Intraoperative Guidance Research Articles

Intraoperative Image Guidance in Orbital and Lacrimal Surgery: A Report by the American Academy of Ophthalmology

To review the efficacy and safety of the use of intraoperative image guidance (IIG) in orbital and lacrimal surgery. A literature search of the PubMed database was last conducted in November 2023 for English-language original research that assessed the use of any image guidance system in orbital and lacrimal surgery that included at least 5 patients. The search identified 524 articles; 94 were selected for full-text analysis by the panel. A total of 32 studies met inclusion criteria. The panel methodologist assigned a level II rating to 2 studies and a level III rating to 30 studies. No study met the criteria for level I evidence. Procedures reported on were as follows: fracture repair (n= 14), neoplasm and infiltrate biopsy or excision (n= 6), orbital decompression for Graves ophthalmopathy (n= 3), dacryocystorhinostomy (n= 1), and mixed etiology and procedures (n= 8). Four studies used more than one IIG system. One study that met level II evidence criteria compared the outcomes of orbital fracture repair with IIG (n= 29) and without IIG (n= 29). Borderline better outcomes were reported in the IIG group: 2% versus 10% with diplopia (P= 0.039) and 3% versus 10% with enophthalmos (P= 0.065). The other level II study compared the repair of fractures with navigation (n= 20) and without (n= 20). The group in which navigation was used had a measured mean volume reduction of 3.82 cm3 compared with 3.33 cm3 (P= 0.02), and there was a greater measured reduction in enophthalmos in the navigation group of 0.72 mm (P= 0.001). Although the remaining 30 assessed articles failed to meet level II criteria, all alleged a benefit from IIG. No complications were reported. A small number of comparative studies suggest that there are improved outcomes when IIG is used in orbital fracture repair, but each study suffers from various limitations. No high-quality comparative studies exist for the management of lacrimal surgery, neoplastic disease, or decompression. Complications attributable to the use of IIG have not been identified, and IIG has not been analyzed for cost savings. Proprietary or commercial disclosure may be found after the references.

Hierarchical segmentation of surgical scenes in laparoscopy.

Segmentation of surgical scenes may provide valuable information for real-time guidance and post-operative analysis. However, in some surgical video frames there is unavoidable ambiguity, leading to incorrect predictions of class or missed detections. In this work, we propose a novel method that alleviates this problem by introducing a hierarchy and associated hierarchical inference scheme that allows broad anatomical structures to be predicted when fine-grained structures cannot be reliably distinguished. First, we formulate a multi-label segmentation loss informed by a hierarchy of anatomical classes and then train a network using this. Subsequently, we use a novel leaf-to-root inference scheme ("Hiera-Mix") to determine the trade-off between label confidence and granularity. This method can be applied to any segmentation model. We evaluate our method using a large laparoscopic cholecystectomy dataset with 65,000 labelled frames. We observed an increase in per-structure detection F1 score for the critical structures, when evaluated across their sub-hierarchies, compared to the baseline method: 6.0% for the cystic artery and 2.9% for the cystic duct, driven primarily by increases in precision of 11.3% and 4.7%, respectively. This corresponded to visibly improved segmentation outputs, with better characterisation of the undissected area containing the critical structures and fewer inter-class confusions. For other anatomical classes, which did not stand to benefit from the hierarchy, performance was unimpaired. Our proposed hierarchical approach improves surgical scene segmentation in frames with ambiguity, by more suitably reflecting the model's parsing of the scene. This may be beneficial in applications of surgical scene segmentation, including recent advancements towards computer-assisted intra-operative guidance.

First-in-man study of the PSMA Minibody IR800-IAB2M for molecularly targeted intraoperative fluorescence guidance during radical prostatectomy

