenoid Version Measurement

Correct understanding of the geometry of the glenoid (the socket of the shoulder joint) is key to successful planning of shoulder replacement surgery. This surgery typically involves placing an implant in the shoulder joint to restore joint function. The most relevant geometry is the glenoid version, which is the angular orientation of the glenoid surface relative to the long axis of the scapula in the axial plane. However, measuring the glenoid version is not straightforward and there are multiple measurement methods in the literature and used in commercial planning software. In this paper we introduce SciKit-SurgeryGlenoid, an open source toolkit for the measurement of glenoid version. SciKit-SurgeryGlenoid contains implementations of the 4 most frequently used glenoid version measurement algorithms enabling easy and unbiased comparison of the different techniques. We present the results of using the software on 10 sets of pre-operative CT scans taken from patients who have subsequently undergone shoulder replacement surgery. We further compare these results with those obtained from a commercial implant planning software. SciKit-SurgeryGlenoid currently requires manual segmentation of the relevant anatomical features for each method. Future work will look at automating the segmentation process to build an automatic and repeatable pipeline from CT or radiograph to quantitative glenoid version measurement.