Automatic Segmentation of Vestibular Schwannomas: A Systematic Review.

BACKGROUND: Vestibular Schwannomas (VS) are benign tumors often monitored over time, with measurement techniques for assessing growth rates subject to significant interobserver variability. Automatic segmentation of these tumors could provide a more reliable and efficient for tracking their progression, especially given the irregular shape and growth patterns of VS. METHODS: Various studies and segmentation techniques employing different Convolutional Neural Network architectures and models, such as U-Net and CATS, were analyzed. Models were evaluated based on their performance across diverse datasets, and challenges, including domain shift and data sharing, were scrutinized. RESULTS: Automatic segmentation methods offer a promising alternative to conventional measurement techniques, offering potential benefits in precision and efficiency. However, these methods are not without challenges, notably the "domain shift" that occurs when models trained on specific datasets underperform when applied to different datasets. Techniques such as domain adaptation, domain generalization, and data diversity were discussed as potential solutions. CONCLUSION: Accurate measurement of VS growth is a complex process, with volumetric analysis currently appearing more reliable than linear measurements. Automatic segmentation, despite its challenges, offers a promising avenue for future investigation. Robust, well-generalized models could potentially improve the efficiency of tracking tumor growth, thereby augmenting clinical decision-making. Further work needs to be done to develop more robust models, address the domain shift, and enable secure data sharing for wider applicability.

Two-Photon Intravital Microscopy of Glioblastoma in a Murine Model.

The delivery of intravenously administered cancer therapeutics to brain tumors is limited by the blood-brain barrier. A method to directly image the accumulation and distribution of macromolecules in brain tumors in vivo would greatly enhance our ability to understand and optimize drug delivery in preclinical models. This protocol describes a method for real-time in vivo tracking of intravenously administered fluorescent-labeled nanoparticles with two-photon intravital microscopy (2P-IVM) in a mouse model of glioblastoma (GBM). The protocol contains a multi-step description of the procedure, including anesthesia and analgesia of experimental animals, creating a cranial window, GBM cell implantation, placing a head bar, conducting 2P-IVM studies, and post-surgical care for long-term follow-up studies. We show representative 2P-IVM imaging sessions and image analysis, examine the advantages and disadvantages of this technology, and discuss potential applications. This method can be easily modified and adapted for different research questions in the field of in vivo preclinical brain imaging.

Musculoskeletal imaging of senescence.

Senescent cells play a vital role in the pathogenesis of musculoskeletal (MSK) diseases, such as chronic inflammatory joint disorders, rheumatoid arthritis (RA), and osteoarthritis (OA). Cellular senescence in articular joints represents a response of local cells to persistent stress that leads to cell-cycle arrest and enhanced production of inflammatory cytokines, which in turn perpetuates joint damage and leads to significant morbidities in afflicted patients. It has been recently discovered that clearance of senescent cells by novel "senolytic" therapies can attenuate the chronic inflammatory microenvironment of RA and OA, preventing further disease progression and supporting healing processes. To identify patients who might benefit from these new senolytic therapies and monitor therapy response, there is an unmet need to identify and map senescent cells in articular joints and related musculoskeletal tissues. To fill this gap, new imaging biomarkers are being developed to detect and characterize senescent cells in human joints and musculoskeletal tissues. This review article will provide an overview of these efforts. New imaging biomarkers for senescence cells are expected to significantly improve the specificity of state-of-the-art imaging technologies for diagnosing musculoskeletal disorders.

Beyond human in neurosurgical exams: ChatGPT's success in the Turkish neurosurgical society proficiency board exams.

Chat Generative Pre-Trained Transformer (ChatGPT) is a sophisticated natural language model that employs advanced deep learning techniques and is trained on extensive datasets to produce responses akin to human conversation for user inputs. In this study, ChatGPT's success in the Turkish Neurosurgical Society Proficiency Board Exams (TNSPBE) is compared to the actual candidates who took the exam, along with identifying the types of questions it answered incorrectly, assessing the quality of its responses, and evaluating its performance based on the difficulty level of the questions. Scores of all 260 candidates were recalculated according to the exams they took and included questions in those exams for ranking purposes of this study. The average score of the candidates for a total of 523 questions is 62.02 ± 0.61 compared to ChatGPT, which was 78.77. We have concluded that in addition to ChatGPT's higher response rate, there was also a correlation with the increase in clarity regardless of the difficulty level of the questions with Clarity 1.5, 2.0, 2.5, and 3.0. In the participants, however, there is no such increase in parallel with the increase in clarity.

Cytodifferentiation of pituitary tumors influences pathogenesis and cavernous sinus invasion.

OBJECTIVE: Pituitary tumors (PTs) continue to present unique challenges given their proximity to the cavernous sinus, whereby invasive behavior can limit the extent of resection and surgical outcome, especially in functional tumors. The aim of this study was to elucidate patterns of cavernoinvasive behavior by PT subtype. METHODS: A total of 169 consecutive first-time surgeries for PTs were analyzed; 45% of the tumors were functional. There were 64 pituitary transcription factor-1 (PIT-1)-expressing, 62 steroidogenic factor-1 (SF-1)-expressing, 38 T-box transcription factor (TPIT)-expressing, and 5 nonstaining PTs. The gold standard for cavernous sinus invasion (CSI) was based on histopathological examination of the cavernous sinus medial wall and intraoperative exploration. RESULTS: Cavernous sinus disease was present in 33% of patients. Of the Knosp grade 3 and 4 tumors, 12 (19%) expressed PIT-1, 7 (11%) expressed SF-1, 8 (21%) expressed TPIT, and 2 (40%), were nonstaining (p = 0.36). PIT-1 tumors had a significantly higher predilection for CSI: 53% versus 24% and 18% for TPIT and SF-1 tumors, respectively (OR 6.08, 95% CI 2.86-13.55; p < 0.001). Microscopic CSI-defined as Knosp grade 0-2 tumors with confirmed invasion-was present in 44% of PIT-1 tumors compared with 7% and 13% of TPIT and SF-1 tumors, respectively (OR 11.72, 95% CI 4.35-35.50; p < 0.001). Using the transcavernous approach to excise cavernous sinus disease, surgical biochemical remission rates for patients with acromegaly, prolactinoma, and Cushing disease were 88%, 87%, and 100%, respectively. The granule density of PIT-1 tumors and corticotroph functional status did not influence CSI. CONCLUSIONS: The likelihood of CSI differed by transcription factor expression; PIT-1-expressing tumors had a higher predilection for invading the cavernous sinus, particularly microscopically, compared with the other tumor subtypes. This elucidates a unique cavernoinvasive behavior absent in cells from other lineages. Innovative surgical techniques, however, can mitigate tumor behavior and achieve robust, reproducible biochemical remission and gross-total resection rates. These findings can have considerable implications on the surgical management and study of PT biology and behavior.

A simple technique for generating 3D endoscopic images.

Background: Most neurosurgical photographs are limited to two-dimensional (2D), in this sense, most teaching and learning of neuroanatomical structures occur without an appreciation of depth. The objective of this article is to describe a simple technique for obtaining right and left 2D endoscopic images with manual angulation of the optic. Methods: The implementation of a three-dimensional (3D) endoscopic image technique is reported. We first describe the background and core principles related to the methods employed. Photographs are taken demonstrating the principles and also during an endoscopic endonasal approach, illustrating the technique. Later, we divide our process into two sections containing explanations, illustrations, and descriptions. Results: The results of taking a photograph with an endoscope and its assembly to a 3D image has been divided into two parts: Photo acquisition and image processing. Conclusion: We conclude that the proposed method is successful in producing 3D endoscopic images.