PurposeProstate-specific membrane antigen (PSMA) is increasingly used to image prostate cancer in clinical practice. We sought to develop and test a humanised PSMA minibody IAB2M conjugated to the fluorophore IRDye 800CW-NHS ester in men undergoing robot-assisted laparoscopic radical prostatectomy (RARP) to image prostate cancer cells during surgery.MethodsThe minibody was evaluated pre-clinically using PSMA positive/negative xenograft models, following which 23 men undergoing RARP between 2018 and 2020 received between 2.5 mg and 20 mg of IR800-IAB2M intravenously, at intervals between 24 h and 17 days prior to surgery. At every step of the procedure, the prostate, pelvic lymph node chains and extra-prostatic surrounding tissue were imaged with a dual Near-infrared (NIR) and white light optical platform for fluorescence in vivo and ex vivo. Histopathological evaluation of intraoperative and postoperative microscopic fluorescence imaging was undertaken for verification.ResultsTwenty-three patients were evaluated to optimise both the dose of the reagent and the interval between injection and surgery and secure the best possible specificity of fluorescence images. Six cases are presented in detail as exemplars. Overall sensitivity and specificity in detecting non-lymph-node extra-prostatic cancer tissue were 100% and 65%, and 64% and 64% respectively for lymph node positivity. There were no side-effects associated with administration of the reagent.ConclusionIntraoperative imaging of prostate cancer tissue is feasible and safe using IR800-IAB2M. Further evaluation is underway to assess the benefit of using the technique in improving completion of surgical excision during RARP.RegistrationISCRCTN10046036: https://www.isrctn.com/ISRCTN10046036.

In vivo non-contact regions of proximal scaphoid in six extreme wrist positions

IntroductionFractures of the scaphoid are the most common carpal injuries, account for 80-90% of all carpal fractures. 5-15% nonunion of scaphoid fractures were reported even with adequate primary treatment, which probably progresses to osteoarthritic changes several decades later. Researches regarding to scaphoid physiological characteristic in vitro and in vivo and kinds of trials in clinical practice are being kept on going, which contribute much to our clinical practice. With the advancing wrist arthroscopy, 3D-print patient-specific drill guide, and intraoperative fluoroscopic guidance, dorsal approach (mini-invasive and percutaneous technique) is being popular, through which we can implant the screw in good coincidence with biomechanics and with less disturbing tenuous blood supply of the scaphoid. Investigating the noncontact area of the dorsal proximal scaphoid in different wrist positions can facilitate preoperatively estimating insert point of the screw.Materials and methodsEight volunteers were recruited to accept CT scans in six extreme wrist positions. The images of DICOM mode were imput into the Mimics analytical system, the segmented scaphoid, lunate and radius were exported in mode of ASCII STL and were opened in the software of Geomagic studio. We created four planes based on anatomic markers on the surface of the radius and scaphoid to confine the proximal scaphoid to form the so-called non-contact regions. We measured and compared the areas in six targeted positions.ResultsAmidst six extreme wrist positions, area of the non-contact region in extreme dorsal extension (59.81 ± 26.46 mm2) was significantly the smallest, and it in extreme palmar flexion significantly was largest (170.51 ± 30.44 mm2). The non-contact regions increased in order of dorsal extension, supination, ulnar deviation, radial deviation, pronation and palmar flexion. As for two-group comparison, the non-contact region showed significantly larger (p < 0.05) in palmar flexion than the others except for in pronation individually, and in radial deviation (p < 0.05) than in dorsal extension.ConclusionsSufficient space was available for the screw started from the dorsal approach despite the wrist positions.

3D printing adoption in NHS trusts within the United Kingdom

Additive manufacturing and 3D printing is being widely adopted by the medical industry. This study provides a comprehensive overview of the current state of 3D printing technology in NHS trusts across the UK. Data was collected through a survey using the freedom of information act. The survey revealed that 53 NHS trusts (∼25 %) across the UK are utilising the technology, with a diverse range of strategies and applications. The most common application was the creation of guides and models, used for pre-operative planning, intraoperative guidance, and educational purposes. The study also highlights the regulatory and ethical considerations involved in 3D printing in healthcare. The findings indicate that there are no 3D printing specific standards or guidelines being followed for medical devices and therefore underscores the need for clear and consistent regulatory guidelines to be established. As the 3D printing technology continues to advance, its applications in healthcare are expected to expand rapidly, warranting further research into its impact on patient outcomes and healthcare costs.

Three-dimensional planning, navigation, patient-specific instrumentation and mixed reality in shoulder arthroplasty: a digital orthopedic renaissance.

Accurate component placement in shoulder arthroplasty is crucial for avoiding complications, achieving superior biomechanical performance and optimizing functional outcomes. Shoulder and elbow surgeons have explored various methods to improve surgical understanding and precise execution including preoperative planning with 3D computed tomography (CT), patient-specific instrumentation (PSI), intraoperative navigation, and mixed reality (MR). 3D preoperative planning facilitated by CT scans and advanced software, enhances surgical precision, influences decision-making for implant types and approaches, reduces errors in guide pin placement, and contributes to cost-effectiveness. Navigation demonstrates benefits in reducing malpositioning, optimizing baseplate stability, improving humeral cut, and potentially conserving bone stock, although challenges such as varied operating times and costs warrant further investigation. The personalized patient care and enhanced operational efficiency associated with PSI are not only attractive for achieving desired component positions but also hold promise for improved outcomes in complex cases involving glenoid bone loss. Augmented reality (AR) and virtual reality (VR) technologies play a pivotal role in reshaping shoulder arthroplasty. They offer benefits in preoperative planning, intraoperative guidance, and interactive surgery. Studies demonstrate their effectiveness in AR-guided guidewire placement, providing real-time surgical advice during reverse total shoulder arthroplasty (RTSA). Additionally, these technologies show promise in orthopedic training, delivering superior realism and accelerating learning compared to conventional methods.

Imaging in shoulder arthroplasty: Current applications and future perspectives

Shoulder arthroplasty has become a standard surgical procedure for treating a variety of complex shoulder disorders, including those with degenerative and traumatic aetiologies. The ever-improving success rates of shoulder arthroplasty could be attributed to advancements in endoprosthesis design, improvements in the biomechanics of endoprosthetic components, and improvements in surgical techniques. It improves patient outcomes and helps restore shoulder joint function and mobility.Imaging plays a vital role by enabling surgeons to plan arthroplasty procedures, help guide endoprosthesis placement, and monitor postoperative outcomes. In addition, imaging plays a role in assessing the residual bone stock and status of rotator cuff integrity and in correcting the placement of prosthetic components to restore shoulder mobility.CT-guided navigation aids surgeons by helping them choose appropriate components for implants and ensuring that implants are placed optimally during surgery. It can lead to better surgical results with reduced patient morbidity and a longer duration of prosthetic stability. After surgery, it is crucial to use imaging techniques to detect issues such as periprosthetic loosening, infections, or fractures to start effective management strategies to enhance patient recovery.This article aims to provide orthopaedic surgeons and radiologists with knowledge on the imaging methods used in shoulder arthroplasty and their role in presurgical planning, intraoperative guidance and postoperative assessment. In this study, we aimed to investigate the rationale behind utilising various types of shoulder replacements: total shoulder replacement (TSA), reverse total shoulder arthroplasty (RTSA), and hemiarthroplasty; methods, their respective advantages and limitations; and outcomes. Our objective is to comprehensively analyse the procedures mentioned above and highlight their unique features and benefits to facilitate a better understanding of these approaches. Additionally, we will discuss how these imaging techniques help identify issues such as loose components, fractures around the implant site, joint instability and infections.

An Imaging-Compatible Oral Retractor System for Transoral Robotic Surgery.

This study aimed to develop and validate a Computed Tomography (CT)/Magnetic Resonance Imaging(MRI)-compatible polymer oral retractor system to enable intraoperative image guidance for transoral robotic surgery (TORS). The retractor was designed based on standard-of-care metallic retractors and 3D (three-dimensional) printed with carbon fiber composite and nylon. The system was comprehensively evaluated in bench-top and cadaveric experiments in terms of its ability to enable intraoperative CT/MR images during TORS, functionality including surgical exposure and working volume, usability, compatibility with da Vinci surgical systems, feasibility for disinfection or sterilization, and robustness over an extended period of time. The polymer retractor system enabled the acquisition of high-resolution and artifact-free intraoperative CT/MR images during TORS. With an inter-incisive distance of 42.55mm and a working volume of 200.09cm3, it provided surgical exposure comparable to standard-of-care metallic retractors. The system proved intuitive and compatible with da Vinci S, Xi, and Single Port systems, enabling successful mock surgical tasks performed by surgeons and residents. The retractor components could be effectively disinfected or sterilized for clinical use without significant compromise in material strength, with STERRAD considered the optimal method. Throughout a 2h mock procedure, the retractor system showed minimal displacements (<1.5mm) due to surrounding tissue deformation, with insignificant device deformation. The 3D-printed polymer retractor system successfully enabled artifact-free intraoperative CT/MR imaging in TORS for the first time and demonstrated feasibility for clinical use. This breakthrough opens the door to surgical navigation with intraoperative image guidance in TORS, offering the potential to significantly improve surgical outcomes and patients' quality of life.

Enabling extracorporeal ultrasound imaging with the da Vinci robot for transoral robotic surgery: a feasibility study.

Transoral robotic surgery (TORS) is a challenging procedure due to its small workspace and complex anatomy. Ultrasound (US) image guidance has the potential to improve surgical outcomes, but an appropriate method for US probe manipulation has not been defined. This study evaluates using an additional robotic (4th) arm on the da Vinci Surgical System to perform extracorporeal US scanning for image guidance in TORS. A stereoscopic imaging system and da Vinci-compatible US probe attachment were developed to enable control of the extracorporeal US probe from the surgeon console. The prototype was compared to freehand US by nine operators in three tasks on a healthy volunteer: (1) identification of the common carotid artery, (2) carotid artery scanning, and (3) identification of the submandibular gland. Operator workload and user experience were evaluated using a questionnaire. The robotic US tasks took longer than freehand US tasks (2.09x longer; ) and had higher operator workload (2.12x higher; ). However, operator-rated performance was closer (avg robotic/avg freehand=0.66; ), and scanning performance measured by MRI-US average Hausdorff distance provided no statistically significant difference. Extracorporeal US scanning for intraoperative US image guidance is a convenient approach for providing the surgeon direct control over the US image plane during TORS, with little modification to the existing operating room workflow. Although more time-consuming and higher operator workload, several methods have been identified to address these limitations.

Semi-supervised segmentation of abdominal organs and liver tumor: uncertainty rectified curriculum labeling meets X-fuse

Precise liver tumors and associated organ segmentation hold immense value for surgical and radiological intervention, enabling anatomical localization for pre-operative planning and intra-operative guidance. Modern deep learning models for medical image segmentation have evolved from convolution neural networks to transformer architectures, significantly boosting global context understanding. However, accurate delineation especially of hepatic lesions remains an enduring challenge due to models’ predominant focus solely on spatial feature extraction failing to adequately characterize complex medical anatomies. Moreover, the relative paucity of expertly annotated medical imaging data restricts model exposure to diverse pathological presentations. In this paper, we present a three-phrased cascaded segmentation framework featuring an X-Fuse model that synergistically integrates spatial and frequency domain’s complementary information in dual encoders to enrich latent feature representation. To enhance model generalizability, building upon X-Fuse topology and taking advantage of additional unlabeled pathological data, our proposed integration of curriculum pseudo-labeling with Jensen–Shannon variance-based uncertainty rectification promotes optimized pseudo supervision in the context of semi-supervised learning. We further introduce a tumor-focus augmentation technique including training-free copy-paste and knowledge-based synthesis that show efficacy in simplicity, contributing to the substantial elevation of model adaptability on diverse lesional morphologies. Extensive experiments and modular evaluations on a holdout test set demonstrate that our methods significantly outperform existing state-of-the-art segmentation models in both supervised and semi-supervised settings, as measured by the Dice similarity coefficient, achieving superior delineation of bones (95.42%), liver (96.26%), and liver tumors (89.53%) with 16.41% increase comparing to V-Net on supervised-only and augmented-absent scenario. Our method marks a significant step toward the realization of more reliable and robust AI-assisted diagnostic tools for liver tumor intervention. We have made the codes publicly available [https://github.com/lyupengju/X-Fuse].

Enhancing Surgical Approach: Breakthrough Markerless Surface Registration With Augmented Reality for Zygomatic Complex Fracture Surgeries.

Innovative technologies with surgical navigation have been used for enhancing surgical accuracies for zygomaticomaxillary complex (ZMC) fractures and offers advantages in precision, accuracy, effectiveness, predictability, and symmetry improvement. Moreover, augmented reality (AR) navigation technology combines virtual reality, 3-dimensional (3D) reconstruction, and real-time interaction, making it ideal for bone tissue operations. Our study explored the usefulness and clinical efficacy of AR technology in intraoperative guidance for reducing ZMC fractures. We retrospectively studied 35 patients with zygomatic complex fractures, comparing outcomes of AR-guided and conventional methods. Furthermore, the AR system provided real-time visualization and guidance. The evaluation included reduction accuracy using root mean square (RMS) value and symmetry analysis using a mirror image of 3D models. Results demonstrated the feasibility and effectiveness of the AR-guided method in improving outcomes and patient satisfaction. In 35 patients (25 males, 10 females), AR-guided (n = 19) and conventional (n = 16) approaches were compared. Age, sex, and fracture type exhibited no significant differences between groups. No complications occurred, and postoperative RMS error significantly decreased ( P < 0.001). The AR group had a lower postoperative RMS error ( P = 0.034). Augmented reality-guided surgery improved accuracy and outcomes in zygomatic complex fractures. Real-time visualization enhanced precision during reduction and fixation. This innovative approach promises enhanced surgical accuracy and patient outcomes in craniofacial surgery.

Clinical and Surgical Applications of Large Language Models: A Systematic Review.

Background: Large language models (LLMs) represent a recent advancement in artificial intelligence with medical applications across various healthcare domains. The objective of this review is to highlight how LLMs can be utilized by clinicians and surgeons in their everyday practice. Methods: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Six databases were searched to identify relevant articles. Eligibility criteria emphasized articles focused primarily on clinical and surgical applications of LLMs. Results: The literature search yielded 333 results, with 34 meeting eligibility criteria. All articles were from 2023. There were 14 original research articles, four letters, one interview, and 15 review articles. These articles covered a wide variety of medical specialties, including various surgical subspecialties. Conclusions: LLMs have the potential to enhance healthcare delivery. In clinical settings, LLMs can assist in diagnosis, treatment guidance, patient triage, physician knowledge augmentation, and administrative tasks. In surgical settings, LLMs can assist surgeons with documentation, surgical planning, and intraoperative guidance. However, addressing their limitations and concerns, particularly those related to accuracy and biases, is crucial. LLMs should be viewed as tools to complement, not replace, the expertise of healthcare professionals.

Intraoperative in vivo confocal endomicroscopy of the glioma margin: performance assessment of image interpretation by neurosurgeon users.

Confocal laser endomicroscopy (CLE) is an intraoperative real-time cellular resolution imaging technology that images brain tumor histoarchitecture. Previously, we demonstrated that CLE images may be interpreted by neuropathologists to determine the presence of tumor infiltration at glioma margins. In this study, we assessed neurosurgeons' ability to interpret CLE images from glioma margins and compared their assessments to those of neuropathologists. In vivo CLE images acquired at the glioma margins that were previously reviewed by CLE-experienced neuropathologists were interpreted by four CLE-experienced neurosurgeons. A numerical scoring system from 0 to 5 and a dichotomous scoring system based on pathological features were used. Scores from assessments of hematoxylin and eosin (H&E)-stained sections and CLE images by neuropathologists from a previous study were used for comparison. Neurosurgeons' scores were compared to the H&E findings. The inter-rater agreement and diagnostic performance based on neurosurgeons' scores were calculated. The concordance between dichotomous and numerical scores was determined. In all, 4275 images from 56 glioma margin regions of interest (ROIs) were included in the analysis. With the numerical scoring system, the inter-rater agreement for neurosurgeons interpreting CLE images was moderate for all ROIs (mean agreement, 61%), which was significantly better than the inter-rater agreement for the neuropathologists (mean agreement, 48%) (p < 0.01). The inter-rater agreement for neurosurgeons using the dichotomous scoring system was 83%. The concordance between the numerical and dichotomous scoring systems was 93%. The overall sensitivity, specificity, positive predictive value, and negative predictive value were 78%, 32%, 62%, and 50%, respectively, using the numerical scoring system and 80%, 27%, 61%, and 48%, respectively, using the dichotomous scoring system. No statistically significant differences in diagnostic performance were found between the neurosurgeons and neuropathologists. Neurosurgeons' performance in interpreting CLE images was comparable to that of neuropathologists. These results suggest that CLE could be used as an intraoperative guidance tool with neurosurgeons interpreting the images with or without assistance of the neuropathologists. The dichotomous scoring system is robust yet simple and may streamline rapid, simultaneous interpretation of CLE images during imaging.

Multimodality Cardiovascular Imaging for Totally Video-Guided Thorascopic Cardiac Surgery.

Totally video-guided thorascopic cardiac surgery (TVTCS) represents one of the most minimally invasive access routes to the heart. Its feasibility and safety can be guaranteed by an experienced surgeon with skilled operative techniques under the guidance of a video signal via thoracoscopy and the imaging from transesophageal echocardiography. At present, this surgical approach has been applied for atrioventricular valve disease, atrial septum defects plus and partial anomalous pulmonary venous drainage, cardiac tumors, hypertrophic obstructive cardiomyopathy, aortic valve disease, and atrial fibrillation. Multimodality cardiovascular imaging, including echocardiography, X-ray, computed tomography (CT), magnetic resonance imaging (MRI) and cardiac catheterization, provides morphologic characteristics and function status of the cardiovascular system and a comprehensive view of the target anatomy. In this review, the benefits of multimodality cardiovascular imaging are summarized for the clinical practice of TVTCS, including the preoperative preparation, intraoperative guidance and postoperative supervision. The disease categories are also individually reviewed on the basis of multimodality cardiovascular imaging, to ensure the feasibility and safety for TVTCS. Cardiovascular imaging technologies not only confirm who is a candidate for this surgical technique, but also provide technical support during the procedure and for postop follow to assess the clinical outcomes. Multimodality cardiovascular imaging is instrumental to provide the requirements to solve the problems for conduction of TVTCS; and to provide individualized protocols with high-resolution and real-time dynamic imaging fusion.

Normscan: open-source Python software to create average models from CT scans.

Age-matched average 3D models facilitate both surgical planning and intraoperative guidance of cranial birth defects such as craniosynostosis. We aimed to develop an algorithm that accepts any number of CT scans as input and generates highly accurate, average models with minimal user input that are ready for 3D printing and clinical use. Using a compiled database of 'normal' pediatric computed tomography (CT) scans, we report Normscan, an open-source platform built in Python that allows users to generate normative models of CT scans through user-defined landmarks. We use the basion, nasion, and left and right porions as anatomical landmarks for initial correspondence and then register the models using the iterative closest points algorithm before downstream averaging. Normscan is fast and easy to use via our user interface and also creates highly accurate average models of any number of input models. Additionally, it is highly repeatable, with coefficients of variance for the surface area and volume of the average model being less than 3% across ten independent trials. Average models can then be 3D printed and/or visualized in augmented reality. Normscan provides an end-to-end pipeline for the creation of average models of skulls. These models can be used for the generation of databases of specific demographic anatomical models as well as for intraoperative guidance and surgical planning. While Normscan was designed for craniosynostosis repair, due to the modular nature of the algorithm, Normscan has many applications in other areas of surgical planning and research.

Deep Learning Method for Rapid Simultaneous Multistructure Temporal Bone Segmentation.

To develop and validate a deep learning algorithm for the automated segmentation of key temporal bone structures from clinical computed tomography (CT) data sets. Cross-sectional study. A total of 325 CT scans from a clinical database. A state-of-the-art deep learning (DL) algorithm (SwinUNETR) was used to train a prediction model for rapid segmentation of 9 key temporal bone structures in a data set of 325 clinical CTs. The data set was manually annotated by a specialist to serve as the ground truth. The data set was randomly split into training (n = 260) and testing (n = 65) sets. The model's performance was objectively assessed through external validation on the test set using metrics including Dice, Balanced accuracy, Hausdorff distances, and processing time. The model achieved an average Dice coefficient of 0.87 for all structures, an average balanced accuracy of 0.94, an average Hausdorff distance of 0.79 mm, and an average processing time of 9.1 seconds per CT. The present DL model for the automated simultaneous segmentation of multiple structures within the temporal bone from CTs achieved high accuracy according to currently commonly employed objective analysis. The results demonstrate the potential of the method to improve preoperative evaluation and intraoperative guidance in otologic surgery.

Preoperative embolization and microsurgical resection of a cerebellar hemangioblastoma: embolization goals and technical nuances of the approaches. Illustrative case.

Resection remains the optimal treatment for hemangioblastomas, highly vascular tumors commonly located in the cerebellum or spinal cord. Preoperative embolization can be used with caution to reduce intraoperative blood loss and promote gross-total resection while reducing neurological morbidity. The authors report a case of a 44-year-old male who presented with worsening dizziness, gait imbalance, and diplopia. Imaging revealed a large vascular cerebellar mass with brainstem compression and hydrocephalus, concerning for hemangioblastoma. The patient underwent preoperative embolization of the main arterial supply from the right superior cerebellar artery, which devascularized the tumor and reduced the early venous shunting, followed by gross-total resection of the tumor. Preoperative embolization helped to facilitate safe microsurgical resection because this main arterial supply was deep to the planned surgical approach, and the Onyx cast served as a landmark of the dorsal midbrain and remaining arterial supply. This resulted in minimal intraoperative blood loss. At 2-year follow-up, the patient's diplopia and vertigo had resolved, and his gait continues to improve. Despite controversy regarding the use of preoperative embolization for hemangioblastoma resection, the authors emphasize its safety and utility during resection of a large cerebellar hemangioblastoma. Onyx embolization provided benefit in both reducing the tumor blood supply and serving as intraoperative visual guidance.

High-sensitivity THz-ATR imaging of cerebral ischemia in a rat model.

The fast label-free detection of the extent and degree of cerebral ischemia has been the difficulty and hotspot for precise and accurate neurosurgery. We experimentally demonstrated that the fresh cerebral tissues at different ischemic stages within 24 hours can be well distinguished from the normal tissues using terahertz (THz) attenuated total reflection (ATR) imaging system. It was indicated that the total reflectivity of THz wave for ischemic cerebral tissues was lower than that for normal tissues. Especially, compared to the images stained with 2,3,5-triphenyl tetrazolium chloride (TTC), the ischemic tissues can be detected using THz wave with high sensitivity as early as the ischemic time of 2.5 hours, where THz images showed the ischemic areas became larger and diffused as the ischemic time increasing. Furthermore, the THz spectroscopy of cerebral ischemic tissues at different ischemic times was obtained in the range of 0.5-2.0 THz. The absorption coefficient of ischemic tissue increased with the increase of ischemic time, whereas the refractive index decreased with prolonging the ischemic time. Additionally, it was found from hematoxylin and eosin (H&E) staining microscopic images that, with the ischemic time increasing, the cell size and cell density of the ischemic tissues decreased, whereas the intercellular substance of the ischemic tissues increased. The result showed that THz recognition mechanism of the ischemia is mainly based on the increase of intercellular substance, especially water content, which has a stronger impact on absorption of THz wave than that of cell density. Thus, THz imaging has great potential for recognition of cerebral ischemia and it may become a new method for intraoperative real-time guidance, recognition in situ, and precise excision.

Computer-Assisted Transcatheter Mitral Valve Implantation for Valve-in-Valve Procedures.

Transcatheter mitral valve-in-valve is an alternative to high-risk reoperation on a failing bioprosthesis. It entails specific challenges such as left ventricular outflow tract obstruction. We propose a patient-specific augmented imaging based on preoperative planning to assist the procedure. Valve-in-valve simulation was performed to represent the optimal level of implantation and the neo-left ventricular outflow tract. These data were combined with intraoperative images through a real-time 3D/2D registration tool. All data were collected retrospectively on one case (pre and per-procedure imaging). We present for the first time an intraoperative guidance tool in transcatheter mitral valve-in-valve procedure.

Focused ultrasound as a treatment modality for gliomas.

Ultrasound waves were initially used as a diagnostic tool that provided critical insights into several pathological conditions (e.g., gallstones, ascites, pneumothorax, etc.) at the bedside. Over the past decade, advancements in technology have led to the use of ultrasound waves in treating many neurological conditions, such as essential tremor and Parkinson's disease, with high specificity. The convergence of ultrasound waves at a specific region of interest/target while avoiding surrounding tissue has led to the coined term "focused ultrasound (FUS)." In tumor research, ultrasound technology was initially used as an intraoperative guidance tool for tumor resection. However, in recent years, there has been growing interest in utilizing FUS as a therapeutic tool in the management of brain tumors such as gliomas. This mini-review highlights the current knowledge surrounding using FUS as a treatment modality for gliomas. Furthermore, we discuss the utility of FUS in enhanced drug delivery to the central nervous system (CNS) and highlight promising clinical trials that utilize FUS as a treatment modality for gliomas.